.png){kind=icon}
.png){kind=icon}
Return
Codevelop Learning Tasks With Generative AI: Mapping Challenges, Gains, and Professional Development Needs
.png){kind=icon}
PRE
AI
DOI：10.1109/TLT.2026.3675467.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The design of learning tasks represents a fundamental pedagogical process that directly shapes educational effectiveness, but this process is time-consuming and knowledge-intensive for teachers. The rapid emergence of generative artificial intelligence (GenAI) technologies has created unprecedented opportunities for supporting teachers’ teaching practice. However, despite growing interest in teacher–GenAI collaboration, current research primarily focuses on preservice teachers and overall lesson plan design, with limited attention to challenges inherent in teacher–GenAI codesign of learning tasks or what teachers learn from such collaboration. To address this gap, we employed a mixed-methods approach involving 28 in-service teachers who collaborated with GenAI tools to codevelop learning tasks across three weeks. Qualitative analyses identified four overarching interaction challenges: inefficient interactions, low-quality tasks, lack of distributed cognition, and negative human–GenAI feedback loops. These overarching challenges emerged from bilateral deficiencies—three teacher-related shortcomings (providing too little context information, providing too little pedagogical guidance, and lacking GenAI skills) and six GenAI-related shortcomings (accuracy issues, limited prompt understanding, weak knowledge of content sequences, limited context knowledge, incomplete instructional solutions, and usability issues). Quantitative analyses of changes from pre to post showed significant improvements in teachers’ technical knowledge and artificial intelligence (AI) literacy, with no changes in self-efficacy and pedagogical knowledge. Finally, teachers expressed professional development needs primarily in two areas: AI foundations and applications and AI pedagogy. This study provides empirical evidence of bidirectional challenges in teacher–GenAI collaboration in designing learning tasks and offers a framework for understanding teacher professional growth through AI collaboration and further needs.
Keywords:
Generative artificial intelligence (GenAI)
learning tasks design
teacher professional development (TPD)
teacher–GenAI collaboration
Journal
IF:
4.9
Papers:
123
Citations:
3.0K
View more organizations