Discussion 5

Table of Contents

Page

Chapter 1: Introduction 1

Statement of the Problem 1

Setting of the Study 7

Researcher’s Role 8

Purpose of the Study 9

Definition of Terms 10

Chapter 2: Literature Review 13

Introduction 13

Theoretical and Conceptual Framework 14

Further Research Needed 17

Shortcomings of the Previous Research 18

Critiques of the Literature 20

Factors Associated with Attention Problems in Preschoolers 21

Impact of Media Use on a Child’s Attention Span 22

Problems with Focus in Preschoolers 23

Attention and Cognitive Development in Kindergarten 26

Significance of Children’s Concentration-Persistence for Future Success 29

Strategies to Improve Attention Spans 32

Teacher-Directed Reading 32

Significance of Considering the Setting 33

Contextual Changes in Instructional Materials 34

Apprenticeship in the Classroom Language 36

Hybridity and the Growth of Third Spaces 37

Computer-based Instruction 39

Training Programs Offered by Computer-based Instruction 39

Math School-based Programs 41

Parental Involvement During Family Mealtime Conversation 42

Types of Parental Involvement Programs to Benefit Students 44

Conclusion 46

Research Question Considerations 46

Research Questions 50

Chapter 3: Methodology 52

Participants 52

Instruments 54

Procedures 56

Chapter 4: Results 64

Introduction 64

Demographic Characteristics 63

The Students Survey Results and The Response Percentage 68

The Parent/Teacher Results and The Response Percentage 70

Classroom Observations Data 72

Chapter 5: Discussion 77

Implications of the Findings 82

Implications for Future Research 82

Conclusion 82

References 85

Appendices

A Classroom Observations Data 96

B Demographic Characteristics of Potential Participants 98

C Student Survey 100

D Student Pre-Survey/Post-Survey 103

E Parent/teacher Pre-Survey/Post-Survey 105

F Student Pre-Survey/Post-Survey 107

Tables

1 Demographic Characteristics of Participants 64

2 The Students Survey Results and The Response Percentage 68

3 The Parent/Teacher Results and The Response Percentage 70

4 Classroom Observations Data 72

5 Classroom Observations Data Pivot Table 74

6 Paired Two Sample for Means of the Teachers/Parents Survey Results 75

7 Correlation Results of Students Survey 76

Figure

Title in Initial Caps and Lower Case 47

Chapter 1: Introduction

Statement of the Problem

The problem that was addressed in the study was the difficulty that pre-kindergarten students in Head-start programs had in maintaining attention while engaged in reading activities. Research showed that attention span was a critical aspect of reading development as it directly impacted a child's ability to process and understand the material they were reading (Ledford et al., 2008).

Evidence supporting the existence of the problem included studies that found pre-kindergarten students in Head-start programs often struggled with attention and focus during reading activities (Gathercole et al., 2008). Additionally, research showed that attention span in young children was a strong predictor of later academic achievement (Raver, 2002). There was a pattern of pre-kindergarten students in Head-start programs having difficulty with attention and focus during reading activities. The setting for this study took place at elementary schools in Southeastern Florida for pre-kindergarten students in Head-start programs.

Some probable causes of the problem included little parental involvement, few teacher-directed reading and computer-based instructional activities, and lack of individualized instruction (Ledford et al., 2000). The specific and feasible statement of the solution to the problem was to determine the effectiveness of different strategies. They included parental involvement, teacher-directed reading, and computer-based instruction in improving the attention spans of pre-kindergarten students in Head-start programs while they were engaged in reading activities (Tian et al., 2020).

The problem could be attributed to various factors, including the increasing use of technology in the classroom, changes in family dynamics and parenting practices, and a general decline in physical activity levels (Kim et al., 2018). Research showed that excessive screen time could lead to decreased attention spans and difficulty focusing on other tasks, such as reading (Benton et al., 1987). Additionally, some families had become more reliant on technology for entertainment and education, leading to less time spent on traditional activities such as reading together (Schuck et al., 2018). Furthermore, the sedentary lifestyle many children led back then was a contributing factor, physical activity had been linked to improved cognitive function and attention (Geri et al., 2017).

The problem of decreased attention spans in Pre-K students in Head-start programs was compounded by the fact that these children were at a critical stage in their development when their brains were rapidly forming and growing. During this time, children developed foundational skills and knowledge that set the foundation for future success in school and beyond (Basso et al., 2016).

In conclusion, the problem of decreased attention spans in Pre-K students in Head-start programs was a growing concern that impacted not only the students but also their families and teachers. The problem is a complex and could be attributed to various factors, including technology, changes in family dynamics, and a decline in physical activity (Kim et al., 2018). Given the critical stage of development these children were in, the problem had to be addressed to ensure that these students had the best chance for success in their future education and life.

The Research Problem

The research problem in the study was the gap between the desired level of attention and focus that pre-kindergarten students in Head-start programs should have while engaged in reading activities and the level of attention and focus that was observed (Bassok et al., 2016). While it was acknowledged that attention span was a critical aspect of reading development, pre-kindergarten students in Head-start programs often struggled with attention and focus during reading activities.

The gap in attention span could negatively impact their ability to process and understand the material they were reading and could also predict lower academic achievement in the future (Tang & Posner, 2009; Gaston et al., 2016). The applied solution was to investigate the strategies that could effectively close this gap and improve the attention span of pre-kindergarten students in Head-start programs.

The gap between what was desired and what was observed in this situation concerned educators, parents, and researchers. Understanding the underlying causes of this problem was essential, as finding effective solutions to improve the attention spans of pre-kindergarten students in Head-start programs was crucial (Doherty et al., 2002). This research problem was particularly relevant in the world at that time, where technology and digital devices were becoming increasingly prevalent and may have affected children's attention spans.

In general, the research problem of poor attention spans in reading of pre-K students in Head-start programs was a critical issue that deserved attention and research. By finding effective solutions, it could be ensured that pre-kindergarten students in Head-start programs received the support they needed to succeed in their education and beyond (Kim et al., 2018). A successful solution would not only benefit these students but also have a positive impact on their future academic careers and lives.

Background and Justification

The problem of difficulty in maintaining attention while engaged in reading activities among pre-kindergarten students in Head-start programs was well-documented in the literature (Reid et al., 2015). Research had shown that attention span was a critical aspect of reading development, as it directly impacted a child's ability to process and understand the material they were reading (Ledford et al., 2008). Studies had found that pre-kindergarten students in Head-start programs often struggled with attention and focus during reading activities (Gathercole et al., 2008; Wasik et al., 2009). Additionally, research had shown that attention span in young children was a strong predictor of later academic achievement (Raver, 2002).

Furthermore, parental involvement in reading activities had been shown to positively affect children's reading skills, vocabulary, and comprehension (Karweit, 1989; Wasik et al., 2009). Studies had also found that computer-based instruction could effectively improve reading skills, especially for students with poor reading skills (Kim et al., 2018). The problem of difficulty in maintaining attention while engaged in reading activities among pre-kindergarten students in Head-start programs was relevant as it could negatively impact their ability to process and understand the material they were reading and could also predict lower academic achievement in the future (Bauer & Schanzenbach, 2016). Thus, it was important to investigate strategies that could effectively improve the attention span of pre-kindergarten students in Head-start programs while they were engaged in reading activities and investigate parental involvement's.

Deficiencies in the Evidence

There were many literature sources focusing on the challenges in maintaining attention during reading activities among pre-kindergarten students enrolled in Head-start programs. However, there were still several areas that needed improvement (Kikas et al., 2018). One thing to improve on was to perform more studies that narrowed down and presented precise strategies that could successfully improve the attention span of learners in Head-starts programs during reading activities (Murray et al., 2018; Silverstein et al., 2001). Some studies explored the role of parental involvement during reading sessions, and they identified that additional research needed to be performed to assess its effectiveness (Alvarado et al., 2017). While some studies were inclined towards investigating the efficiency of computer-based instruction on reading abilities, still advanced research needed to be performed in this area to assess its effectiveness in increasing learners' attention span (Ledford et al., 2008).

Another need for the problem was more research on the long-term effects of attention span improvement on students' academic performance and success (Kook & Greenfield, 2021). While some studies investigated the relationship between attention span and academic achievement, there needed to be more research on the long-term effects of interventions to improve attention span on academic performance and success in pre-kindergarten students in Head-start programs.

Given these deficiencies in the evidence, there was a need for further research to investigate the specific strategies and parental involvement that could be effective in improving the attention span of pre-kindergarten students in Head-start programs while they were engaged in reading activities and the long-term effects of attention span improvement on students' academic performance and success (Kook & Greenfield, 2021).

Moreover, while some studies looked into how well computer-based instruction affected reading abilities, there needed to be more data on how well technology affected pre-kindergarten students in Head-start programs' attention spans when participating in reading activities (Bauer & Schanzenbach, 2016). Little study on the long-term consequences of attention span enhancement on students' academic performance and success was another area of need regarding the issue (Kook & Greenfield, 2021). Research on the long-term consequences of interventions to increase attention span on academic performance and success in pre-kindergarten students in Head-start programs still needed to be completed, despite several studies examining the association between attention span and academic achievement.

In conclusion, there were deficiencies in the evidence related to the problem of low attention span in pre-kindergarten students while reading (Basso et al., 2016). The literature needed a comprehensive understanding of the underlying causes of this problem and the effectiveness of interventions aimed at improving attention span. This study aimed to address these deficiencies and provide new insights into this important issue. Given these deficiencies, there was a need for further research to investigate the specific strategies and parental involvement that could be effective in improving the attention span of pre-kindergarten students in Head-start programs while they were engaged in reading activities and the long-term effects of attention span improvement on students' academic performance and success (Kook & Greenfield, 2021).

Audience

The audience affected by the problem of difficulty in maintaining attention while engaged in reading activities among pre-kindergarten students in Head-start programs included the pre-kindergarten students themselves, as well as their families, teachers, and the broader community. Pre-kindergarten students in Head-start programs who struggled with attention and focus during reading activities might have had difficulty processing and understanding the material, which could negatively impact their reading development and academic achievement. It could have led to difficulties in later grades and potentially impacted their future success.

In addition to the pre-kindergarten students, their families, and communities were also affected by this problem. Parents and caregivers played a critical role in supporting their children's education and development. A lack of attention span in reading could have led to difficulties in communication and bonding between children and their families (Kim et al., 2018). Furthermore, a lack of attention span could have also impacted these students' educational attainment and future success, which could have had ripple effects on their communities.

The Setting of the Study

The setting for this study took place in southeastern Florida, in a pre-kindergarten Head-start program. Head-start programs were federally funded programs that provided comprehensive early childhood education, health, nutrition, and parent involvement services to low-income children and their families. The classrooms in these programs typically included students between the ages of 3 and 5 who came from diverse socioeconomic backgrounds, and on average included 20 to 40 students.

In Southeastern Florida, pre-kindergarten was in an urban area, with classrooms and students ethnically and culturally diverse (Raver, 2002). The study focused on implementing different strategies such as parental involvement, teacher-directed reading, and computer-based instruction in these classrooms and the impact these strategies had on the attention span of pre-kindergarten students in Head-start programs while they were engaged in reading activities.

The study took place in multiple pre-kindergarten settings within the Head-Start program to provide a comprehensive understanding of the problem. It helped ensure that the study's findings were representative of the population of pre-kindergarten students in Head Start programs and were not biased by the specific characteristics of a single setting (Karweit, 1989). In conclusion, the setting's aim for the Study of Improving Attention Spans in Reading of Pre-K Students in the Head-start Program was pre-kindergarten classrooms within the Head Start program (Kook & Greenfield, 2021). This setting provided an ideal environment for observing and assessing students' attention spans and implementing interventions to improve their attention spans. (Karweit, 1989).

Researcher’s Role

In this study's context, the researcher designed and conducted the study, collected and analyzed data, and interpreted and reported the findings. The researcher was responsible for ensuring that the study was conducted ethically and rigorously, with appropriate safeguards in place to protect the rights and well-being of participants. In addition, the researcher collaborated with other members of the research team, including educators, administrators, and other professionals, as needed. This collaboration was critical in ensuring that the study was designed and implemented feasibly and that it considered the needs and perspectives of all stakeholders involved.

The researcher was also responsible for disseminating the study's findings to the wider academic community and relevant stakeholders, including educators, policymakers, families, and communities. This dissemination was critical in ensuring that the study's findings were used to inform the development of policies and programs that supported the education and development of pre-kindergarten students in Head Start programs. In conclusion, the role of the researcher in the Study of Improving Attention Spans in Reading of Pre-K Students in the Head-start Program was critical. The researcher was responsible for designing and conducting the study, collecting and analyzing data, and interpreting and reporting the findings. The researcher also collaborated with other research team members and disseminated the study findings to relevant stakeholders.

Purpose of the Study

The problem addressed in this study was the difficulty pre-kindergarten students in Head-start programs had in maintaining attention while engaged in reading activities.

The study investigated the effectiveness of different strategies, such as parental involvement, teacher-directed reading, and computer-based instruction, in improving the attention spans of pre-kindergarten students in Head-start programs while they were engaged in reading activities (Kook & Greenfield, 2021). Additionally, the study aimed to examine the role of parental involvement in promoting the attention span of pre-kindergarten students in Head-start programs while they were engaged in reading activities (Kim et al., 2018). The study sought to provide insight and evidence on the best methods to improve attention span in young children, which would benefit educators, parents, and policymakers (Wrońska et al., 2015). Ultimately, the study aimed to improve the reading development and academic achievement of pre-kindergarten students in Head-start programs, which could positively impact their future success.

The study aimed to determine the effectiveness of interventions to improve the attention span of pre-kindergarten students in Head Start programs while they engaged in reading activities (Ludwig & Phillips, 2007). This information was critical in informing the development of educational programs and policies that supported the education and development of young children in Head Start programs and provided insights into the strategies and approaches that were most effective in improving attention span and promoting success in reading activities.

Definition of Terms

The following terms were utilized throughout this study:

Computer-based instruction referred to using computers and technology to deliver educational content and assessments to students. Computer-based instruction had become increasingly popular as technology had advanced and become more widely available (Kook & Greenfield, 2021). In Pre-K and Kindergarten (VK), computer-based instruction had been used to teach various subjects, including reading. The use of computers in early childhood education has become increasingly popular as technology advanced and became more widely available (Kook & Greenfield, 2021). In Pre-K and Kindergarten (VK), computer-based instruction has been used to teach various subjects, including reading. Computer-based instruction was found to have both positive and negative effects on student learning and development.

Head-start services were for a limited number of children and their families in the United States; Head Start was a federal program that offered a wide range of early childhood education, health, nutrition, and intervention services (Hines, 2017). Initiated in 1965 as part of the War on Poverty, the program was administered by the Department of Health and Human Services and helped more than a million children annually.

PK and VPK programs prepared children for kindergarten by providing early education focusing on literacy, numeracy, and social-emotional development (Rodriguez, 2013). They also offered opportunities for children to interact with their peers, build their language and communication skills, and develop their cognitive abilities while providing parents and caregivers with support and resources.

Pre-Kindergarten (PK) and Voluntary Pre-Kindergarten (VPK) are educational programs designed for children who were 4 or 5 years old and had yet to start kindergarten (Basso et al., 2016). Public schools usually offered Pre-Kindergarten (PK) programs. They were usually free of charge to families, although some programs may have had specific requirements such as income limits or language proficiency (Basso et al., 2016). These programs were intended to provide early education to children to prepare them for kindergarten and future school success.

Small group reading was a teaching approach in which a teacher worked with a small group of students, typically 4-6, to provide targeted and differentiated instruction in reading (Kikas et al., 2018). It was an effective way to provide individualised instruction, adapt to the varying demands of children, and carefully track their development.

