Introduction to the Special Section on Generative Artificial Intelligence (GenAI) in Learning Design: An Editorial with a Commentary

Generative Artificial Intelligence (GenAI) has rapidly become embedded in the professional practices of educators, learning designers, and learners, changing expectations around productivity, creativity, authorship, and expertise. This Editorial introduces the International Journal of Designs for Learning (IJDL) Special Section on Generative Artificial Intelligence in Learning Design, which features sixteen peer-reviewed Design Cases documenting how GenAI is being designed with, constrained, and interrogated across diverse learning contexts. These contexts include higher education, K–12, informal learning environments, professional learning, civic education, expressive arts, engineering, and open educational resource development. Rather than positioning GenAI as a miraculous or autonomous solution, the Design Cases foreground it as a facilitation tool, creative material, and site for critical inquiry within human-centered design practice. Across cases, GenAI functions as a co-designer, co-writer, co-critic, and provocation—supporting ideation, drafting, reflection, and iterative design—while remaining dependent on human judgment and contextual expertise. Authors explicitly address ethical tensions related to authorship, accuracy, bias, accessibility, equity, and rapid technological change. This Editorial synthesizes key themes across the collection and argues that GenAI does not replace learning designers. Instead, it makes their design work more visible, more complex, and more essential than ever.

Authors

Institutions

Publication Details

Journal
International Journal of Designs for Learning
Published
2025-12-18
DOI
https://doi.org/10.14434/ijdl.v16i2.42712
Primary Topic
Neuroscience, Education and Cognitive Function
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Introduction to the Special Section on Generative Artificial Intelligence (GenAI) in Learning Design: An Editorial with a Commentary

Olgun Sadık, Ahmed Lachheb, Rajagopal Sankaranarayanan, Javier Leung et al.
International Journal of Designs for Learning
Neuroscience, Education and Cognitive Function
article

Introduction to the Special Section on Generative Artificial Intelligence (GenAI) in Learning Design: An Editorial with a Commentary

Olgun Sadık, Ahmed Lachheb, Rajagopal Sankaranarayanan, Javier Leung, Victoria Abramenka‐Lachheb
article en

Abstract

Generative Artificial Intelligence (GenAI) has rapidly become embedded in the professional practices of educators, learning designers, and learners, changing expectations around productivity, creativity, authorship, and expertise. This Editorial introduces the International Journal of Designs for Learning (IJDL) Special Section on Generative Artificial Intelligence in Learning Design, which features sixteen peer-reviewed Design Cases documenting how GenAI is being designed with, constrained, and interrogated across diverse learning contexts. These contexts include higher education, K–12, informal learning environments, professional learning, civic education, expressive arts, engineering, and open educational resource development. Rather than positioning GenAI as a miraculous or autonomous solution, the Design Cases foreground it as a facilitation tool, creative material, and site for critical inquiry within human-centered design practice. Across cases, GenAI functions as a co-designer, co-writer, co-critic, and provocation—supporting ideation, drafting, reflection, and iterative design—while remaining dependent on human judgment and contextual expertise. Authors explicitly address ethical tensions related to authorship, accuracy, bias, accessibility, equity, and rapid technological change. This Editorial synthesizes key themes across the collection and argues that GenAI does not replace learning designers. Instead, it makes their design work more visible, more complex, and more essential than ever.

International Journal of Designs for LearningVol. 16(2)
Boise State University (US), University of Kansas (US), Indiana University Bloomington (US), University of Missouri (US), The University of Texas at Austin (US)
Openalex Percentile: Top 58%
Neuroscience, Education and Cognitive Function
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.