Special Section on Exploring New Frontiers in Learning Analytics through Artificial Intelligence Augmentation

2026-07-09

EDITORS:

- - Elizabeth Koh, Nanyang Technological University, Singapore, elizabeth.koh@nie.edu.sg
  - Srećko Joksimović, University of South Australia, Australia, Srecko.Joksimovic@unisa.edu.au
  - Lishan Zhang, Beijing Institute of Technology, China lishan.zhang@bit.edu.cn
  - Changhao Liang, Kyushu University, Japan, liang.changhao.507@m.kyushu-u.ac.jp

AIMS & SCOPE

We are excited to organize a special section for extended works from the 2^nd International Conference on Learning Evidence and Analytics 2026 (ICLEA 2026), June 25-26, 2026, in Kumamoto, Japan. ICLEA26’s theme, "Exploring New Frontiers in Learning Analytics through Artificial Intelligence (AI) Augmentation”, will be the focus of this special section. This theme foregrounds the dynamic convergence of learning analytics and artificial intelligence, emphasizing the evolving nature of learning processes as shaped by AI-enhanced analytics. Rather than prioritizing the development of AI systems, we focus on the ways in which learning unfolds through the use of learning analytics, and how AI-mediated interactions influence these processes. As AI becomes increasingly embedded within learning environments, not merely as a tool, but as a collaborative agent, we invite critical reflection on how learning data is captured, interpreted, and leveraged to empower both learners and educators. We envisioned that the papers published in this special section would explore learning in AI-augmented contexts, examining how analytics can render learning processes visible, interpretable, and actionable. We invite submissions that address cutting-edge research, case studies, best practices, and emerging trends in the following topics (but not limited to these):

Metrics, indicators and models of learning evidence
- New indicators for learning processes and outcomes such as self-regulation, and learner engagement and collaborative learning
- Unimodal and multimodal data curation, modelling and analytics of learning processes and outcomes
- Synthesis and application of indicators for predicting and simulating learning processes and outcomes
Learning designs and evaluation of analytics-based feedback
- Designing innovations and interventions with AI-augmented learning analytics such as pedagogical agents with large language models, analytics-based feedback
- Formative evaluation and effectiveness of analytics-based feedback
- Real-world applications of AI-augmented learning analytics
Learner and educator competencies and skills needed in AI-augmented learning analytics
- Cognitive and metacognitive skills needed in AI-rich contexts
- Strategies and practices for building data literacy among educators and students
- Tools for interpreting and applying learning analytics insights
Conceptual and critical perspectives on human-system integration and collaboration
- Evolving boundaries of learner and system roles in co-constructed learning
- What counts as learning evidence in AI-augmented education
- Human-AI collaboration and multi-LLM agent systems
Ethical and trustworthy use of data
- Ethical concerns and trustworthy analytics frameworks
- Privacy, security, and data protection in educational environments
- Fairness and transparency in AI-augmented learning analytics tools

SUBMISSION INSTRUCTIONS:

Conference-based special issue papers are expected to have 30-40% new material from the conference, in order to be publishable in the journal.
Author guidelines of the journal should be adhered to.

IMPORTANT DATES

Invites to selected authors: 1 July 2026
Submission of original manuscripts: 1 October 2026
Completion of reviews (Decisions sent): 3 January 2027
Submission of revised manuscripts: 15 March 2027
Completion of 2nd round reviews if any (Decisions sent): 15 April 2027
Submission of revised manuscripts: 15 May 2027
Notification of final acceptance: 15 June 2027
Publication of special section date: August 2027