ASPECT: A Survey to Assess Student Perspective of Engagement in an Active-Learning Classroom

Wiggins, Benjamin; Eddy, Sarah L.; Wener-Fligner, Leah; Freisem, Karen; Grunspan, Daniel Z.; Theobald, Elli J.; Timbrook, Jerry Parmilee; Crowe, Alison J.

doi:10.1187/cbe.16-08-0244

Cited by 78 publications

(86 citation statements)

References 55 publications

(78 reference statements)

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“…See [30] for details about the survey development and validation process, and for survey items. The ASPECT survey is specifically designed to gauge student perception of engagement in an active learning classroom during group work and is focused on three areas: value of group activity, personal effort, and instructor contribution.…”

Section: Methodsmentioning

confidence: 99%

Student perception of group dynamics predicts individual performance: Comfort and equity matter

et al. 2017

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Active learning in college classes and participation in the workforce frequently hinge on small group work. However, group dynamics vary, ranging from equitable collaboration to dysfunctional groups dominated by one individual. To explore how group dynamics impact student learning, we asked students in a large-enrollment university biology class to self-report their experience during in-class group work. Specifically, we asked students whether there was a friend in their group, whether they were comfortable in their group, and whether someone dominated their group. Surveys were administered after students participated in two different types of intentionally constructed group activities: 1) a loosely-structured activity wherein students worked together for an entire class period (termed the ‘single-group’ activity), or 2) a highly-structured ‘jigsaw’ activity wherein students first independently mastered different subtopics, then formed new groups to peer-teach their respective subtopics. We measured content mastery by the change in score on identical pre-/post-tests. We then investigated whether activity type or student demographics predicted the likelihood of reporting working with a dominator, being comfortable in their group, or working with a friend. We found that students who more strongly agreed that they worked with a dominator were 17.8% less likely to answer an additional question correct on the 8-question post-test. Similarly, when students were comfortable in their group, content mastery increased by 27.5%. Working with a friend was the single biggest predictor of student comfort, although working with a friend did not impact performance. Finally, we found that students were 67% less likely to agree that someone dominated their group during the jigsaw activities than during the single group activities. We conclude that group activities that rely on positive interdependence, and include turn-taking and have explicit prompts for students to explain their reasoning, such as our jigsaw, can help reduce the negative impact of inequitable groups.

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Section: Methodsmentioning

confidence: 99%

Student perception of group dynamics predicts individual performance: Comfort and equity matter

et al. 2017

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“…In this way, the estimates as well as the standard error of the estimates are more accurate. In their analysis of survey data that grouped into constructs, Wiggins and colleagues [51] fit a censored regression to confirm that their results did not qualitatively differ from the results of their linear regression. That paper, including the Supplemental Material, provide details of how and why to fit a censored regression.…”

Section: -14mentioning

confidence: 89%

Beyond linear regression: A reference for analyzing common data types in discipline based education research

Theobald

Aikens

Eddy

et al. 2019

Phys. Rev. Phys. Educ. Res.

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This paper is part of the Focused Collection on Quantitative Methods in PER: A Critical Examination.] A common goal in discipline-based education research (DBER) is to determine how to improve student outcomes. Linear regression is a common technique used to test hypotheses about the effects of interventions on continuous outcomes (such as exam score) as well as control for student nonequivalence in quasirandom experimental designs. (In quasirandom designs, subjects are not randomly assigned to treatments. For example, when treatment is assigned by classroom, and observations are made on students, the design is quasirandom because treatment is assigned to classroom, not subject (students).) However, many types of outcome data cannot be appropriately analyzed with linear regression. In these instances, researchers must move beyond linear regression and implement alternative regression techniques. For example, student outcomes can be measured on binary scales (e.g., pass or fail), tightly bound scales (e.g., strongly agree to strongly disagree), or nominal scales (i.e., different discrete choices for example multiple tracks within a physics major), each necessitating alternative regression techniques. Here, we review extensions of linear modeling-generalized linear models (glms)-and specifically compare five glms that are useful for analyzing DBER data: logistic, binomial, proportional odds (also called ordinal; including censored regression), multinomial, and Poisson (including negative binomial, hurdle, and zero-inflated) regression. We introduce a diagnostic tool to facilitate a researcher's identification of the most appropriate glm for their own data. For each model type, we explain when, why, and how to implement the regression approach. When: we provide examples of the types of research questions and outcome data that would motivate this regression approach, including citations to articles in the DBER literature. Why: we name which linear regression assumption is violated by the data type. How: we detail implementation and interpretation of this modeling approach in R, including R syntax and code, and how to discuss the regression output in research papers. Code accompanying each analysis can be found in the online github repository that is associated with this paper (https://github.com/ejtheobald/BeyondLinearRegression). This paper is not an exhaustive review of regression techniques, nor does it review nonregression-based analyses. Rather, it aims to compile and summarize regression techniques useful for the most common types of DBER data and provide examples, citations, and heavily annotated R code so that researchers can easily implement the technique in their work.

