Recently, artificial intelligence (AI) has increasingly been integrated into self-regulated learning (SRL), presenting novel pathways to support SRL. While AI-SRL research has experienced rapid growth, there remains a significant gap in understanding the intersection between AI and SRL, resulting in oversight when identifying critical areas necessitating additional research or practical attention. Building upon a well-established framework, from Chatti and colleagues, this systematic mapping review identified 84 studies through the Web of Science, Scopus, IEEE Xplore, ACM Digital, EBSCOHost, Google Scholar, and Open Alex, to explore the intersection of AI and SRL within the four key aspects—Who (stakeholders), What (theory), How (methods), and Why (objectives). The main results revealed that AI-SRL research predominantly focuses on higher education students, with minimal attention to primary education and educators. AI is primarily implemented as an intervention—through adaptive systems and personalization, prediction and profiling, intelligent tutoring systems, and assessment and evaluation—to support students' SRL and learning processes. The direct impact of AI on SRL was primarily focused on the metacognitive and cognitive aspects of SRL, while the motivational aspect of SRL remains underexplored. While over one-third of the AI-SRL studies did not specify an SRL theory, Zimmerman’s model of SRL was the most frequently applied among those that did. The use of AI in supporting SRL has extended beyond just focusing on and supporting SRL itself; it has also aimed to enhance various educational and learning activities as end outcomes such as improving academic performance, motivation and emotions, engagement, and collaborative learning. The results of this study extend our understanding of the effective application of AI in supporting SRL and optimizing educational outcomes. Suggestions for further research and practice are provided.

Access to AI-driven chatbots is triggering schools to transform. Easy access and questions of cheating are balanced against potential upsides of individual support, time savings, and the risk of falling behind. Therefore, insights into teachers’ AI self-efficacy and attitudes towards the integration of AI-driven chatbots in education necessitate research. This study approaches teachers' readiness to use AI-driven chatbots. A survey and poll questions were administered, yielding 312 and 406 responses respectively, focusing on AI self-efficacy, attitudes, and perceived usefulness in education. Preliminary findings show that while teachers are generally positive about the potential of AI in education, their AI self-efficacy varies significantly based on prior use of the technology, perceived relevance, and the support available to them. The study highlights the need for internal support and targeted professional development interventions and offers practical insights for policymakers, educators, and curriculum developers to foster teacher readiness and competence in using AI-driven chatbots in their professional tasks, in and outside of class.

Student wellbeing is recognised as a critical factor in supporting learning outcomes. However, when teachers are assigned expanded roles as mentors to monitor and support wellbeing, they often lack the necessary support to fulfil these responsibilities effectively. This study explores the tensions and behaviours that arise when teachers implement a novel wellbeing tool designed to provide insights into students’ wellbeing. Adopting a mixed-methods approach, data were gathered through a survey and interviews with teachers (n = 39) and analysed through the lenses of Activity Theory (AT) and the Theory of Planned Behaviour (TPB). The findings reveal that integrating the wellbeing tool introduced new practices, resulting in primary and secondary tensions concerning roles, implementation, and use. The integration of TPB uncovered psychological factors influencing teachers’ intentions and behaviours, complementing the systemic insights from AT. The study contributes to the broader conversation on enhancing educational practices to support student wellbeing, fundamental to achieving positive learning outcomes.

Telepresence robots (TPRs) have gained increased attention in education, yet most studies focus on single-case scenarios. There is growing recognition of the need to explore how TPRs can enhance inclusion and engagement within compulsory education, particularly for students who cannot attend school regularly. Although early research has identified positive attitudes towards TPRs, it also highlights a lack of research on multiple levels regarding what educational departments and practitioners experience and most urgently call for to support their day-to-day practice. Contributing with preliminary insights, we are conducting a pilot study across five Swedish municipalities, involving participants representing different educational system levels (teachers and administrators). Using a multi-case design, the study examines TPR usage in school, focusing on organisational, pedagogical, and technological dimensions. Our preliminary findings indicate that while TPRs can foster social and academic participation, schools often lack unified policies and established routines for effective integration; moreover, what is critically lacking is pedagogical instructions suitable for the different groups of students who participate through TPRs.

How K-12 education will handle generative artificial intelligence (GAI) is dependent upon educators’ preparedness and support structures. This study explores educational professionals’ perceptions regarding GAI and their support needs. 452 educational professionals, representing all years levels and educational roles in K-12, participated in a professional development (PD) intervention focused on GAI in education. Drawing on this cross-sectional design we adopted a mixed-methods approach. Data from polls, surveys, and collegial reflections were analysed using descriptive statistics, thematic analysis and Transformative Learning Theory. One of the key findings revealed a notable gap between positive attitudes toward GAI and an actual confidence in using it: although only 31% had used AI chatbots, 88% were inclined to adopt them. These results signal simultaneous enthusiasm and hesitation, and emphasise the need for comprehensive PD and organisational support that extends beyond technical skills to advocate for responsible, sustainable and ethical GAI use. This study offers insights for policymakers aiming to achieve effective, whole-school GAI integration, highlighting how design and innovation perspectives can guide the process.

