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This new journal is dedicated to advancing the field of applied pedagogy and learning theory by disseminating research, best practices and innovative approaches to teaching and learning in higher education.

In alignment with its vision to become a national leader in higher education teaching and learning research, this journal emphasizes interdisciplinary scholarship, innovation and evidence-based practices that inform policy and professional development.

Thematic Focus: AI in Teaching and Learning in Higher Education

• Artificial intelligence is rapidly reshaping higher education, offering unprecedented opportunities to enhance teaching effectiveness and student learning. From AI-driven personalized learning platforms to intelligent tutoring systems and administrative automation, these tools promise to boost educational outcomes and efficiency. At the same time, these technologies raise important questions about ethics, value and the evolving role of instructors, underscoring the urgency of addressing its opportunities and challenges in education now, noting that AI can help achieve educational priorities at scale while educators proactively mitigate risks. Since students have already begun embracing generative AI tools, it is crucial for higher education to adopt a thoughtful, balanced approach to integrating AI in teaching and learning.
• We seek original contributions that explore how these technologies intersect with pedagogy, curriculum design, assessment and student engagement in postsecondary contexts. Papers may investigate the benefits of AI for personalized learning, analyze challenges such as academic integrity and data privacy, or examine the implications of AI-driven tools supporting opportunity for all in teaching and learning.

Possible Topics of Interest

• Artificial Intelligence-Enhanced Learning Experiences: Personalized and adaptive learning systems, intelligent tutoring and AI-driven feedback mechanisms for students.
• Curriculum and Instructional Design with AI: Innovative uses of AI in course design, content creation (e.g., generative AI for simulations or materials) and AI’s role in fostering critical thinking and creativity.
• Assessment and Academic Integrity: AI applications in student assessment and grading, plagiarism detection, and strategies to uphold academic integrity in the age of AI.
• Faculty Development and AI Literacy: Preparing and training instructors to effectively use AI tools, as well as case studies of faculty integrating AI into their teaching practice.
• Policy and Ethical Implications: Governance of AI in higher education, ethical considerations (bias, privacy and access disparities) and the impact of AI on higher education policies and decision-making.

Some Submission Types

• Research Articles (Empirical Studies): Rigorous quantitative, qualitative or mixed-method studies that report original research findings on AI in teaching and learning.
• Conceptual and Theoretical Papers: Scholarly essays or analytical papers that advance pedagogical theory, propose new frameworks or critique existing paradigms related to AI in higher education.
• Case Studies and Practice-Based Reflections: Detailed examinations of AI implementations or innovations in classroom or institutional settings, highlighting lessons learned and evidence of impact on teaching effectiveness or student outcomes.
• Book Reviews: Critical reviews of recent books or reports relevant to the theme of AI in teaching and learning. Please inquire about the suitability of titles before submitting a full review.

All submissions must be original works not previously published and not under consideration elsewhere. Interdisciplinary collaborations are especially encouraged. The journal serves as a hub for educators and researchers across disciplines to share insights and advance the scholarship of teaching and learning.