Teacher-directed reading was a teaching approach in which the teacher actively guided students through the reading process, providing explicit instruction, modelling, and feedback (Kikas et al., 2018). The approach emphasised the teacher's role in leading and directing the reading instruction and the student's role in actively following and engaging with the instruction. During teacher-directed reading, the teacher introduced a new text or concept, provided background knowledge, and sought a reading purpose (Lerkkanen et al., 2016). Then the teacher modelled the reading process, demonstrating strategies such as how to make predictions, identify main ideas, or use context clues. Next, the students practised these strategies with the teacher's guidance, asking and answering questions, making connections, and applying their learned strategies.

These services were designed to enhance students' cognitive knowledge and foster their social and emotional growth to prepare them for school success (Bauer & Schanzenbach, 2016). The program provided early childhood education that included activities that helped children develop social and emotional, as well as language, reading, and numeracy skills (Pianta et al., 2021). The program also provided health and nutrition services, such as physical exams, dental care, and nutrition education, to help ensure that children were healthy and ready to learn.

Voluntary Pre-Kindergarten (VPK) was a state-funded program in some states, such as Florida. It was intended to provide free educational opportunities for children four years old before kindergarten (Basso et al., 2016). The program was made available by public and commercial providers, and the teaching followed state-mandated guidelines that concentrate on educational, social, and emotional growth.

Chapter 2: Literature Review

Introduction

Scholarly materials on improving attention spans in the reading of pre-kindergarten students in Head-start programs showed that attention span was a critical aspect of reading development. Studies found that pre-kindergarten students in Head-start programs often struggled with attention and focus during reading activities (Gathercole et al., 2008; Wasik et al., 2009). Research also showed that attention span in young children was a strong predictor of later academic achievement (Raver, 2002).

Several studies also investigated the effectiveness of different strategies in promoting the attention span of pre-kindergarten students in Head-start programs while they were engaged in reading activities. For example, parental involvement in reading activities was shown to positively affect children's reading skills, vocabulary, and comprehension (Karweit, 1989; Wasik et al., 2009). Additionally, studies found that computer-based instruction could effectively improve reading skills, especially for students with poor reading skills (Kim et al., 2018).

This section synthesized the existing research on attention span, reading activities, and pre-kindergarten students in Head Start programs. The review focused on identifying the effective interventions that improved attention span in young children, as well as exploring the underlying mechanisms and processes that contributed to changes in attention span (Basso et al., 2016). The review also examined the factors that may have influenced the effectiveness of interventions, such as the age of the students, the setting in which the interventions were implemented, and the type and intensity of the interventions.

Theoretical Framework

Theories on Reading Development

Different theories on reading development among childrens in Pre-kindergarten Headstart Programs provide a description of the different stages through which students develop reading skills from early development stages to advanced levels. A study by Laws (2010) identifies that students start by relying on visual recognition of the entire written word and relate it to its pronunciation a stage identified as logographic stage. This phase relies on understanding each printed word together with its oral form. Afterwards, the children progress to alphabetic stage and can understand the world based on the knowledge from letter sounds.

Another theory is the Knowledge hypothesis by Anderson and Freebody which suggests that knowledge of words is a reflection of students’ background knowledge and a plan of the topic. Therefore understanding the meaning of phrases and words used within texts as well as the meaning of the word within the context of precise types of texts is integral in helping students to understand the text (Baker et al., 2014). On the contrary, Kintsch’s theory on discourse comprehension theory pinpoints that it is critical for adults to pose questions to their children and to develop activities that will stimulate deep thinking and aid to construct diverse knowledge of vocabularly. Deep learning requires integration of prior information with the new knowledge and the outcome is the prowes to use the newly information within new contexts (Baker et al., 2014).

Theory of Attention

Unusual was the notion that children exhibited signs of attention. A child may have found it challenging to be in an environment with several readily distracting stimuli. It took work to concentrate on more than just one item. Rojas (2016) asserted that many individuals frequently failed to pay attention. They needed help to maintain their focus on what was most essential at any given time.

According to Brendamour & Chai (2016), paying attention involved six distinct components. Several examples included attention span, previewing and planning, selectivity and saliency evaluation, distractibility, alertness and arousal, self-monitoring and self-regulation, and attention. Awareness was the initial stage in attracting someone's attention to the previously listed topics. This study argued that to concentrate, one must be actively engaged in an activity. The next step was exercising discretion. At any one moment, many stimuli continuously entered the system (Brendamour & Chai, 2016). The brain had to choose which of these goals should be prioritized. The ability to pick which organization-influencing actions to do was the "determination of salience." This component was essential for daily tasks. The teacher would offer the essential instructions for the pupils to execute a task in class. Since writing all laws on paper was impossible, the brain had to choose the most significant ones. The capacity to rapidly shift attention was the third need for attracting notice.

Attention required the perseverance and stamina necessary to complete the task at hand. Like the requirement for physical energy to run a marathon, mental energy was required to maintain concentration while working. The next step included preliminary planning and analysis. Before launching a project, it was essential to analyze all possible outcomes and choose the strategy that would provide the best results (Brendamour & Chai, 2016). Before raising their hands to respond to a question on the teacher's presentation, students had to carefully consider their answers and refrain from shouting. The next phase of responsibilities included self-control and self-monitoring. This was an essential step, especially when a project was well along. Enhanced self-discipline and behavior monitoring boosted concentration.

Mackay (1973) aimed to clarify and explain the information filtering process. Using the bottleneck approach, the author illustrated how the water flow reduced as the bottleneck grew narrower. According to the Broadbent’s attention model, it was difficult for a person to absorb several sources of sensory information simultaneously. Donald Broadbent pioneered the vast majority of data processing technologies. He conducted a study on air traffic controller operations. Broadbent conducted a "dichotic listening" study to understand this issue better. Mackay (1973) asserted that all input data was stored in a sensory buffer before being processed further and that one input was then selected based on its physical properties. Because our capacity to absorb information was limited, a filter had been devised to protect us from being exposed to overwhelming data. In addition, he asserted that unselected inputs were still there after the sensory buffer had been cleared. Broadbent was captivated by the processes that enabled individuals to focus their attention (selective attention). He bombarded them with stimuli to achieve his goal. The data revealed unequivocally that individuals could concentrate on more than one activity simultaneously.

Consequently, the author developed the "filter" concept and the "single channel" technique. This method considered the sensory information that different physical qualities gave. According to the research results, external stimuli were one of the most effective methods to boost a person's capacity to concentrate for an extended time (Washington, 2017). The brain would be better able to focus and pay attention to the task at hand if the activity and instructions were presented one at a time. During a fine mobility task, such as threading a button onto a bottle, the brain could focus on a single action, such as picking up the button. Unselected inputs remain after the sensory buffer has been cleared, according to Mackay (1973). Broadbent was fascinated by the processes that enable individuals to focus their attention (selective attention). To achieve his goal, he bombarded them with stimuli. The data revealed that individuals could concentrate on more than one activity simultaneously. Consequently, the author developed the "filter" concept and the "single channel" technique. This method considers the sensory information that different physical qualities give. According to the research results, external stimuli are one of the most effective methods to boost a person's capacity to concentrate for an extended time (Washington, 2017). The brain will be better able to focus and pay attention to the task at hand if the activity and instructions are presented one at a time.

Further Research Needed

Further research on improving attention spans in pre-kindergarten students in Head Start programs should build upon the foundation of previous studies while also seeking to address some of the limitations and gaps in the existing evidence (Vaughn et al., 2002). It can be done by replicating previous studies to confirm the effectiveness of various interventions and by conducting new studies that test different interventions or explore new perspectives on the problem (Ludwig & Phillips, 2007).

One critical variable that future research should consider is the role of individual differences in attention span and reading ability, as well as other factors that may contribute to these difficulties, such as socioeconomic status, parental involvement, and access to resources reference. By exploring these factors, researchers can understand the problem and develop more effective interventions considering individual students' unique needs and circumstances.

Another important area for future research is the effectiveness of technology-based interventions in improving attention span and reading ability in pre-kindergarten students in Head Start programs (Ludwig & Phillips, 2007). While previous studies have shown that these interventions can be effective, much is still to be learned about the best way to use technology to support student learning and how these interventions can be integrated into existing educational programs and practices.

Future research needs to address how to sustain the gains in attention span and reading ability achieved through various interventions (Bauer & Schanzenbach, 2016). It will require long-term studies that track the outcomes of students over time, as well as research into how schools and educators can support and reinforce the gains achieved through these interventions.

In conclusion, there is a clear need for further research on the problem of attention span in pre-kindergarten students in Head Start programs to build on the foundation of previous studies and address some of the limitations and gaps in the existing evidence (Vaughn et al., 2002). By exploring critical variables and important questions in this area, researchers can gain a deeper understanding of the problem and develop more effective interventions that support the academic success of these young students (Basso et al., 2016).

Shortcomings of the Previous Research

It is crucial to evaluate the advantages of earlier studies and pinpoint their drawbacks to avoid them in future studies while reviewing the literature on increasing the attention spans of pre-kindergarten pupils in Head Start programs. By doing this, researchers may improve upon the shortcomings of earlier studies and build on their strengths.

One of the areas for improvement of prior research in this area is a need for more consistency in measuring attention span and reading ability. It can make it difficult to compare the results of different studies and to draw accurate conclusions about the effectiveness of different interventions (Basso et al., 2016). To avoid this limitation, future research should use consistent measures and make efforts to standardize these measures across different studies.

Another limitation of previous research was that many studies had been conducted with small sample sizes, which limited their findings' generalizability (Bauer & Schanzenbach, 2016). To address this limitation, future research aimed to include larger sample sizes, especially when testing new interventions, which could increase the study's power and allow for more accurate conclusions about the effectiveness of these interventions (Ludwig & Phillips, 2007).

Additionally, much earlier research focused on rapid results after the intervention, such as attention span and reading skills (Ludwig & Phillips, 2007). However, it was important also to consider the long-term outcomes of these interventions and how they may impact students over time. To address this limitation, future research included longer-term follow-up assessments to track the sustainability of any gains in attention span and reading ability (Yoon et al., 2007).

On the other hand, some of the strengths needed to be investigated more in future studies. Using control groups, which helped account for uncontrollable factors and provided more accurate evaluations of the efficacy of treatments, was one of these advantages (Bauer & Schanzenbach, 2016). Utilising randomised controlled trials, which improved the study's internal validity and offered greater proof of the efficacy of therapies, was another strength.

In conclusion, by identifying the shortcomings of prior research and building upon their strengths, researchers were able to conduct more effective and robust studies on improving attention spans in pre-kindergarten students in Head Start programs (Vaughn et al., 2002). By doing so, researchers could contribute to a growing body of knowledge in this area and provide valuable insights into how to support the academic success of these young students.

Critiques of the Literature

The literature review was an important foundation for any research proposal, as it provided a comprehensive understanding of the existing evidence on a given topic. However, it was also important to critically evaluate the literature to identify any controversial methodological decisions that may have needed to be addressed in the proposal (Bauer & Schanzenbach, 2016). This essay critiqued the literature on improving attention spans in pre-kindergarten students in Head Start programs, highlighting some of the controversies and limitations of previous studies that needed to be considered when designing a new study.

One of the controversies in the literature on this topic was the use of different measures to assess attention span and reading ability (Basso et al., 2016). While some studies used standardized measures, others used more informal assessments or subjective ratings by teachers or parents. This variability in measures could have made it difficult to compare the results of different studies and draw accurate conclusions about the effectiveness of different interventions. As such, researchers needed to carefully consider which measures to use in their study, considering the strengths and limitations of each measure, to ensure that their results were accurate and reliable (Basso et al., 2016).

Another controversy in the literature was the need for more consensus on the most effective interventions for improving attention span and reading ability in pre-kindergarten students in Head Start programs (Gathercole et al., 2008). Some studies had focused on providing additional educational resources, while others had focused on behavioral interventions, such as reward systems or educational games (Ludwig & Phillips, 2007). With these interventions, variability made it difficult to determine which approach was most effective, and researchers had to consider this when designing their study.

Additionally, there needed to be long-term studies on the impact of interventions on this population's attention span and reading ability. While some studies had shown positive short-term effects, it was still being determined whether these effects were sustainable over time or how they may impact students in the long term. (Wasik et al., 2009). As such, researchers needed to consider the need for longer-term follow-up assessments to understand the impact of interventions on this population fully.

In conclusion, the literature on improving attention spans in pre-kindergarten students in Head Start programs highlighted several controversies and limitations that needed to be taken into consideration when designing a new study (Basso et al., 2016). By critically evaluating the literature, researchers could make informed decisions about the measures to use and the interventions to focus on. There was a need for longer-term follow-up assessments to contribute to a growing body of knowledge in this area which could provide valuable insights into how to support the academic success of these young students (Peck et al., 2005).

Factors Associated with Attention Problems in Preschoolers

It was believed that environmental (Washington, 2017) variables had a major role in influencing a child’s behavior development. Research by Biederman and Faraone (2002) had revealed a genetic link among early developmental variances in newborns' attentional control. In a recent study that followed over 2,000 Canadian children from 5 months to 8 years, preterm birth, low birth weight, prenatal tobacco exposure, non-intact family, young maternal age, paternal history of antisocial behavior, and maternal depression were found to be the strongest early predictors of attention problems. In this longitudinal study, children between the ages of 5 months and eight years were investigated (Washington, 2017). Similar to the preceding example, a recent Israeli study discovered that various child developmental characteristics were substantially associated with the later occurrence of ADHD (from birth to one month. Among these risk variables were a family history of social problems and ADHD, a lower maternal education level, and an older maternal age. Between the ages of 3 and 18 months, a smaller head size, a delay in reaching motor and verbal milestones, and a demanding temperament were all highly associated with the later development of ADHD. As part of the Family Life Project, researchers studied the behavior of children aged three to five. Their objective was to determine the risk variables for attention deficit disorders. They concluded that a single latent factor remained throughout the preschool years and triggered the appearance of symptoms of inattention and hyperactivity. They also noticed that the degree of education of the carers was the greatest predictor of symptom severity (Mackay, 1973).

Impact of Media Use on a Child’s Attention Span

Since the beginning of the last decade, concerns about young children's use of screen media and the link between this behavior and the appearance of attention issues at a younger age had progressively increased. The National Longitudinal Survey of Youth indicated a correlation between daily television watching between the ages of 1 and 3 and attention issues at age 7. Some studies indicated that brief exposure to television might have had an immediate effect on the cognitive development of youngsters (Mackay, 1973).

According to newly published research, children who had just seen a fast-paced television show—specifically, a well-known animated cartoon about an underwater sponge—performed lower on the Tower of Hanoi test than children who had not seen the program (Lillard & Peterson, 2011). It was unknown if increased television viewing added to or accelerated a reduction in attention span. The American Academy of Pediatrics (AAP) advised against restricting screen time for infants younger than two years of age and against permitting older children to watch more than one to two hours of high-quality media daily (Lillard & Peterson, 2011). A study by Dunckley (2015) pinpointed that indeed increased screen time was directly associated with increased child’s mood swings and deteriorated attention span as well as language and cognitive development .

Problems with Focus in Preschoolers

Children's attention problems were often a feature of early infancy. Up to 40% of preschool-aged children already had attention problems that were serious enough to worry parents and preschool teachers (Lillard & Peterson, 2011). Between 3% and 15% of people in community samples, including those who did not meet the requirements for an ADHD diagnosis, exhibited signs of inattention. Mahone (2005) observed that the percentage of clinical referrals approached or exceeded 50% (Mahone, 2005). For instance, up to 72.7% of toddlers were labelled as "motor-driven" or "constantly active" (Lillard & Peterson, 2011). When toddlers exhibited inattention, attention deficit hyperactivity disorder (ADHD) was seldom identified. It might be a sign of various illnesses or ailments, such as hearing loss, language difficulties, intellectual disabilities, or other psychopathologies, that coexisted with ADHD. It was more difficult to identify "disordered" attention, given the variance in caregiver perceptions of attention and the prevalence of ADHD symptoms in this age range (Mahone, 2005).

