Oct 2026· Qualitative Research Journal· 0 citations· 81 references
Educational Theory and Curriculum Studies
Abstract
This study investigates the entanglement of researcher’s agency and authorship in curriculum development mediated by generative artificial intelligence (GenAI). Despite growing enthusiasm for GenAI’s transformative potential, little is known about the process of becoming-with AI in the epistemic and ethical labor of design. Guided by the research question – what forms of agency and authorship emerge through the process of becoming-with AI in AI-mediated curriculum design?
Employing a hermeneutic autoethnographic methodology, the researcher documented a lived experience through iterative interactions with GenAI across curriculum planning, sequencing, mapping, alignment and implementation. Data sources included structured prompting protocols, reflective analytic memos and Photovoice artifacts capturing critical decision points in AI-assisted design.
Qualitative content analysis has revealed five configurations in curriculum work: GenAI as a mediator of curricular coherence, an architect of sequencing learning, a cartographer of curricular alignment, a curator of contextualized learning experiences and an orchestrator of aligned and active learning.
Findings indicate that agency and authorship are not diminished in AI-mediated contexts but reconstituted as distributed and ethically intensified practices. GenAI redistributes cognitive labor while amplifying the need for disciplined discernment in evaluating alignment, coherence and epistemic integrity. Curriculum development thus emerges as a negotiated sociotechnical practice in which professional judgment remains the locus of accountability.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
Related blog posts
MIT News · Artificial Intelligence· news.mit.eduOct 18, 2026
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.