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Generative AI as a Tool or Leader? Exploring AI-Augmented Thinking in Student Programming Tasks

Project Overview

This document investigates the integration of Generative Artificial Intelligence (GAI) in educational settings, specifically in enhancing students' cognitive processes during programming tasks. It highlights four pivotal dimensions of AI-augmented thinking: Question Formulation, Solution Development, Solution Analysis and Evaluation, and Solution Refinement. The study reveals that students who engage interactively with GAI can dedicate more time to critical thinking and refining their solutions, in contrast to those who depend on AI for straightforward answers. This reliance on direct responses may hinder deeper engagement with the material. The findings underscore the necessity of promoting student agency within AI-supported learning environments, suggesting that active participation with GAI can lead to improved educational outcomes. Overall, the document advocates for a balanced approach where GAI serves as a tool to enhance, rather than replace, student-driven learning processes.

Key Applications

Use of GAI tools like ChatGPT for programming tasks

Context: Undergraduate and master's students in programming education

Implementation: Participants engaged in programming activities with GAI support, reflecting on their experiences

Outcomes: Enhanced understanding of programming processes, improved computational thinking and self-efficacy, and a structured framework for analyzing student thinking

Challenges: Overreliance on AI, potential reduction in critical thinking and manual coding skills

Implementation Barriers

Academic Integrity

Concerns about students potentially cheating by relying on AI for direct answers instead of developing their programming skills.

Proposed Solutions: Promoting a mindset that GAI should augment thinking rather than replace it, and educating students about ethical AI use.

Overreliance on AI

Students may become too dependent on AI, potentially diminishing their critical thinking and problem-solving skills.

Proposed Solutions: Encouraging active engagement and critical evaluation of AI outputs to maintain student agency.

Bias and Limitations of AI

GAI outputs may contain biases or inaccuracies, which could affect students' learning outcomes.

Proposed Solutions: Training students to critically assess and refine AI-generated content to ensure accuracy and relevance.

Project Team

Tianlong Zhong

Researcher

Gaoxia Zhu

Researcher

Kang You Lim

Researcher

Yew Soon Ong

Researcher

Contact Information

For information about the paper, please contact the authors.

Authors: Tianlong Zhong, Gaoxia Zhu, Kang You Lim, Yew Soon Ong

Source Publication: View Original PaperLink opens in a new window

Project Contact: Dr. Jianhua Yang

LLM Model Version: gpt-4o-mini-2024-07-18

Analysis Provider: Openai

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