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Given that the active learning literature lacks systematic investigations on how the intensity and integration of lecture and active learning affects learning, we conducted two experiments to examine the impact of these variables. The first experiment involved 146 participants who learned about biological taxonomies through pure lecture or pure active learning. Participants in the pure lecture condition scored significantly higher on a posttest than those in the pure active learning condition. The second experiment involved 219 participants who learned about biological taxonomies through pure lecture, a lecture and active learning activity that were interspersed, or a lecture and active learning activity that were blocked. Participants in the interspersed condition scored significantly higher than participants in the blocked and pure lecture conditions (which did not significantly differ). Based on these experiments, it may not be a question of either/or but rather a question of how to integrate lecture and active learning.
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GTAs’ Conceptualization of Active Learning in Undergraduate Mathematical Sciences Courses
Throughout the past few decades, the term active learning has been used to describe a variety of classroom instructional techniques and pedagogy. In this poster, we explore the conceptualization and implementation of active learning strategies for graduate teaching assistants (GTAs) in three Departments of Mathematical Sciences at the start of a funded project evaluating a multifaceted GTA training model.
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- Award ID(s):
- 1821619
- PAR ID:
- 10294755
- Editor(s):
- Karunakaran, Shiv Smith; Reed, Zackery; Higgins, Abigail
- Date Published:
- Journal Name:
- 23rd Annual Conference on Research in Undergraduate Mathematics Education Conference (RUME)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Hannula, K. (Ed.)Active learning research emerged from the undergraduate STEM education communities of practice, some of whom identify as discipline-based education researchers (DBER). Consequently, current frameworks of active learning are largely inductive and based on emergent patterns observed in undergraduate teaching and learning. Alternatively, classic learning theories historically originate from the educational psychology community, which often takes a theory-driven, or deductive research approach. The broader transdisciplinary education research community is now struggling to reconcile the two. That is, how is a theory of active learning distinct from other theories of knowledge construction? We discuss the underpinnings of active learning in the geosciences, drawing upon extant literature from the educational psychology community on engagement. Based on Sinatra et al. engagement framework, we propose a model for active learning in the geosciences with four dimensions: behavioral, emotional, cognitive, and agentic. We then connect existing literature from the geoscience education community to the model to demonstrate the current gaps in our literature base and opportunities to move the active learning geoscience education research (GER) forward. We propose the following recommendations for future investigation of active learning in the geosciences: (1) connect future GER to our model of active learning in the geosciences, (2) measure more than content learning, (3) document research methods and outcomes with effect sizes to accumulate evidence, and (4) prioritize research on dimensions of active learning essential to the geosciences.more » « less
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This paper will highlight a small subsection of a larger scale project that focuses on increasing the use of active learning in science, technology, engineering, and mathematics (STEM) classrooms. Our overall project goals seek to expand the adoption of active learning in STEM classrooms. Active learning has been shown to improve student grades, retention rates, and overall understanding of course material. We define active learning as any time an instructor goes beyond lecturing to their students (e.g., think-pair-shares, class discussions). Research has shown adoption of active learning in STEM courses has been slow with one common cited reason for not implementing active learning in their courses is the fear of student resistance. Student resistance can be defined as any negative student reaction to active learning (e.g., distracting others, giving lower course evaluations, or refusing to participate in the activity). For this study, we recruited instructors from across the nation in the Summer of 2021 and collected data from instructors and students from Fall 2021-Winter 2022. During recruitment, we paid particular attention on ensuring we were recruiting instructors from a broad swath of institution types, including doctoral granting institutions, community colleges, and everything in between. While much of the research on active learning has focused on 4-year schools, this research aims to elucidate what active learning looks like in community colleges, as well as community college student perspectives on these activities. Additional data will share common strategies used for implementing active learning that differ between community college and four-year settings. This paper focuses on how instructors teaching at community colleges are using active learning in their classrooms and their attitudes towards active learning. Additionally, we will explore the instructor’s self-efficacy towards using active learning in the hopes of having a better overall understanding of what is occurring in STEM community college classrooms and where potential improvements can be made in terms of faculty development.more » « less
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It is widely acknowledged that active learning strategies increase engagement and long-term retention, while reducing attrition and frustration of students with less academic preparation and self-efficacy. Promoting active learning methods in STEM has been a long-term project in higher education. This study examines the perceptions of active learning techniques in online STEM education, leveraging a large, diverse sample (N = 727) across four STEM fields. The post-pandemic context of the study offers unique insights into how students and faculty perceive the effectiveness of various active learning methods in a rapidly changing educational environment. For eight of the nine methods studied, more than half of students and faculty found each active learning strategy to be helpful for online learning achievement. On average, both students and faculty found active learning methods to be modestly more important in online courses than face-to-face courses. A novel finding that was striking was that by a wide margin, both students and faculty perceived requiring activities more helpful than offering them on an optional basis. This implies that active learning methods become a meaningful portion of the course grade. However, faculty and students disagree on how heavily such activities should contribute to course grades. On average, students believe about half of their grade (52%) should comprise active learning activities, whereas faculty report that 32% of grades in their courses come from formative active learning assessments. The implications of activity-based STEM learning in online courses are discussed.more » « less
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Adaptive learning systems that generate spacing intervals based on learner performance enhance learning efficiency and retention (Mettler, Massey & Kellman, 2016). Recent research in factual learning suggests that initial blocks of passive trials, where learners observe correct answers without overtly responding, produce greater learning than passive or active trials alone (Mettler, Massey, Burke, Garrigan & Kellman, 2018). Here we tested whether this passive + active advantage generalizes beyond factual learning to perceptual learning. Participants studied and classified images of butterfly genera using either: 1) Passive Only presentations, 2) Passive Initial Blocks followed by active, adaptive scheduling, 3) Passive Initial Category Exemplar followed by active, adaptive scheduling, or 4) Active Only learning. We found an advantage for combinations of active and passive presentations over Passive Only or Active Only presentations. Passive trials presented in initial blocks showed the best performance, paralleling earlier findings in factual learning. Combining active and passive learning produces greater learning gains than either alone, and these effects occur for diverse forms of learning, including perceptual learning.more » « less
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Accepted Manuscript1.0
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