Seven research priorities for AI in learning, spanning expanded scenarios, teacher assistance, assessment, responsible AI, equity policy, stakeholder engagement, and ecosystem strengthening¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The panel issued seven recommendations: investigate AI designs for an expanded range of learning scenarios; develop AI systems that assist teachers and improve teaching; intensify and expand research on AI for assessment of learning; accelerate development of human-centered or responsible AI; develop stronger policies for ethics and equity; inform and involve educational policy makers and practitioners; and strengthen the overall AI and education ecosystem. The report urges that "Now is the time to begin planning for how to best develop and use AI in education in ways that are equitable, ethical, and effective and to mitigate weaknesses, risks, and potential harm."

Design Implications¶

Context¶

Requirements¶

• Further discussion must involve practitioners, policymakers, innovators, and industry, which the expert panel alone lacked

Constraints¶

• The panel had limited involvement of other stakeholders and framed the report as an initial discussion

Target Learners¶

• All students, with explicit attention to vulnerable populations and equity

Target Learning Goals¶

• Equitable, ethical, and effective development and use of AI in education

Related Strategies¶

• Reorient AI assessment toward formative, holistic portraits of learner competencies rather than automated grading
• Design AI as a classroom orchestration partner that helps teachers form groups, nurture conversations, and track participation without taking control
• Ground AI integration in higher education on core principles of human agency, academic freedom, transparency, ethics, inclusivity, and critical thinking
• Involve teachers as co-designers of AI-based intelligent systems, with agency to train, correct, interpret, and override system recommendations
• Use generative AI to make assessment systems more instructionally relevant, not to reify problematic practices
• Cross-stakeholder policy, research, and practice actions for collaborative AI initiatives in education

Examples¶

-

Key Sources¶

• Roschelle, J., Lester, J. & Fusco, J. (Eds.) (2020). AI and the future of learning: Expert panel report [Report]. Digital Promise. https://circls.org/reports/ai-report. doi:10.51388/20.500.12265/106