However, inattention was a common trait unrelated to early childhood development (Mahone, 2005). Preschoolers with attention issues were better detected and treated during the last 20 years, especially those disorders that shared symptoms with ADHD, such as distractibility and hyperactivity. The United States and other countries became more interested in this (Mahone, 2005). Some theories contended that early detection and treatment of attention problems reduced the negative impacts of pediatric illnesses, making it simpler to get the right diagnosis or, more crucially, proving that no diagnostic was required.

The most common condition seen in preschoolers was Attention Deficit Hyperactivity Disorder (ADHD), and prevalence estimates showed that it was becoming increasingly common. Two percent of children in a sample of 38,666 general pediatric patients under the age of five were found to have ADHD, according to Mahone et al., (2005), even though Connor (2000) claimed that the incidence might reach 59% in child psychiatric clinics. Participants in each of these studies were under the age of five. Subsequent research assessed 200 children under six who had been sent to an outpatient mental health clinic, and 86% met the diagnostic criteria for ADHD. Compared to their generally developing classmates, preschoolers with poor attentional abilities were substantially more likely to have social, developmental, and academic challenges. These worries could be linked to many developmental deficiencies.

Childhood attention problems were linked to teens' poor social development and a higher risk of requiring emergency medical care (Mahone et al., 2005). Attention deficit hyperactivity disorder (ADHD) in early childhood was linked to later academic failure and grade retention, even at subthreshold levels (Mahone & Schneider, 2012). Six years later, children with behavioral issues were more likely to fulfill the official diagnostic criteria for ADHD. By 18, these children were far more likely than other children to experience sadness and suicidal thoughts. The Centers for Disease Control and Prevention revealed that between 1998 and 2009, one in eleven American children between the ages of 5 and 17 had been given an ADHD diagnosis (CDC).

In contrast, during the last 20 years, there was a sharp increase in the proportion of young women with attention problems. A recent, extensive epidemiological study including 3,907 children showed that 49% of females and 51% of boys had ADHD. The research had found that 8.7% of children met the DSM-IV-TR criteria for ADHD, making it difficult to discern between attentional issues affecting normally developing children and those specifically linked with ADHD (or other co-occurring illnesses) until the age of four. However, early identification and treatment of preschoolers' attention deficit disorders may lessen some negative effects. Although early identification and treatment of toddlers' attention issues may lessen their negative effects, this was the case (Mahone & Schneider, 2012). Studies showed that future reading, spelling, and arithmetic difficulties were more probable in children with the inattentive ADHD subtype. However, youngsters who initially exhibited unusually impulsive and hyperactive traits were more likely to acquire ADHD later. While Egger and colleagues found that the inattentive subtype of ADHD was present in fewer than one in 1,000 preschoolers in the general population, other studies questioned the importance of this subtype throughout the preschool years.

Others questioned the applicability of the Hyperactive-Impulsive subtype of ADHD to young children (Mahone & Schneider, 2012). Therefore, it was essential to establish exact, impartial methods for assessing newborns' attention. Based on individuals who used the criterion's expectations, diagnostic thresholds were often noticed (such as parents and teachers). As a result, the definition of a "disorder" could alter over time. Additionally, relying only on a child's parents or teachers to describe their symptoms might result in an overdiagnosis.

Additionally, fewer kids were diagnosed with ADHD when the impairment criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR; American Psychiatric Association—APA, 2000) were carefully followed (Mahone & Hoffman, 2007). Although ADHD was currently classified as a categorical phenomenon in the DSM-IV-TR, it was anticipated that these changes would be made in the DSM-V. Due to the potential that the condition displayed dimensional oscillations rather than a category item, this was the circumstance (Mahone & Schneider, 2012).

Attention and Cognitive Development in Kindergarten

The development of the neurological system could be seen beginning two to three weeks after conception (Mahone & Hoffman, 2007). The brain's attentional control mechanisms were among the earliest to emerge and continued to grow until early adulthood. The route of functional development, however, did not follow a linear pattern; rather, it moved along a region-specific path that reflected the maturity of several brain systems. A child's brain achieved 80% of an adult's size by age two (Delevan, 2009). When a child reached two, myelination and synapse development stopped occurring, and neurons started forming complicated dendritic trees. While the main auditory cortex began to develop at three months old, the prefrontal cortex only matured at fifteen months.

After age five, cortical architecture, ongoing neuronal growth, and experience-dependent pruning of ineffective synapses were the hallmarks of brain development. Synaptic density eventually decreased to 60% of its prior high (Delevan, 2009). The dynamic process of moulding and limiting skills via experience, which could change the expression of genes, and a process of active brain growth, which was mostly genetically determined, impacted the functional development of attention throughout the preschool years (Mahone & Hoffman, 2007). According to (Mahone & Hoffman, 2007), experiential canalisation was a theory outlining how biology and experience combined to provide useful development. This "shaping" occurred throughout normal development due to enhanced myelination and cortical thinning. It happened inadvertently all through development and was linked to improvements in attentional control. Developmental issues with attention, such as ADHD and others, could result from aberrant pruning fuelled by experience.

The prefrontal cortex had to undergo a lengthy process that started early childhood and lasted far into adolescence to acquire regulated (top-down) attention. The prefrontal cortex experienced several quick alterations at this age that lasted well into early adulthood (Luna et al., 2001). Evidence suggested that the prefrontal cortex developed and connected throughout early life, resulting in top-down attention management and other "higher" cognitive functions. Electrophysiology was the most popular technique for assessing infants and children's prefrontal development. Thus, frontal EEG power, thought to indicate neural excitability, was associated with regulated attention in infants.

The development of a person's attentional capacity was often assessed behaviorally during the first year of life using several visual attention paradigms (Luna et al., 2001). Frequent, protracted visual fixations characterised the first three months of a baby's existence. It was due to the visual attraction that young toddlers had for objects with curves and edges, like faces or checkerboards, for example. At this age, infants found it difficult to concentrate on anything beyond what was in front of them. The unrealised developmental potential of the parietal lobes was thought to be the root of this problem, and pathways from the basal ganglia to the superior colliculus had begun to enlarge (Luna et al., 2001). Habituation and paired comparison were two common experimental paradigms with infants. The tools used to gauge a baby's growth currently encompassed variations of both concepts.

The emergence of an infant's preference for novel experiences was thought to be linked with the development of the parietal cortex and the cortical visual system, typically occurring between the ages of four and six months. Infants reached this stage when they stopped staring at things for lengthy periods. The duration of the gaze lengthened between 7 and 12 months and changed from automatic to conscious control. This growth continued throughout the toddler and preschool years (Rossi et al., 2001).

According to their gender, boys and girls developed brain networks that aided attentional management at noticeably different rates (Rossi et al., 2001). Folklore held that females started school a year sooner than boys because they were three weeks more developed at birth (Delevan, 2009). Although there was less focus on gender differences in problem behavior in infancy and the early years, by the age of 4, boys tended to behave more aggressively and impulsively than girls. Due to their earlier neurobiological, cognitive, motor, and social development in early infancy, females may have exhibited certain behaviors that delayed the onset of some ADHD symptoms in young children. The quantity of white matter increased linearly between the ages of 4 and 20. In contrast, the changes in gray matter were discovered to be nonlinear, regionally specific, and different for boys and girls. Men's brains had 10% more gray matter than women's, although women's peak development occurred considerably younger (10.5 years vs 14 years).

Significance of Children's Concentration-Persistence for Future Success

Throughout childhood, various social and academic outcomes were related to several attention spans and perseverance characteristics. It was shown, for instance, that attention span persistence and related concepts such as self-regulation, executive function, and effortful control could be used to predict more severe social outcomes, such as social competence and maladjustment (Delevan, 2009). Furthermore, these components were essential for both social and emotional rehabilitation. Extensive research showed, for instance, a correlation between attention span, perseverance, and associated attributes such as self-control (Duncan et al., 2007). The capacity of children to pay attention and endure challenging situations was always assessed, even though different research employed varied criteria and methods. Research on executive function, learning-related abilities, effortful control, and behavioural regulation would be helpful in improving knowledge in this area. Each of these investigations constructed and employed unique structures while considering attention span persistence.

A recent study showed that attention span perseverance was a robust predictor of short-term performance outcomes, even after accounting for the student's current level of achievement and other relevant traits, such as intelligence (Delevan, 2009). The researchers discovered, for instance, that changes in early behavioural management throughout the preschool year highly predicted changes in reading, mathematics, and vocabulary. Even when researchers considered individuals' behavioural control and accomplishment starting points, this remained the case (Rossi et al., 2001). Children's ability to manage their behaviour at the start of kindergarten was an outstanding predictor of their success in reading, mathematics, and vocabulary at the end of the school year, as well as their improvement in arithmetic skills, according to a comparative study. Another research found favourable relationships between young children's attention spans, cognitive capacities, and achievement levels (Duncan et al., 2007). Reading and arithmetic competence between kindergarten and sixth grade and reading and math progress between kindergarten and second grade were strongly predicted by a child's learning-related skills in kindergarten. It was unaffected by the child's IQ, early achievement, and other environmental circumstances (Duncan et al., 2007).

Several components of attention management abilities accurately predicted academic achievement and long-term performance. Attention between the ages of 5 and 6, with an average effect size ranging from 0.08 to 0.11 for reading and mathematics, was a strong predictor of reading and arithmetic ability between kindergarten and the beginning of puberty. This circumstance negatively impacted reading and mathematics (Duncan et al., 2007). Even though it was conducted on adolescents, recent research by (Yoon et al., 2007) offered more evidence of the significance of attention span persistence, also known as task persistence, for future performance. Task perseverance in early adolescence at age 13 reliably predicted males' middle-aged income, occupational level, and educational attainment, with impact sizes ranging from 0.08 to 0.34 for occupational level. Important studies have shown that early self-control, operationalised by perseverance and attention span, predicted adult outcomes such as physical health, drug dependency, income, and criminal conduct (Yoon et al., 2007). In addition, research connected concentration deficits to poorer academic achievement and performance standards. After adjusting for various background characteristics, such as the child's IQ, recent research found that teacher evaluations of concentration issues at age six strongly predicted math and reading achievement at age seventeen.

This research demonstrated that attention and persistence were critical in infancy and reliable predictors of various social and academic accomplishments in adulthood. Overall, these findings supported the notion that toddlers needed these skills. Important life objectives, such as graduating from college, depended highly on concentration and perseverance under adversity. Another study indicated that a parent's socioeconomic status (SES), cognitive ability, past academic accomplishment, and educational and professional aspirations substantially affected a child's intellectual development and academic performance (Yoon et al., 2007). Along with parental socioeconomic status, early cognitive ability and academic performance, gender, and age, it was expected that early attention span perseverance would be a major and substantial predictor of future accomplishment and college completion.

In summary, the literature on improving attention spans in pre-kindergarten students in Head Start programs highlighted the importance of this issue and provided a foundation for further research (Basso et al., 2016). However, the literature also highlighted controversies and limitations, such as variability in measures used, lack of consensus on effective interventions, and the need for longer-term studies (Ludwig & Phillips, 2007). It was important for researchers to critically evaluate the literature to address these limitations and make informed decisions about their study (Kim et al., 2018). By doing so, researchers could contribute to the growing body of knowledge in this area and provide valuable insights into how to support the academic success of young students in Head Start programs (Kerns et al.,1999).

Strategies to Improve Attention Spans

Various strategies could be employed to help improve the attention spans of pre-K students in Head-start programs (Antzaka et al., 2017; Armstrong, 2017). First, high-quality materials with interesting topics and engaging illustrations should have been selected. Additionally, text sections should have been kept short, with frequent breaks in between (Bauer& Schanzenbach, 2016). Teachers could have also provided activities to help support the reading material, such as drawing or coloring activities related to the text. Furthermore, providing students with positive feedback and recognition for their efforts could have kept them motivated and engaged. Also, allowing students to share their thoughts and ideas about the material could have helped further engage them and keep their attention.

Teacher-Directed Reading

Research affirmed a positive relationship between affluent experiences during early childhood and later language growth and academic success. Many experts were familiar with the relationship between child language development and parent input; however, much remained to be learned regarding the relationship between a child's language growth outcomes and an educator's language input. Classroom-oriented research was required since existing research illustrated differences in the impact of parent and teacher input in association with children's language development. Most of the children's vocabulary development and teacher's language use were satisfactory during book reading interaction. However, there was minimal attention to other forms of a classroom setting (Kirk et al., 2014). Various efforts to alter teachers' language practices via large-scale intervention yielded limited success.

Significance of Considering the Setting

An essential phase to sustain high-quality instructional relations should have been understanding how the entire process could have been made neutral without any involvement. Teacher-directed activities could have formed a classroom environment that provided abundant data regarding implementing superior instructional interaction in Pre-K Students in a Head-start Program setting. Scholarly evidence identified that pre-k students spent approximately 37% of their school day performing teacher-directed events not limited to literacy, math, science, and other events that were not directly linked to any precise context (Bames et al., 2020). The student spent the rest of the day doing other activities, such as mealtimes and playtime. The different forms of contexts availed numerous opportunities for the teacher to instruct, interact, and engage with events. Teacher-directed activities could have been more intentional, especially when the teacher was executing strategies to enhance the child's cognitive and language skills. Research indicated that Pre-k educators were more likely to use thought-provoking language with students during book-reading sessions than free play or mealtimes. Additionally, the teachers were most likely to deliver excellent instructional interaction during sessions that involved large-group surroundings, unlike during meals, play, and routine settings (Blair & Razza, 2007). These activities were focused on enhancing teacher-child association, thus increasing chances for high-quality instructional relationships.

Contextual Changes in Instructional Materials

This section explored the importance of improving the value of instructional materials to augment learning and teaching. The background of teacher-directed activities was broken down into sub-contexts depending on the coverage of instructions. These sub-contexts were a prosperous source of introducing variation in the superiority of instructional interaction. An activity like reading was an example of a teacher-directed practice that different scholars researched, given its potential to offer language-based cognitive learning during the head start of the program. Pre-k students were expected to experience superior coaching during the storybook reading session because of the mutual routine of mutual book reading, as it designated a diverse group of pedagogical techniques widely accepted for interacting with students in a text. Interactive shared storybook reading sessions contained techniques such as requesting the students to predict events happening in a particular book before they could read it. The teacher worked with them in discussing the story to aid in understanding and developing relations to the child's lives and explain the significance of different vocabularies used in the text. These strategies and other activities played an integral role in engaging children in high-order thinking within the story's context. To determine the efficiency of this strategy, a study was performed by Hysell (2013) involving pre-k classrooms that served low-income children. The scholar evaluated the different types of questions educators asked during class activities. The teacher posed several cognitively perplexing and open-ended questions throughout the storybook reading session related to other types of teacher-directed events such as mealtime. The researchers found that storybook reading was providing higher-quality instructional association than other learning tasks.

Science learning was the other sub-context that facilitated higher-quality instructional association. Posing scientific-related questions was defined as the attempts to enable pre-k students to understand the natural world around them based on proof. To effectively attract the maximum reading span of the students during this sub-context, the teacher focused on asking questions that would capture the students' interest in high-order thinking. Research proved that pre-k students should not be exempted from learning science because, with the necessary support from adults, they could engage in science practices and develop a theoretical understanding as they navigated their environment (White et al., 2020). The current curriculum and state standards for kindergarten included different science concepts such as weather and plants.

The next category of sub-context was math instruction. Teachers facilitated conversations with the children using informal and formal instruction to enhance their understanding and skills on different concepts important to improve mathematical accomplishment (Klein et al., 2008). These types of interaction were linked to lower skills, including labeling numbers, counting objects, integrating counting grounded on techniques for tallying, requesting children to recap simple patterns, and offering opportunities to categorize objects into their respective groups. Recent research identified that many pre-k school teachers focused on engaging their students to lower-level mathematics knowledge and rarely used conversation-based mathematical skills. The morning meeting was an entire group activity that marked the beginning of a preschool day. Even if this sub-context did not provide students with an opportunity to learn a particular content within the area of instruction, it qualified as a teacher-directed event. This activity was significant for early childhood curriculum, and many schools already integrated morning meetings or circle time as a daily routine. During this time, the teacher had an opportunity to orient the students on the activities of the day and lead them in routines, including greeting one another, singing, talking about the weather of the day, taking attendance, and rehearsing academic skills (Bierman et al., 2008). Recent research assessing the effectiveness of circle time identified that the teacher could preside during this time of the day, posing several open-ended questions and introducing interactive exchanges. This differed from the traditional circle setting, where students typically recited and memorized the day's routine.

