Milestone 1.

In this study, the researcher examined whether the use of POGIL pedagogy was an effective instructional strategy to improve high school chemistry student’s SAGE chemistry exam scores and ACT science exam scores. Over the past 25 years, the POGIL model (Farrell & Moog, 2014) has shown itself to be effective at improving student classroom performance and increasing higher-level reasoning skills for students at the college and high school levels (Balasubramanian, 2015; Barthlow & Watson, 2014; DeGale & Boisselle, 2015; DeMatteo, 2016; Meeks, 2015; Qureshi, Vishnumolakala, Southam, & Treagust, 2016). Currently, no empirical studies have been conducted to examine whether POGIL is an effective intervention on actual student ACT performance; therefore, this current study was necessary to address this gap in the literature. There existed a need to determine whether POGIL might be an effective instructional strategy at improving student ACT science scores (Judd, 2014), and why this study was important and necessary to bridge the gap in the existing research.

The purpose of this quantitative, causal-comparative research study was to determine if and to what extent there were differences in chemistry EOC exam scores and ACT science exam scores for high school chemistry students taught using POGIL pedagogy, versus high school chemistry students taught using non-POGIL pedagogy, in the state of Utah. The research questions for this study provided a guide by analyzing how the literature review examined the effectiveness of POGIL pedagogy at improving American high school student EOC chemistry exam scores and ACT science scores. Through an exhaustive review of the literature, the researcher identified a gap. This study was driven by the fact that there existed a gap within the research literature whether POGIL was an effective instructional strategy for improving high school chemistry student EOC exam scores and actual student ACT science scores. The gap in the literature was identified using a detailed history of POGIL pedagogy and how it may be a remedy for improving high school student EOC chemistry scores and performance on the ACT science exam. Second, the theoretical foundations of the Cognitive Development Theory (CDT) (Piaget, 1973) and the Information Processing Model (IPM) (Johnstone, 1997) were addressed, in addition to the relationship between the problem statement and these two theories.

There are a limited number of empirical studies that examined ACT performance versus differences in math and science instructional strategies. These empirical studies included a single study on the effect of a particular mathematic metacognitive strategies on ACT exam scores (LeMay, 2016) and a single study on the effectiveness of POGIL pedagogy on practice ACT exams (Judd, 2014). This current study focused on the effectiveness of POGIL pedagogy on SAGE chemistry exam scores and ACT science scores. POGIL was designed to provide students with an opportunity to develop communication, problem-solving, and critical thinking skills (Barthlow & Watson, 2014; Perry & Wight, 2008). The use of content knowledge as the foundation for the development of higher-level thinking skills allows students to apply their newly acquired knowledge to new situational experiences (Farrell & Moog, 2014). POGIL has shown itself to be highly effective at improving student classroom performance and increasing higher-level reasoning skills for students at the college and high school levels over the past 25 years (Barthlow & Watson, 2014; Farrell & Moog, 2014). Since students had low math, science, and STEM benchmark scores, the effectiveness of POGIL at increasing student higher-level reasoning skills was unknown; therefore, there existed a need to determine whether POGIL might be an effective strategy at improving student ACT science test scores (Judd, 2014).

The theoretical foundations of the Cognitive Development Theory (CDT) and the Information Processing Model (IPM) were addressed for the current causal-comparative study. To best address the problem statement and identified gap in the literature, two research questions and four hypotheses were developed to guide this study:

RQ1: To what extent, if any, does POGIL pedagogy produce a statistically significant difference in high school EOC chemistry scores?

H01: POGIL pedagogy does not produce a statistically significant difference in high school EOC chemistry scores.

H1a: POGIL pedagogy does produce a statistically significant difference in high school EOC chemistry scores.

RQ2: To what extent, if any, does POGIL pedagogy produce a statistically significant difference in high school ACT science exam scores?

H02: POGIL pedagogy does not produce a statistically significant difference in high school ACT science exam scores.

H2a: POGIL pedagogy does produce a statistically significant difference in high school ACT science exam scores.

