Skip to main content
 

Research & Teaching

Active Learning Classrooms

Addressing Learning Differences in Large-Enrollment Introductory Science Courses

Journal of College Science Teaching—September/October 2022 (Volume 52, Issue 1)

By Carolyn Hushman, Aurora Pun, and Sushilla Knottenbelt

Active learning classrooms (ALCs) are designed to support collaborative learning in large class sections that are often taught with a lecture format. Studies on ALCs indicate that they have positive influences on student learning, but the same studies fail to look at learning differences between subgroups of students. In the current study, students enrolled in an introductory STEM course (N = 273) instructed in ALCs completed learning inventories and questionnaires designed to measure the influence of social context. Results showed a lack of learning differences within the classroom environment, a positive relationship between learning gains and perceptions of the student-student interactions, and differences in the perception of the social context unique to ALCs based on gender and ethnic and racial diversity.

 

For some, large-enrollment introductory courses bring up images of long rows of students listening to an instructor at the front of the classroom. A recent trend in higher education strives to change that. Many institutions of higher education design active learning classrooms (ALC) for large-enrollment courses that support interactive learning, typically aided by technology. Examples of this trend include Student-Centered Activities for Large Enrollment Undergraduate Programs (SCALE-UP) at North Carolina State University (Beichner et al., 2007); ALC at University of Minnesota (Brooks, 2011), Technology-Enabled Active Learning (TEAL) at Massachusetts Institute of Technology (Dori & Belcher, 2005); and Transform, Interact, Learn, Engage (TILE) at the University of Iowa (Van Horne et al., 2012). These universities intend to improve student learning by designing learning spaces that have the potential to enhance teaching practices.

Many ALCs share common features such as round tables to enhance student interactivity, easily accessible whiteboard space for all student groups, and computers and televisions to enhance students’ ability to work together. The instructor’s station is located in the center of the room—as opposed to the front—to encourage instructor movement around the room and to remove the perception that the teacher should be the focal point for attention. These rooms are designed to accommodate large classes of more than 50 students and encourage constructive and interactive learning (Chi & Wylie, 2014). These types of learning strategies are based in constructivist theory, or the idea that deep learning occurs when students are able to create their own understandings (Dori & Belcher, 2005).

Studies with ALC students indicate positive influence on student learning (e.g., Baepler et al., 2016; Beichner et al., 2007; Chiu & Cheng, 2017). Some studies suggest that active learning is more important than the actual teaching environment (Andrews et al., 2011; Stoltzfus & Libarkin, 2016). Other studies have suggested greater learning achievement is an artifact of both the learning space and active learning (Brooks, 2011; Beichner et al., 2007; Brooks & Solheim, 2014; Cotner et al., 2013; Walker et al., 2011). Either way, this research typically uses student grades to compare traditional classrooms to ALCs. Such studies do not typically examine relative performance between groups of students within the same course, nor do they look at learning gains across a single assignment.

Ethnicity- and gender-related learning gaps exist in traditionally taught science, technology, engineering, and mathematics (STEM) courses (Haak et al., 2011; Lorah & Ndum, 2013; Miyake et al., 2010). One finding for ALCs is that the strongest learning gains are found with students who make up the traditionally lowest-performing groups (Oliver-Hoyo et al., 2004). While little research has looked specifically at learning measures for diverse students in ALCs, dropout rates for diverse students learning in ALCs is significantly smaller than dropout rates in traditional classrooms in one study (Beichner et al., 2007). There is also evidence that learning environments that foster strong interdependence between students will also have a positive effect on learners across gender, race, and socioeconomic status (Miyamoto et al., 2018; Nelson, 1996).

One way ALC environments hypothetically enhance interdependence among students and instructors is by having the instructor’s podium removed from the front of the room and using round tables for students. These features enhance the opportunity for students to have different types of interactions with their peers and the instructor. The technology-supported learning environment allows students to connect their understandings to other student perspectives at their tables as well as to other learners across the classroom. These environments also build interdependence among students so that learning is the responsibility of all learners in the environment.

Teaching introductory science classes in ALCs to facilitate interdependence among learners could decrease differences in achievement among students with different racial and ethnic backgrounds and students of different genders. The purpose of this study was to examine learning outcomes and measures of connectedness between students and instructors in nine sections of large-enrollment introductory science courses taught in ALCs at a majority-minority institution. Our study addressed two research questions: (1) Are there differences in learning gains between students from different genders and diverse racial and ethnic backgrounds when large-enrollment introductory science courses are taught in ALCs? (2) Can the unique social environment in ALCs help explain differences, or a lack of differences, in learning gains?