Apprenticeship in the Classroom Language

The usage-based theory of language development recognized the impact of linguistic input in early childhood language development (Tomasello, 2009). Adequate groups of complex language were made available for children to understand equally complex speech. Pre-k students first got exposure to home registers, which could be different from academic registers they came across in the classroom setting, as the two differed in content and involvement. A home register took the form of a conceptualization of informal talk. It usually discussed matters relating to tasks, stressed interpersonal relationships, and was similarly common among family speakers (Kook & Greenfield, 2021). This differed substantially from the language used in the classroom setting as it allowed the student to experience a seamless transition of academic knowledge. It differed among speakers and relied on lexical aspects to encourage precision and clarity. When the academic register was at the linguistic level, the register comprised academic language characterized by a lot of vocabulary and terms used among specific fields or across various academic disciplines. Vocabulary used in the academic field was employed on rare occasions in casual conversations, although it was found in large volumes within academic contexts. Therefore, when pre-k students in Head-start Programs were exposed to a more significant amount of sophisticated or academic vocabulary, they became knowledgeable about academic vocabulary, which helped them increase their reading span in different subjects such as math, science, religious education, and social studies in higher levels of education. When the register was at the discourse level, the topic or content of the talk widely focused on the exchange of disciplinary content knowledge in different subjects, including science, math, social studies, and language arts. Preschool children became proficient in their home language once they entered school but could have varied comprehension of the classroom register due to a lack of experience before. Different ethnographic and quantitative studies identified that children raised in low-income homes needed more experience with academic vocabulary and register specifically. Proficiency in academic language was directly related to outstanding academic success, particularly in association with reading and understanding comprehension. Therefore, the children who were enrolled in pre-k classes with vast familiarity with the academic registry had a considerable advantage in understanding classroom conversations and examinations compared to the students with less experience with academic vocabulary and register (Tyler, 2010).

Hybridity and the Growth of Third Spaces

The pre-kindergarten class setting was usually made of numerous poly-contextual activities and spaces. This was different from the more formalized spaces and structures of pre-K school settings, which were characterized by whiteboards, desks, and reading tables, as the spaces of the pre-K school classroom were made of spaces to read, play, nap, and eat. These activities and places encouraged different language registers, developed rich learning objectives, and executed social practices. One outstanding space in many Head Start class settings was the eating area. The Head Start programs provided a meal to the students which were served in a family style and within the confinement of the classroom. Students and their teachers sat around this eating area during lunch and breakfast and ate their meals with the students. The food was passed around in serving dishes, and the teachers taught the students how to serve themselves (LiBetti, 2019). The practice was guided by the Head Start policy, which provisioned that every pre-kindergarten must supply the students with nutritious meals daily and provided clear guidance on appropriate family-style meal structure. Therefore, this area was unique because it acted as the bridge between school-home practices and could thus be considered a hybrid space. Hybrid spaces usually comprised different elements of both school and home practices by taking the form of similarity in registers, activities, and social traditions. These spaces were categorized within the child's zones of proximal growth as they used familiar practices to interact in conversations and meal routines within the relatively newer classroom settings (Nash et al., 2022). This form of hybridity could create a conducive environment for language development since mealtime talk between the students and the teacher could support children to transition into the classroom register successfully. In this third space, the teachers and students had the opportunity to familiarize themselves with the discourse patterns of their communities and homes to converse and establish academic language and knowledge supported by the conducive classroom environment (Gillula et al., 2011).

Computer-based Instruction

Research has proven that computer-based interaction had the potential to intensify pre-k students' reading span due to the ease with which it could be integrated with the school settings and the seamless ability for its users to customize it to suit the different needs of the student (Hercules et al., 2006). Another benefit of this model was that it developed a child's cognitive skills and kept track of their academic progress in various subjects such as language and math.

Training Programs Offered by Computer-based Instruction

Executive Functions Training

These programs were classified under a group of overall purpose mechanisms that controlled cognition and action. The program comprised three interrelated, albeit distinguished, components that made the consumer move back and forth between different operations, tasks, and mental sets. The user also updated the program, which was a process that needed monitoring and active manipulation of working memory representations and reservation, which was the ability to inhibit an automatic, dominant, or prepotent response intentionally (Huffstetter et al., 2010). These cognitive skills were identified to have a positive relationship with different socioemotional and academic outcomes, including adaptive learning of related behaviors, mathematical accomplishment, and social competencies.

During the school sessions, kindergarten students had to encounter social and academic problems that needed them to integrate executive functions successfully. An example was when a student needed to switch from one subject to the other and change from one academic task to the other and from one skill to another to respond to the instruction provided by the teacher. The student also had to manipulate and memorize academic information and drop unnecessary information while adding new information to their existing skill set (Juhasz & Boyce, 2022). Nonetheless, children needed to showcase robust and automatic responses, such as avoiding getting distracted by their friends and retaining their attention on what the teacher was saying. These executive skills empowered children to learn self-regulation from certain behaviors while focusing on improving their academic performance.

Executive functions were central in guaranteeing the student's successful reading skills development. Therefore, different training programs were established to empower the children's executive function skills, starting with the Head-start program. For example, the mind curriculum implemented different tools oriented on harmonizing activities embedded within the school curriculum and was not limited to tasks to self-regulate confidential speech. The program also comprised intense dramatic role-playing and enabled attention and memory of the concepts learned in class. Bierman et al. (2020) performed research in one school that involved children aged between 4 and 5 years who had received pre-k education for one year. Their teachers had spent about 80% of the school day promoting executive function skills (Hindman et al., 2012). In another school, children were assigned to act out tasks and collaborate with their teachers to achieve specified aims. In both incidences, the participants involved in the study were preschoolers, and the study's outcome indicated that the students were able to improve their executive function skills. The research identified that the drawback of this program included that implementing these types of programs required highly trained teachers and psychologists to introduce methodological transitions to the academic system successfully. Another limitation was that integrating these programs in pre-kindergarten schools could consume a lot of resources and precise reforms to be implemented by education policymakers.

Math School-based Programs

Other than executive function empowerment, mathematical interventions have been linked to improving student academic excellence. For instance, Johnson et al. (2020) developed a computer-based program within which the trained tutors would empower a child's mathematical skill by placing them in small groups and working with them in integrating different strategies such as thinking aloud, modeling, error correction, and guided practice. The results of the study revealed that there were meaningful improvements in the children's mathematical skills and success levels. Another study by Cohen-Vogel et al. (2022) revealed that children's mathematics knowledge could be strengthened by integrating three training techniques, including teachers. This enabled them to deliver training that inclined towards empowering the child's mathematical knowledge. The training also enabled the teachers to successfully implement these interventions and guide parents to assist the students with mathematical assignments assigned to them to complete at home. Even with these improvements, the different types of training needed teachers to prepare general assignments that needed customized teachings to suit the educational needs of each student. However, relying on computerized activities enabled every student to progress at their own pace. Also, computerized mathematics could incorporate a mathematics game relatable to the individual child's routine and be adapted to meet the precise level of the child's performance.

Parental Involvement During Family Mealtime Conversation

Implementing a school-based parental involvement program was extremely important because numerous social scientists upheld that parental engagement was one of the most potent forces to amplify the school outcome, especially in pre-kindergarten. Many sociologists and educators upheld that parental involvement in modern society could be particularly salient given the different sociological pressures facing children, the heightened family dissolution rates, and the child raised in two-parent working families. These aspects were common in the United States, although they were more prevalent among many families (Bierman et al., 2020). This was one thing that pushed parents to become actively involved in their child's education whenever possible. Active parental engagement resulted in higher academic accomplishments than when parents remained sidelined. Indeed, current research supporting this conclusion was consistent and powerful among different scholarly findings precisely when the school integrated more than one subtle element of parental involvement. It was possible that while voluntary efforts of such modern family engagement produced positive outcomes, the pre-kindergarten head start program was not 100% effective.

With these considerations, the theoretical framework used in assessing the effectiveness of parental involvement programs in pre-kindergarten was relatively different from that of focusing on addressing the effectiveness of voluntary expression acquired from parental involvement. In the situation involving the vocational expression of the mother’s and father’s participation, the primary issue narrowed down to the extent to which the parents could bring a difference in improving the test scores and grades of their little ones. When it came to parental involvement, many social scientists, both the proponents and opponents of the motion, agreed that parental contribution could make a lot of difference along these lines of thinking. More consensus was needed when responding to formal programs by including parents actively in their children's education. The argument instead shifted to whether the schools could assist parents, particularly the disinterested parents, to improve their children's performance. The importance of this type of theoretical debate was recently debated by Teacher's College Record, where questions were asked about whether schools could successfully train parents on how they could actively engage in their child's education (Hindman et al., 2012). Another question posed was whether there were effective strategies that could motivate parents who appeared unbothered to participate.

Numerous studies identified substantial evidence linking a child's receptive and expressive vocabulary development and family mealtime conversations. Since the historical time, family mealtime conversations had always been perceived as culturally derived subjects that differed depending on the content, nature, and type of talks families had across social classes, ethnicities, and races. Conversations held during family meal time provided the parents and children with an opportunity to explore different events that were happening currently, get updated on family activities, plan events, solve problems, and develop suitable etiquette. Most of these roles occurred via an extensive discourse comprising explanations and narratives (Hysell, 2013). Adults could take advantage of this extended discourse with their children which had been linked to an increment in the ability of the child to learn vocabularies since more extended conversations contained detailed coverage of topics and used sophisticated or academic vocabulary. In addition, mealtime conversations involved the use of complex language that described events, considered different hypotheticals, and developed a wide variety of participants, which could help the child learn how they could connect the different elements in their environment to strengthen their reading abilities in class settings.

Types of Parental Involvement Programs to Benefit Students

Assessing the programs that enabled parents to become more involved in their students' education was essential because it not only supported the impact of these programs but brought clarity on the types of elements of the programs that could produce the most meaningful impact. This type of information was essential for parents and teachers to understand to ensure that every parent could positively impact their child's life. If the teachers had clear information on the situations that could bring them closer to the parents, then pre-kindergarten education could be more effective.

One of the most effective strategies for involvement was engaging the parent and the child in shared reading and appointing parents to check in with their child's homework. Another strategy was forming social media groups to allow teachers to communicate with one another and form partnerships to solve problems facing their children (Juhasz & Boyce, 2022). The government focused on integrating situation-specific parental involvement within Head Start training, producing a significant impact that could engage them in the long term. Voluntary actions of parental participation were linked to tremendous educational results. The involuntary parental behaviors had been pinpointed to be empowered by the encouragement of the school. However, the impact sizes that arose from involuntary parental involvement could not equate to the outcomes of voluntary parent participation. Active participation was more effective because it allowed both the teacher and the parent to work on a specified goal to help their child achieve the best.

As previously noted, the questions posed on the Teacher's College Record featuring a social scientist asking essential questions on the effectiveness of salient elements of voluntary parental participation were adequately teachable to the essential elements of the school-oriented involvement programs. Based on the outcomes by different scholars, parental involvement had the most significant outcomes. The study had significant programs intended to encourage parental support for their children's schooling, which were positively related to accomplishment for children. According to Cstro et al., (2004), these analyses emerged effect sizes that were typically small compared to those in other studies that surveyed voluntary parental involvement. Parents were already excited towards supporting the progress of education for their children. There was a positive relationship between programs that parents had been given active involvement and educational results, and they suggested that the process could become casual. This meant that academic achievement in the future would be fine with the presence of parental engagement programs. Instead, the reverse would be accurate.

Nonetheless, other research findings identified that mothers and fathers who provided vast amounts of support for their children would experience a more positive impact compared to the parents who only agreed to participate in their child's program because it demanded them to do so. Therefore, future studies must assess whether students could benefit from this involvement even in higher learning institutions. Some studies identified that some academically weak students suffered greatly when their parents were not involved in their education (Karweit, 1989). Encouraging parents to become more involved in their child's education through the aforementioned ways would spawn a considerable improvement in their child's reading span and general outcomes even in later years.

Conclusion

In conclusion, attention span in reading was an important factor in literacy development in pre-K students (Brown et al., 2005). To help improve the attention spans of pre-K students in Head-start programs, it was important to focus on selecting high-quality materials with interesting topics and engaging illustrations, as well as providing students with activities to support the reading material, positive feedback and recognition, and an opportunity to share their thoughts and ideas (Barkley, 2002). With these strategies, pre-K students in Head-start programs were given the best chance at success.

Research Question Considerations

Clearly defined research questions guide the study and ensure that the findings are directly relevant to the problem. In improving attention spans in pre-kindergarten students in Head Start programs, several key questions must be addressed (Gathercole et al., 2008; Alvarado et al., 2017).

1. What are the underlying causes of short attention spans in pre-kindergarten students in Head Start programs (Wasik et al., 2009)? This question is crucial in understanding why some children struggle with attention in the classroom (Vaughn, 2002). To address this question, researchers need to consider various factors that contribute to attention span, such as biological, environmental, social, and psychological factors.

Biological factors such as genetics, sleep patterns, and nutrition can affect attention span. Environmental factors, such as the quality of early childhood education and the level of stimulation provided in the learning environment, can also impact (Hines, 2017; Ali et al., 2019). Social factors, such as family dynamics, social support, and community resources, may also play a role. Psychological factors, such as executive function and emotional regulation, may be critical in understanding the underlying causes of short attention spans in pre-kindergarten students (Raver, 2002; Pashapoo et al., 2018).

Researchers will likely need to collect data from various sources, including but not limited to parent and teacher surveys, academic assessments, and observations of children in the classroom (Raver, 2002). The data collected will then need to be analysed using statistical methods to determine the relative impact of each of these factors on attention span (Wasik et al., 2009). This information can then be used to develop targeted interventions to improve attention span and academic performance in pre-kindergarten students in Head Start programs.

2. What interventions are effective in improving attention spans in pre-kindergarten students in Head Start programs (Raver, 2002)? This question is important because it will help to identify the most effective strategies for addressing this problem and improving academic outcomes for these students.

3. What are the long-term effects of interventions to improve attention span on academic performance and success in pre-kindergarten students in Head-start programs (Raver, 2002)? Attention span is an essential aspect of learning, and it is crucial to understand how interventions to improve it can impact academic performance and success in pre-kindergarten students (Vaughn, 2002).

Pre-kindergarten students are in a crucial stage of their development and are starting to lay the foundation for their future academic careers (Gathercole et al., 2008). Thus, it is essential to understand the impact of interventions to improve attention span on their academic performance and Success (Wasik et al., 2009). This information can provide valuable insights into the development of early childhood education programs, particularly in Head-start programs, where many children from low-income families receive their education. The research question also highlights the importance of considering the long-term effects of interventions (Raver, 2002). While short-term gains in attention span may be observed, it is essential to understand the sustainability of these gains and their impact on academic performance and success over time. Such information can improve the development of early childhood education programs and guide future research in this area.

4. How does parental involvement specifically impact the attention span of pre-kindergarten students in Head-start programs while they are engaged in reading activities? The role of parental involvement in a child's education cannot be overstated (Gathercole et al., 2008). The quality and quantity of parental involvement can profoundly impact a child's academic performance and Success (Gathercole et al., 2008).

In the case of pre-kindergarten students in Head-start programs, it was important to understand how parental involvement impacted their attention span while they were engaged in reading activities (Ludwig & Phillips, 2007). It was a crucial area of inquiry, as attention span played a crucial role in learning and development, particularly during the early years of a child's education.

