Exploring interfaces and implications for integrating social-emotional competencies into AI literacy for education: a narrative review

Synthesis: Palmquist, Sigurdardottir, and Myhre (2025) conduct a narrative literature review examining the intersection of AI literacy and social-emotional competencies (SEC) in education, proposing an integrated framework to create a supportive, technologically adept, and emotionally intelligent educational ecosystem. Grounded in the SETCOM project, the review identifies three key themes — AI's transformative potential in reshaping educational practices, its influence on educational providers and stakeholders, and the ethical considerations of AI integration — and argues that integrating AI literacy with SEC can enhance educational outcomes by promoting personalized learning, fostering collaboration, and addressing ethical challenges.

Key Findings

• AI literacy and SEC are complementary: technical proficiency alone is insufficient for navigating AI-mediated learning environments; combining technological understanding with relational and emotional intelligence supports a holistic approach to skill development.
• Three themes emerged from thematic analysis of the literature: (1) AI's transformative potential (reshaping educational practices, adapting to student needs, demanding human-centered, ethical design); (2) AI's influence on educational providers and stakeholders (changing teachers' roles, functions, and attitudes, and the need for collaboration with external stakeholders); and (3) ethical considerations of AI integration (data privacy, algorithmic bias, equitable access, and responsible decision-making).
• Personalization and relational practices: AI-driven personalization (intelligent tutoring, adaptive learning) parallels SEC's focus on teacher-student and student-student relationships; AI should deepen — not replace — human connections in learning environments.
• Educators' roles are shifting: as AI automates administrative tasks, educators can focus more on guiding students' emotional and cognitive development, where human touch is indispensable (drawing on Selwyn); teacher training should incorporate SEC-infused AI literacy.
• A robust framework should blend AI literacy with SEC, fostering critical thinking, ethical awareness, empathy, self-management, and responsible decision-making, so that technological advancement supports rather than undermines human connection.

Study Design & Method

This is a narrative literature review building on the knowledge base of the SETCOM project (Supportive Environments to Enhance Transversal Competencies in Education). A curated bibliography of 64 sources (31 on AI, 18 on SEC, 13 on both) was compiled from expert recommendations, then filtered through two stages: (1) inclusion/exclusion criteria (peer-reviewed sources in English, AI sources post-2017) and (2) quality assessment, removing 43 sources to leave a data corpus of 19. Sources were categorized into three groups (C1: AI in Education, n=8; C2: SEC in Education, n=7; C3: AI and SEC in Education, n=4). The corpus was thematically synthesized using a three-stage approach (pre-analysis, exploration, treatment/interpretation) informed by Ferrari (2015), with MAXQDA used for coding and analysis. The reviewed literature spanned primary (57.1%), secondary (46.4%), higher (35.7%), adult (17.9%), pre-school (14.3%), special-needs (10.7%), and teacher-training (3.6%) education contexts.

What this means for practice

• Instructors. Teach AI literacy and social-emotional competencies together rather than leaving emotional skills to pastoral provision: the review's framework pairs technological understanding with empathy, self-management, and responsible decision-making so that AI-mediated learning does not thin out human connection.
• Instructors. Design AI-driven personalization (Intelligent Tutoring, Adaptive Learning) to deepen teacher-student and student-student relationships rather than to substitute for them, since the review treats personalization as a parallel to relational practice, not a replacement.
• Instructors. Make ethical literacy content rather than a warning appended to a tools unit: data Privacy, algorithmic bias, equitable access, and responsible decision-making recurred as the ethical concerns of the reviewed literature and belong in the AI curriculum itself.
• Instructors. Press for SEC-infused teacher training and competency standards: the reviewed literature (drawing on Selwyn) argues that as AI absorbs administrative work, educators should redirect effort to the emotional and cognitive development AI cannot perform.
• Researchers. Treat the integrated framework as a hypothesis rather than a template: it is conceptual, built on a curated corpus of 19 sources, and needs empirical validation before it structures programs or assessments.

Limitations

As a narrative review, the study faces potential selection bias and subjective interpretation of findings (acknowledged by the authors), and its small final corpus (19 sources) reflects a curated rather than exhaustive literature base. The AI sources were limited to post-2017 publications, which may not capture the most recent rapid advances, and the review synthesizes concepts as of its curation date. The SEC literature was not subject to the same 2017 cutoff, creating asymmetry. The proposed integrated framework is conceptual and requires empirical validation.

Citation

Palmquist, A., Sigurdardottir, H. D., & Myhre, H. (2025). Exploring interfaces and implications for integrating social-emotional competencies into AI literacy for education: A narrative review. Journal of Computers in Education, 13, 127–163.