For this assignment, you will submit an initial draft of your final project Discussion section. This section should recap your findings, discuss how the findings fit in with prior research on the topic, discuss areas for future research, and mention limit

Running Head: POSITIVE REINFORCEMENT 1

POSITIVE AND NEGATIVE REINFORCEMENT 30

Positive Reinforcement

Matthew Rosario

Southern New Hampshire University

Reinforcement

Reinforcement is used to condition a particular behavioral response or action. According to Berger (2014), Reinforcement is a stimulus or event that increases the frequency of response it follows. To increase the frequency of the desired behavior, positive or negative reinforcement must be used. Positive reinforcement works by establishing a motivating stimulus after the desired behavioral response. For example, when a child completes their homework and receives a reward like candy. Negative reinforcement is when a particular stimulus is removed when a particular behavior is displayed. By removing a negative stimulus, it is less likely to occur again. For example, a driver follows the speed limit to avoid receiving a ticket. Keep in mind negative reinforcement is not a punishment because it increases a behavioral response instead of decreasing it.

Integrated Research

The ability to shape appropriate behavior while extinguishing misbehavior is critical to teaching and learning in physical education. The scientific principles that affect student learning in the gymnasium also apply to the methods teachers use to influence social behaviors. Downing and colleagues describe the results of an experiment that examined the ability to shape behavior to student to be teachable. The authors hypothesized that reinforcement, the stimulus is far more effective than the traditional punishment. Positive and negative reinforcement is never to be looked at as a punishment; it is a corrective action to change a specific behavior. The author found that participants who had an exemplary teacher who utilized both positive and negative reinforcement motivate the students to learn. It complements the work of Biederman, Valerie, Ryder, & Franchi (1994) who found that teachers who paid more attention to their student had a better turnout of positive grades. Mendres and Borrero (2010) found a student who received positive help from their teacher were more likely to change behavior to succeed in the particular class. Magg (2001) describes the results of an experiment that examined the various forms of rules used to handle a student who was disrupted in class. The author hypothesized that their student who is constantly being removed from class does not stop the disruptions because the only negative reinforcement is being used. The author found that participants who were removed from class were only receiving negative reinforcement, and little encouragement was being made to correct the behavior.

Thiel (2013) founded participant who received positive reinforcement continue to strive and receive more positive stimulus. Thiel and colleagues describe the results of an experiment that examined Auditory Discrimination Task, which correct performance results in a financial gain and wrong performance resulted in financial losses. The authors hypothesized negative and positive stimuli are a key requirement for understanding learning. The participants who received financial gain for judging the durations of frequencies were more likely to continue the required performance. MacPherson and colleagues (2010) described the results of an experiment that examined the behavioral task measuring risk with positive and negative reinforcement. The researchers hypothesized that there would be a connection with DT and RTP relationship of specific gender due to the developmental advancement between males and females. The researchers found distress tolerance was higher in males, which lead male to have more risky behavior or choices. Maag (2001) found a disruptive male student who received negative reinforcement did not change their behavior. Reinforcement is a stimulus or event that increases the frequency of response it follows. Dad and colleagues (2010) describe the results of an experiment that examined how teachers used positive and negative reinforcement in urban schools. The authors hypothesized that the teachers would not distinguish between the use of positive and negative reinforcement. It was later found out by a survey that teachers in urban school were using positive and negative reinforcement with their student to receive the results the teacher wanted. This article is extremely useful for my paper because it provides evidence that students who received reinforcement from their teacher did a better job in the classroom. It can be determined that positive reinforcement leads to a successful student if applied correctly. My hypothesis is positive and negative reinforcement increase student success in online education.

Research Designs

Downing and colleagues (2005) used one research design to conduct their experiments in multiple secondary school areas. The researchers used a sample of 1,000 teachers from different schools outside of the United States. This experiment did not use citizen of the United States. The teachers were randomly selected which led the secondary school teachers to be evenly balanced throughout the school systems in the secondary countries. To gather data from the participants, a survey was developed and administered by the research to have 100 percent accountable for the survey. This design has an advantage because it uses a comprehensive questionnaire to gather their information and using descriptive data analysis to compare the data. To analyze the data, they used descriptive and one-way chi-square and two-way chi-square to see how the questionnaire was answered and compared to another participant. Although this research design has its advantage, it also has its disadvantages. The disadvantage of this experiment is that it was conducted in a different country and has not been conducted in the United States. Another disadvantage to this experiment was although the teachers were randomly picked, they truly are not random. Since the teachers are already associated with the schools, the selection of teachers are not random, and the experiment can have bias data. Therefore the authors should have conducted the experiment in several countries to validate their results.