Materials and methods

This study included 269 undergraduate students as participants. Students were enrolled in introductory chemistry or introductory geoscience courses and gave consent for their assessment and survey scores to be included in the study. Students also had to complete all instruments at each of two administrations. Demographic information was collected during the second administration, which occurred during the last few weeks of the courses. The average age of the chemistry students was 19.3 (SD = 5.2) and for the geoscience students it was 20.5 (SD = 6.3). For both subject areas, the plurality of students were female (56% in both courses), Hispanic (52% for chemistry and 46% for geoscience), and in their freshman year (57% for chemistry and 50% for geoscience). Other demographic information can be found in Table 1. Data for this study were collected in courses taught in both fall and spring semesters.

These courses serve many purposes within a student’s program of study. The majority of students in the general chemistry courses were STEM majors who were required to take the course. The majority of those students were biology, chemistry, or biochemistry majors. For the geoscience courses, non-STEM majors made up the majority of students enrolled. Those students were mostly undecided or liberal arts majors. Within the STEM majors in the geoscience courses, the majority of students were majoring in engineering, geoscience, or secondary education.

The ALCs used in this study seat 126 students at 14 round tables or 63 students at 7 round tables. Each table included three laptop computers and seated nine students. Each room had two projectors and two projection screens. A flat-screen monitor and a large whiteboard were mounted to the wall close to each table, and three huddle boards were provided to students at each table. The huddle boards provided groups of three students whiteboard space during small-group work but were mobile and could rest on the table or students’ laps. Students worked in groups of three or larger table groupings of nine during class sessions. The instructor’s podium was located in the center of the room. Instructors roamed around the classroom during group work to answer questions and ask students questions to encourage deeper engagement with the activity. Both instructors were experienced in teaching the courses and knowledgeable users of active learning strategies—especially interactivity in small groups—in introductory STEM courses, and they had extensive training and experience teaching within an ALC environment. In fact, both instructors led university-wide workshops for faculty members new to teaching in the ALCs.

Three surveys and concept inventories were used to measure student perceptions and learning in the ALC environment. The Social Context and Learning Environments (SCALE) measured classroom social context (Baepler et al., 2014; Walker & Baepler, 2017) through four subscales: student-to-student interactions (St-St), student-to-instructor formal interactions (St-Inf), student-to-instructor informal interactions (St-Ini), and student-as-instructor interactions (St-as-In). The Motivated Strategies for Learning Questionnaire (MSLQ) measured student motivation with regard to learning (Pintrich, et al., 1991); we used the self-efficacy subscale. The Student Perceptions of Classroom Impact (SPCI)—a researcher-designed instrument based on feedback to the instructors in prior semesters—measured students’ perceptions of the learning environment’s impact on their learning.

Principal axis-factor analysis revealed that the SPCI items measured a single factor, explaining 46.25% of the variance. Table 2 includes key characteristics of each survey as well as evidence of the reliability of the scores. As the course content was different for each instructor, unique course concept inventories were used for each course (Libarkin, 2008). These inventories were aligned to course objectives and designed by the instructors. Questions were selected from the Geosciences Concept Inventory (Libarkin & Anderson, 2005) for the geology courses and modified from the Chemical Concept Inventory (Mulford, 1996) for the chemistry courses. The inventories included multiple-choice questions and had been used for multiple semesters before this research began.

Students completed the surveys and concept inventories as part of their course work, and only students who consented to be part of our research were included in the analysis. All surveys were administered online without time limitations. During the first week of class, students enrolled in the courses completed the course-based concept inventory and the MSLQ. At the end of the semester, students completed the course-based concept inventory, SCALE, SPCI, and the demographics survey.

Results

To answer each research question, a two-way analysis of covariances (ANCOVA) was conducted with gender and race and ethnic diversity as independent variables and the SCALE subscales, SPCI, or learning gains from the concept inventories as the dependent variables. As learning in science courses has been tied to self-efficacy (Ballen et al., 2017), self-efficacy was used as a covariate. Concept inventory learning gains were calculated using the average normalized gain method (Hake, 1998). Means and standard deviations for all measures are presented in Table 3.

