Learning: Research and Practice

The launch of ChatGPT (https://openai.com/blog/chatgpt) on 30 November 2022 has taken the world (including the education world) by storm, accelerating a new wave of innovation – the age of generative artificial intelligence (AI). For decades, AI researchers have been working on generative models that can generate speech, text, music, etc., but with the recent rise of deep learning, generative AI allows users to create content at a speed and accuracy that was not possible before. With advances in recent months, generative AI has become accessible to the general public. For language generation, we now have ChatGPT, Bard, LLaMA, and BLOOM; for image generation, there is DALL·E 2, Midjourney, and Stable Diffusion; Google’s MusicLM can be used to generate music; Meta’s Make-a-Video can be used to generate videos. By the time this special issue gets published, this list is likely to be outdated.

Generative AI has stimulated a lot of discussion in the field of learning, with many debates, opinion pieces, webinars, and research investigations. This issue intends to capture and identify some of the recent discourse on generative AI, notably its potential intended and unintended effects on learning. We invite manuscripts that fall broadly into any of these categories or beyond:

• Learning design/applications with generative AI
• Assessment with generative AI
• Strategies, opportunities, and concerns in schooling/education/learning
• How generative AI challenges or changes the nature of what we learn and teach
• Generative AI as a tool for simulating or investigating learning
• Stakeholder (e.g., students, teachers, parents) perceptions of generative AI for learning
• Future of learning with generative AI
• Subject-based investigations of generative AI for learning and teaching (e.g., social sciences, arts, STEM)
• Generative AI applied in various educational contexts (e.g., early childhood to adult learning, informal learning)

Submissions need to have good argumentation and substantiation as well as direct contributions and implications for learning and teaching. Submissions can be conceptual, reviews/syntheses and/or empirical.

We will accept the following types of submissions:

• Research Articles (6,000 words): articles of empirically supported studies on learning or extended theoretical arguments.
• Brief Reports (3,000 words): reports of innovative current work at earlier stages of idea conceptualization and/or empirical exploration that is of high value to learning researchers and practitioners.
• Letter to the Editor/Commentaries (1,000 – 3,000 words): article commentaries, responses to commentaries, and/or discussions of general relevance.

Submitted manuscripts will undergo a blind peer-review process and be evaluated in accordance with the Journal’s quality standards for acceptance into the special issue. Articles submitted need to be substantially different to previously published work though they may constitute significant extensions of prior work.

To be quick to capture the ongoing discourse, this special issue is intended for fast-track publication in September 2023. As the timeline is rather tight, authors are encouraged to be mindful of the expected timings of the submissions and/or revisions. There might also be some minor adjustments to the timeline.

To submit your abstract, please email to [email protected] with the subject line: Learning Special Issue.

Timeframe

• Submission of abstracts (400 words maximum): by 10 May 2023
• Notification of abstract acceptance: no later than 15 May 2023
• Submission of full manuscripts for review: by 15 June 2023
• Completion of reviews (decisions sent): no later than 17 July 2023
• Submission of revised manuscripts: by 10 August 2023
• Notification of final acceptance: no later than 25 August 2023
• Publication: 25 September 2023

Instructions for AuthorsSubmit an Article