The current study focused on a single high school district, located in the state of Utah, which implemented POGIL instructional strategies in the 2015 - 2017 academic school years. The research questions sought to examine whether the implementation of POGIL pedagogy was statistically significant ( p < .05) on SAGE chemistry exam scores and ACT science scores for high school students taught chemistry using POGIL instructional strategies versus high school students taught chemistry using non-POGIL instructional strategies. The study focused on eleventh grade high school students taught using POGIL instructional strategies and high school student taught using non-POGIL instructional strategies. The two comparison groups for the study consisted of students enrolled in chemistry during the 2015-2016 and 2016-2017 academic school years.

The study was conducted using de-identified student archival data collected by the office of assessment at a single school district in the state of Utah. The total sample data produced a total of 316 participants (158 POGIL students and 158 non-POGIL students). According to the results of the a priori power analysis, which indicated a minimum total sample size of 158 was required to achieve the desired power of .80 with an alpha of .05 (Appendix E), the total sample size of 316 was sufficient to achieve the required power level. The lack of a normal distribution for the sample size required the researcher to transform the two dependent variables. After transformation and the removal of outliers, the final sample size was N = 305.

Using IBM SPSS version 26 software, the data were imported and cleaned to ensure no data limits or data errors were violated. Descriptive statistics were performed on the data followed by the test of assumptions for the one-way MANOVA to determine which of the ten assumptions were met. Subsequently, to test the research questions and hypotheses for this study, the researcher conducted a one-way MANOVA to determine if there was a statistically significant difference ( p < .05) in student SAGE chemistry scores and student ACT science scores by comparing the effectiveness of POGIL pedagogy between the two comparison groups. The results of this data analysis are presented in the next section of the chapter.

The purpose of this quantitative, causal-comparative research study was to determine if and to what extent there were differences in chemistry EOC exam scores and ACT science exam scores for high school chemistry students taught using POGIL pedagogy versus high school chemistry students taught using non-POGIL pedagogy, in the state of Utah. In order to obtain this objective, the researcher formulated two research questions, each supported by a null hypothesis and an alternative hypothesis.

The first research question (RQ1) investigated to what extent, if any, did POGIL pedagogy produce a statistically significant difference in high school EOC chemistry scores? The alternative hypothesis for RQ1 was expressed as there was a statistically significant difference in high school EOC chemistry scores between POGIL students and non-POGIL students, along with the null hypothesis indicating no statistically significant difference existed for the high school EOC chemistry scores between POGIL students and non-POGIL students. The second research question (RQ2) investigated to what extent, if any, did POGIL pedagogy produce a statistically significant difference in high school ACT science exam scores? The alternative hypothesis for RQ2 was stated as there was a statistically significant difference in high school ACT science exam scores between POGIL students and non-POGIL students, while the null hypothesis conveyed there was no statistically significant difference for the high school ACT science exam scores between POGIL students and non-POGIL students.

Using IBM SPSS version 26, the research questions were examined by testing the respective hypotheses utilizing the parametric statistical test one-way MANOVA. Specifically, the one-way MANOVA was used to support or not support the alternative hypotheses by examining any difference between independent group means of the dependent variables (Laerd Statistics, 2015a). The results of the analysis determined if there was a statistically significant difference in the combined dependent variables (SAGE chemistry exam scores and ACT science exam scores) for high school students taught chemistry using POGIL instructional strategies versus high school students taught chemistry using non-POGIL instructional strategies.

Prior to performing the one-way MANOVA test, the assumptions for the one-way

MANOVA were tested using the de-identified student archival data set. All assumptions of the one-way MANOVA were met with the exceptions of homogeneity of variance-covariance matrices and homogeneity of variances, which were justified as the one-way MANOVA is robust to violations (Warner, 2013). The data analysis findings were organized by research question and hypotheses used to guide this study, and research findings were bound by the following research parameters: (a) participants were all eleventh-grade students when enrolled in high school chemistry during the 2015-2016 or 2016-2017 academic school year; (b) all students took the SAGE chemistry exam and ACT exam in the spring after completing at least 70% of the chemistry course; and (c) student GPA’s were matched either identically for each student from the two comparison groups or matched within +/- 0.10 grade point to ensure similar test subjects between the POGIL high school group and the non-POGIL high school group. The study findings and related conclusions associated with the two research questions and their corresponding hypotheses follow.