Appropriateness of the Research

Call and Mevers (2014) results evaluated how positive reinforcement affected problem behavior after negative reinforcement was maintained. The authors hypothesized that analytic strategies were proven effective in reducing problem behavior. Call and Mevers (2014) found that a participant who received positive reinforcement were more effective than negative reinforcement after the follow-on treatment. This article is useful because it provides evidence that positive reinforcement may be the key of a successful student, for example, receiving good grades after an assignment. Also, it nicely complements the work of Weis, Puschmann, Brechmann, Thiel. (2013) who found a participant who received positive reinforcement continue to strive and receive more positive stimulus. Mendres and Borrero (2010) describe the results of an experiment that examined class development for students. The experiment was testing the students’ response in a class by using positive and negative reinforcement. They hypothesized that there would be a relationship between students grades who participate because of positive reinforcement and those who participate because of negative reinforcement. They found the participant who used positive reinforcement to avoid losing points. Also, it nicely complements the work of Dad, Janja, Shahzad, & Khan. (2010) who found teachers who used positive reinforcement had successful student than those who did not receive any stimulus.

Unknown Research

To understand how a student uses positive reinforcement, we must understand their development. It is unknown to researchers the development of their participants, which can affect the experiment. Downing and colleagues (2005) evaluated the teacher’s use of positive and negative stimulus to help the learning of their students. Although this is beneficial, it is unknown if the teachers are using the same stimulus through the entire secondary schools. Not knowing if the teachers are using the same type of stimulus this can lead to the question whether or not students learn differently depending on the specific teacher. It is also unknown if the student is retaining to the information after the stimulus is used. In other words, after the teacher teaches a specific section after a few months does the student retain the information after receiving the stimulus? In the experiment I will be conducting their will be two unknowns. I will be using students for SNHU, whose background will be unknown and their developmental childhood and learning process are different from one another. SNHU accepts students from all over the country; there will know why to range each participant academic background due to the academic standards of each state and individual students. This will lead to an unknown variable of academic background and materials learned. Positive and negative stimulus in the academic background can be used difficulty in the development of children. As students continue to pursue higher education, it can be hard to determine which stimuli were used in their academic development. It is unknown if the participants will recall their academic background from high school to college because it is not known whether or not they understand and can recognize a positive and negative stimulus. As a college psychology student we understand the stimulus of positive and negative reinforcement, but for those who do not understand this stimulus it will be hard to evaluate the answers in the survey for accuracies. Furthermore, if research experiments have an unknown, it can harm the experiment if the entire unknown is not pointed out in advance. In the article, there are a few unknowns which the authors did not address.

Method

To analyze the data in the experiment listed above, I would use descriptive and one-way chi-square and two-way chi-square to see how the questionnaire was answered and compared to another participant. According to APA (2016), the term test data refer to raw and scaled scores, client/patient responses to test questions or stimuli and psychologists notes and recordings concerning client/patient statements and behavior during an examination. Informed consent in psychology involves both verbal and written communication between clients and therapists. Informed consent is in the agreement between professionals and client, which bonds rules, regulations, and confidentiality. According to APA (2014) Standard 3.10 states, informed consent is a requirement when conducting research, counseling, therapy, or assessment (Koocher & Keith-Spiegel, 2008, pg. 555). Therefore, the code of ethic has guidelines when using participant and how to interrupt and release the data.

Research Hypothesis

Skinner believed to understand behavior; cause of action and consequences first must be understood. In other words, to understand how to change properly behavior the action must be understood to change a specific behavioral response. Understanding the route action and route stimulus will contribute to either using a positive or negative reinforcement. Punishment is used to weaken a behavior and should not be confused with the other two stimuli because positive and negative reinforcement is used to increase a behavior and is the recommended use for specific behavioral changes. Punishment is used as a disciplinary action or an act which is intended to correct a behavior but is not as useful because it is intended to forcefully change a behavior or deprive an action. As online graduate students, there is a lot of stress, work, and daily task which can contribute to an unsuccessful student. My hypothesis is positive reinforcement increase student success in online education.

