APA Discusses Generative AI in Education: Learning Science, Cheating, and AI Literacy

In this Speaking of Psychology episode, the American Psychological Association hosts Dr. Eddie Watson and Dr. Beth Schwartz to discuss the rapid integration of generative AI in classrooms, what counts as cheating in the AI era, and how educators can design learning experiences that harness AI without compromising understanding. The conversation covers current usage patterns in K-12 and higher education, the disruption AI represents compared to calculators and internet search, and the need for practical policy and curriculum design to ensure students develop true AI literacy.

• AI usage in higher education is widely reported but varies across surveys, with educators noting a mix of adoption and resistance.
• Cheating definitions differ among students and faculty; ongoing discussions and explicit guidelines reduce academic dishonesty.
• Assignments should be redesigned to use AI as a learning partner, not a shortcut, emphasizing reflection and critical evaluation.
• Curricular agility and AI literacy are essential as AI becomes embedded in education and the workforce.

Overview

The episode of Speaking of Psychology features Dr. Eddie Watson and Dr. Beth Schwartz from the American Psychological Association, who discuss the rapid adoption of generative AI in classrooms, the complexity of defining cheating with AI, and how educators can design assignments that promote learning while integrating AI tools. The guests emphasize that AI should augment rather than replace human teaching and learning, and that decisions should be guided by robust evidence on how students learn.

Current Landscape in AI in Education

The discussion opens with a look at how common AI use is in K-12 and higher education. Data are mixed, with student self-reports of AI use in higher education ranging from a minority to the majority of students, depending on the survey. Educators report that AI is being used to support tasks across the teaching-learning cycle, from course design to feedback and even grading, but opinions differ on whether these uses are appropriate or beneficial. The speakers note that policy and practice often lag behind the technology, and professional development is frequently insufficient.

AI as Disruption and Opportunity

The conversation distinguishes AI from earlier disruptions such as calculators and search engines. The calculator helped with routine computations but did not automate higher order thinking; the internet removed the search process. AI, by contrast, can generate explanations and write tasks, potentially altering what constitutes learning and requiring new pedagogical approaches. The experts argue for a learning-first approach, using AI to enhance thinking rather than outsourcing it, and for a renewed emphasis on how AI literacy fits into curricula and the workforce.

Cheating, Integrity, and Policy

Cheating is not new, but AI introduces new modalities. There is currently no universal consensus on legitimate AI use, as opinions vary by discipline and learning goals. The best practice to reduce cheating is to discuss academic integrity openly and repeatedly with students, not just once at the start of the semester. Clear guidelines about when AI can be used for a given assignment, along with transparent communication about grading and feedback methods, can reduce anxiety and improve compliance.

Designing for Learning with AI

The hosts and guests stress the need to redesign assignments to incorporate AI as a collaborative tool. A key message is that students should maintain an ongoing process of critique and evaluation of AI outputs, with instructors providing concrete expectations and opportunities for reflection. In some cases, in-class assessments or blue-book style exams may help ensure that learning goals are being met, while AI-assisted methods can still support practice and feedback outside of high-stakes tasks.

Future Directions and Curricular Agility

The participants discuss the importance of curricular reform that can adapt quickly to the evolving AI landscape. They identify the need to define AI literacy as a core outcome for college students and to build frameworks that connect workplace needs with learning outcomes. Collaboration between APA and AACU aims to support faculty in conducting scholarship on AI's impact on learning and to develop methodologies that isolate the effect of AI on long-term learning outcomes.

Conclusion and Recommendations

The episode closes with a reaffirmation of core learning science as the foundation for AI integration in education. The guests advocate for evidence-informed practices, transparency with students, and ongoing conversations about what constitutes fair use of AI in teaching and learning. They call for agility in higher education to prepare students for an AI-enabled workforce while preserving essential cognitive and pedagogical principles.