Findings explained. To examine the hypotheses of the two research questions,

the de-identified student numbers, SAGE chemistry exam scores, and ACT science exam scores were imported from the archival data set, provided by the school district’s office of assessment, into SPSS version 26 software. After meeting most of the assumptions, a one-way MANOVA was conducted using SPSS version 26 to test if there was a statistically significant difference between the independent group means of the dependent variables, SAGE chemistry exam scores and ACT science exam scores. The results of the one-way MANOVA demonstrated there was a statistically significant difference between the POGIL group taught chemistry using POGIL instructional strategies, and the non-POGIL group taught chemistry using non-POGIL instructional strategies. Specifically, Pillai’s Trace = .10, F(2, 302) = 16.72, p < .001, partial η2 = .10, p < .05 (Table 13).

With a main multivariate effect result of significance, the researcher continued

with a univariate level of analysis in which a standard ANOVA was conducted for each

dependent variable, and a Welch ANOVA was conducted due to the assumption violation of homogeneity of variances. Prior to examining the univariate ANOVA, the level of statistical significance was adjusted for multiple comparisons, and a Bonferroni correction was made in order to accept statistical significance for the standard and Welch ANOVAs (Laerd Statistics, 2017). The level of statistical significance was set at p < .025 rather than p < .05 since there were two dependent variables for the sample size (Laerd Statistics, 2017). Through the univariate level of analysis using a standard and Welch ANOVA, the researcher was able to specifically examine whether any statistically significant differences existed between the mean values of the independent groups. A two-way independent sample t-test was conducted for each dependent variable since the standard and Welch ANOVAs were statistically significant. The hypothesis for RQ1 was tested first with a standard and Welch ANOVA.

Research hypothesis 1 stated there was a statistically significant difference in the SAGE chemistry exam scores between POGIL students and non-POGIL students. The ANOVA results indicated there was a statistically significant difference between the POGIL students and non-POGIL students on their SAGE chemistry exam scores, which showed F(1, 135.34) = 33.47, p < .001, partial η2 = .099, p < .025 (Table 14). The Welch ANOVA for the SAGE chemistry exam scores yielded p < .001 value (Table 18), which was statistically significant. The two-way independent sample t-test for the SAGE chemistry exam scores produced a p < .001 value (Table 19), which was statistically significant. The decision was to reject the null hypothesis ( p > .025) for research hypothesis 1.

With the results of one-way MANOVA reflecting a main multivariate effect result of statistical significance, the researcher performed a standard and Welch ANOVA to examine whether any statistically significant differences existed between the mean values of the independent groups for the ACT science exam scores dependent variable of hypothesis 2 of the second research question (RQ2). The results of the standard ANOVA for ACT science exam scores demonstrated there was a statistically significant difference between POGIL students and non-POGIL students on their ACT science exam scores, which produced F(1, 135.34) = 33.47, p < .001, partial η2 = .099, p < .025 (Table 14). The Welch ANOVA for the ACT science exam scores yielded p = .004 value (Table 18), which was statistically significant. The two-way independent sample t-test for the ACT science exam scores produced a p =.004 value (Table 19), which was statistically significant. The decision was to reject the null hypothesis ( p < .025) for research hypothesis 2.

With an indication of significant difference between the independent groups for the transformed SAGE chemistry exam scores and the transformed ACT science exam scores, the means exhibited in Table 7 were examined to observe the differences between the mean values for the independent groups. As indicated by the mean values, non-POGIL high school students demonstrated significantly higher transformed SAGE chemistry exam scores ( M = 9.43, SD = 2.33) than did POGIL students ( M = 8.10, SD = 1.62); however, when interpreting a reflected variable (transformed SAGE chemistry exam score) the researcher needed to reverse the direction of the interpretation (Tabachnick & Fidell, 2019), which means the POGIL students had higher mean scores than the non-POGIL students. In addition, Table 7 shows higher mean values for POGIL high school students demonstrated significantly higher transformed ACT science exam scores ( M = 4.79, SD = .42) than did non-POGIL students ( M = 4.65, SD = .43).