Preliminary analysis included one-way analysis of variances (ANOVA) to ensure equality between the chemistry and geoscience courses and across the two semesters. No statistical differences were found between learning gains, the ratio of male to female students, or the percentages of students from different racial and ethnic backgrounds in either course. Differences between the percentage of students enrolled in each course and those who participated in the study were also not found. Finally, no differences were found across semesters between the courses for learning gains, gender ratios, or percentages of students from different racial and ethnic backgrounds.

In answering the first research question—Are there differences in learning gains between students from different genders and diverse racial and ethnic backgrounds when large-enrollment introductory science courses are taught in ALCs?there were no significant differences with regard to learning gains.

For the second research question— Can the unique social environment in ALCs help explain differences, or a lack of differences, in learning gains?—the SPCI and subscales of the SCALE survey were examined. There were significant differences in the SPCI, with female students (M = 3.36, SD = 1.02) having significantly more favorable views of the classroom than male students (M = 2.79, SD = 0.98; F(6, 267) = 3.415, p = 0.02, η2 = 0.061), but there were no significant differences based on differences in students’ racial and ethnic backgrounds. The SCALE factor student-to-student interactions were significant (F(6, 267) = 3.415, p = 0.003, η2 = 0.075). Follow-up analysis using Tukey’s honestly significant difference procedures demonstrated Hispanic female students and Asian American male students had more favorable perceptions than their Asian American female counterparts. Student-to-instructor formal interactions were also statistically significant (F(6, 267) = 3.94, p = 0.001, η2 = 0.085), with Hispanic female students and African American male students having more favorable perceptions of formal instructor interactions than Native American and Asian American female students. Student-to-instructor informal interactions were statistically significant (F(6, 267) = 2.56, p = 0.02, η2 = 0.057), as African American and Asian American male students had more positive perceptions of these interactions than their Native American counterparts. There were no significant interactions for Student-as-Instructor. Together, these findings suggest that students have different perceptions of the social context of ALCs, and the classroom environment in general, based on their gender and racial and ethnic backgrounds.

Discussion

This study contributes to the research that supports the use of ALCs to improve student learning in introductory STEM courses. Contrary to results from research in traditionally taught STEM courses (Miyake et al., 2010; Lorah & Ndum, 2013), there were no evident differences in learning based on students’ gender or racial or ethnic background. However, there were differences in the perceptions of the contribution of the classroom to learning, student-to-student relationships, student-to-instructor informal interactions, and student-to-instructor informal interactions. There were no differences between perceptions of students as instructor.

These findings can be explained by application of research addressing the interdependence of learners within a classroom. In a review of literature, Talbert and Mor-Avi (2018) concluded that the single design feature that is common among studies that find positive results for all students in ALCs is the concept of connectedness. ALC environments allow students to move more freely and facilitate better visual contact, which in turn helps students feel more connected to all individuals in the learning space. The freedom of movement in the room also enhances the authenticity of the learning. Using technology, students connect content with their communities outside the classroom more readily, and the table and room layout allow the students to connect more with their instructor and fellow students. This connectedness within the learning environment could be beneficial for students from underrepresented backgrounds.

Ke et al. (2013) propose eight cultural constructs that describe an individual’s experiences within STEM classrooms, many of which overlap with the ideas of connectedness and interdependence fostered in ALC environments. While an individual can fall anywhere on the continuum for each of these constructs, groupings among these constructs are common for certain student populations. Hispanic, Native American, and other Indigenous student populations tend toward a more integrated worldview in which all parts depend on each other. In this framework, the purpose of knowledge is to better the life of the community, and knowledge results from understanding how individual pieces affect the whole. Learning is a social activity, and the individual is responsible for not only their understanding but others’ understanding as well. Finally, learning occurs with a facilitator of experiences who offers a variety of interactions between students and the facilitator.

These findings suggest that instructing courses taught in ALC, which include more interactions between students and instructors, could play a role in helping to close the learning achievement gap found in higher education introductory science courses. These environments support learning for students through designs that enhance interactivity and increase learner interdependence. Learning environments that enhance the interconnectedness between students enhance learning for female students and students from underrepresented backgrounds in a variety of courses (Eddy & Brownell, 2016; Ke et al., 2013; Kulturel-Konak et al., 2011; Stump et al., 2011). Postsecondary organizations should consider the impact that ALCs have on student learning, especially if they are serving underrepresented student populations.

