TY - JOUR
T1 - FEAL
T2 - 124th ASEE Annual Conference and Exposition
AU - Lu, Sixing
AU - Lazos, Loukas
AU - Lysecky, Roman
N1 - Publisher Copyright:
© American Society for Engineering Education, 2017.
PY - 2017/6/24
Y1 - 2017/6/24
N2 - Numerous studies have shown the effectiveness of collaborative active-learning pedagogies compared to traditional lectures across STEM fields. However, incorporating active learning in large classes presents unique challenges in stimulating student engagement and developing quality activities. A growing trend at universities is to create collaborative learning spaces (CLSs) that are purposefully designed and equipped to facilitate active learning. While some research has identified some effective learning strategies for CLS environments based on learning psychology, the success of individual activities is neither defined nor measured. This gap in knowledge is often met with a trial and error approach over numerous semesters. Activity adjustments are made solely based on the instructors' partial perceptions, whereas activity effectiveness is neither directly evaluated nor correlated to student performance. We present a novel measurement instrument called Fine-grained Evaluation of Active Learning (FEAL) for large CLS-based classes. FEAL can be quickly administered by preceptors to record key measures of activity success such as student engagement, activity difficulty, activity time, and associated lecture time. Other relevant information such as the concepts covered by the activity and the activity type are also recorded to be later cross-analyzed. FEAL can be applied to code exam questions and to assess student performance for the same concepts. We applied FEAL to a large freshman-level computer programming course with an enrollment of 200 students over the course of one semester. We present an overview of FEAL, its administration process within the CLS, and a detailed account of our evaluation methodology. We also highlight key lessons learned on the engagement and success achieved by individual activities, and outline planned improvements to in-class activities based on the obtained results.
AB - Numerous studies have shown the effectiveness of collaborative active-learning pedagogies compared to traditional lectures across STEM fields. However, incorporating active learning in large classes presents unique challenges in stimulating student engagement and developing quality activities. A growing trend at universities is to create collaborative learning spaces (CLSs) that are purposefully designed and equipped to facilitate active learning. While some research has identified some effective learning strategies for CLS environments based on learning psychology, the success of individual activities is neither defined nor measured. This gap in knowledge is often met with a trial and error approach over numerous semesters. Activity adjustments are made solely based on the instructors' partial perceptions, whereas activity effectiveness is neither directly evaluated nor correlated to student performance. We present a novel measurement instrument called Fine-grained Evaluation of Active Learning (FEAL) for large CLS-based classes. FEAL can be quickly administered by preceptors to record key measures of activity success such as student engagement, activity difficulty, activity time, and associated lecture time. Other relevant information such as the concepts covered by the activity and the activity type are also recorded to be later cross-analyzed. FEAL can be applied to code exam questions and to assess student performance for the same concepts. We applied FEAL to a large freshman-level computer programming course with an enrollment of 200 students over the course of one semester. We present an overview of FEAL, its administration process within the CLS, and a detailed account of our evaluation methodology. We also highlight key lessons learned on the engagement and success achieved by individual activities, and outline planned improvements to in-class activities based on the obtained results.
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M3 - Conference article
AN - SCOPUS:85030545931
SN - 2153-5965
VL - 2017-June
JO - ASEE Annual Conference and Exposition, Conference Proceedings
JF - ASEE Annual Conference and Exposition, Conference Proceedings
Y2 - 25 June 2017 through 28 June 2017
ER -