Human–AI Collaboration: Students’ Changing Perceptions of Generative Artificial Intelligence and Active Learning Strategies

This paper explores ways to use AI for active learning strategies so that students in higher education may perceive generative artificial intelligence (generative AI) as a collaborative partner in their learning experience. This study proposes AI can help advance educational sustainability when students read texts on critical posthumanism, reflect on the philosophical and ontological paradigms through which the human has been understood, and discuss the collaborative relationship between humans and AI using literary texts. By analyzing AI-collaborated writing assignments, student questionnaires, and peer evaluations, this study concludes there are three learning types based on the different levels of students’ perceived difficulties: a cognitive learner, who focuses on AI’s functional aspects such as information retrieval; a metacognitive learner, who engages with generative AI in a two-way communication; and an affective learner, who strictly differentiates the human from the nonhuman and claims reciprocity in human–AI communication to be impossible. This study utilizes a mixed-methods approach by integrating quantitative analysis of the student questionnaires and qualitative analysis of the writing assignments. The findings of the study will serve as a valuable resource for researchers and educators committed to fostering future-oriented citizenship through collaboration between humans and generative AI in higher education.

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Publication Details

Journal
Sustainability
Published
2025-09-18
DOI
https://doi.org/10.3390/su17188387
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00
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article

Human–AI Collaboration: Students’ Changing Perceptions of Generative Artificial Intelligence and Active Learning Strategies

Hyunju Woo, Yoon Y. Cho
Sustainability
Online Learning and Analytics
article

Human–AI Collaboration: Students’ Changing Perceptions of Generative Artificial Intelligence and Active Learning Strategies

Hyunju Woo, Yoon Y. Cho
article en

Abstract

This paper explores ways to use AI for active learning strategies so that students in higher education may perceive generative artificial intelligence (generative AI) as a collaborative partner in their learning experience. This study proposes AI can help advance educational sustainability when students read texts on critical posthumanism, reflect on the philosophical and ontological paradigms through which the human has been understood, and discuss the collaborative relationship between humans and AI using literary texts. By analyzing AI-collaborated writing assignments, student questionnaires, and peer evaluations, this study concludes there are three learning types based on the different levels of students’ perceived difficulties: a cognitive learner, who focuses on AI’s functional aspects such as information retrieval; a metacognitive learner, who engages with generative AI in a two-way communication; and an affective learner, who strictly differentiates the human from the nonhuman and claims reciprocity in human–AI communication to be impossible. This study utilizes a mixed-methods approach by integrating quantitative analysis of the student questionnaires and qualitative analysis of the writing assignments. The findings of the study will serve as a valuable resource for researchers and educators committed to fostering future-oriented citizenship through collaboration between humans and generative AI in higher education.

SustainabilityVol. 17(18)
Kyonggi University (KR)
Openalex Percentile: Top 72%
Online Learning and Analytics
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