The right tool for the job: matching active learning techniques to learning objectives

Sarah Jacobson, Luyao Zhang and Jiasheng Zhu
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Luyao Zhang: N/A
Jiasheng Zhu: N/A

Advances in Economics Education, 2024, vol. 3, issue 2, 164-187

Abstract: Active learning comprises techniques that engage students in the construction of understanding. Different techniques may work best for different learning objectives. We study students’ perceptions of some active learning techniques (including a Python simulation and a game) and traditional techniques (such as lecture). Students engage actively with them all, though more with those influential in course grades and with some active learning techniques. They particularly enjoy most active learning techniques. All techniques are rated as effective for each learning objective, but to varying extents. Traditional techniques like exams are rated highest for remembering concepts (associated with lower order cognitive skills). In contrast, some active learning techniques are rated highest for objectives related to higher order cognitive skills, including learning to conduct research, though lectures performed surprisingly well for these objectives. Other technique-objective matches are intuitive. Our results imply that a mix of techniques may be optimal in course design.

Keywords: active learning; student engagement; student perceptions; learning objectives (search for similar items in EconPapers)
JEL-codes: A20 A22 I21 (search for similar items in EconPapers)
Date: 2024
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Working Paper: The Right Tool for the Job: Matching Active Learning Techniques to Learning Objectives (2022)
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