One limitation on which potential future research could focus is the relationship between student learning preferences and learning in ALCs. Students who prefer interactive environments could be responding more positively than those who do not prefer such environments. This could be especially important for introductory STEM courses that are typically required of all STEM students regardless of their interests or preferences. Also, students could be identifying with the demographics of the instructors in this study (both female faculty of color) and not just responding to the collaborative and interconnectedness aspects of the classroom. Future research could explore how instructor characteristics—including gender, race, experience using active learning strategies, and experience teaching in ALCs—affect student learning.

This study provides evidence that ALCs facilitate learning that could close learning achievement gaps for female students and students from underrepresented racial and ethnic backgrounds in STEM general education courses. This outcome is likely related to the enhanced interaction between instructors and students that ALC design encourages.


Carolyn Hushman (ckimble@unm.edu) is an associate professor of educational psychology, Aurora Pun is a principal lecturer of Earth and planetary science, and Sushilla Knottenbelt is a senior lecturer and undergraduate director of the UNM Combined BA/MD Degree Program in the Chemistry Department, all at the University of New Mexico in Albuquerque, New Mexico.

References

Andrews, T. M., Leonard, M. J., Colgrove, C. A., & Kalinowski, S. T. (2011). Active learning not associated with student learning in a random sample of college biology courses. CBE—Life Science Education, 10(4), 394–405. https://doi.org/10.1187/cbe.11-07-0061

Baepler, P., Walker, J. D., Brooks, D. C., Saichaie, K., & Petersen, C. I. (2016). A guide to teaching in the active learning classroom: History, research, and practice. Stylus.

Baepler, P., Walker, J. D., & Driessen, M. (2014). It’s not about seat time: Blending, flipping, and efficiency in active learning classrooms. Computers & Education, 78, 227–236. https://doi.org/10.1016/j.compedu.2014.06.006

Ballen, C. J., Wieman, C., Salehi, S., Searle, J. B., & Zamudio, K. R. (2017). Enhancing diversity in undergraduate science: Self-efficacy drives performance gains with active learning. CBE—Life Sciences Education, 16(4), 56–67. https://doi.org/10.1187/cbe.16-12-0344

Beichner, R. J., Saul, J. M., Abbott, D. S., Morse, J. J., Deardorff, D., Allain, R. J., Bonham, S. W., Dancy, M. H., & Risley, J. S. (2007). The Student-Centered Activities for Large Enrollment Undergraduate Programs (SCALE-UP) project. In E. Redish & P. Cooney (Eds.), Research-based reform of university physics (pp. 1–42). American Association of Physics Teachers. 

Brooks, D. C. (2011). Space matters: The impact of formal learning environments on student learning. British Journal of Educational Technology, 42(5), 719–726. https://doi.org/10.1111/j.1467-8535.2010.01098.x

Brooks, D. C., & Solheim, C. A. (2014). Pedagogy matters, too: The impact of adapting teaching approaches to formal learning environments on student learning. New Directions for Teaching and Learning, 137, 53–61. https://doi.org/10.1002/tl.20085

Chi, M. T., & Wylie, R. (2014). The ICAP framework: Linking cognitive engagement to active learning outcomes. Educational Psychologist, 49(4), 219–243. https://doi.org/10.1080/00461520.2014.965823

Chiu, P. H. P., & Cheng, S. H. (2017). Effects of active learning classrooms on student learning: A two-year empirical investigation on student perceptions and academic performance. Higher Education Research & Development, 36(2), 269–279. https://doi.org/10.1080/07294360.2016.1196475

Cotner, S., Loper, J., Walker, J. D., & Brooks, D. C. (2013). It’s not you, it’s the room—Are the high-tech, active learning classrooms worth it? Journal of College Science Teaching, 42(6), 82–88. https://www.jstor.org/stable/43632160

Dori, Y. J., & Belcher, J. (2005). How does technology-enabled active learning affect undergraduate students’ understanding of electromagnetism concepts? Journal of Learning Science, 14(2), 243–279. https://doi.org/10.1207/s15327809jls1402_3

Eddy, S. L., & Brownell, S. E. (2016). Beneath the numbers: A review of gender disparities in undergraduate education across science, technology, engineering, and math disciplines. Physical Review Physics Education Research, 12(2), 1–20. https://doi.org/10.1103/PhysRevPhysEducRes.12.020106

Haak, D. C., HilleRisLambers, J., Pitre, E., & Freeman, S. (2011). Increased structure and active learning reduce the achievement gap in introductory biology. Science, 332(6034), 1213–1216. https://doi.org/10.1126/science.1204820

Hake, R. R. (1998). Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses. American Journal of Physics, 66(1), 64–74. https://doi.org/10.1119/1.18809

Ke, F., Chávez, A. F., & Herrera, F. (2013). Web-based teaching and learning across culture and age. Springer.