Discussion of conclusions relative to findings and summary. There were no empirical studies conducted that examined the effects of different instructional strategies on actual ACT science scores, and this study differed from other studies by addressing whether POGIL pedagogy improved SAGE chemistry scores and ACT science scores. This current study addressed this gap in the literature and advanced scientific knowledge by determining that POGIL pedagogy was an effective instructional strategy at improving both SAGE chemistry scores and ACT science scores for high school students.

The results of this study advanced scientific knowledge by extending scholarly research on the Cognitive Development Theory which states learners’ build on previous knowledge to develop cognitive development that results in better complex understandings (Piaget, 1973). In addition, the results of this study supported the Information Processing Model that a student-centered pedagogy, like POGIL, is more effective at increasing concept mastery and student performance than traditional, teacher-centered pedagogies (Johnstone, 1997).

There was a need to determine whether POGIL was effective at improving high school chemistry student SAGE exam scores and actual ACT scores for students on their science tests (Judd, 2014) and whether the POGIL strategy was an effective strategy to help students perform better on the math, science, and STEM ACT benchmarks (ACT, 2016a). The results of this study determined that implementation of POGIL strategies are statistically significant at increasing student SAGE chemistry exam scores and ACT science scores. In addition, this current study was the first to publish descriptive statistics with robust parametric statistics demonstrating statistically significant differences between the groups on the combined dependent variables of SAGE chemistry exam scores and ACT science exam scores.

When examining specific findings, in relation to the causal-comparative research design of the study, one must be cautious in formulating definite conclusions. The causal-comparative design was the most appropriate research study design for the ex-post facto examination of de-identified archival data in the effort to investigate differences in SAGE chemistry exam scores and ACT science exam scores for POGIL and non-POGIL students. However, the use of the causal-comparative research design imposes limits on the researcher’s ability to generalize conclusions to the larger population that allows conclusions to be considered an absolute effect of both the dependent and independent variables being examined in the study. Stated another way, the researcher cannot state a definitive cause and effect relationship among the variables examined, nor can a direct conclusion of causation be supported from this single study (Schenker & Rumrill, 2004). The researcher is limited to a statement of observed differences among the variables reviewed, and this researcher concluded that POGIL students displayed higher achievement levels that were significantly different from non-POGIL students in both SAGE chemistry exam scores and ACT science exam scores.

The findings of this current study are different than the correlational research design conducted by Judd (2014), where findings on the effectiveness of POGIL pedagogy using practice ACT science exams showed no statistically significant difference in the mean scores of secondary students’ practice ACT science scores for students taught with a POGIL strategy versus students taught using a traditional lecture strategy (Judd, 2014). The conclusions of this current study contributed to the literature and eliminated the gap within the scientific body of knowledge regarding the effectiveness of POGIL pedagogy on SAGE chemistry exam scores and ACT science exam scores.

The findings of this study support the POGIL model has a student-centered, inquiry-based strategy (Farrell & Moog, 2014) that is effective at the secondary levels for improving content mastery and increasing higher-level reasoning skills for chemistry students (Balasubramanian, 2015; Barthlow & Watson, 2014; DeGale & Boisselle, 2015; DeMatteo, 2016; Farrell & Moog, 2014; Meeks, 2015; Qureshi et al., 2016). The findings of this study also provided usable research evidence for POGIL pedagogy has an effective instructional strategy to improve high school chemistry student academic performance on SAGE chemistry exam scores and ACT science exam scores.

American high school students express a high interest in pursuing STEM degrees and careers in college; however, high school student performance remains low on the ACT College Readiness Benchmark in STEM, with only 19% of the graduating class of 2016 and 21% of the graduating class of 2017 meeting or exceeding the ACT College Readiness Benchmark in STEM (ACT, 2018). Based on this low student readiness for STEM, more focus on improving ACT exam scores for American high school students is needed. In order to address these deficiencies, it is necessary to pursue innovative and effective teaching strategies that will better prepare American high school students to pursue STEM degrees and careers, allowing them to compete in the global workforce. This current study has demonstrated that POGIL pedagogy is an effective teaching strategy that makes that goal possible.