Methods

Participants in the dataset for this study will be 8-12 online students from Southern New Hampshire (SNHU). The total sampling will be the convenience of the students who select to participate in the study through SNHU psychology lounge, and I will be completely unknown of their gender and academic background. Prospective participants will have some fundamental knowledge of the study based on the introduction of the study survey and will not have any information of the other participants. The dataset will be unknown until the research study begins to keep the sampling random. The researcher will not have any background information about the sampling to minimize any bias tendencies and to validate the survey. SNHU has minimized the experiment sampling only to current students taking PSY 520 who are online students. The only information the research will have about the participants are there first and last name. Keep in mind the participant's name will be disclosed to the researcher do with establishing 100 percent participation. It is currently unclear if the total sampling will be efficient enough to determine whether or not correlation can be determined. The dataset will be finalized once PSY 520 convenes. The sampling and dataset will prove positive and negative reinforcement develops a successful online graduate student at SNHU. By aligning materials with the research question, this will allow the study to use materials such as surveys and observations from the participants this will help understand the mean and correlation of the variables being compared and contrast to one another.

Measures

Baumeister, Vohs, and Funder (2007) indicated a remarkable amount of behavior turns out to be just marked on a self-report questionnaire. Self-reports are completed using a survey, which has been the proven method the gather information about behavior. For many types of research involving personality, self-reports are used as a method of gathering information. The questionnaire in the research will be self-reported which will use the five-point Likert-type response scale to indicate different levels of agreement to determine the effectiveness of the reinforcer. Each five-point Likert-type will have a sufficient point value which will determine the level of the reinforcer, which the researcher will only know to calculate the dataset. After the questionnaire is completed, it will be forwarded to the other researchers (Professor) participating in the experiment. After approved by the fellow researchers the survey will be e-mailed out to the SNHU online students currently in the same PSY 520 and a read receipt will accompany the email to validate all participants have received the questionnaire to have 100 percent contact. The participants will have two weeks to answer and return the questionnaire where the researchers will check off their names when the questionnaire is returned to the originator. If some questionnaires have not been returned a follow-up email will follow until all questionnaires is returned. All the dataset will be entered into SSPS to correlate the information and to determine the results.

Ethical Considerations

The ethical concerns involved in the study are confidentiality and release of raw dataset scale. This concern of confidentiality is important because the questionnaire will ask a few personal questions which can make the participants feel uncomfortable to answer the questions. The participants may not want to disclose any information they feel might get out to their families or local employment agencies. To remediate this issue, I will educate the participant of the American Psychological Association code of ethics and standards. Confidentiality “refers to a general standard of professional conduct that obliges a professional not to discuss information about a client with anyone. Confidentiality is an agreement between client and psychologist which requires informed consent. According to APA (2014) Standard 3.10 states, informed consent is a requirement when conducting research, counseling, therapy, or assessment (Koocher & Keith-Spiegel, 2008, pg. 555). To minimize this I will write an agreement for the participants and other researchers (Professor) to sign stating no names will be disclosed to the public and the identity of the participant will not be relieved except for the age and gender of the participant. This shall minimize any worries and breach of confidentiality.

Raw Data

The procedures which will be used to analyze the dataset will be SSPS. To analyze the dataset using SSPS, the program will allow an analysis of the mean, independent samples t-test, and dependent samples t-tests of the dataset to determine the correlation the dataset. By analyzing the mean, this will determine the relationship between the dataset to show the middle or mean number set through descriptive statistics. The independent sample t-test and dependent samples will allow an analysis to determine the correlation of the data set to validate if the datasets are sufficient by determining the p-value. This analysis will allow in an analytical procedure to take place to interpret the dataset. To obtain valid and reliable results, I must make sure I have received 100 percent returns on the survey. It order to validate the survey for reliability I will administer the same survey three times to the same participants to validate and compare to make sure the answers are accurate to validate the results.

