Date
Publisher
arXiv
AI's integration into education promises to equip teachers with data-driven insights and intervene in student learning. Despite the intended advancements, there is a lack of understanding of interactions and emerging dynamics in classrooms where various stakeholders including teachers, students, and AI, collaborate. This paper aims to understand how students perceive the implications of AI in Education in terms of classroom collaborative dynamics, especially AI used to observe students and notify teachers to provide targeted help. Using the story completion method, we analyzed narratives from 65 participants, highlighting three challenges: AI decontextualizing of the educational context; AI-teacher cooperation with bias concerns and power disparities; and AI's impact on student behavior that further challenges AI's effectiveness. We argue that for effective and ethical AI-facilitated cooperative education, future AIEd design must factor in the situated nature of implementation. Designers must consider the broader nuances of the education context, impacts on multiple stakeholders, dynamics involving these stakeholders, and the interplay among potential consequences for AI systems and stakeholders. It is crucial to understand the values in the situated context, the capacity and limitations of both AI and humans for effective cooperation, and any implications to the relevant ecosystem.
Study at a glance
- Question: How do students perceive AI tools that monitor them and alert teachers to provide targeted help?
- Setting and data: Narratives from 65 participants about higher education classrooms.
- Method: Narrative analysis (story completion method).
Why it matters
Although AI promises to equip teachers with data-driven insights, there is a lack of understanding of emerging classroom dynamics when teachers, students, and AI collaborate, particularly when AI observes students to notify teachers to provide targeted help.
Key findings
- In a higher education study with 65 participants, students expressed concern that AI monitoring tools overlook crucial context when alerting teachers to help.
- Participants were concerned that AI-teacher collaboration could lead to biased decisions and amplify power imbalances in the classroom.
- Participants reported that AI observation could alter student behavior in ways that ultimately undermine the tool's effectiveness.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
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