Kulturel-Konak, S., D’Allegro, M. L., & Dickinson, S. (2011). Review of gender differences in learning styles: Suggestions for STEM education. Contemporary Issues in Education Research, 4(3), 9–18. https://doi.org/10.19030/cier.v4i3.4116

Libarkin, J. (2008, October 13–14). Concept inventories in higher education science [Paper presentation]. National Research Council Promising Practices in Undergraduate STEM Education Workshop 2, Washington, DC, United States. https://biotap.utk.edu/wp-content/uploads/2018/06/Libarkin-2008-Concept-Inventories-in-Higher-Education-Science.pdf

Libarkin, J. C., & Anderson, S. W. (2005). Assessment of learning in entry-level geoscience courses: Results from the Geoscience Concept Inventory. Journal of Geoscience Education, 53(4), 394–401. https://doi.org/10.5408/1089-9995-53.4.394

Lorah, J., & Ndum, E. (2013). Trends in achievement gaps in first-year college courses for racial/ethnic, income, and gender subgroups: A 12-year study. American College Testing.

Miyake, A., Kost-Smith, L. E., Finkelstein, N. D., Pollock, S. J., Cohen, G. L., & Ito, T. A. (2010). Reducing the gender achievement gap in college science: A classroom study of values affirmation. Science, 330(6008), 1234–1237. https://doi.org/10.1126/science.1195996

Miyamoto, Y., Yoo, J., Levine, C. S., Park, J., Boylan, J. M., Sims, T., … Ryff, C. D. (2018). Culture and social hierarchy: Self- and other-oriented correlates of socioeconomic status across cultures. Journal of Personality and Social Psychology, 115(3), 427–445. https://doi.org/10.1037%2Fpspi0000133

Mulford, R. D. (1996). An inventory for measuring college students’ level of misconceptions in first semester chemistry [Unpublished master’s thesis]. Purdue University.

Nelson, C. E. (1996). Student diversity requires different approaches to college teaching, even in math and science. American Behavioral Scientist, 40(2), 165–175. https://doi.org/10.1177/0002764296040002007

Oliver-Hoyo, M. T., Allen, D., Hunt, W. F., Hutson, J., & Pitts, A. (2004). Effects of an active learning environment: Teaching innovations at a research I institution. Journal of Chemical Education, 81(3), 441. http://doi.org/10.1021/ed081p441

Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the motivated strategies for learning questionnaire (MSLQ). ERIC Institute of Educational Science.

Stoltzfus, J. R., & Libarkin, J. (2016). Does the room matter? Active learning in traditional and enhanced lecture spaces. CBE—Life Sciences Education, 15(4). https://doi.org/10.1187%2Fcbe.16-03-0126

Stump, G. S., Hilpert, J. C., Husman, J., Chung, W. T., & Kim, W. (2011). Collaborative learning in engineering students: Gender and achievement. Journal of Engineering Education, 100(3), 475–497. https://doi.org/10.1002/j.2168-9830.2011.tb00023.x

Talbert, R., & Mor-Avi, A. (2018, October 19). A space for learning: A review of research on active learning spaces. SocArXiv. https://doi.org/10.31235/osf.io/vg2mx

Van Horne, S., Murniati, C., Gaffney, J. D. H., & Jesse, M. (2012). Promoting active learning technology infused TILE classrooms at the University of Iowa. Journal of Learning Spaces, 1(2). http://libjournal.uncg.edu/index.php/jls/article/view/344

Walker, J. D., Brooks, D. C., & Baepler, P. (2011). Pedagogy and space: Empirical research on new learning environments. EDUCAUSE Quarterly, 34(4), 1–21. http://www.educause.edu/ero/article/pedagogy-and-space-empirical-research-new-learning-environments

Walker, J. D., & Baepler, P. (2017). Measuring social relations in new classroom spaces: Development and validation of the Social Context and Learning Environments (SCALE) survey. Journal of Learning Spaces, 6(3), 34–41. https://files.eric.ed.gov/fulltext/EJ1164634.pdf

New Science Teachers Pedagogy Teaching Strategies

Asset 2