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“…While several studies demonstrated that active learning techniques enhance students' 978 learning [20,40], few studies evaluated students' perception of active learning [21,79], 979 and none, to our knowledge, compared these two perspectives. As far as learning 980 involves both the teachers and the students, comparing their perspectives is valuable 981 and informs about the mechanisms involved in learning.…”

mentioning

confidence: 97%

“…We discuss the third 683 effect, that of students' previous knowledge, and the absence of collinearity, after that. 684 We were not able to fully validate the survey and questions answered by the 685 students, as, for example, the pioneering work on validating the students' perspective on 686 their engagement in active-learning of as seen in Wiggins et al [21]. Such validation 687 would require a follow-up of several semesters, and extrapolates the available education 688 atmosphere within which we work.…”

mentioning

confidence: 98%

“…The use of more 120 sophisticated statistical analyses is proving efficient [39], distinguishing the impact of an 121 March 26, 2020 4/31 instructional intervention from the impact of student characteristics, thus helping to 122 elucidate the mechanisms and effectiveness of active learning. 123 Aims 124Most studies on active learning focus on students' performance [20,37,40], or on 125 students' perspective [21]. Evaluation of the efficiency of active learning by the students 126 themselves faces widespread suspicion concerning the accuracy of students' 127 self-evaluation still haunts the academic community [41], meaning there is a clear 128 demand for data that evaluates the correlation between self-evaluation and actual exam 129 grades.…”

mentioning

confidence: 99%

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Effectiveness of active learning for ecology teaching: the perspective of students vs their grades

Sperber

Szinwelski

Ferreira

et al. 2020

Preprint

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We evaluated the effectiveness of active learning for ecology teaching in a Brazilian university by comparing the perspective of students to their grades in exams. We estimated the perspective of the students through anonymous survey; we used students' exam grades to estimate their ecology learning, and their effort and performance in the active learning tasks through their grades and proportion of intermediate steps for each active learning task. Active learning involved teachers' stimuli for students' active involvement, extra-class group task, individual online writing assessments, redoing exam in pairs, and classroom writing group assessments. We also evaluated the impact, unto the effectiveness of active learning, of several student characteristics, such as sex, age, individual study effort, and previous basic knowledge. We found that self-evaluated March 26, 2020 1/31 learning increased linearly with teachers' attempts to stimulate students' active involvement (P = 0.0003), extra-class group task (P = 0.0003), and previous basic knowledge (P = 0.02), while students' grades increased asymptotically with extra-class group task (P < 2 −16 ), and increased linearly with online writing assessments (P = 9.3 −8 ) and classroom-based writing group assessments (P = 0.03). Our results showed that students perceive most part of the effectiveness of active-learning tasks and of teachers' efforts. We showed that active learning tasks are complementary, so we recommend that teachers in both college and high school should implement simultaneous active-learning tasks, that include extra-class work in group, individual and group writing assessments, and should stimulate students' engagement through respectful and non-authoritarian behavior of the teacher. Our results also showed that previous basic knowledge also plays a central role in driving effective learning, evidencing the importance of students instruction outside college. The applied teaching methodology is cheap and feasible for large classes. In these times of rising intolerance, prejudice, dismiss of environmental issues and disregard of science itself, we need an effective, pluralistic, respectful, and student-centred education, that fosters critical thinking, tolerance and respect for differing points of view. We feel that our results suggest that active learning can be an especially useful model for teaching science in a post-colonial rising education system. Introduction 1Ecology is integral to curricula in several undergraduate programs, ranging from 2 biologically centered programs like biological sciences and applied biology subjects (e.g. 3 agronomy), to programs such as civil and electrical engineering. Within Brazilian higher 4 education, ecology sits at a critical place for a country with a rising economy and an 5 unique ecosystem of world resources. Motivated by an urge to foster effective learning 6 and critical thinking, in the year 2000 the ecology teachers 1 at the Federal University 7 of Viçosa's General Biology Department introduced weekly class...

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ASPECT: A Survey to Assess Student Perspective of Engagement in an Active-Learning Classroom

Cited by 78 publications

References 55 publications

Student perception of group dynamics predicts individual performance: Comfort and equity matter

Student perception of group dynamics predicts individual performance: Comfort and equity matter

Beyond linear regression: A reference for analyzing common data types in discipline based education research

Effectiveness of active learning for ecology teaching: the perspective of students vs their grades

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