Author(s):
This collaborative project seeks to (1) expand the development and adoption of an online platform known as the Concept Warehouse, which engages students in concept-based learning and metacognition.Needs: Given the preponderance of evidence to support the relative effectiveness of active learning compared with traditional learning, continued development of methods and approaches to engage students in active learning are necessary. If this is so, then, it is further necessary to promote faculty adoption, and understand related patterns and barriers.Guiding Questions: Some key questions that guide this project are as follows: (1) How do students make sense of engineering concepts, and how can well-designed concept questions promote this? (2) What can faculty learn from engaging students in wrestling with concepts? (3) What factors and attitudes influence instructor adoption of the Concept Warehouse and related active learning techniques?Outcomes and Findings: The outcomes and findings of this project range across practical developmental milestones to development of knowledge about student knowing and faculty attitudes and practices, including (1) nearly 800 new questions in Mechanics (principally Statics and Dynamics) were created, deployed, and evaluated; (2) over 600 new faculty accounts have been created, over 3500 new unique students of engaged the platform, and over 50,000 responses to mechanics questions have been collected; (3) several workshops and community of practice meetings have been convened, leading to ongoing faculty Communities of Practice; (4) a deep cross-case analysis followed instructors’ trajectories and found that these are tool-mediated and community-mediated, and include narratives of (i) how instructors gained insight into student learning from student responses in the tool, (ii) the role played by the project’s Community of Practice, and (iii) the complexity of an evolving instructional ecosystem and its role in instructors’ satisfaction and continued use; (5) analysis of student responses revealed (i) divergence between the students’ expressed multiple-choice answers and their corresponding written explanations, (ii) effects of problem wording and deployment method (e.g., online or offline) on student responses, and (iii) confirmation of prior findings that self-reported confidence is higher among men vs women; (6) progress is being made on using machine learning to automate the analysis of student-written explanations.Broader Impacts: Beyond the numbers of faculty and students directly engaged are further impacts, such as the development of a cadre of faculty who are committed to growing their approaches to active learning methods, which will engage more students in deeper cognitive practices beyond simply ‘getting the right answer’. This will play a role in potentially transforming the STEM workforce toward innovation and creativity. Also, throughout the study, a diverse cross section of students and faculty were engaged, ranging across public, private, bilingual, rural, and urban contexts.
Coauthors
Christopher Papadopoulos, University of Puerto Rico, Mayaguez; Milo Koretsky, Tufts University; Brian Self, Cal Poly San Luis Obispo; Michael Prince, Bucknell University; Dominc DalBello, Allan Hancock College; Susan Nolan, University of Washington