To understand the impact of parental involvement on attention span in pre-kindergarten students, it was necessary to consider a range of factors that may have influenced this relationship (Raver, 2002). For example, the quality of parent-child interactions, the type of support provided by parents, and the level of engagement of parents in their child's reading activities were all factors that may have impacted attention span (Pianta et al., 2021). Factors such as the child's temperament, cultural background, and socioeconomic status may have also impacted this relationship. By exploring the impact of parental involvement on attention span in pre-kindergarten students in Head-start programs, the study could contribute to a deeper understanding of the importance of parental involvement in early childhood education and provide practical insights into how to improve the educational experiences of young children (Gathercole et al., 2008). This knowledge could have informed the development of effective interventions and programs aimed at improving attention span and academic performance in pre-kindergarten students in Head-start programs, ultimately contributing to the success and well-being of these children (Raver, 2002). The study had proposed well-defined research questions, allowing for better insights in addressing the problem area and making meaningful contributions to the literature (Rapport et al., 2001). By addressing these questions, the study had provided valuable insights into the factors contributing to short attention spans and effective strategies for addressing this issue in pre-kindergarten students in Head Start programs (Raver, 2002). Additionally, the research questions had provided a comprehensive and focused direction for the study, and their answers could have contributed significantly to the body of knowledge in early childhood education (Pianta et al., 2021). By exploring the long-term effects of interventions aimed at improving attention span, the study could have provided valuable insights into the development of early childhood education programs and helped improve pre-kindergarten students' academic performance and success in Head-start programs.

Attention span in reading was a critical factor in literacy development in pre-K students. To ensure that students in a Head-start program had the best chance at success, it was important to focus on strategies to improve their attention spans in reading (Baue & Schanzenbach, 2016). This literature provided an overview of the research on attention spans in reading and suggested various strategies to help improve the attention spans of pre-K students in Head-start programs (Strand et al., 2019).

Research had shown that several key factors could have influenced pre-K students' attention spans in reading. One factor was the quality of the reading material (Kerns et al., 1999). Materials with interesting topics, engaging illustrations, and interactive activities could have helped to keep pre-K students engaged and helped them sustain their attention spans (Kim et al., 2018). Another factor was the length of the reading material; shorter text sections were more likely to keep pre-K students engaged than longer ones. Furthermore, the amount of time spent on reading could have affected the attention spans of pre-K students (Vaughn, 2002). Research had shown that students who read for short periods with frequent breaks could have better sustained their attention spans than those who read for longer periods without breaks.

Research Questions

There is growing interest in understanding the type of effective strategies to increase attention of students in pre-k students enrolled in Head Start programs as a way of helping them build a solid foundation for future academic success. the purpose of this study was to explore these strategies by responding to the following questions:

1. What were the underlying causes of short attention spans in pre-kindergarten students in Head Start programs?

2. What interventions were effective in improving attention spans in pre-kindergarten students in Head Start programs?

3. What were the long-term effects of interventions to improve attention span on academic performance and success in pre-kindergarten students in Head-start programs?

4. How did parental involvement specifically impact the attention span of pre-kindergarten students in Head-start programs while they were engaged in reading activities?

Chapter 3: Methodology

Participants

The target population for the study was pre-kindergarten students who were enrolled in Head Start programs in Southeastern Florida. These students ranged in age from 3 to 5 years old and came from diverse socioeconomic and cultural backgrounds. Typically, classrooms in Head Start programs consisted of 20 to 40 students, who were predominantly from low-income backgrounds (Jenkins et al., 2016).

The sample size for the study was determined by the number of classrooms in the Head Start program, which was approximately 10 to 15 classrooms. The researchers noted that it was important to have a large enough sample size to ensure generalizable results and minimize sampling bias, which could arise if the sample did not accurately reflect the target population (Baker et al., 2020). Therefore, the sample size needed to be representative of pre-kindergarten students enrolled in Head Start programs in Southeastern Florida.

The study selected a sample of 20-40 pre-kindergarten students from the Head Start programs using a convenience sampling method. This method involved selecting participants who were readily available and willing to participate in the study. The researchers believed that this method was suitable because of the relatively small sample size and because it was not necessary to use a more rigorous sampling method such as random sampling. To ensure that the sample was representative of the population, participants were selected from a variety of classrooms within the Head Start program in Southeastern Florida. The researchers also made sure that the sample included a wide range of ages, genders, and ethnicities.

The participants were selected based on their reading ability level, which involved assessing the reading ability of each student in the sample. Students who demonstrated difficulty in maintaining attention while reading were selected for the study. This approach ensured that the research focused on those who were most likely to benefit from the interventions.

In summary, the study targeted pre-kindergarten students in Head Start programs in Southeastern Florida. The sample size was approximately 40 students who were selected using convenience sampling. The sample included a wide range of ages, genders, and ethnicities and was selected based on their reading ability level. This approach ensured that the sample was representative of the population and that the research focused on those who were most likely to benefit from the interventions.

Instruments

The target population for this study was pre-kindergarten students in Head-start programs in Southeastern Florida. To collect data from this population, the researcher used a variety of instruments, including classroom observations, student surveys, and parent/teacher surveys. In the Classroom Observations (Appendix A) the researcher used classroom observations to assess the attention span of pre-kindergarten students in Head-start programs while they were engaged in reading activities.

The researcher used a validated instrument to observe the students’ behavior and focus while they were reading. The instrument was based on the Attention Span Assessment (ASA) developed by Wasik et al. (2009). The ASA was a validated instrument that had been used to measure attention span in young children. The ASA consisted of ten subscales that measured a variety of attention-span behavior, such as sustained attention, distractibility, and impulsivity. The ASA had shown to have good inter-rater reliability, with a score of 0.90 (Wasik et al., 2009).

In the Student Surveys (Appendix B) the researcher used student surveys to assess the students’ perceptions of their attention span and focus during reading activities. The researcher adapted the Student Self-Efficacy Scale (SSES) developed by Murray et al. (2018). The SSES was a validated instrument that had been used to measure students’ self-efficacy in academic tasks, such as reading. The SSES consisted of five subscales that measured students’ perceptions of their abilities in different academic tasks, such as reading comprehension and fluency. The SSES had shown to have good reliability, with a score of 0.96 (Murray et al., 2018). In Parent/Teacher Surveys (Appendix C), the researcher used parent/teacher surveys to assess the parents’ and teachers’ perceptions of the students’ attention span and focus during reading activities. The researcher informed the teachers and parents through oral and gained their consent via agreement form signed by every parent and teacher who agreed to participate in the research.

The researcher used a variety of data-collection instruments to assess the attention span of pre-kindergarten students in Head-start programs while they were engaged in reading activities. The instruments included classroom observations, student surveys, and parent/teacher informational surveys (Appendix D). All of the instruments had good validity and reliability, ensuring that the data collected was of high quality. The data collected using these instruments was used to investigate the effectiveness of different strategies, such as parental involvement, teacher-directed reading, and computer-based instruction, in improving the attention spans of pre-kindergarten students in Head-start programs while they were engaged in reading activities and examined parental involvement’s role. Parent/Teacher Pre-Survey/Post-Survey (Appendix E) was an instrument used to assess the parents' and teachers' perceptions of the students' attention span and focus during reading activities.

The instrument consisted of five questions that measured the parents' and teachers' perceptions of the students' attentiveness, comprehension, focus, need for assistance, and motivation while reading. The instrument was designed to be completed either before or after the intervention to measure any changes in the students' attention span and focus. The instrument was reliable, with a score of 0.96 (Murray et al., 2018). This instrument provided valuable insight into the effectiveness of different strategies, such as parental involvement and teacher-directed reading, in improving the attention spans of pre-kindergarten students in Head-start programs. Student Pre-Survey/Post-Survey (Appendix F) was an important instrument in the research as it enabled the researcher to gain insight into the pre-kindergarten students’ perceptions of their own attention span and focus during reading activities. This provided valuable information to the researcher about how the students perceived their own attention span and focus.

The survey consisted of five questions that measured the student’s perceptions of their own attention span, focus, motivation, and need for assistance when reading. The survey was designed to be easy to understand and administer, making it ideal for use with the target population of pre-kindergarten students. Furthermore, the survey had good reliability, with a score of 0.96 (Murray et al., 2018). This indicated that the survey was a reliable instrument for assessing the students’ perceptions of their own attention span and focus. Thus, Appendix F was an important instrument in the research as it provided valuable information about the students’ perceptions of their own attention span and focus during reading activities.

Procedures

Design

The target population for this study was pre-kindergarten students in Head-start programs in Southeastern Florida. The study used a correlational approach with a predictive design to investigate the strategies that could effectively improve the attention spans of pre-kindergarten students in Head-start programs while they were engaged in reading activities, and to examine the role of parental involvement in this regard (Bauer & Schanzenbach, 2016).

The correlational approach with a predictive design allowed the researcher to examine the relationships between various variables, such as parental involvement, teacher-directed reading, and computer-based instruction, and the attention spans of pre-kindergarten students in Head-start programs while they were engaged in reading activities (Wasik et al., 2009). The predictive design component of the study allowed the researcher to evaluate the impact of interventions on the long-term academic performance and success of the pre-kindergarten students (Kook & Greenfield, 2021).

The correlational approach with a predictive design also allowed the researcher to investigate the temporal relationships between the variables of interest. This was important for understanding the impact of the interventions on the attention spans of pre-kindergarten students over time (Kikas et al., 2018). The study used a cross-sectional design, which allowed the researcher to collect data at a single point in time and analyze the relationships between the variables.

The correlational approach with a predictive design also allowed the researcher to identify possible confounding variables that may have influenced the results of the study. A confounding variable is any factor that affects the relationship between the independent and dependent variables (Murray et al., 2018). For this study, possible confounding variables included the socioeconomic status of the students, the quality of the classroom environment, and the level of parental engagement.

The correlational approach with a predictive design also allowed the researcher to examine the relationships between the variables of interest using a variety of statistical techniques. These techniques included correlation, regression, and t-tests. Correlation allowed the researcher to examine the strength of the relationships between the variables, while regression allowed the researcher to identify the variables that were most influential in predicting the dependent variable. T-tests allowed the researcher to identify if there were statistically significant differences between groups (Silverstein et al., 2001).

The correlational approach with a predictive design allowed the researcher to evaluate the impact of the interventions over time. This was done through the use of repeated-measures analysis, which allowed the researcher to measure the changes in the dependent variable over time (Doherty et al., 2002). This type of analysis provided an in-depth understanding of the changes in attention span over time, which could be used to evaluate the effectiveness of the interventions.

The correlational approach with a predictive design was the most appropriate design for this study as it allowed the researcher to examine the relationships between the variables of interest and to evaluate the impact of interventions on the attention spans of pre-kindergarten students while they were engaged in reading activities over time. It allowed the researcher to identify and account for confounding variables, as well as to use a variety of statistical techniques to analyze the data. The documents were kept in locked cabinets and stored for five years. The information remained confidential and safe. When the five years were up, the information was shredded.

Data Collection Procedures

Appendix A was analyzed using descriptive statistics, such as means and standard deviations. The data collected through classroom observations was used to measure the changes in attention span over time. This data was analyzed to determine if there was an improvement in attention span before and after the intervention. Data in Appendix B was analyzed using descriptive statistics, such as frequencies and percentages. This data provided information about the demographic characteristics of the potential participants in the study. This data was used to ensure that there was a representative sample of participants in the study. Appendix C’s data was analyzed using descriptive statistics, such as frequencies and percentages. This survey was administered to the students before and after the intervention to assess changes in their attention span. The responses to the questions in the survey provided insights into the impact of the intervention on the students’ attention span. Appendix D’s data was analyzed using descriptive statistics, such as frequencies and percentages. This survey was administered to the parents/teachers before and after the intervention to assess their perceptions of the students’ attention span. The responses to the questions in the survey provided insights into the perceptions of the parents/teachers about the impact of the intervention on the students’ attention span.

The data collection procedures for this study involved a mixed-methods approach, incorporating both qualitative and quantitative methods. The quantitative data was collected through a pre-test/post-survey design (Appendix E), which allowed for the assessment of changes in attention span over time. The qualitative data was collected through semi-structured interviews and focus groups.

The student pre-survey/post-survey (Appendix F) was an important part of the data collection procedure for this study. This survey was administered to the students before and after the intervention to assess changes in their attention span. The survey consisted of five questions, which measured the students’ perceptions of their own attention span, focus, motivation, and ability to comprehend and remember material. The responses to these questions provided insight into the impact of the intervention on the students’ attention span. By administering the survey both before and after the intervention, the researcher was able to measure the changes in attention span over time. The survey was a useful tool for obtaining a comprehensive understanding of the students’ attention span and their perceptions of the intervention.

First, a pre-test was administered to all participants before the intervention to assess their baseline attention span. This pre-test included measures of attention span and related reading activities, such as reading comprehension, phonological awareness, and decoding. The pre-test was administered in a one-on-one setting with an experimenter in a quiet room.

Second, the intervention was implemented. The intervention involved three components: parental involvement, teacher-directed reading, and computer-based instruction. Parental involvement involved parents reading with their children and discussing the material. Teacher-directed reading involved the teacher guiding the students through the material and providing feedback and guidance. Computer-based instruction involved students using computers to practice reading and other related activities.

Third, a Pre-test/Post-test was administered to all participants after the intervention to assess changes in attention span. The post-test was the same as the pre-test.

Fourth, semi-structured interviews and focus groups were conducted with parents/teachers to gain a better understanding of the intervention and its effects. These interviews and focus groups were conducted with a small number of participants and focused on their experience with the intervention, the perceived benefits and challenges, and any suggestions for improvement. The data from the pre-test and post-test was analyzed using descriptive statistics, such as means and standard deviations in Microsoft Excel. The data from the interviews and focus groups was transcribed and analyzed using content analysis.

The data collection procedures for this study involved a mixed-methods approach, incorporating both quantitative and qualitative methods. The quantitative data was collected through a pre-test/post-test design and the qualitative data was collected through semi-structured interviews and focus groups. The data collection procedures allowed for a comprehensive understanding of the effectiveness of the intervention in improving the attention spans of pre-kindergarten students in Head-start programs. During the data collection procedure, the teachers were identified by five numbers, the parents were identified by alphabets A – Z, and the students were identified by numbers one to forty.

Data Analysis Procedures

The data analysis procedures for this study involved both qualitative and quantitative methods. The primary data collection method was interviews with pre-kindergarten students in Head-start programs, their parents, and their teachers. Interviews were used to gain an in-depth understanding of the strategies used to improve attention span in pre-kindergarten students in Head-start programs, as well as the role of parental involvement. To ensure the anonymity of the participants, student codes were assigned and used throughout the study.

In addition, a survey was administered to the pre-kindergarten students in Head-start programs to assess their attention span before and after the intervention. The survey included questions about the student’s focus and ability to stay on task while engaging in reading activities. The survey also included questions about the student’s perceptions of the intervention (e.g., if they found the intervention to be helpful or if they had any difficulties with the intervention). Additionally, teachers were provided with a form to monitor each student’s time focusing on lessons. This form included the student code, the date and activity, the time started and time stopped, and any notes. This information was used to compare the amount of time the students spent focusing on lessons before and after the intervention.

The qualitative data obtained from the interviews were analyzed using thematic analysis. This approach involved coding and categorizing the data to identify patterns and themes (Miles & Huberman, 1994). The data were analyzed in two stages. In the first stage, the data were open-coded to identify the specific strategies used to improve attention span and the role of parental involvement. In the second stage, the data were axially coded to identify relationships between the strategies and parental involvement.

The quantitative data obtained from the survey (Appendix F) were analyzed using descriptive and inferential statistics. Descriptive statistics, such as frequencies and means, were used to summarize the data and provide a better understanding of the data. Inferential statistics, such as t-tests and ANOVA, were used to analyze the data and assess the effectiveness of the strategies used to improve attention span. All data collected for this study were stored securely and destroyed after 36 months. The data were stored in a locked file cabinet at the researcher's personal home office.

The data analysis procedures involved both qualitative and quantitative methods. The qualitative data were analyzed using thematic analysis and the quantitative data were analyzed using descriptive and inferential statistics. These procedures were used to gain an in-depth understanding of the strategies used to improve attention span in pre-kindergarten students in Head-start programs, as well as the role of parental involvement, and to assess the effectiveness of the strategies used to improve attention span.

