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Cognitive Apprenticeship and Artificial Intelligence Coding Assistants
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Author(s): Eric Poitras (Dalhousie University, Canada), Brent Glen Charles Crane (Dalhousie University, Canada), David Dempsey (Dalhousie University, Canada), Tavis A. Bragg (Acadia University, Canada), Angela A. Siegel (Dalhousie University, Canada)and Michael Pin-Chuan Lin (Mount Saint Vincent University, Canada)
Copyright: 2024
Pages: 21
Source title:
Navigating Computer Science Education in the 21st Century
Source Author(s)/Editor(s): Chantelle Bosch (North-West University, South Africa), Leila Goosen (University of South Africa, South Africa)and Jacqui Chetty (University of Birmingham, UK)
DOI: 10.4018/979-8-3693-1066-3.ch013
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Abstract
The aim of this chapter is to examine the impact that AI coding assistants have on the manner in which novice programmers learn to read, write, and revise code. These discussions revolve around the concept of cognitive apprenticeship, a pedagogical framework informed by extensive research on tutoring dialogues and collaborative problem-solving practices. It involves guided instruction through modeling, coaching, and scaffolding. Within the realm of programming, these principles hold the key to nurturing skills in reading, writing, and revising code, thus making the learning process more effective and engaging. The chapter concludes by reflecting on the challenges and considerations of implementing cognitive apprenticeship within AI coding assistants. These insights are intended to benefit educators, developers, and researchers alike, offering a roadmap to enhance the learning experiences of novice programmers through AI support.
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