<p>Artificial intelligence is increasingly implemented in higher education, offering customized interventions and timely feedback to enhance learning experiences. While these tools have the potential to improve educational outcomes, they also introduce ethical risks and sociotechnical implications such as reduced learner autonomy. Current ethical discussions often focus on computational issues and overlook the nuanced impacts from students’ perspectives, which may increase students’ vulnerability. Taking a student-centered approach, we apply the Story Completion Method to investigate students’ concerns about adopting analytics-based AI tools in education. Seventy-one participants responded to the story prompts, which we analyzed qualitatively to uncover perceptions about how these tools may reshape pedagogical aspects such as learner autonomy, learning environments and approaches, interactions and relationships, and pedagogical roles. Our findings reveal that these potential impacts not only occur in isolation but also interact with one another. This study makes two primary contributions: first, it marks a novel application of the speculative design method to explore students’ perceptions of AIEd tools. Second, it provides a qualitative analysis of key themes derived from student responses, offering design implications for AIEd systems that are sensitive to student concerns and ethical considerations. These insights offer a foundation for future research and contribute to a more student-centered approach to the ethical development of AIEd.</p>

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Students’ Perceptions: Exploring the Interplay of Ethical and Pedagogical Impacts for Adopting AI in Higher Education

  • Bingyi Han,
  • Sadia Nawaz,
  • George Buchanan,
  • Dana McKay

摘要

Artificial intelligence is increasingly implemented in higher education, offering customized interventions and timely feedback to enhance learning experiences. While these tools have the potential to improve educational outcomes, they also introduce ethical risks and sociotechnical implications such as reduced learner autonomy. Current ethical discussions often focus on computational issues and overlook the nuanced impacts from students’ perspectives, which may increase students’ vulnerability. Taking a student-centered approach, we apply the Story Completion Method to investigate students’ concerns about adopting analytics-based AI tools in education. Seventy-one participants responded to the story prompts, which we analyzed qualitatively to uncover perceptions about how these tools may reshape pedagogical aspects such as learner autonomy, learning environments and approaches, interactions and relationships, and pedagogical roles. Our findings reveal that these potential impacts not only occur in isolation but also interact with one another. This study makes two primary contributions: first, it marks a novel application of the speculative design method to explore students’ perceptions of AIEd tools. Second, it provides a qualitative analysis of key themes derived from student responses, offering design implications for AIEd systems that are sensitive to student concerns and ethical considerations. These insights offer a foundation for future research and contribute to a more student-centered approach to the ethical development of AIEd.