In summary, the one-way multivariate effect test assessed for the differences on the combined dependent variables of SAGE chemistry exam scores and ACT science exam scores between high school students taught chemistry using POGIL instructional strategies versus students taught using non-POGIL instructional strategies. Using the significance criterion of p = .05, the probability value ( p < .001) was statistically significant. The standard and Welch one-way analysis of variance demonstrated a statistically significant difference ( p < .001) between POGIL students and non-POGIL students on the individual dependent variable SAGE chemistry exam scores. Similarly, the standard and Welch one-way analysis of variance showed a statistically significant difference ( p = .004) between the POGIL students and non-POGIL students on ACT science exam scores. In addition, the two-tailed independent sample t-test demonstrated a statistically significant difference between POGIL students and non-POGIL students for both SAGE chemistry exam scores ( p < .001) and ACT science exams scores ( p = .004). Therefore, the next section of Chapter 5 was used to expand upon the theoretical, practical, and future implications of the research study findings as well as discuss the strengths and weaknesses of this current study.

The purpose of this quantitative, causal-comparative research study was to determine if and to what extent there were differences in SAGE chemistry exam scores and ACT science exam scores for high school chemistry students taught using POGIL pedagogy, and high school chemistry students taught using non-POGIL pedagogy, in the state of Utah. Implications from this current study have suggested the potential impact that the results of the findings of this study may have on future research. Some of these implications relate to the theoretical framework referenced within this current study, while other implications relate to more practical aspects that may prove useful for education practitioners and scholars to better understand the impact of POGIL instructional strategies on improving SAGE chemistry exam scores and ACT science exam scores for high school students. Finally, discussion of the implications along with specific strengths and potential weaknesses of the study follows.

The current study partially replicated the previous investigation conducted by Judd (2014) who found no statistical significance ( p = 0.85) regarding the effectiveness of POGIL pedagogy on practice ACT science exam scores. However, this current study found a statistically significant difference ( p = .004) that POGIL instructional strategies improved high school student ACT science exam scores, given a larger sample size, a longer POGIL treatment time, and the use of actual ACT science exam scores. Given that this current study measured a significant change in academic achievement levels with students receiving either POGIL or non-POGIL chemistry instruction for at least 70% or more of the school year, affected the results and indicated a larger impact on academic achievement levels for POGIL students than for the non-POGIL students.

Regarding theoretical framework, the results of this current study advanced scientific knowledge by extending scholarly research on the Cognitive Development Theory which states learners’ build on previous knowledge to develop cognitive development that results in better complex understandings (Piaget, 1973). In addition, the results of this current study supported the Information Processing Model that a student-centered pedagogy, like POGIL, is more effective at increasing concept mastery and student performance than traditional, teacher-centered pedagogies (Johnstone, 1997).

The results of this current study strengthens the findings of previous studies on the effectiveness of POGIL instructional strategies significantly improving academic achievement of high school students who received POGIL instruction at the secondary level (Balasubramanian, 2015; Barthlow & Watson, 2014; DeGale & Boisselle, 2015; DeMatteo, 2016; Farrell & Moog, 2014; Meeks, 2015; Qureshi et al., 2016).

results from the SAGE chemistry exam scores and the ACT science exam scores used to

measure the difference in academic achievement between POGIL students and non-POGIL students, following the end of a year of chemistry instruction. Accordingly, as a result of this study, the use of POGIL instructional strategies to significantly improve high school student academic performance on SAGE chemistry exam scores and ACT science exam scores, could lead to an expansion of high school science teachers to implement POGIL instructional strategies in their classrooms to better prepare students to pursue STEM majors in college and STEM careers.

This current study supports the use of POGIL pedagogy as a model that is practical, proactive, and effective at supporting high school students for success in the STEM field of their choice. The findings of this current study supported the utilization and implementation of POGIL instructional strategies, at the high school level, as an effective intervention to better prepare students for admission to college as a STEM major and potential success in attaining a STEM career. The resulting findings of the current study suggests on-going research is necessary to confirm the effectiveness of POGIL instructional strategies on EOC chemistry exam scores and ACT science exam scores. The impact of the results of continued study may result in extensive nationwide implementation of POGIL instructional strategies to continue increasing high school student participation in the pursuit of STEM careers.