Analytic Procedures

The analytical procedures for analyzing data for this study is to use the descriptive and one-way chi-square and two-way chi-square analysis to describe, explain, and interpret patterns of relationships between variable frequency of common answers. By descriptive and one-way chi-square and two-way chi-square, this will allow the interpretation of the dataset for information understood by others to shift the information to knowledge. This will allow an understanding and view of the relationship between the data set and the collection of the data analysis. Descriptive and one-way chi-square and two-way chi-square data analysis will contribute to frequencies of variables, differences between variables, the significance of the results to determine that the probability of results did not happen by chance. This will evaluate trends and relationships between variables were data would be observed and study to see if there is a difference between the usages of positive and negative reinforcement by analyzing the collected data only. Rosnow and Rosenthal (2013) the chi-square test provide a method for testing the association between the row and column variables in a two-way table. This will allow me to compare the null hypothesis and see if there is a relationship between both of my hypothesis of positive and negative stimulus. The methodology of this analytic procedure is to compare and contrast to see the correlation of the raw data set and variables. Rosnow and Rosenthal (2013) the chi-square test is based on a test statistic that measures the divergence of the observed values from the data that would be expected under the null hypothesis of no association. The methodology of this analytic procedure is to compare and contrast to see the correlation of the raw data set and variables

Descriptive Statistics

The descriptive statistics obtained from the data which would be used to answer the hypothesis is the five-point Likert-type. The five-point Likert-type will use a scale based on the answer given. The question being asked will determine what type of stimulus is being used and the level of stimulus. The levels will be determined as follows -1 being the less 3 the most.

SRONGLY DISAGREE	DISAGREE	I DON’T KNOW	AGREE	STONGLY AGREE
-1	0	1	2	3

Using this descriptive statistics to categories the questions being asked will allow a statistical and descriptive analysis of the dataset to compare and correlate with one another. This will be the most informative and efficient because it will allow the questions to be numbered and analyzed by the question to determine also how many other students answered the same questioned currently. Descriptive statistics of the five-point Likert-type will gather a valid and honest deceptive analysis of the dataset.

Principles and Standards

According to APA (2014) when interpreting assessment results, including automated interpretations, psychologists take into account the purpose of the assessment as well as the various test factors, test-taking abilities and other characteristics of the person being assessed, such as situational, personal, linguistic and cultural differences, that might affect psychologists' judgments or reduce the accuracy of their interpretations. The proposed data analysis used in this experiment is ethical because the sampling is randomized which subtracts the element of bias since the sampling was not chosen by the psychologist. Also, the interpreting assessment results are valid because the dataset is being correlated through the p-value to validate the sufficiency of the dataset. Also, the participants will sign an informed consent form to validate the test data to be released, so there are no legal or ethical issues. Also, according to APA (2014) Regardless of whether the scoring and interpretation are done by psychologists, by employees or assistants or by automated or other outside services, psychologists take reasonable steps to ensure that explanations of results are given to the individual or designated representative. In other words, regardless of the results and outcome researchers must be honest and accurate when interpreting the results to other professional without bias. This will allow an accurate and honest study with no or minimal ethical dilemmas. Although there may be more ethical issues the APA code of ethical principles and standards is a reference for all research methods and data release.

Anticipated Results

The prediction for the experiment is that SNHU student will suggest they have been exposed to or use positive and negative reinforcement to be a successful online graduate student. This predicate is best in peer literature and previous research conduct to see the correlation between positive and negative stimulus. Some literature suggests that positive and negative reinforcement is the key to behavioral manipulation and the ability to understand specific behavior function and thinking. For example, Maag (2001) Most approaches dealing with student disruptions involve the use of various forms of punishment, although some of these approaches may make schools safer by removing the offending students, they have little effect on encouraging students to perform socially appropriate behaviors. The author found that participants who were removed from class were only receiving negative reinforcement, and little encouragement was being made to correct the behavior. This article complements the work of Mendres and Borrero (2010) who found that student who received positive help from their teacher were more likely to change behavior to succeed in the particular class. Also, Biederman, Valerie, Ryder, and Franchi, (1994) found that teachers who paid more attention to their student had a better turnout of positive grades. This allows the rationale prediction about the experiment and the results. The results will complement the previous literature and support their finding that stimulus is used to get a specific result or respond. By the results showing that positive and negative stimulus was used for students to be successful, this demonstrates when parents and teachers use reinforced in a positive or negative way they will receive the results they are looking for. Therefore, positive and negative reinforcement contributes to a successful online graduate student.