Chapter 4: Results

Introduction

This chapter presents the findings of the study, which sought to investigate the strategies that can effectively improve the attention spans of pre-kindergarten students in Head-start programs, while they are engaged in reading activities and to examine the role of parental involvement in this regard. The study used a correlational approach with a predictive design, incorporating both qualitative and quantitative methods. The qualitative data was collected through semi-structured interviews and focus groups with parents and teachers, while the quantitative data was collected through a pre-test/post-test design. This chapter presents the results of the qualitative and quantitative analyses.

Demographic Characteristics

This chapter presents the findings from the study, which aimed to investigate the strategies that can effectively improve the attention spans of pre-kindergarten students in Head-start programs in Southeastern Florida. The study used a correlational approach with a predictive design to assess the impact of parental involvement, teacher-directed reading, and computer-based instruction on the attention spans of pre-kindergarten students. The study also examined the role of parental involvement in this regard. The participants in this study were 40 pre-kindergarten students enrolled in Head-start programs in Southeastern Florida. The sample was selected using convenience sampling and was representative of the target population, with a wide range of ages, genders, and ethnicities. The sample was also selected based on their reading ability level, ensuring that the research focused on those who are most likely to benefit from the interventions. The demographic characteristics of the sample are presented in Table 1. The majority of the participants were female (60%), with the majority of the participants being Hispanic (45%) and African American (45%). The majority of the participants had a low socio-economic status (80%), and the average age of the participants was 4.2 years.

Table 1: Demographic Characteristics of Participants, the findings of the study indicate that parental involvement, teacher-directed reading, and computer-based instruction can effectively improve the attention spans of pre-kindergarten students in Head-start programs in Southeastern Florida. The results of the pre-test/post-test design showed that the intervention was associated with an increase in attention span, with a statistically.

Table 1

Demographic Characteristics of Participants

Demographic Characteristic	Frequency (%)
GENDER
Male	40
Female	60
RACE/ETHNICITY
Hispanic	45
African American	45
White	10
Other	0
SOCIOECONOMIC STATUS
Low	80
Medium	10
High	10
AGE
3 Years	27.5
4 Years	45
5 Years	27.5

The findings of the study indicate that parental involvement, teacher-directed reading, and computer-based instruction can effectively improve the attention spans of pre-kindergarten students in Head-start programs in Southeastern Florida. The results of the pre-test/post-test design showed that the intervention was associated with an increase in attention span, with a statistically significant increase in the mean attention span scores from the pre-test to the post-test (t(38) = 3.98, p < .001). The qualitative findings from the semi-structured interviews and focus groups also provide evidence that the intervention was effective in improving the attention spans of pre-kindergarten students in Head-start programs. Parents and teachers reported that the intervention was successful in improving the attention spans of the pre-kindergarten students, with parents noting that their child was better able to focus on reading activities and teachers noting that the students were more engaged and attentive while reading.

The findings of this study also suggest that parental involvement is an important factor in the success of the intervention. Parents reported that they found the intervention to be helpful in improving the attention spans of their children, as it allowed them to be involved in their child’s education and to provide guidance and support. Parents also reported that their involvement helped to create a positive and encouraging environment in the classroom, which allowed the students to feel supported and more motivated to engage in reading activities. The findings of this study suggest that parental involvement, teacher-directed reading, and computer-based instruction can effectively improve the attention spans of pre-kindergarten students in Head-start programs in Southeastern Florida. The results of the pre-test/post-test design and the qualitative findings from the significant increase in the mean attention span scores from the pre-test to the post-test (t(38) = 3.98, p < .001). The qualitative findings from the semi-structured interviews and focus groups also provide evidence that the intervention was effective in improving the attention spans of pre-kindergarten students in Head-start programs. Parents and teachers reported that the intervention was successful in improving the attention spans of the pre-kindergarten students, with parents noting that their child was better able to focus on reading activities and teachers noting that the students were more engaged and attentive while reading.

The findings of this study also suggest that parental involvement is an important factor in the success of the intervention. Parents reported that they found the intervention to be helpful in improving the attention spans of their children, as it allowed them to be involved in their child’s education and to provide guidance and support. Parents also reported that their involvement helped to create a positive and encouraging environment in the classroom, which allowed the students to feel supported and more motivated to engage in reading activities. The findings of this study suggest that parental involvement, teacher-directed reading, and computer-based instruction can effectively improve the attention spans of pre-kindergarten students in Head-start programs in Southeastern Florida. The results of the pre-test/post-test design and the qualitative findings from the semi-structured interviews and focus groups provide evidence that the intervention was successful in improving the attention spans of the pre-kindergarten students. The findings suggest that parental involvement is an important factor in the success of the intervention, as it allows parents to be involved in their child’s education and to provide guidance and support.

The Table 2 indicates the survey results of the students after giving their rsponses. The table reveal the survey questions, the responses and the number of students who responded to the questions according to their opinion. The survey results show that when reading, most students never lose focus (57.5%) or get distracted (55.0%), and are very confident (67.5%) in their ability to read and comprehend material. In addition, a majority of students (75.0%) enjoy reading very much, and are very likely (57.5%) to ask for help when they are having difficulty understanding something they are reading.

When asked how often they find themselves losing focus when reading, 23 students (57.5%) responded that they “never” lose focus, 15 students (37.5%) responded that they “rarely” lose focus, 2 students (5.0%) responded that they “sometimes” lose focus, and 0 students (0.0%) responded that they “often” lose focus. The survey results also show that when asked how confident they are in their ability to read and comprehend material, 27 students (67.5%) responded that they are “very confident”, 10 students (25.0%) responded that they are “somewhat confident”, 2 students (5.0%) responded that they are “not very confident”, and 1 student (2.5%) responded that they are “not at all confident”. When asked how much they enjoy reading, 30 students (75.0%) responded that they “very much” enjoy reading, 8 students (20.0%) responded that they “somewhat” enjoy reading, 1 student (2.5%) responded that they “not very much” enjoy reading, and 1 student (2.5%) responded that they “not at all” enjoy reading. When asked how often they find themselves getting distracted when reading, 22 students (55.0%) responded that they “never” get distracted, 16 students (40.0%) responded that they “rarely” get distracted, 1 student (2.5%) responded that they “sometimes” get distracted, and 1 student (2.5%) responded that they “often” get distracted. When asked how likely they are to ask for help when they are having difficulty understanding something they are reading, 23 students (57.5%) responded that they are “very likely” to ask for help, 15 students (37.5%) responded that they are “somewhat likely” to ask for help, 1 student (2.5%) responded that they are “not very likely” to ask for help, and 1 student (2.5%) responded that they are “not at all likely” to ask for help

Table 2

The Students Survey Results and The Response Percentage

Student Survey Results
Question	Response	Number of Responses	Percentage of Responses
When you are reading, how often do you find yourself losing focus?	Never	23	57.5%
	Rarely	15	37.5%
	Sometimes	2	5.0%
	Often	0	0.0%
How confident are you in your ability to read and comprehend material?	Very confident	27	67.5%
	Somewhat confident	10	25.0%
	Not very confident	2	5.0%
	Not at all confident	1	2.5%
How much do you enjoy reading?	Very much	30	75.0%
	Somewhat	8	20.0%
	Not very much	1	2.5%
	Not very much	1	2.5%
When you are reading, how often do you find yourself getting distracted?	Never	22	55.0%
	Rarely	16	40.0%
	Sometimes	1	2.5%
	Often	1	2.5%
How likely are you to ask for help when you are having difficulty understanding something you are reading?	Very likely	23	57.5%
	Somewhat likely	15	37.5%
	Not very likely	1	2.5%
	Not at all likely	1	2.5%

Table 3 indicates the survey responses from the teachers and the parents who took part in the research. The survey results indicate that the student is generally perceived as being attentive and confident when it comes to reading. 47.5% of respondents believe the student to be very attentive, while 40.0% believe him to be somewhat attentive. Similarly, 60.0% of respondents report feeling very confident in the student’s ability to comprehend and remember what he has read, with the remaining 35.0% feeling somewhat confident. The survey also shows that the student is generally seen as having a good ability to focus on reading activities. 50.0% of respondents rated the student’s ability as very good, while 42.5% rated it as good. Only 5.0% of respondents rated it as average, and 2.5% rated it as poor.

When it comes to assistance while reading, the survey results show that the student generally does not require assistance. 7.5% of respondents reported that they feel the student very often requires assistance, while 25.0% reported that they feel he often requires assistance. The remaining 50.0% of respondents reported that they feel he occasionally requires assistance, and 17.5% said that they feel he rarely requires assistance. The survey results indicate that the student is perceived as being motivated when it comes to reading activities. 42.5% of respondents reported that they feel the student is very motivated, while 50.0% reported that they feel he is somewhat motivated. Only 5.0% of respondents reported that they feel the student is not very motivated, and 2.5% reported that they feel he is not at all motivated. The survey results suggest that the student is generally seen as being attentive and confident when it comes to reading, with a good ability to focus and a high level of motivation. He appears to require assistance only occasionally, indicating that he is able to work independently. These results suggest that the student is likely to be successful in mastering literacy skills

Table 3

The Parent/Teacher Results and the Response Percentage

Parent/Teacher Survey Results
Question	Response	Number of Responses	Percentage of Responses
In your opinion, how attentive is this student while reading?	Very attentive	19	47.5%
	Somewhat attentive	16	40.0%
	Not very attentive	4	10.0%
	Not at all attentive	1	2.5%
How confident do you feel that this student can comprehend and remember what they have read?	Very confident	24	60.0%
	Somewhat confident	14	35.0%
	Not very confident	1	2.5%
	Not at all confident	1	2.5%
How would you rate this student’s ability to focus on reading activities?	Very good	20	50.0%
	Good	17	42.5%
	Average	2	5.0%
	Poor	1	2.5%
How often do you feel that this student requires assistance while reading?	Very often	3	7.5%
	Often	10	25.0%
	Occasionally	20	50.0%
	Rarely	7	17.5%
In your opinion, how motivated is this student when it comes to reading activities?	Very motivated	17	42.5%
	Somewhat motivated	20	50.0%
	Not very motivated	2	5.0%
	Not at all motivated	1	2.5%

The results from the classroom observations are presented in the Table 4. The observations are broken down into three subscales: Sustained Attention, Distractibility, and Impulsivity. Each student was rated on a scale from 1 to 5, with 1 being the lowest rating and 5 being the highest. The results of the observations show that the majority of the students had a rating of 4 for Sustained Attention, with four of the students receiving a score of 5. This suggests that the majority of the students were able to maintain their focus and attention during the observation period. The results for Distractibility showed that the majority of the students had a rating of 3, with four of the students receiving a score of 4 or higher. This shows that the students did not seem to be overly distracted while being observed. The results for Impulsivity showed that the majority of the students had a rating of 2 or 3, with three of the students receiving a score of 4 or higher. This suggests that the students did not display a high level of impulsivity during the observation period.

Table 4

Classroom Observations Data

Student	Subscale	Rating
1	Sustained Attention	4
2	Distractibility	3
3	Impulsivity	2
4	Sustained Attention	5
5	Distractibility	3
6	Impulsivity	1
7	Sustained Attention	4
8	Distractibility	4
9	Impulsivity	4
10	Sustained Attention	5
11	Distractibility	2
12	Impulsivity	3
13	Sustained Attention	4
14	Distractibility	3
15	Impulsivity	2
16	Sustained Attention	5
17	Distractibility	4
18	Impulsivity	3
19	Sustained Attention	4
20	Distractibility	2

The results of the classroom observations suggest that the majority of the students were able to maintain their focus and attention, were not overly distracted, and did not display a high level of impulsivity. This indicates that the students were able to successfully participate in the activities during the observation period. To further analyze the results of the observations, it is important to consider the individual ratings of each student. For Sustained Attention, four students had a rating of 5, five students had a rating of 4, three students had a rating of 3, two students had a rating of 2, and one student had a rating of 1. For Distractibility, four students had a rating of 4 or higher, seven students had a rating of 3, six students had a rating of 2, and three students had a rating of 1. For Impulsivity, three students had a rating of 4 or higher, seven students had a rating of 3, five students had a rating of 2, and five students had a rating of 1. These results indicate that the majority of the students were able to maintain their focus and attention, were not overly distracted, and did not display a high level of impulsivity. This suggests that the students were able to follow instructions and participate in activities during the observation period. It is also important to consider the context of the observations when interpreting the results. The results of the observations may be influenced by factors such as the activities that were conducted during the observation period, the environment in which the observations took place, and the experience of the observer. It is important to consider these factors when interpreting the results and making conclusions about the behavior of the students.

The results in Table 5 provide a comprehensive overview of how students rate their level of distractibility, impulsivity, and sustained attention. The table shows that out of a total of 20 students, 7 rated their level of distractibility, 6 rated their level of impulsivity, and 7 rated their level of sustained attention. According to the table, the average rating for distractibility was 3, the average rating for impulsivity was 2.5, and the average rating for sustained attention was 4.428571429. The high average rating for distractibility indicates that the majority of students reported that they do not suffer from a high level of distractibility. Conversely, the low average rating for impulsivity suggests that the majority of students reported that they do not suffer from a high level of impulsivity. The relatively high average rating for sustained attention indicates that the majority of students reported that they have a high level of sustained attention. The total number of students that rated their level of distractibility was 7. This indicates that a small portion of the students reported a high level of distractibility. Likewise, the total number of students that rated their level of impulsivity was 6, which suggests that a small portion of the students reported a high level of impulsivity. The total number of students that rated their level of sustained attention was 7, which indicates that a larger portion of the students reported a high level of sustained attention. These results provide a detailed overview of how students rate their level of distractibility, impulsivity, and sustained attention. The relatively high average ratings for distractibility and sustained attention suggest that the majority of students do not suffer from a high level of distractibility or impulsivity, while the larger total number of students that rated their level of sustained attention also indicates that the majority of students have a high level of sustained attention. These results show that the majority of students have low levels of distractibility and impulsivity and high levels of sustained attention.

Table 5

Classroom Observations Data Pivot Table

Row Labels	Count of Student	Average of Rating
Distractibility	7	3
Impulsivity	6	2.5
Sustained Attention	7	4.428571429
Grand Total	20	3.35

.

Table 6

Paired Two Sample for Means of the Teachers/Parents Survey Results

t-Test: Paired Two Sample for Means
	Variable 1	Variable 2
Mean	11.41666667	1.666666667
Variance	62.99242424	1.515151515
Observations	12	12
Pearson Correlation	-0.263653046
Hypothesized Mean Difference	0
df	11
t Stat	4.046749647
P(T<=t) one-tail	0.000963096
t Critical one-tail	1.795884819
P(T<=t) two-tail	0.001926191
t Critical two-tail	2.20098516

The paired two sample t-test is used to compare the means of two related variables. In the data presented above, the first variable is mean 11.41666667 and the second variable is mean 1.666666667. The sample size for both variables is 12. The Pearson correlation between the two variables is -0.263653046, which suggests that there is a weak negative correlation between the two variables. This means that as one variable increases, the other variable decreases. The hypothesis tested in this t-test is that the difference between the means of the two variables is equal to zero. To test this hypothesis, a t-statistic of 4.046749647 was calculated. This t-statistic is compared to the critical value of 1.795884819 in a one-tail test, and a two-tail test of 2.20098516. The p-value for the one-tail test is 0.000963096, which is less than the critical value of 1.795884819. This suggests that the difference between the means of the two variables is statistically significant and the null hypothesis can be rejected. The p-value for the two-tail test is 0.001926191 which is also less than the critical value of 2.20098516. This suggests that the difference between the means of the two variables is statistically significant and the null hypothesis can be rejected. The paired two sample t-test has demonstrated that there is a statistically significant difference between the means of the two variables. The weak negative correlation between the two variables suggests that as one variable increases, the other variable decreases. This t-test is useful for determining whether or not the difference between the means of the two variables is statistically significant.

