Best peer active learning strategies for problem solving using C programming
By: Saraswathi, Meena R
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Contributor(s): Saranya, R.
Publisher: Pune Engineering Education Foundation 2023Edition: Vol.36(4), Apr.Description: 140-149p.Subject(s): Humanities and Applied SciencesOnline resources: Click here
In:
Journal of engineering education transformations (JEET)Summary: Peer learning is a process where one or more students teach other students and provides support throughout the learning process. Active learning is a process of learning concepts through thinking, discussing, investigating, and creating. In order to improve the learning of students in the concept of "problem solving using C programming," peer and active learning approaches are implemented by forming groups. The general four methods for peer active learning, such as think-pair-share, the zig-zag method, the coding test, and mini project, are chosen as activities for the students. An unsupervised machine learning algorithm is used to create clusters of students based on pretest and posttest scores. With the help of the K-Means clustering technique, the increased change in student performance after peer active learning approaches is clearly visible.
| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
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Articles Abstract Database
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School of Engineering & Technology Archieval Section | Not for loan | 2023-1190 |
Peer learning is a process where one or more students teach other students and provides support throughout the learning process. Active learning is a process of learning concepts through thinking, discussing, investigating, and creating. In order to improve the learning of students in the concept of "problem solving using C programming," peer and active learning approaches are implemented by forming groups. The general four methods for peer active learning, such as think-pair-share, the zig-zag method, the coding test, and mini project, are chosen as activities for the students. An unsupervised machine learning algorithm is used to create clusters of students based on pretest and posttest scores. With the help of the K-Means clustering technique, the increased change in student performance after peer active learning approaches is clearly visible.
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