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  • Collaborative Programming for Work-Relevant Learning: Comparing Programming Practice with Example-Based Reflection for Student Learning and Transfer Task Performance
Title: Collaborative Programming for Work-Relevant Learning: Comparing Programming Practice with Example-Based Reflection for Student Learning and Transfer Task Performance
Computer science pedagogy, especially in the higher education and vocational training context, has long-favored the hands-on practice provided by programming tasks due to the belief that this leads to better performance on hands-on tasks at work. This assumption, however, has not been experimentally tested against other modes of engagement such as worked example-based reflection. While theory suggests that example-based reflection could be better for conceptual learning, the concern is that the lack of practice will leave students unable to implement the learned concepts in practice, thus leaving them unprepared for work. In this paper, therefore, we experimentally contrast programming practice with example-based reflection to observe their differential impact on conceptual learning and performance on a hands-on task in the context of a collaborative programming project. The industry paradigm of Mob Programming, adapted for use in an online and instructional context, is used to structure the collaboration. Keeping with the prevailing view held in pedagogy, we hypothesize that example-based reflection will lead to better conceptual learning but will be detrimental to hands-on task performance. Results support that reflection leads to conceptual learning. Additionally, however, reflection does not pose an impediment to hands-on task performance. We discuss possible explanations for this effect, thus providing an improved understanding of prior theory in this new computer science education context. We also discuss implications for the pedagogy of software engineering education, in light of this new evidence, that impacts student learning as well as work performance in the future.  more » « less
Award ID(s):
1917955 1822831
PAR ID:
10356430
Author(s) / Creator(s):
; ; ; ; ; ;
Date Published:
Journal Name:
IEEE Transactions on Learning Technologies
ISSN:
2372-0050
Page Range / eLocation ID:
1 to 1
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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