The future study might incorporate the use of POGIL instructional strategies used by certified chemistry teachers in chemistry classes, along with the credential and experience of instructors of POGIL student participants and instructors of non-POGIL student participants. Utilizing this approach would allow for the examination into POGIL instructional methods of chemistry teachers to determine if differences exist among student participants receiving non-POGIL instructional strategies. The approach would also allow for the examination of differences between POGIL student participants and non-POGIL student participants overall, as well as, any differences between the independent groups according to instructional methods of certified chemistry teachers. Future research could also be performed on EOC chemistry exam and ACT science exam academic achievement of participants according to school calendar versus those students attending schools with year-round school or block scheduling. Due to ethical considerations, random assignment would not be recommended since it would deny or exclude students from the opportunity of receiving specialized POGIL instruction; as such, the suggested future research implications would need to be conducted using a causal-comparative research design to implement the investigation.

there are strengths and weaknesses that have been identified and require critical conversation. One strength of the study was the use of a quantitative, causal-comparative research design to implement this study utilizing de-identified archival data. The causal-comparative design is recommended by Schenker and Rumrill (2004) to be the most appropriate design to compare differences between non-manipulated dependent measures. The main strength of the causal-comparative design is further supported as the literature indicates the design to align with and permit the use of a one-way MANOVA as a between-group comparative method that gauges whether any observed mean differences between independent groups on selected outcome measures are statistically significant (Schenker & Rumrill, 2004; Wells et al., 2015), as demonstrated within this study.

Though the data analysis was implemented using the robust one-way MANOVA

which strengthens the statistical accuracy of the results and findings of the study, the

assumption of accuracy in archival data originally collected by the Utah school district data collectors is a possible weakness of the study. Though the de-identified archival data

fell within the scoring limits of the range of scores included within this study, the scores could have included data entry inaccuracies that resulted in skewing data at the source. If the data are in fact accurate, the total acquired sample size of 305 students has resulted in a power of 0.98 as indicated by post hoc power analysis (Appendix E), thereby exceeding the desired power of 0.80 originally calculated with an alpha level of 0.05 (α = 0.05), and served as adequate power to detect a medium effect (Appendix E). Considering the statistically significant difference in the change in SAGE chemistry exam scores between POGIL students and non-POGIL students (i.e., hypothesis 1) as indicated by standard and Welch ANOVA results for SAGE chemistry exam scores where F (1, 135.34) = 33.47, p < .001, partial η2 = .099, p < .025 (Table 14 and Table 18), a medium effect size was realized. Additionally, statistically significant difference in the change in ACT science exam scores between POGIL students and non-POGIL students (i.e., hypothesis 2) as indicated by standard and Welch ANOVA results for ACT science exam scores where F (1, 1.54) = 8.62, p = .004, partial η2 = .028, p < .025 (Table 14 and Table 18), a medium effect size was realized. In addition, the two-way independent sample t-test produced a p < .001 value and p = .004 value for the SAGE chemistry exam scores and ACT science exam scores, respectively (Table 19). The findings of this data have provided foundational insight into the impact of the program model included within this study.

Though the causal-comparative design is a strength, it may serve as a weakness

of the study relative to conclusions that may be drawn. That is, the causal-comparative research design is similar to the experimental design in terms of the design including the use of nominal independent variables and a type of continuous dependent variable measure (Schenker & Rumrill, 2004). However, unlike true experimental designs, both experimental manipulation of the independent variable and random assignment of subjects to experimental and control groups to manage extraneous variables are absent from the causal-comparative design. Consequently, any conclusions resulting from causal-comparative studies are limited. The researcher can only state differences among the variables, rather than state any definitive causal or cause and effect relationship among the variables (Schenker & Rumrill, 2004). The generalizability of the findings of the study serve as a limitation of this study, as well as, the offering of any conclusions regarding causality.

