Investigating the impact of generative AI integration on the sustenance of higher-order thinking skills and understanding of programming logic

维持 订单(交换) 高阶思维 生成语法 逻辑程序设计 计算机科学 归纳程序设计 数学教育 人工智能 程序设计范式 心理学 程序设计语言 业务 政治学 教学方法 认知指导教学 财务 法学
作者
Jemimah Nathaniel,Solomon Sunday Oyelere,Jarkko Suhonen,Matti Tedre
出处
期刊:Computers & Education: Artificial Intelligence [Elsevier BV]
卷期号:9: 100460-100460 被引量:9
标识
DOI:10.1016/j.caeai.2025.100460
摘要

This study investigates how integrating generative AI (GenAI) with instructional scaffolding and prompt engineering supports higher-order thinking skills (HOTS) and programming logic. A mixed-methods design was used, combining quantitative and qualitative data. The intervention followed a one-group pretest-post-test structure over seven weeks with 25 computer science students with no prior C++ experience. The GenAI-Ped framework guided the design. It combines Bloom's taxonomy, Seelf-Regulated Learning, Universal Design for Learning, and Vygotsky's Zone of Proximal Development. Students received scaffolded support across six instructional phases, including prompt training and guided GenAI use. Quantitative results showed significant gains in problem-solving (applying constructs: t = 2.38, p = 0.013, d = 0.475), critical thinking (conditional reasoning: t = 2.53, p = 0.018, d = 0.506), creativity (applying new ideas: t = 2.28, p = 0.032, d = 0.456), and programming logic (loops: t = 2.78, p = 0.010, d = 0.555). However, smaller gains were observed in code optimization ( t = 1.693, p = 0.103, d = 0.339) and evaluating solutions ( t = 1.732, p = 0.096). Qualitative data, including feedback and GenAI chat logs, showed that prompt specificity and scaffolded feedback improved engagement, HOTS, and programming logic. The novelty of the study lies in its demonstration that the integration of GenAI into programming education using GenAI-Ped framework can sustain HOTS and programming logic while mitigating overreliance. These findings offer a practical model for integrating GenAI into programming education. • Integrated GenAI with scaffolding to sustain programming logic and HOTS. • Scaffolding + prompt engineering boosts programming logic and HOTS. • Novel GenAI-Ped framework prevents overreliance while enhancing programming logic and HOTS. • Mixed-methods reveal students' prompt quality directly impacts learning gains. • Scaffolding prevents overreliance while enhancing creativity in coding tasks.
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