The Teachers AI Café
The Teachers AI Café is a podcast designed for educators eager to harness the power of artificial intelligence in their classrooms. Join us for engaging conversations, practical tips, and real-world examples on how AI can streamline lesson preparation, provide insightful feedback, and foster student skill development. Whether you’re a tech novice or a digital native, this café is your go-to space to learn, share, and revolutionize your teaching with AI.
The Teachers AI Café
AI in Education: Research Highlights and Practical Insights for 2026
In this episode of the Teacher's AI Cafe, host Kane reviews key AI research papers from 2025, highlighting their implications for educators. He discusses studies on AI-human synergy, the risks of cognitive offloading, student use of AI without proper guidance, economic disparities in AI adoption, and the role of AI in mental health support. Emphasizing the importance of teacher-customized training programs and ethical considerations, Kane explores how AI can positively impact classroom culture, assessment practices, and student well-being while advocating for equity and thoughtful integration of AI technologies.
00:00 Introduction and Welcome
00:23 Reflecting on the Past Year
00:38 Importance of AI Research in Education
02:16 Study 1: AI-Human Synergy
03:33 Study 2: Risks of Large Language Models
04:50 Study 3: Teaching AI-Native Generation
06:50 Study 4: Underreporting of AI Use
07:49 Study 5: ChatGPT's Impact on Learning
10:39 Study 6: AI Chatbots for Mental Health
12:12 Study 7: AI Adoption in Schools
13:25 Conclusion and Future Outlook
1. Quantifying Human–AI Synergy
Christoph Riedl, Ben Weidmann
• Found that effective collaboration with AI is a distinct skill, separate from subject knowledge.
• Student success depended on questioning, interpretation, and adaptive thinking.
• Relevance: Challenges traditional assessment models.
• Access: SSRN and university research repositories.
2. From Superficial Outputs to Superficial Learning: Risks of Large Language Models in Education
Iris Delikoura, Yi-R. Fung, Pan Hui
• Review of 70 studies showed polished AI work can mask shallow learning.
• Overuse linked to weaker memory and motivation.
• Relevance: Reinforces the value of struggle and guided AI use.
• Access: Education and HCI journals; Google Scholar.
3. Teaching the AI-Native Generation: Empowering Schools in the Age of AI
Oxford University Press
• UK student survey revealed AI helps skills but can reduce challenge and creativity.
• Fewer than half of students trust their ability to judge AI outputs.
• Relevance: Students want guidance, not bans.
• Access: Oxford University Press education reports.
4. Underreporting of AI Use: The Role of Social Desirability Bias
Yier Ling, Alex Kale, Alex Imas
• Students underreport AI use due to fear and stigma.
• Surveys likely underestimate actual usage.
• Relevance: Punitive approaches drive AI use underground.
• Access: SSRN and behavioural research journals.
5. The Effect of ChatGPT on Students’ Learning Performance, Learning Perception, and Higher-Order Thinking: Insights from a Meta-Analysis
Jin Wang, Wenxiang Fan
• Meta-analysis of 51 studies showed benefits only when AI use was instructional.
• Outcomes depended on pedagogy, subject, and duration.
• Relevance: AI amplifies good teaching, not poor design.
• Access: Education technology journals; ERIC.
6. Cyborgs, Centaurs and Self-Automators: T
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