An additional limitation and factor of weakness for this study was limitations of generalizability due to the sample group of high school students residing in a single school district in the state of Utah, enrolled in the eleventh grade during the 2015-2016 or 20116-2017 school year, and attending either a POGIL taught chemistry course or a non-POGIL chemistry course, in the same school district. The representativeness for the POGIL student population of interest as defined within this study was limited. Furthermore, without the ability to conduct a true experimental design which incorporated randomization to assign statistically similar and balanced groups in the category of controlled group and experimental or treatment groups, the ability to generalize outside of the context of the study was further limited based on the research design.

Another limitation and factor of weakness for this study was possible differences

in POGIL instructional strategies or non-POGIL instructional strategies by chemistry instructors when delivering content to student participants and any change in instruction as a result of teacher selection of instructional strategies. The researcher sent out a teacher demographic survey to chemistry teachers at both high schools; however, the low participation rate (12.5%) only allowed the researcher to determine that POGIL instructional strategies were utilized at the POGIL high school and non-POGIL instructional strategies were utilized at the other high school. Consequently, it is unknown if the chemistry teachers utilized additional instructional strategies which may have been used for POGIL taught students and non-POGIL taught students. Without knowledge of the additional instructional strategies used by both POGIL and non-POGIL instructors, the conclusions are further limited for this study.

The final limitation and factor of weakness for this study was that all assumptions were not met for the one-way MANOVA, one-way ANOVA, and two-tailed independent samples t-tests. While assumption violations are quite common in the fields of education and psychology studies (Lix, Keselman, & Keselman, 1996), both the MANOVA and ANOVA parametric tests are highly robust to violations (Warner, 2013). Lix et al. (1996) states that violation of the variance homogeneity assumption can be severe, if the group sizes are unequal, and endanger control of the Type I error rate. However, the current study had approximately equal sample sizes for the POGIL student group ( N = 151) and non-POGIL student group ( N = 154). There were violations of the assumptions in the current study, which was a weakness of the study. These specific assumption violations included the homogeneity of variance-covariance and homogeneity of variance for the one-way MANOVA test and the violation of homogeneity of variance for the one-way ANOVA test and the two-way independent sample t-test.

The following are recommendations for future research and practice based on the current study’s findings, strengths, and weaknesses. The significance of this study was to advance the scientific knowledge of the impact of POGIL pedagogy on SAGE chemistry exam scores and ACT science exam scores for both POGIL high school students and non-POGIL high school students in the state of Utah. The current study’s findings revealed several areas of potential future research and practical future applications.

The first recommendation is to replicate this current study with a larger student population from a larger school district where multiple high schools utilize POGIL pedagogy. In this study the researcher limited the target population to a single school district in the state of Utah. It could be valuable for future researchers to target a larger school district with multiple high schools teaching the same chemistry curriculum and with specific high schools utilizing POGIL pedagogy versus specific high schools utilizing non-POGIL pedagogy. This would help to determine if the findings in this current study would generalize to the larger high school student population.

The second recommendation is to use interim chemistry benchmark tests throughout the school year to monitor student progress and compare students taught chemistry using POGIL instructional strategies versus students taught chemistry using non-POGIL instructional strategies. In this current study, the researcher used a single summative test administered in the spring semester to determine end-of-course academic performance for individual students. The use of interim chemistry benchmark tests would allow for multiple comparisons throughout the academic school year and provide multiple measures of student performance.

The third recommendation is to conduct a similar research study on POGIL pedagogy effectiveness with an emphasis on comparing student performance between public, private, and charter school populations. In this study the researcher limited the scope of the study to examine only public schools. It would be interesting to see whether POGIL pedagogy produced statistically significant results for private and charter school populations.

The final recommendation is to conduct additional longitudinal studies on a national level to investigate the effectiveness of the POGIL model. The researcher limited the study to the state of Utah; however, a future study that examined the impact of POGIL pedagogy on a national level would generalize to the secondary education level as a whole. Perhaps an alliance with the American College Testing (ACT) organization could reveal the impact of POGIL pedagogy on a much larger and diverse student population. The ACT has access to national student data that could be mined and reveal ACT science exam performance for entire school districts that implemented POGIL instructional strategies versus school districts that utilized more traditional non-POGIL instructional strategies.

