The role of pedagogical tools in active learning: a case for sense-making

Evidence from the research literature indicates that both audience response systems (ARS) and guided inquiry worksheets (GIW) can lead to greater student engagement, learning, and equity in the STEM classroom. We compare the use of these two tools in large enrollment STEM courses delivered in different contexts, one in biology and one in engineering. The instructors studied utilized each of the active learning tools differently. In the biology course, ARS questions were used mainly to check in with students and assess if they were correctly interpreting and understanding worksheet questions. The engineering course presented ARS questions that afforded students the opportunity to apply learned concepts to new scenarios towards improving students conceptual understanding. In the biology course, the GIWs were primarily used in stand-alone activities, and most of the information necessary for students to answer the questions was contained within the worksheet in a context that aligned with a disciplinary model. In the engineering course, the instructor intended for students to reference their lecture notes and rely on their conceptual knowledge of fundamental principles from the previous ARS class session in order to successfully answer the GIW questions. However, while their specific implementation structures and practices differed, both instructors used these tools to build towards the same basic disciplinary thinking and sense-making processes of conceptual reasoning, quantitative reasoning, and metacognitive thinking.Comment: 20 pages, 5 figure

Gender and Participation in an Engineering Problem-Based Learning Environment

The use of problem-based learning (PBL) is gaining attention in the engineering classroom as a way to help students synthesize foundational knowledge and to better prepare students for practice. In this work, we study the discourse interactions between 27 student teams and two instructors in an engineering PBL environment to analyze how participation is distributed among team members, paying particular attention to the differences between male and female students. There were no statistically significant differences between the amount that male and female students spoke; however, stereotypical gender roles and traditional gendered behavior did manifest in the discussion. Also, regardless of the gender composition of the team, the amount of time that each member talked was usually unbalanced. Our findings lead to recommendations to instructors interacting with student teams and contribute to knowledge about team and gender interactions in PBL environments

Using social network analysis to develop relational expertise for an instructional change initiative

Background Change leaders (faculty, administrators, and/or external stakeholders) need to develop relational expertise, recognizing the perspectives of others, to enable emergent, systemic change. We describe how change leaders of a grant-funded instructional change initiative developed relational expertise by analyzing faculty relationships and social subgroups to identify who was involved in discussions about teaching and learning and what specific topics were discussed. Results Faculty discussions focused on daily classroom needs. Faculty who were in different departments or schools were mostly disconnected from each other, and faculty within these units often had subdivisions among them. Conclusions Faculty lacked opportunities to discuss education, specifically, systems-level perspectives. The change leaders created organizational structures to catalyze communities, including an action research fellowship program, to support faculty in education discussions

Significance of forms and foci of metacognitive regulation in collaborative science learning of less and more successful outcome groups in diverse contexts

This study investigated how metacognitive regulation (MR), especially its forms and foci, was manifested in less and more successful outcome groups' collaborative science learning in diverse learning contexts. Whilst previous research has shown that different forms and foci of MR exist in collaborative learning, their role in groups' learning outcomes remains unexplored. Drawing conclusions from different studies has been difficult because these have used different conceptualisations and analytic methods. In the present study, the learning processes of less and more successful outcome groups from three diverse collaborative science learning contexts were scrutinised. The contexts differed in academic level, disciplinary subject, and national culture. The same theory-based conceptualisations, coding systems, coders, and analyses were used across contexts. In addition, the tasks studied were designed using the same guiding principles. Transcribed video and audio recordings of the groups' verbal interactions for two distinct interaction segments from these tasks formed the basis of the analyses. Manifestation of forms and foci of MR were quantitatively and qualitatively illustrated in each context. The main findings show that the manifestation of MR of less and more successful outcome groups demonstrated similarities and differences in the three different learning contexts. This study contributes to a contextualised understanding of MR in collaborative science learning, and highlights the importance of using similar, rigorous analytical tools across diverse contexts.</p

Productive Disciplinary Engagement in High- and Low-Outcome Student Groups: Observations From Three Collaborative Science Learning Contexts

This study explored how productive disciplinary engagement (PDE) is associated with the level of cognitive activity and collective group outcome in collaborative learning across multiple contexts. Traditionally, PDE has been studied in a single collaborative learning environment, without analysis of how these environments fulfill the supporting conditions for PDE. In addition, research on the quality of a collective learning outcome and product in relation to the extent of the group’s PDE during actual collaborative learning processes is scarce. In this study, the learning processes of low- and high-outcome small groups were compared within three collaborative learning contexts: high school general science, second year university veterinary science, and fourth year university engineering. Two meaningful and self-contained phases from each context were selected for analysis. The same theory-based analytical methods were used across contexts. The findings revealed similar patterns in the high school science and second year university veterinary science data sets, where high-outcome groups displayed a greater proportion of high-level cognitive activity while working on the task. Thus, they could be distinctively perceived as high- and low-performing groups. These high-performing groups’ interactions also reflected more of the supporting conditions associated with PDE than the low-performing groups. An opposite pattern was found in the fourth year university engineering data set, calling for interpretation grounded in the literature on the nature and development of expertise. This study reveals the criticality of using comparable analytical methods across different contexts to enable discrepancies to emerge, thus refining our contextualized understanding of PDE in collaborative science learning.</p

Cultivating creative thinking in engineering student teams: Can a computer‐mediated virtual laboratory help?

In engineering design, engineers must be able to think creatively, effectively toggling between divergent thinking (developing multiple novel ideas) and convergent thinking (pursuing an appropriate idea using engineering analyses). However, creative thinking is not emphasized in many undergraduate engineering programs. In this empirical study, we analyze the divergent thinking of teams working on a virtual laboratory project. Fifteen student teams’ solution paths–as represented by Model Maps–were analyzed to characterize and compare the various elements of divergent thinking: fluency, flexibility, and originality. The solution paths of these teams were compared in two physical laboratory projects and to experts completing the same virtual laboratory project. We found that students demonstrated more divergent thinking in the virtual laboratory project than in the physical laboratory projects; yet, divergent thinking and quality of solution did not correlate. There was little difference between measured elements of divergent thinking between student teams and experts.Lay DescriptionWhat is currently known about the subject matterCreative thinking is an essential skill for engineers to develop innovative products and processes.Creative thinking involves toggling between divergent thinking (coming up with many different original ideas) and convergent thinking (executing an appropriate idea based on engineering analyses).Despite its importance, creative thinking is not often encouraged nor taught in undergraduate engineering curricula, and, similarly, is not well‐researched in that context.The development of creative thinking is supported by students working in Problem‐Based Learning (PBL), in which students work in teams on an open‐ended, “real world” problem.What our paper adds to thisWe developed an innovative methodology to analyze aspects of divergent thinking in an open‐ended, computer‐based virtual laboratory project.Students engaged in divergent thinking significantly more in the virtual laboratory project as compared to two physical laboratory projects in the same course.The degree of divergent thinking did not correlate to the quality of solution in the virtual laboratory project.The degree of divergent thinking of student teams was about the same as that of experts.The implications of study findings for practitionersFindings support the use of open‐ended, computer‐based virtual laboratory projects to provide students opportunities to practice divergent thinking.The aspects of student teams’ divergent thinking in this context is similar to experts.The relationship between divergent thinking and quality of solution is complex.More work needs to be done to understand how to encourage broader creative thinking where student teams toggle between divergent and convergent thinking.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/167077/1/jcal12509.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/167077/2/jcal12509_am.pd