Call for Special Issues:AI

Call for Special Issue (Open Access)
Journal of Interactive Learning Research (JILR)

Artificial Intelligence + Education: Love or Hate?

Submission Deadline: April 15, 2023

Key Information

Important Dates:

Manuscript submission: April 15, 2023.

Reviews returned/Decisions made: May 1, 2023

Final Accepted Papers: May 19, 2023

Publication: Approximately June 2023

Topics of interest include, but are not limited to, the following aspects:

  • AI features and affordances for instructional objectives
  • AI design frameworks and challenges for education
  • User behaviors and perceptions within AI educational experiences
  • AI integration in classroom and workforce settings
  • AI-empowered professional development and training
  • Accessibility in AI to promote inclusive interactive learning
  • Evaluation and assessment of instructional AI
  • Student-led AI creation and related learning outcomes
  • Solutions to AI-related issues (e.g., plagiarism) in education and training
  • Communities of practice in AI-related social media
  • The impact of AI on academic research effort

Submit after Feb. 15 to: (choose JILR 34:2, Special Issue on AI)


This special issue aims to collect an interdisciplinary corpus of work that addresses the following questions and advances our theoretical and analytical understanding of AI as applied to human interactive learning (across disciplines and across the lifespan). Preference will be given to empirical research, though strong theoretical papers and literature reviews are also welcomed.

  1. What are theory-informed and empirical frameworks that can facilitate our understanding of AI’s instructional implications?
  2. How can AI creative editors (e.g., ChatGPT, MidJourney) be used to promote learning (prek-12 education, higher education, professional development, corporate training), where learning can include both hard skills (related to any content area/domain) and soft skills (e.g., self-reflection, leadership, clinical judgment, self-confidence)?
  3. What solutions can be envisioned and enforced to address the issues currently associated with AI (e.g., plagiarism, the potential impact on critical and creative thinking)?
  4. What is the role of online communities (e.g., Discord, Reddit) in informing AI production and awareness for education and training?


Artificial Intelligence (AI) can broadly be defined as the capacity of a machine to process information and execute tasks by mimicking the abilities of intelligent and sentient beings. AI has been around for decades; it has a strong connection to computer science (from machine learning to robotics), adaptive technologies, and learning. It has enjoyed a rise in popularity that is due, in part, to the recent availability, interest, and fear of tools like ChatGTP and MidJourney.

With such AI editors, it is now possible to generate content (e.g., text, images) from simple prompts at little to no cost. Moreover, these instruments are surrounded by online communities with millions of active users who create and discuss their creations. Companies are also increasingly deploying AI to improve their services and scope, from consumer services (e.g., smart bots) to content and planning.

However, these same AI tools are now under scrutiny due to the potential impact of AI on education. For instance, some educators have suggested that AI has and will replace human intellectual efforts, facilitating plagiarism and cheating practices among learners at multiple instructional levels. Many educational institutions are even starting to ban AI software to contain these risks. Others are raising concerns about AI content’s copyright and applications.

Conversely, other scholars and researchers are starting to explore the potential benefits of this technology to improve self-reflection, critical thinking, and inquiry practice. They have even gone so far as to suggest that it is our responsibility to teach AI to our students and our employees. As with any interactive innovation, the learning impact of AI depends on the conditions under which this technology is applied and delivered.

Given the potential affordances and constraints, more theory-driven and empirical efforts are needed to shed light on leading factors and best practices related to AI + Education.

Questions:  Contact Dr. Rick Ferdig ([email protected]) or Dr. Enrico Gandolfi ([email protected])

JILR information:

Wish to Serve on the JILR Editorial Review Board?

Authors and non-authors contact [email protected]