The future recommendations for this current study outline only a few of the potential pathways that could be taken based specifically on the findings of this study. The findings of this study did indicate significant differences between POGIL high school students and non-POGIL high school students’ SAGE chemistry exam scores and ACT science exam scores. The implementation of the POGIL model has been occurring in urban, suburban, and rural settings in the United States over the past 25 years; however, the total impact of the POGIL pedagogy model on both chemistry end-of-course exam and ACT science exam performance needs to be further investigated. The next step that needs to be taken is further research to support and substantiate the findings of this current study through similar empirical investigations of the use of POGIL instructional strategies in high school settings. These recommendations promote future research that will add to the foundational literature as a result of this current study, while emphasizing the need for additional study of this subject matter.

The current study was conducted in a large, public school district in the state of Utah with an emphasis on one high school that implemented POGIL instructional strategies during the 2015 - 2016 and 2016 - 2017 academic school years, and another high school, in the same school district, that utilized non-POGIL instructional strategies during the same time period. The results of this current study indicated a significant difference ( p < .05) between the two high schools in both SAGE chemistry exam scores and ACT science exam scores between the POGIL taught high school students and the non-POGIL taught high school students. The revelation of significant differences in both of these measures helps to advance the need for further study as well as implementation of the POGIL model for high school chemistry teachers in public school districts. Recommendations for the high school chemistry teacher follow.

Based on the findings from this current study, the first recommendation would be for high school chemistry teachers to receive formal POGIL training through workshops conducted by The POGIL Project based in Lancaster, Pennsylvania. These teacher training workshops are presented several times throughout the year in various locations around the United States and provide POGIL training for science teachers to implement POGIL instructional strategies within their teaching practices to enhance student content mastery and develop critical thinking skills. Specifically, high school chemistry teachers should utilize a variety of POGIL instructional strategies to challenge and develop their students’ cognitive abilities and foster a higher depth of knowledge (DOK) level to better prepare their students for chemistry end-of-course exams and the ACT science exam. The implementation of POGIL pedagogy would benefit all students, at all levels, by improving their overall cognitive abilities.

The second recommendation would be to encourage school districts to partner with the American College Testing (ACT) organization to better prepare students for STEM majors and STEM careers. The ACT is the only college placement organization that promotes STEM preparation and offers tools to school districts, educators, and students through partnerships. Students that are interested in pursuing STEM majors in college and STEM careers after college need to be better prepared to perform better on college placement exams to gain admission to the STEM college of their choice. This can only be achieved through decisive and intentional efforts that help students perform better on the ACT exam which will increase student opportunity to be admitted as STEM majors during the college admissions process.

The third recommendation would be for chemistry teachers to develop and implement end-of-course chemistry exams to measure student mastery and depth of knowledge levels. These exams could be benchmark exams administered throughout the school year to monitor student progress in concept mastery and drive curriculum decisions on reteaching or reinforcement strategies. These benchmark exams should be comprehensive in nature with initial benchmark performance expectations being retested on future benchmark exams to ensure concept mastery and track student progression throughout the academic school year.

The fourth and final recommendation would be for chemistry teachers to utilize practice ACT science exams. This would allow students to better familiarize themselves with the ACT science exam format in a lower stress environment that would build student confidence. This would provide students the opportunity to become more comfortable and confident when taking the actual ACT exam, which in normally a more stressful, high stakes testing environment.

In summary, the recommendations for future practice supports the sharing of current and future research findings to school district policymakers and secondary chemistry teachers on a national level. While these two groups could possible benefit from adopting and implementing the results of this current study, it is of particular value to secondary chemistry teachers to support high school students and increase their opportunity to pursue STEM majors in college and ultimately becoming part of the future American STEM workforce.

The results of this causal-comparative study advanced scientific knowledge by showing a statistically significant difference between the effectiveness of POGIL pedagogy on both SAGE chemistry exam scores and ACT science exam scores for high school students taught chemistry using POGIL instructional strategies versus high school students taught chemistry using non-POGIL instructional strategies. Causal-comparative studies examine relationships without any manipulation of the variables and are not useful in determining specific causation (Salkind, 2019); therefore, the researcher made no causation claim due to a limited sample size and lack of demonstrating similar patterns in multiple settings. While the present study supports these findings, continued investigation of the POGIL model is recommended.