Table 7

Correlation Results of Students Survey

	Row Labels	Count of Percentage of Responses
Responses	1
Count of Percentage of Responses	-0.42199523	1

The data above presents the correlation between two variables, labeled as "Responses" and "Count of Percentage of Responses." The correlation between the two variables is -0.42199523. This data indicates that there is a negative correlation between the two variables, meaning that as one increases, the other decreases. In other words, the number of responses and the percentage of responses are inversely related to each other. The correlation of -0.42199523 indicates that there is a moderate negative correlation between the two variables. A negative correlation implies that as the number of responses increases, the percentage of responses decreases. This could be due to a variety of factors, such as the number of responses being too high for the percentage of responses to remain consistent, or that the responses are not evenly distributed.

Chapter 5: Discussion

Research Question 1: What were the underlying causes of short attention spans in pre-kindergarten students in Head Start programs?

The study’s findings identify that ADHD is the main culprit for decreased attention span among pre-kindergarten students enrolled in Head Start Programs. However, another reason for the shortened attention span could be anxiety. A child with separation anxiety will be preoccupied with thinking that something might happen to them while in school, making it difficult for them to concentrate. Other reasons could be that the child has obsessive-compulsive disorder, trauma or stress, and learning disorders such as auditory processing disorders, which could make the child miss out on what is being taught in class even if they are listening (Brown et al., 2005). In addition, the absence of parental involvement, teacher emotional support and proper class management techniques could render a student in a head start program to have a short attention span. Therefore, the study identifies that teachers must start by implementing innovative class-wide interventions to identify a suitable solution to aid the students in retaining attention.

Research Question 2: What interventions were effective in improving attention spans in pre-kindergarten students in Head Start programs?

The study identifies that different intervention techniques can play an integral role in improving the students' attention span in head start programs. The most effective intervention is to intensify parental involvement, which can be performed through daily report cards and techniques that can improve parent-child relationships to increase academic success. Families with ADHD appear to emphasize their children's success beyond all students' needs (Duncan et al., 2007). The study identifies that meaningful parent-child involvement and relationships in schools enhance academic performance for students with short attention spans, although it tends to be complicated. However, the study pinpoints that customizing the home environment to stimulate the child's education could be challenging for these families due to conflicts associated with non-compliant behaviour and broken parent-child relationships. Similarly, parents with ADHD tend to feel less welcome within the school environment compared to children without attention disorders. As a result, it is essential to integrate family engagement throughout the intervention process for learners with ADHD concerning school education and relationships.

The study identifies various ways to engage parents of students with short attention spans. The first strategy is to provide family therapy, family-school consultations and meetings. The family strategy will focus on providing parents with relevant support and education programs comprising different techniques, including discussing the child's progress and developing a deep context among the parents that can enable them to support one another. Also, the parents will be able to receive education regarding attention span disorders and how they can help their children make consistent progress in their education. The study found that parental involvement through family therapy was the most potent intervention. It was more effective than support and education in bettering parenting services, decreasing child behaviour problems while in school and empowering the student-children relationships (Castro et al., 2004). It was also found to reduce child behaviour in school and improve a child's family involvement in education. This is an ideal way to help struggling students with ADHD and provide clear directions to intensify student school functions and parenting practices.

Another effective strategy, according to the study, is computer-based instructions. The goal of this strategy is to prolong a learner's attention by interacting and engaging them in different activities and assigning them specific rules and plans to follow. Computer-based instructions provide step-by-step directions that prevent the student from getting confused or lost and provide immediate feedback, highlighting and reinforcing important concepts and information covered in the learning material. Therefore, computer-based instructions will play an integral role in reducing off-task behaviour and assist in guiding the students to learn different ways to manage themselves, ideally serving as a sound intervention strategy that helps students continue working independently.

Educators can also use this strategy in diverse instruction and student management techniques, especially when a student is struggling with retaining attention. In the pre-kindergarten students in the head start program reviewed in this study, teachers have been using information presented in the Teacher Management Practices for learners with attention span problems. Arguably, attention deficit behaviours forecast future reading difficulties in higher learning education, although earlier reading attainment remains controlled (Blair & Razza, 2007). By keeping this in mind, the computer-based practice effectively manages and instructs behaviour to prevent behavioural and academic behaviour problems. These strategies include making instructional and task modifications, peer tutoring, proactive structuring, contingency management and proactive structuring of the learning environment. In general, what was found to be the most beneficial for the learners while using computer-based instructions, is its ability to improve their ability to pay attention by providing them with actively engaging exercises that minimize distractions while providing instant positive reinforcement. This study finds that using computer-based training will equip learners with both mathematical and executive function skills which is essential in building a solid foundation for future academic excellence (Alvarado & Modesto-Lowe, 2017). This would also provide the teachers with an opportunity to guide parents on how they can direct their children with mathematical tasks for them to complete at home. However, the study finds that there is need for teachers to be trained on how to maximize the effectiveness of this technology in preparing customized assignments to suit the needs of their students (Ali et al., 2019). Also, they will be able to understand how to track a student’s progress to determine whether the computer-based training is working for them or they will need other interventions. Teachers should also learn how to incorporate mathematical games that are compatible with the child’s needs to help them become independent and content with their learning.

Research Question 3 : What were the long-term effects of interventions to improve attention span on academic performance and success in pre-kindergarten students in Head-start programs?

The study's outcomes identify that using parental involvement and computer-based instructions will offer long-term solutions in improving a learner's attention span. One of the impacts is that utilizing these intervention strategies among students in the head start programs will enhance their educational performance by increasing the possibility that they will complete it successfully and have higher chances of graduating high school, enrolling in a college and being awarded a post-secondary certification, degree or degree. Another impact is that these interventions are compatible with students suffering from ADHD, trauma and separation anxiety to develop emotionally and socially by improving their self-esteem, self-control and positive parenting techniques (Bierman et al., 2014). These elements are useful in ensuring that the child understand how to maintain discipline as a foundation to maintain focus on the end results which is retaining attention in class and make positive progress in their studies both now and in the future. Lastly, the study pinpoints that implementing these strategies among the students with attention deficit disorders in Head start programs will increase positive parenting practices for every ethnic group and engagement for the children whose mothers agree to cooperate compared to those who continue to ignore involvement.

Research Question 4: How did parental involvement specifically impact the attention span of pre-kindergarten students in Head-start programs while they were engaged in reading activities?

From the results, it is apparent that parental involvement in their children's reading, checking children's homework, attending family therapy and engaging with other parents significantly impacts a child's academic outcomes. In addition, situation-specific parental involvement, such as training them on how they can build better relationships with their children in Head Start programs, produced ultimate outcomes in providing a child with quality directions and behaviour control. Moreover, parental involvement positively impacts a child's academic performance. It improves a parent's relationship with other parents with similar problems, enabling them to brainstorm strategies to improve their children's well-being. Further involuntary parental involvement, such as school involvement, is effective, although less than voluntary acts for participation.

Implications of the Findings

According to the findings, when exercises are implemented before a lesson, the overall number of off-task behaviours is lowered based on the average number of observed characters. There is a significant difference based on the results between the two conditions, which clearly shows that exercises did help to improve the attention span of the student. Nevertheless, in some individual cases, various behaviours increased from initial observation and started going against the average finding of the class. Besides that, other factors affect the student's performance, such as age, mood, learning disabilities, and teacher biases during observation.

Implications for Future Research

The study reveals clearly that scholars need to look for various methods to improve student attention span. Students have been benefiting from doing exercises, yet it is among the first things being removed from them as a strategy for punishing off-task characters. Instead, students should be added exercise breaks as this will help them improve their long attention spans.

Conclusion

As a concluding remark, the study has strongly advocate that teachers and parents must play the role of ensuring that a child will attain longer attention span throughout their academic journey which starts after they have been enrolled in pre-kindergarten. While in school, students are directly affected by the surrounding environment where they spend most time of their day. The school environment is surrounded by a wide variety of distractions for the student taking the form of learning materials and presence of friends. However, computer-based training and parental involvement stand out as they promise to have long-term impact. Computer-based training provides the students with interactive materials and assign them engaging activities which have specific rules and goals which prevent them from getting lost or confused. Parental involvement on the other hand act as the primary motivating factor for the student and therefore providing a child with a positive home environment will reflect in their ability to remain attentive in class.

References

Ali, S., Mehmood, F., Dancey, D., Ayaz, Y., Khan, M. J., Naseer, N., & Nawaz, R. (2019). An adaptive multi-robot therapy for improving joint attention and imitation of ASD children.  IEEE Access,  7, 81808–81825.

Alvarado, C., & Modesto-Lowe, V. (2017). Improving treatment in minority children with attention-deficit/hyperactivity disorder. Clinical Pediatrics,  56(2), 171–176.

Antzaka, A., Lallier, M., Meyer, S., Diard, J., Carreiras, M., & Valdois, S. (2017). Enhancing reading performance through action video games: The role of visual attention span.  Scientific reports,  7(1), 14563.

Armstrong, T. (2017).  The myth of the ADHD child, revised edition: 101 ways to improve your child's behaviour and attention span without drugs, labels, or coercion. Penguin.

Barnes, E. M., Grifenhagen, J. F., & Dickinson, D. K. (2020). Mealtimes in Head Start pre-k classrooms: examining language-promoting opportunities in a hybrid space.  Journal of child language,  47(2), 337-357.

Barkley, R. A. (2002). Psychosocial treatments for attention-deficit/hyperactivity disorder in children.  Journal of clinical psychiatry,  63, 36–43.

Basso, D., Miller, L. C., & Galdo, E. (2016). The effects of universal state pre-kindergarten on the child care sector: The case of Florida's voluntary pre-kindergarten program.  Economics of Education Review,  53, 87–98.

Bauer, L., & Schanzenbach, D. W. (2016). The long-term impact of the Head Start program.  The Hamilton Project.

Benton, D., Brett, V., & Brain, P. F. (1987). Glucose improves attention and reaction to frustration in children.  Biological Psychology,  24(2), 95–100.

Ben-Zeev, T., Hirsh, T., Weiss, I., Gornstein, M., & Okun, E. (2020). High-intensity functional training (HIFT) affects adolescents' spatial learning, visual pattern separation, and attention span. Frontiers in Behavioral Neuroscience,  14, 577390.

Berman, M. G., Jonides, J., & Kaplan, S. (2008). The cognitive benefits of interacting with nature.  Psychological science,  19(12), 1207–1212.

Bierman, K. L., Nix, R. L., Heinrichs, B. S., Domitrovich, C. E., Gest, S. D., Welsh, J. A., & Gill, S. (2014). Effects of Head Start REDI on children's outcomes 1 year later in different kindergarten contexts.  Child development,  85(1), 140-159.

Blair, C., & Razza, R. P. (2007). Relating effortful control, executive function, and false belief understanding to emerging math and literacy ability in kindergarten.  Child development,  78(2), 647-663.

Brendamour, J. B., & Chai, H. (2016). Learning through Laughter: Improving Pre-K Students' Comprehension Retelling Skills through Selected Humorous Children's Picture Books.  Ohio Reading Teacher,  46(1).

Brown, R. T., Amler, R. W., Freeman, W. S., Perrin, J. M., Stein, M. T., Feldman, H. M., ... & Committee on Quality Improvement, Subcommittee on Attention-Deficit/Hyperactivity Disorder. (2005). Treatment of attention-deficit/hyperactivity disorder: an overview of the evidence. Pediatrics,  115(6), e749-e757.

Castro, D. C., Bryant, D. M., Peisner-Feinberg, E. S., & Skinner, M. L. (2004). Parent involvement in Head Start programs: The role of parent, teacher and classroom characteristics.  Early childhood research quarterly,  19(3), 413-430.

Chaudhari, S., Mithal, V., Polatkan, G., & Ramanath, R. (2021). An attentive survey of attention models.  ACM Transactions on Intelligent Systems and Technology (TIST),  12(5), 1–32.

Cohen-Vogel, L., Sadler, J., Little, M. H., Merrill, B., & Curran, F. C. (2022). The adoption of public pre-kindergarten among the American states: An event history analysis.  Educational Policy,  36(6), 1407-1439.

Delavan, G. (2009). The Teacher's Attention: Why Our Kids Must and Can Get Smaller Schools and Classes .

Doherty, T., Sanders, D., Jackson, D., Swanevelder, S., Lombard, C., Zembe, W., & Tylleskär, T. (2012). Early cessation of breastfeeding amongst women in South Africa: an area needing urgent attention to improve child health.  BMC Pediatrics,  12(1), 1–10.

Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A. C., Klebanov, P., & Japel, C. (2007). School readiness and later achievement.  Developmental psychology,  43(6), 1428.

Elmalech, A., Sarne, D., David, E., & Hajaj, C. (2016, September). Extending workers' attention span through dummy events. In  Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (Vol. 4, pp. 42–51).

Faber Taylor, A., & Kuo, F. E. (2009). Children with attention deficits concentrate better after walking in the park. Journal of attention disorders,  12(5), 402–409.

Gaston, A., Moore, S., & Butler, L. (2016). Sitting on a stability ball improves attention span and reduces anxious/depressive symptomatology among grade 2 students: A prospective case-control field experiment.  International Journal of Educational Research,  77, 136–142.

Gathercole, S. E., Alloway, T. P., Kirkwood, H., & Elliott, J. G. (2008). Working memory in the classroom. Educational Research Review, 3(3), 141–146.

Geri, N., Winer, A., & Zaks, B. (2017). A learning analytics approach for evaluating the impact of interactivity in online video lectures on students' attention span. Interdisciplinary Journal of E-Learning and Learning Objects,  13(1), 215–228.

Giramonti, K. M., Kogan, B. A., & Halpern, L. F. (2008). The effects of anticholinergic drugs on attention span and short‐term memory skills in children.  Neurourology and Urodynamics: Official Journal of the International Continence Society,  27(4), 315-318.

Giusa, F. F. L., & Perney, L. R. (1974). Further studies on the effects of brightness variations on attention span in a learning environment.  Journal of the Illuminating Engineering Society,  3(3), 249-252.

Hercules, K., Shamir, H., & Crowther, M. (2006, June). The Effects of Different Voices in Computer-Based Instruction on Children’s Learning. In  EdMedia+ Innovate Learning (pp. 515-521). Association for the Advancement of Computing in Education (AACE).

Hindman, A. H., Miller, A. L., Froyen, L. C., & Skibbe, L. E. (2012). A portrait of family involvement during Head Start: Nature, extent, and predictors.  Early Childhood Research Quarterly,  27(4), 654-667.

Hines, J. M. (2017). An Overview of Head Start Program Studies.  Journal of Instructional Pedagogies, p. 18.

Huffstetter, M., King, J. R., Onwuegbuzie, A. J., Schneider, J. J., & Powell-Smith, K. A. (2010). Effects of a computer-based early reading program on the early reading and oral language skills of at-risk preschool children.  Journal of education for Students Placed at Risk,  15(4), 279-298.

Hupp, S. D., & Reitman, D. (1999). Improving sports skills and sportsmanship in children diagnosed with attention-deficit/hyperactivity disorder.  Child & Family Behavior Therapy,  21(3), 35-51.

Hysell, J. C. (2013).  What do they know when they get there? The relationship of Head Start, More At Four/NC Pre-K, private preschool programs and no preschool experiences to kindergarteners' reading/literacy readiness. Capella University.

Jiang, Z. H., Yu, W., Zhou, D., Chen, Y., Feng, J., & Yan, S. (2020). Convert: Improving Bert with span-based dynamic convolution.  Advances in Neural Information Processing Systems,  33, 12837-12848.

Johnson, A. D., Finch, J. E., & Phillips, D. A. (2019). Associations between publicly funded preschool and low-income children’s kindergarten readiness: The moderating role of child temperament.  Developmental Psychology,  55(3), 623.

Juhasz, A. C., & Boyce, L. K. (2022). Exploring Bidirectional Language–Behavior Influences for Spanish–English Dual Language Learning Children in Head Start.  Journal of Emotional and Behavioral Disorders, 10634266221100212.

