Students Know AI Should Not Replace Thinking, but How Do They Regulate It? The TACO Framework for Human-AI Cognitive Partnership

• URL: http://arxiv.org/abs/2604.18737v1
• Date: Mon, 20 Apr 2026 18:43:18 GMT
• Title: Students Know AI Should Not Replace Thinking, but How Do They Regulate It? The TACO Framework for Human-AI Cognitive Partnership
• Abstract summary: This study examines how learners perceive their management of the boundary between assistance and outsourcing in practice.<n>By shifting attention from ethical awareness to cognitive regulation, the study contributes a learner-grounded approach to sustaining AI as a dynamic cognitive partner in education.
• Score: 0.8122270502556375
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: As generative artificial intelligence becomes increasingly embedded in educational practice, a central concern is whether students use AI as cognitive support or as a substitute for thinking. Prior research shows that learners recognise this boundary conceptually and acknowledge that "AI should not replace thinking." However, whether such awareness translates into structured regulation during actual AI use remains unclear. Drawing on data from Hong Kong secondary students, this study examines how learners perceive their management of the boundary between assistance and outsourcing in practice. Findings show that awareness did not consistently translate into regulation; ethical belief did not necessarily lead to strategic execution; and conceptual endorsement did not guarantee operational behaviour. These findings suggest that the challenge is not teaching students that AI should not replace thinking, as they already know this, but providing them with structured mechanisms to regulate how AI is used within learning processes. In response, the study introduces the TACO framework (Think-Ask-Check-Own), a process-oriented model designed to operationalise the boundary between cognitive support and cognitive substitution. By shifting attention from ethical awareness to cognitive regulation, the study contributes a learner-grounded approach to sustaining AI as a dynamic cognitive partner in education.

Related papers

• Who Is Doing the Thinking? AI as a Dynamic Cognitive Partner: A Learner-Informed Framework [0.0]
  This study proposes a framework positioning AI as a dynamic cognitive partner whose function shifts across learning situations.<n>We identified nine interrelated dimensions through which learners described AI as partnering with their cognition.<n>Students distinguished between productive support that extends understanding and unproductive reliance that replaces cognitive effort, indicating situational awareness of when AI should and should not be used.
  arXiv  Detail & Related papers  (2026-02-17T15:07:06Z)
• Strategies for Creating Uncertainty in the AI Era to Trigger Students Critical Thinking: Pedagogical Design, Assessment Rubric, and Exam System [0.0]
  Generative exam AI challenges traditional assessments by allowing students to produce correct answers without demonstrating understanding or reasoning.<n>Rather than AI, this work argues that one way to integrate AI into education is by creating uncertain situations with help of AI models.<n>We introduce MindsaicAIExam, an exam system that integrates AI tools and requires students to provide initial answers, critically evaluate AI outputs, and refine their reasoning.
  arXiv  Detail & Related papers  (2026-01-17T10:29:43Z)
• Bridging Minds and Machines: Toward an Integration of AI and Cognitive Science [48.38628297686686]
  Cognitive Science has profoundly shaped disciplines such as Artificial Intelligence (AI), Philosophy, Psychology, Neuroscience, Linguistics, and Culture.<n>Many breakthroughs in AI trace their roots to cognitive theories, while AI itself has become an indispensable tool for advancing cognitive research.<n>We argue that the future of AI within Cognitive Science lies not only in improving performance but also in constructing systems that deepen our understanding of the human mind.
  arXiv  Detail & Related papers  (2025-08-28T11:26:17Z)
• Do AI tutors empower or enslave learners? Toward a critical use of AI in education [7.673465837624366]
  The paper argues that while AI can support learning, its unchecked use may lead to cognitive atrophy.<n>The paper advocates for an intentional, transparent, and critically informed use of AI that empowers rather than diminishes the learner.
  arXiv  Detail & Related papers  (2025-07-09T14:15:49Z)
• ChatGPT produces more "lazy" thinkers: Evidence of cognitive engagement decline [0.0]
  This study investigates the impact of generative artificial intelligence (AI) tools on the cognitive engagement of students during academic writing tasks.<n>The results revealed significantly lower cognitive engagement scores in the ChatGPT group compared to the control group.<n>These findings suggest that AI assistance may lead to cognitive offloading.
  arXiv  Detail & Related papers  (2025-06-30T18:41:50Z)
• AI in Education: Rationale, Principles, and Instructional Implications [0.0]
  Generative AI, like ChatGPT, can create human-like content, prompting questions about its educational role.<n>The study emphasizes deliberate strategies to ensure AI complements, not replaces, genuine cognitive effort.
  arXiv  Detail & Related papers  (2024-12-02T14:08:07Z)
• Aligning Generalisation Between Humans and Machines [74.120848518198]
  AI technology can support humans in scientific discovery and forming decisions, but may also disrupt democracies and target individuals.<n>The responsible use of AI and its participation in human-AI teams increasingly shows the need for AI alignment.<n>A crucial yet often overlooked aspect of these interactions is the different ways in which humans and machines generalise.
  arXiv  Detail & Related papers  (2024-11-23T18:36:07Z)
• Imagining and building wise machines: The centrality of AI metacognition [78.76893632793497]
  We examine what is known about human wisdom and sketch a vision of its AI counterpart.<n>We argue that AI systems particularly struggle with metacognition.<n>We discuss how wise AI might be benchmarked, trained, and implemented.
  arXiv  Detail & Related papers  (2024-11-04T18:10:10Z)
• Using AI Alignment Theory to understand the potential pitfalls of regulatory frameworks [55.2480439325792]
  This paper critically examines the European Union's Artificial Intelligence Act (EU AI Act) Uses insights from Alignment Theory (AT) research, which focuses on the potential pitfalls of technical alignment in Artificial Intelligence. As we apply these concepts to the EU AI Act, we uncover potential vulnerabilities and areas for improvement in the regulation.
  arXiv  Detail & Related papers  (2024-10-10T17:38:38Z)
• Combining AI Control Systems and Human Decision Support via Robustness and Criticality [53.10194953873209]
  We extend a methodology for adversarial explanations (AE) to state-of-the-art reinforcement learning frameworks. We show that the learned AI control system demonstrates robustness against adversarial tampering. In a training / learning framework, this technology can improve both the AI's decisions and explanations through human interaction.
  arXiv  Detail & Related papers  (2024-07-03T15:38:57Z)
• Building Bridges: Generative Artworks to Explore AI Ethics [56.058588908294446]
  In recent years, there has been an increased emphasis on understanding and mitigating adverse impacts of artificial intelligence (AI) technologies on society. A significant challenge in the design of ethical AI systems is that there are multiple stakeholders in the AI pipeline, each with their own set of constraints and interests. This position paper outlines some potential ways in which generative artworks can play this role by serving as accessible and powerful educational tools.
  arXiv  Detail & Related papers  (2021-06-25T22:31:55Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.