Artificial intelligence (AI) has recently emerged as an influencing factor in several parts of society, not least in the education sector. When it comes to learning and teaching in higher education (HE), the discourse around AI has often been about the dangers, such as cheating, that can be linked to the use of generative AI. In this paper, we explore how 37 Swedish university teachers reflect upon the pros and cons about using generative AI. The study is based on two round-table discussions with university teachers at two separate Swedish educational development conferences. The research questions posed are: How do university teachers perceive the integration of generative AI into teaching and what are their main concerns and expected advantages when it comes to the use of generative AI in teaching? and How can HE institutions support university teachers to use generative AI for pedagogical innovation in an efficient way, whilst maintaining academic integrity? Drawing from the framework on communities of practice, the reflections of the university teachers are discussed in relation to their shared domain of teaching and learning in higher education. By deploying a thematic analysis, the results of the study underscore the importance of promoting responsible AI use within the academic community and identifying strategies to support educators in transitioning towards a more AI-integrated approach to teaching.

Although the field of Artificial Intelligence in Education (AIEd) has a substantial history as a research domain, never before has the rapid evolution of AI applications in education sparked such prominent public discourse. Given the already rapidly growing AIEd literature base in higher education, now is the time to ensure that the field has a solid research and conceptual grounding. This review of reviews is the first comprehensive meta review to explore the scope and nature of AIEd in higher education (AIHEd) research, by synthesising secondary research (e.g., systematic reviews), indexed in the Web of Science, Scopus, ERIC, EBSCOHost, IEEE Xplore, ScienceDirect and ACM Digital Library, or captured through snowballing in OpenAlex, ResearchGate and Google Scholar. Reviews were included if they synthesised applications of AI solely in formal higher or continuing education, were published in English between 2018 and July 2023, were journal articles or full conference papers, and if they had a method section 66 publications were included for data extraction and synthesis in EPPI Reviewer, which were predominantly systematic reviews (66.7%), published by authors from North America (27.3%), conducted in teams (89.4%) in mostly domestic-only collaborations (71.2%). Findings show that these reviews mostly focused on AIHEd generally (47.0%) or Profiling and Prediction (28.8%) as thematic foci, however key findings indicated a predominance of the use of Adaptive Systems and Personalisation in higher education. Research gaps identified suggest a need for greater ethical, methodological, and contextual considerations within future research, alongside interdisciplinary approaches to AIHEd application. Suggestions are provided to guide future primary and secondary research.

Research informing adult education teachers' didactic practices in distance education is scarce. Approaching the adult learner's perspectives on how distance education is perceived is key to informing future initiatives. This study explores adult learners' perception of distance education, concentrating on aspects such as, social presence, course structure, and perceived learning and satisfaction. A survey was distributed to teachers (n = 78) in five schools organising adult distance education. Findings show that teacher accessibility and course structure correlated positively with social presence and perceived learning and satisfaction. Overall, adult learners are satisfied with their distance teaching. A challenge facing adult distance education is to create a sense of social presence despite the high demand for flexibility. Thus, we explored learner perceptions of benefits and challenges in distance education and structured these into social, cognitive, spatio-temporal, emotional, and technical dimensions. Findings reveal that one challenge in the social dimension was a lack of connection with peers, and a benefit in the cognitive dimension referred to autonomy and self-regulation. These findings are important as educational institutions and policymakers may strive for high flexibility, which in turn may lead to lower group cohesion and a lack of social presence.

Children with cancer experience recurring hospitalizations and isolation during treatment, which affect their school attendance. This study explores experiences of children with cancer, their classmates, and teachers with using the telepresence robot as a learning mediator in the hybrid classroom during treatment periods. 31 children with cancer (aged 7–17 years), 30 teachers, and 118 classmates participated in interviews and 19 h of participant observations were undertaken in nine classrooms. The Agential Realism Theory and Situational Analysis framed the data analysis. There was a single overarching theme, “Telepresence robot didactic,“ and five sub-themes (Telepresence mediated learning, school-home collaboration, hybrid robot teaching, intra-actions in class, and inclusive spatiality). This study advocates the complexity of telepresence robot didactics, emphasizing that numerous human and other factors must intra-act and work simultaneously to achieve optimal learning conditions for children during cancer treatment. This includes considerations such as modality availability for the remote child; the teacher’s understanding of telepresence robot didactic and hybrid learning; the classmate’s ability to involve the remote child in groupwork; the child’s own treatment protocol, the robot’s functionalities, and spatiality in the class. Strategies for use and the systematic surveillance of telepresence robots are needed to ensure that children during cancer treatment do not lag in academic achievement. This study proposes that children with cancer can continue participating in class while hospitalized or isolated and consequently reduce social and academic setbacks.

Student well-being is important for inclusive societies and academic achievement. As studies have shown, well-being is associated with school success. Today, it's common for schools to use different technologies to collect and analyse digital data with the purpose of improving educational outcomes. Generally, this collected data focus on student engagement, attendance, and results, with novel advancements being aimed at supporting student well-being. In this pilot study, we analyse teachers' experiences to identify benefits and challenges during a spearhead integration of a data-driven tool for examining student well-being in upper secondary school. Using thematic analysis of teacher interview transcripts, we identified four themes: insight diversity, caring pedagogies, teacher leadership tools, and faculty transformation. The themes are discussed using the theoretical perspectives of orchestration, practice, process, and actors. Key results show that some high-value benefits teachers report on are gaining insights, saving time, and informing decision-making. The challenges include a lack of systematisation, guidance, and resources, and tensions related to defining the role and responsibilities of a teacher or mentor. We conclude that schools that work to support student well-being can benefit from the diversity of insights and practices related to the presented tool. However, an informed and systematic approach would be needed to leverage the benefit of spearhead integration. The contribution of the study is to provide insights on how a well-being tool can be used in an educational context to bring understanding of student well-being to teachers. Our results may inform decisions and guide integration and implementation practices in schools.