Descriptive statistics

1. After I finish an assignment, I reward myself.

Figure 1

Q1
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	disagree	7	46.7	46.7	46.7
	agree	5	33.3	33.3	80.0
	strongly agree	3	20.0	20.0	100.0
	Total	15	100.0	100.0

Table 1

From the figure above, shows that 46.7 % (n=7) strongly disagreed, 33. 3 % (n=3) agreed and 20 % (n=3) strongly agreed with the idea of awarding themselves after they finish an assignment.

2. When I receive above an 80 percent on an assignment, it motivates me

Figure 2

Q2
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	disagree	3	20.0	20.0	20.0
	i dont know	1	6.7	6.7	26.7
	agree	6	40.0	40.0	66.7
	strongly agree	5	33.3	33.3	100.0
	Total	15	100.0	100.0

Table 2

The Figure shows that 40 % (n=6) agree, 33.3% (n=5) strongly agreed, 20% (n=3) while 6.7% (n=1) do not know that when they receive above 80 % on an assignment as it motivates them.

3. I do not do assignments until just before they are to be handed in.

Figure 3

Q3
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	strongly disagree	2	13.3	13.3	13.3
	disagree	4	26.7	26.7	40.0
	dont know	1	6.7	6.7	46.7
	agree	4	26.7	26.7	73.3
	stronly agree	4	26.7	26.7	100.0
	Total	15	100.0	100.0

Table 3

The Figure shows that 26.7 % (n=4) agree, 26.7% (n=4) strongly agreed, 26.7% (n=3) disagreed 13.3% (n=2) strongly disagree and 6.7 % (n=1) do not know if they wait to do the assignment until just before they are handed in.

4. I often find myself performing tasks that I had intended to do days before.

Figure 4

Q4
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	strongly disagree	2	13.3	13.3	13.3
	disagree	6	40.0	40.0	53.3
	dont know	2	13.3	13.3	66.7
	agree	3	20.0	20.0	86.7
	strongly agree	2	13.3	13.3	100.0
	Total	15	100.0	100.0

Table 4

The Figure shows that 20 % (n=3) agree, 13.3% (n=2) strongly agreed, 40% (n=6) disagreed 13.3% (n=2) strongly disagree and 13.3% (n=2) do not know if they would get out of their way to complete an assignment before their children came home.

5. I would go out of my way to complete an assignment before my children come home.

Figure 5

Q5
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	strongly disagree	1	6.7	6.7	6.7
	disagree	3	20.0	20.0	26.7
	i don’t know	3	20.0	20.0	46.7
	agree	4	26.7	26.7	73.3
	strongly agree	4	26.7	26.7	100.0
	Total	15	100.0	100.0

Table 5

The Figure shows that 26.7 % (n=4) agree, 26.7% (n=4) strongly agreed, 20% (n=3) disagreed, 6.7 % (n=2) strongly disagree and 20% (n=3) do not know if they can spend two or more hours completing an assignment.

6. I spend 2 or more hours completing an assignment.

Figure 6

Q6
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	agree	6	40.0	40.0	40.0
	strongly agree	7	46.7	46.7	86.7
	6	2	13.3	13.3	100.0
	Total	15	100.0	100.0

Table 6

The Figure shows that 40 % (n=6) agree, 46.67% (n=7) strongly agreed that they receive B and higher grade in their courses.

7. I receive B and higher in my courses.

Figure 7

Q7
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	agree	3	20.0	20.0	20.0
	strongly agree	12	80.0	80.0	100.0
	Total	15	100.0	100.0

Table 7

The Figure shows that 20 % (n=3) agree, 80% (n=12) strongly agreed that if they receive bad grades they would study more.

8. When I receive a bad grade, I study more.

Figure 8

Q8
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	dont know	1	6.7	6.7	6.7
	agree	8	53.3	53.3	60.0
	strongly agree	6	40.0	40.0	100.0
	Total	15	100.0	100.0

Table 8

The Figure shows that 53.3 % (n=8) agree, 40% (n=4) strongly agreed, and 6.7% (n=1) do not know if they feel disappointed when they do not complete their assigned on time.