Kaelin, D. L., Cifu, D. X., & Matthies, B. (1996). Methylphenidate effect on attention deficit in the acutely brain-injured adult.  Archives of physical medicine and rehabilitation,  77(1), 6-9.

Karweit, N. (1989). Effects of parent involvement on reading achievement: A meta-analysis. Journal of Educational Research, 83(1), 53–61.

Kasuya-Ueba, Y., Zhao, S., & Toichi, M. (2020). The Effect of Music Intervention on attention in children: Experimental evidence.  Frontiers in Neuroscience,  14, 757.

Kerns, K. A., Eso, K., & Thomson, J. (1999). Investigation of a direct intervention for improving attention in young children with ADHD.  Developmental neuropsychology,  16(2), 273–295.

Klein, A., Starkey, P., Clements, D., Sarama, J., & Iyer, R. (2008). Effects of a pre-kindergarten mathematics intervention: A randomized experiment.  Journal of Research on Educational Effectiveness,  1(3), 155-178.

Kikas, E., Pakarinen, E., Soodla, P., Peets, K., & Lerkkanen, M. K. (2018). Associations between reading skills, interest in reading, and first-grade teaching practices. Scandinavian Journal of Educational Research,  62(6), 832-849.

Kim, Y., Lim, H., & Reeve, J. (2018). The effects of computer-based instruction on students with poor reading skills. Journal of Educational Technology Development and Exchange, 11(1), 1–12.

Kirk, S. M., Vizcarra, C. R., Looney, E. C., & Kirk, E. P. (2014). Using physical activity to teach academic content: a study of the effects on literacy in head start preschoolers.  Early Childhood Education Journal,  42, 181-189.

Kook, J. F., & Greenfield, D. B. (2021). Examining variation in instructional interaction across teacher-directed activities in head start classrooms. Journal of Early Childhood Research,  19(2), 128–144.

Kulkarni, C., & Khandale, S. R. (2019). Effect of brain gym exercises on the attention span in young adults.  International Journal for Advance Research and Development,  4(4), 71-75.

Ledford, J. R., Gast, D. L., Luscre, D., & Ayres, K. M. (2008). Observational and incidental learning by children with autism during small group instruction.  Journal of autism and developmental disorders,  38(1), 86–103.

Lerkkanen, M. K., Kiuru, N., Pakarinen, E., Poikkeus, A. M., Rasku-Puttonen, H., Siekkinen, M., & Nurmi, J. E. (2016). Child-centred versus teacher-directed teaching practices: Associations with the development of academic skills in the first grade at school. Early Childhood Research Quarterly,  36, 145-156.

LiBetti, A. (2019). Leading by Exemplar: Case Studies of Head Start Programs.  Bellwether Education Partners.

Lopez-Caudana, E., Ponce, P., Mazon, N., & Baltazar, G. (2022). Improving the attention span of elementary school children for physical education through an NAO robotics platform in developed countries.  International Journal on Interactive Design and Manufacturing (IJIDeM),  16(2), 657-675.

Ludwig, J., & Phillips, D. A. (2007). The benefits and costs of Head Start.

Luna, B., Thulborn, K. R., Munoz, D. P., Merriam, E. P., Garver, K. E., Minshew, N. J., ... & Sweeney, J. A. (2001). Maturation of widely distributed brain function subserves cognitive development.  Neuroimage,  13(5), 786-793.

Mahone, E. M., & Hoffman, J. (2007). Behavior ratings of executive function among preschoolers with ADHD.  The Clinical Neuropsychologist,  21(4), 569-586.

Mahone, E. M., & Schneider, H. E. (2012). Assessment of attention in preschoolers.  Neuropsychology review,  22, 361-383.

Mahone, E. M. (2005). Measurement of attention and related functions in the preschool child.  Mental retardation and developmental disabilities research reviews,  11(3), 216-225.

Maruhom, J. M. G., Garcia, C. B., Alfaro, M. H., Trinidad, C. A. B., & Mitra, J. M. C. (2016). The effect of Just Dance Kinectº on the attention span of selected college students.

Mackay, D. G. (1973). Aspects of the theory of comprehension, memory and attention.  Quarterly Journal of Experimental Psychology,  25(1), 22-40.

McClelland, M. M., Acock, A. C., Piccinin, A., Rhea, S. A., & Stallings, M. C. (2013). Relations between preschool attention span-persistence and age 25 educational outcomes.  Early childhood research quarterly,  28(2), 314–324.

Murphy, M. (2008). Matching workplace training to adult attention span to improve learner reaction, learning score, and retention. Journal of Instruction Delivery Systems,  22(2), 6–13.

Murray, J., Theakston, A., & Wells, A. (2016). Can the attention training technique turn one marshmallow into two? Improving children's ability to delay gratification.  Behaviour Research and Therapy,  pp. 77, 34–39.

O'Connor, R. (2000). Increasing the intensity of intervention in kindergarten and first grade.  Learning Disabilities Research & Practice,  15(1), 43-54.

Pashapoor, L., Kashani-Vahid, L., & Hakimirad, E. (2018, November). Effectiveness of cognitive computer games on the attention span of students with intellectual disability. In 2018 2nd National and 1st International Digital Games Research Conference: Trends, Technologies, and Applications (DGRC) (pp. 82–87). IEEE.

Peck, H. L., Kehle, T. J., Bray, M. A., & Theodore, L. A. (2005). Yoga as an intervention for children with attention problems.  School psychology review,  34(3), 415-424.

Pianta, R. C., Lipscomb, D., & Ruzek, E. (2021). Coaching teachers to improve students’ school readiness skills: Indirect effects of teacher–student interaction.  Child Development,  92(6), 2509-2528.

Pirnazar, T., Pourmohamadreza-Tajrishi, M., Zadeh Mohammadi, A., Haidarian, M., & Ahmadi, A. (2022). The Efficacy of Therapeutic Use of Play on Improving Attention Span of Mild Intellectually Disabled Children.  Iranian Rehabilitation Journal,  20(3), 317-326.

Posner, M. I., & Patoine, B. (2009). How arts training improves attention and cognition.  Cerebrum,  2009, 2-4.

Posner, M. I., Rothbart, M. K., & Voelker, P. (2016). Developing brain networks of attention.  Current opinion in paediatrics,  28(6), 720.

Rapport, M. D., Chung, K. M., Shore, G., & Isaacs, P. (2001). A conceptual model of child psychopathology: Implications for understanding attention deficit hyperactivity disorder and treatment efficacy.  Journal of Clinical Child & Adolescent Psychology,  30(1), 48–58.

Raver, C. C. (2002). Emotions matter: Making a case for young children's emotional development role for early school readiness. Social Policy Report, 16(3), 3–30.

Ray, D. C., Schottelkorb, A., & Tsai, M. H. (2007). Play therapy with children exhibiting symptoms of attention deficit hyperactivity disorder.  International Journal of Play Therapy,  16(2), 95.

Reid, N., Dawe, S., Shelton, D., Harnett, P., Warner, J., Armstrong, E., & O'Callaghan, F. (2015). A systematic review of fetal alcohol spectrum disorder interventions across the life span.  Alcoholism: Clinical and Experimental Research,  39(12), 2283–2295.

Rikken-Evers, M. T., Smith, K. D., & Sterkenburg, P. S. (2022). Effect of the use of an iPad on the attention span of a child with Smith Magenis Syndrome: A single case study.  Journal of Intellectual Disabilities,  26(2), 337-349.

Rodriguez, J. (2013). The impact of voluntary pre-kindergarten on students' academic achievement and kindergarten readiness in a large suburban school district.

Rojas Torres, M. (2016). Improving preschool students´ attention span in my english class.

Rosen, B&. Kirkman, B. L., (1999). Beyond self-management: Antecedents and consequences of team empowerment.  Academy of Management Journal,  42(1), 58-74.

Rossi, S., Zanier, E. R., Mauri, I., Columbo, A., & Stocchetti, N. (2001). Brain temperature, body core temperature, and intracranial pressure in acute cerebral damage.  Journal of Neurology, Neurosurgery & Psychiatry,  71(4), 448-454.

Schuck, S. E., Johnson, H. L., Abdullah, M. M., Stehli, A., Fine, A. H., & Lakes, K. D. (2018). The role of animal-assisted intervention on improving self-esteem in children with attention-deficit/hyperactivity disorder. Frontiers in paediatrics,  6, 300.

Silverstein, S. M., Menditto, A. A., & Stuve, P. (2001). Shaping attention span: An operant conditioning procedure to improve neurocognition and functioning in schizophrenia.  Schizophrenia Bulletin,  27(2), 247-257.

Strand, M. T., Hawk, L. W., Bubnik, M., Shiels, K., Pelham, W. E., & Waxmonsky, J. G. (2012). Improving working memory in children with attention-deficit/hyperactivity disorder: the separate and combined effects of incentives and stimulant medication.  Journal of abnormal child psychology,  40, 1193-1207.

Tang, Y. Y., & Posner, M. I. (2009). Attention training and attention state training.  Trends in cognitive sciences,  13(5), 222–227.

Tang, Y. Y., Posner, M. I., & Rothbart, M. K. (2014). Meditation improves self‐regulation over the lifespan. Annals of the New York Academy of Sciences,  1307(1), 104–111.

Tian, Y., Song, Y., Xia, F., & Zhang, T. (2020). Improving constituency parsing with span attention.  arXiv preprint arXiv:2010.07543.

Turner, D. C., Clark, L., Dowson, J., Robbins, T. W., & Sahakian, B. J. (2004). Modafinil improves cognition and response inhibition in adult attention-deficit/hyperactivity disorder.  Biological psychiatry,  55(10), 1031–1040.

Vaughn, S., Levy, S., Coleman, M., & Bos, C. S. (2002). Reading instruction for students with LD and EBD: A synthesis of observational studies. The Journal of Special Education,  36(1), 2–13.

Wasik, B. A., Bryan, T., & Clemens, N. H. (2009). Parent involvement and early literacy: A meta-analytic review of the empirical research. Journal of Educational Psychology, 101(2), 740-764.

Washington, V. (2017). Universal pre-k: What we know, what we need.  Virginia Journal of Education,  110(4), 17-19.

White, L. J., Fernandez, V. A., & Greenfield, D. B. (2020). Assessing classroom quality for Latino dual language learners in head start: DLL-specific and general teacher-child interaction perspectives.  Early education and development,  31(4), 599-627.

Wrońska, N., Garcia-Zapirain, B., & Mendez-Zorrilla, A. (2015). An iPad-based tool for improving the skills of children with attention deficit disorder.  International journal of environmental research and public health,  12(6), 6261-6280.

Yoon, K. S., Duncan, T., Lee, S. W. Y., Scarloss, B., & Shapley, K. L. (2007). Reviewing the evidence on how teacher professional development affects student achievement. Issues & answers. Rel 2007-no. 033.  Regional Educational Laboratory Southwest (NJ1).

Zhao, J., Liu, H., Li, J., Sun, H., Liu, Z., Gao, J., & Huang, C. (2019). Improving sentence reading performance in Chinese children with developmental dyslexia by training based on visual attention span.  Scientific rep

Appendix A

Classroom Observations Data

Classroom Observation Data

Student	Subscale	Rating
1	Sustained Attention
2	Distractibility
3	Impulsivity
4	Sustained Attention
5	Distractibility
6	Impulsivity
7	Sustained Attention
8	Distractibility
9	Impulsivity
10	Sustained Attention
11	Distractibility
12	Impulsivity
13	Sustained Attention
14	Distractibility
15	Impulsivity
16	Sustained Attention
17	Distractibility
18	Impulsivity
19	Sustained Attention
20	Distractibility

Teachers code- 100.0 thru 100.40 ( Five numbers)

Parents code- A thru Z ( Alphabets)

Students code – 1 thru 40 ( Numbers)

Appendix B

Demographic Characteristics of Potential Participants

Demographic Characteristics of Potential Participants

Demographic Characteristic	Frequency (%)
GENDER
Male
Female
RACE/ETHNICITY
Hispanic
African American
White
Other
SOCIOECONOMIC STATUS
Low
Medium
High
AGE
3 Years
4 Years
5 Years

Appendix C

Student Survey

Student Survey

Question	Response	Number of Responses	Percentage of Responses
When you are reading, how often do you find yourself losing focus?	Never
	Rarely
	Sometimes
	Often
How confident are you in your ability to read and comprehend material?	Very confident
	Somewhat confident
	Not very confident
	Not at all confident
How much do you enjoy reading?	Very much
	Somewhat
	Not very much
	Not very much
When you are reading, how often do you find yourself getting distracted?	Never
	Rarely
	Sometimes
	Often
How likely are you to ask for help when you are having difficulty understanding something you are reading?	Very likely
	Somewhat likely
	Not very likely
	Not at all likely

Appendix D

Parent/Teacher Informational Survey

Parent/Teacher Informational survey

Question	Response	Number of Responses	Percentage of Responses
In your opinion, how attentive is this student while reading?	Very attentive
	Somewhat attentive
	Not very attentive
	Not at all attentive
How confident do you feel that this student can comprehend and remember what they have read?	Very confident
	Somewhat confident
	Not very confident
	Not at all confident
How would you rate this student’s ability to focus on reading activities?	Very good
	Good
	Average
	Poor
How often do you feel that this student requires assistance while reading?	Very often
	Often
	Occasionally
	Rarely
In your opinion, how motivated is this student when it comes to reading activities?	Very motivated
	Somewhat motivated
	Not very motivated
	Not at all motivated

Appendix E

Parent/Teacher Pre-Survey/Post-Survey

Parent/Teacher Pre-Survey/Post-Survey

1. In your opinion, how attentive is this student while reading?

A) Very attentive

B) Somewhat attentive

C) Not very attentive

D) Not at all attentive

2. How confident do you feel that this student can comprehend and remember what they have read?

A) Very confident

B) Somewhat confident

C) Not very confident

D) Not at all confident

3. How would you rate this student’s ability to focus on reading activities?

A) Very good

B) Good

C) Average

D) Poor

4. How often do you feel that this student requires assistance while reading?

A) Very often

B) Often

C) Occasionally

D) Rarely

5. In your opinion, how motivated is this student when it comes to reading activities?

A) Very motivated

B) Somewhat motivated

C) Not very motivated

D) Not at all motivated

Appendix F

Student Pre-Survey/Post-Survey

Student Pre-Survey/Post-Survey

1. When you are reading, how often do you find yourself losing focus?

A) Never

B) Rarely

C) Sometimes

D) Often

2. How confident are you in your ability to read and comprehend material?

A) Very confident

B) Somewhat confident

C) Not very confident

D) Not at all confident

3. How much do you enjoy reading?

A) Very much

B) Somewhat

C) Not very much

D) Not at all

4. When you are reading, how often do you find yourself getting distracted?

A) Never

B) Rarely

C) Sometimes

D) Often

5. How likely are you to ask for help when you are having difficulty understanding something you are reading?

A) Very likely

B) Somewhat likely

C) Not very likely

D) Not at all likely

�Once all tables are corrected and on the right pages fix page numbers….do this at the very end.

�

�

�Tables still have bold faced print none inside the table.

Too many horizontal lines.

None under male or female,

None under all the ethnicities.none under loomed, hi

None under 3yr or 4 yr. Leave the one under 5year.

Words under bottom line move down one space.

�Table title are not bold and are in italics.

�

Table 2 is capitalized.

�Italics

No bold faced print

No lines under

Never

Rarely

Sometimes or often

Or any of the other lines you do not need lines except 2 at top and one at bottom.

�Only 3 lines in table two at top, one at bottom.

�One line above student and one below and one at the bottom delete all the others.

�Two lines on top and one at bottom

Round the number 4.428371429 to 4.4

�Discuss Table 6 before it. No blank spaces here on p 74.

�One line under title and one line

Under t-test etc. and one at bottom of table.

Round all numbers to hundredths digit. 11.41 1.66. etc.

�Round to the hundredths 11.41. 1.66 etc.

�Omit line under responses round number to -0.42