Special Issue: Pedagogy in Perpetual Motion

Pedagogy in Perpetual Motion: Navigating AI Tool Churn, Cognitive Overload, and the Psychology of Adaptive Literacy

Guest Editors: Tufan ADIGUZEL, Ph.D. & Kinshuk Kinshuk Ph.D.

Aims and Scope:

The initial rush to adopt Artificial Intelligence in education has given way to a more complex and exhausting reality: relentless technological churn. As AI tools continuously evolve, the psychological toll on potential users has become increasingly fuzzy, marked by decision paralysis, cognitive overload, and "AI fatigue." Recent data shows that the constant "adapt-learn-repeat" cycle is actually driving a regression in AI adoption intent among educators and creating anxiety among students.

This special issue of Contemporary Educational Technology moves beyond basic adoption metrics to investigate the psychological and cognitive realities of teaching and learning in an environment of perpetual technological flux. We are seeking research that redefines AI literacy—shifting from tool-specific competencies to adaptive, resilient frameworks that protect human cognition, pedagogical goals, and institutional strategy from the noise of constant updates.

We invite empirical studies, psychological analyses, and theoretical frameworks that address how schools, universities, and executive leadership can stabilize learning environments while integrating continuously shifting AI technologies.

Topics of Interest Include:

• The Psychology of AI Fatigue: Measuring and mitigating the cognitive load, techno-stress, and emotional exhaustion experienced by educators and students facing rapid tool churn.

• Adaptive AI Literacy: Frameworks for teaching computational thinking and AI skills that remain relevant regardless of which specific platform is currently dominant.

• Stakeholder Exposure & Institutional Resilience: How executive boards and educational leaders can manage the psychology of tech adoption without falling into reactive policy-making.

• Moving-Target Pedagogy: Designing flexible syllabi, self-study tasks, and assessment methods that anticipate and absorb continuous technological disruption.

• The Student-AI Trust Dynamic: How shifting tool capabilities impact student reliance, academic integrity, and trust in AI as a personal learning companion.

Submission Deadlines:

• Abstract Submission: December 1, 2026

• Notification of Abstract Acceptance: December 15, 2026

• Full Manuscript Submission: March 15, 2027

• Final Editorial Decisions: July 10, 2027

• Publication: August, 2027

Submission

To submit your manuscripts, log in to https://www.editorialpark.com/cedtech, click the 'Submit New Manuscript' button, select 'Special Issue'

Authors' Guidelines

https://www.bastas.me/home/submission-guidelines