9. I feel disappointed when I do not complete my assignment on time.

Figure 9

Q9
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	dont know	1	6.7	6.7	6.7
	agree	2	13.3	13.3	20.0
	strongly agree	12	80.0	80.0	100.0
	Total	15	100.0	100.0

Table 9

The Figure shows that 13.3 % (n=2) agree, 80% (n=12) strongly agreed, and 6.7% (n=1) do not know if they do hesitate to start the assignment when it is time.

10. When it is time to start my assignment I do not hesitate

Figure 10

Q10
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	disagree	5	33.3	33.3	33.3
	i dont know	2	13.3	13.3	46.7
	agree	4	26.7	26.7	73.3
	strongly agree	4	26.7	26.7	100.0
	Total	15	100.0	100.0

Table 10

The Figure shows that 26.7 % (n=4) agree, 26.7% (n=4) strongly agreed, 33.3% (n=5) disagreed, and 13.3% (n=2) do not know if they can come home and complete their assignment at home.

11. After Work I come home to complete my assignment.

Figure 11

Q11
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	strongly disagree	1	6.7	6.7	6.7
	diasgree	4	26.7	26.7	33.3
	agree	7	46.7	46.7	80.0
	strongly agree	3	20.0	20.0	100.0
	Total	15	100.0	100.0

Table 11

The Figure shows that 46.7 % (n=7) agree, 20% (n=3) strongly agreed, 6.7 % (n=1) strongly disagreed and 6.7% (n=1) do not know if they can contact their professors if they are having difficulties.

12. . I contact my Professor when I am having difficulties.

Figure 12

Q12
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	disgaree	1	6.7	6.7	6.7
	i dont know	1	6.7	6.7	13.3
	agree	5	33.3	33.3	46.7
	strongly agree	8	53.3	53.3	100.0
	Total	15	100.0	100.0

Table 12

The Figure shows that 33.3 % (n=5) agree, 53.3% (n=8) strongly agreed, 6.7% (n=1) disagreed, and 6.7% (n=1) do not know if they can stay up late to complete an assignment.

13. I stay up late to complete my assignment.

Figure 13

Q13
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	strongly disagree	1	6.7	6.7	6.7
	disagree	2	13.3	13.3	20.0
	i dont know	1	6.7	6.7	26.7
	agree	4	26.7	26.7	53.3
	strongly agree	7	46.7	46.7	100.0
	Total	15	100.0	100.0

Table 13

The Figure shows that 26.7 % (n=4) agree, 46.7% (n=7) strongly agreed, 13.3% (n=2) disagreed, 6.7 % (n=1) strongly disagree and 20% (n=3) do not know if they can lose sleep in order to complete an assignment.

14. I am willing to lose sleep in order to complete in assignment.

Figure 14

Q14
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	disagree	1	6.7	6.7	6.7
	i don’t know	2	13.3	13.3	20.0
	agree	7	46.7	46.7	66.7
	strongly agree	5	33.3	33.3	100.0
	Total	15	100.0	100.0

Table 14

The Figure shows that 46.7 % (n=7) agree, 33.3% (n=5) strongly agreed, 6.7 % (n=1) strongly disagreed and 6.7% (n=1) do not know if they can contact their professors if they are having difficulties.

Inferential statistics

Two-way chi square

Chi-Square Tests
	Value	d.f	Asymp. Sig. (2-sided)
Pearson Chi-Square	3.187a	6	.785
Likelihood Ratio	4.150	6	.656
Linear-by-Linear Association	.643	1	.422
N of Valid Cases	15
a. 12 cells (100.0%) have expected count less than 5. The minimum expected count is .07.

From the chi square test above it is quite evident the p-value =0.785>0.05 thus there is no statistically significant association between receiving a bad grade and consulting with the professor when face difficulties. This means that many individuals who receive bad grades do not consult the professor when they have difficulties in their studies. This means that a negative reinforcement do increase student success in online education.

One-way chi-square

Test Statistics
	Q2
Chi-Square	3.933a
df	3
Asymp. Sig.	.009
a. 4 cells (100.0%) have expected frequencies less than 5. The minimum expected cell frequency is 3.8.

From the one-way chi square analysis above P-value = 0.009 < 0.05. Thus we reject the null hypothesis and conclude that the respondents who score more than 80 % feels motivated and works extra harder. This can also mean that a positive reinforcement increases student success in online education.

References

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