Given an increased interest in the Science of Learning to translate how children learn into teaching and practice, this special issue seeks to advance understanding of how theoretical frameworks and research-based approaches can enhance EdTech design and implementation, with a specific focus on the Science of Learning (SoL). We invite well-developed empirical studies that examine the integration of science of learning principles with educational technologies (EdTech), underpinned by established theoretical frameworks.

For example, submitted papers could offer new insights into how the neurological or cognitive mechanisms can be activated by gamified elements, framed through theories like Social Cognitive Theory and Cognitive Load Theory. We are also interested in investigations of how digital platforms promote collaborative learning and knowledge co-construction, drawing on Distributed Cognition and Connectivism-informed data interpretations.

Submissions should explicitly connect theoretical foundations and SoL strategies to the design, implementation, and evaluation of EdTech tools. Papers addressing any (but not limited) of the following topics, while drawing on relevant theories, are highly encouraged:

• Learner Engagement, Gamification, and Motivation
• Multisensory and Multimodal Learning
• Congruent Learning and Prior Knowledge Activation
• Consolidation, Spacing Effects, and Adaptive Learning
• AI and Personalized Learning
• Mobile Learning and Open Educational Practices
• Game-Based Learning and Augmented Reality
• Evaluation frameworks and rubrics

We look forward to contributions that elevate the current state of knowledge about the intersection of theory, research, and practical applications in EdTech. Both empirical and conceptual articles are encouraged.

Submission Guidelines

We welcome empirical studies employing diverse methodologies, including experiments, quasi-experiments, case studies, and mixed methods. Theoretical and conceptual papers are considered beyond the focus of this special issue. Additionally, experiments with limited sample size, with superficial self-report use, or solely focusing on educational technology validation without any focus on Science of Learning are excluded. Submitted papers should:

• Clearly outline the theoretical foundations, including the SoL principals and strategies, guiding the EdTech design.
• Demonstrate how the principles of the selected theory were operationalized in the tool or intervention under examination.
• Provide robust evidence of the intervention’s impact on learning outcomes.
• Offer actionable insights for researchers, designers/developers of EdTech tools and practitioners.

Important Dates

• Abstract Submission Deadline: 15th September 2026
• Notification of Acceptance: 15th October 2026
• Full paper submission deadline: 1st November 2026
• Publication Date: Papers will be published immediately after acceptance and proofing by the journal

How to Submit

Abstracts should be sent by email to the corresponding guest editor, Natalia Kucirkova, by the indicated deadline at: Natalia.kucirkova@uis.no

Invited full manuscripts should be submitted via Smart Learning Environments Editorial Manager:

Editorial Manager®

Please adhere the journal’s formatting and referencing guidelines:

Submission guidelines | Smart Learning Environments

The Nexus between Learning Analytics and Artificial Intelligence Special Issue explores the intersection of Learning Analytics (LA) and Artificial Intelligence (AI) to support teaching and learning across all educational contexts. The rapid growth in LA and AI have resulted in several opportunities and challenges that remain unexplored especially, the pedagogical applications, the theoretical alignments and the cognitive and psychological aspects. These complex realities and emerging opportunities require a serious engagement beyond the hype that harness the technology while advancing education and preserving the cognitive and developmental skills of the future generations.

We are inviting the global community of educators, researchers, policymakers, and developers to explore how AI and data-driven insights are transforming education and how smart systems can genuinely support learners and teachers across all environments. The topic is highly timely and generates both discussion and questions: How different learning theories can inform the design, analysis, and interpretation of learning and teaching processes involving LA and AI? What underlying assumptions about learning and agency are embedded in LA and AI educational practices, and how do these assumptions align with or challenge established learning theories? How are questions of trust, accountability, and responsibility conceptualized and enacted in LA- and AI-mediated educational practices?

Authors are encouraged to present their latest research, methodological advances, empirical findings, and theoretical insights, and discuss the broader role of educational science in shaping the future of LA and AI.

Call for Contributions:

We invite empirical and theoretical-led contributions as well as systematic reviews on the role of LA and AI in education. Purely conceptual papers are beyond the SI scope. Additionally, experiments with limited sample size, with superficial self-report use, or solely focusing on educational technology validation without any LA focus are considered beyond the SI focus. Submissions may engage with (but are not limited to) the following themes:

• Pedagogy, Curriculum & Learning Design: LA- and AI-supported approaches to teaching and learning, including personalization, assessment and feedback, curriculum design, and AI literacy, as well as the use of learning data to inform and improve instructional decisions and learning experiences.
• LA and AI Technologies & Methodologies: Technical and methodological advances in LA and AI, such as NLP, multimodal learning analytics, adaptive systems, and gamified learning, alongside data integration, modeling, and evaluation approaches for understanding and supporting learning processes.
• Ethics, Policy & Governance: Ethical and regulatory dimensions of LA and AI, including data privacy, fairness, transparency, and accountability, as well as institutional practices, policy development, and teacher professional development for responsible use.
• AI-Augmented Learning Support: Digital assistants, virtual tutors, and AI agents informed by LA that scaffold learning, provide timely feedback, support self-regulation, and facilitate individual and collaborative learning processes.
• Generative AI and LA in Practice: Everyday uses of generative AI alongside LA by students and educators for writing, content creation, feedback, and instructional design, and how these practices reshape learning, assessment, and academic work.
• Human–AI–LA Interaction & Collaboration: Evolving relationships between humans, AI systems, and learning data, including trust, agency, interpretability of analytics, and the changing roles of teachers and learners in data-informed educational environments.
• Underlying Assumptions & Untapped Theories: Theoretical approaches to learning, LA and AI, critical societal insights and conceptualizations of LA and AI in education.

Submission Guidelines:

For consideration in this Special Issue, authors are invited to submit their manuscripts for a pre-submission evaluation. Submissions that satisfy the initial scope and meet appropriate quality standards for the Special Issue, will be invited to proceed to the full submission stage.

Authors whose papers are positively evaluated during the pre-screening process will receive detailed instructions for submitting their manuscripts through the official submission platform. For consideration, please submit your manuscript for pre-submission evaluation via the official system no later than 1st September: Link to Submission System (EasyChair)

Papers will be published immediately after acceptance and proofing by the journal.

Invited full manuscripts should be later on submitted via Smart Learning Environments Editorial Manager: Editorial Manager®

Please adhere the journal’s formatting and referencing guidelines: Submission guidelines | Smart Learning Environments

For inquiries regarding the special issue, please contact mohammed.saqr@uef.fi or sonsoleslp@uef.fi with the subject line LANAI SI.