Abstract Teacher education students play double role as present learners and future educators. Hence, they need targeted training to navigate the growing influence of Generative Artificial Intelligence (GenAI) on teaching, learning and professional identity. However, existing artificial intelligence (AI) literacy programmes predominantly emphasize technical AI knowledge and pre‐GenAI tools or are offered by GenAI platforms that focus on their own technologies' features, thereby lacking pedagogically structured frameworks that address non‐technical dimensions such as ethics, contextual understanding and the development of human‐centered, critical and lifelong learning mindsets to adapt to rapid technology changes. Furthermore, limitation of time in teacher education syllabus and faculty's lack of AI literacy require targeted intervention. This design‐based research (DBR) aims to fill this gap by developing and evaluating a set of design principles for GenAI literacy training in teacher education. Integrating contemporary AI competency frameworks for learners and teachers, the study implements these principles in a workshop that serves as the research prototype. The prototype was first piloted with 14 master's students and then evaluated with 29 teacher education (TE) students. Results show significant gains in participants' AI competence self‐efficacy, attitudes towards GenAI and commitment to critical, ethical and pedagogical engagement with GenAI tools. The findings highlight the need for teacher education programmes to integrate GenAI literacy that supports teachers' evolving roles as reflective practitioners, co‐creators and lifelong learners in an AI‐driven world. Practitioner notes What is already known about this topic Students' self‐efficacy and mindset influence their adoption of GenAI in learning and teaching. GenAI competency is essential for teacher education students, encompassing technological, ethical and sociocultural dimensions. Implementing AI literacy training faces challenges such as educators' limited AI literacy, the lack of pedagogical frameworks and the need to integrate technical knowledge with ethical reasoning, self‐regulated learning and metacognitive skills. Transformative learning is crucial in preparing teacher education students as co‐creators and facilitators in AI‐enhanced education. What this paper adds This study presents the design and evaluation of an AI competency training programme to enhance teacher education students' self‐efficacy, critical and human‐centered AI mindsets and human–AI interaction skills. Using design‐based research, it identifies key principles for AI literacy training, demonstrating how transformative, active and experiential learning approaches can prepare teacher education students for evolving roles in AI‐enhanced education. Implications for practice and/or policy Educational technologists can apply the proposed design principles to develop GenAI tools and AI systems that enhance AI competency and self‐regulated learning (SRL). Educators can integrate these AI training principles into their teaching strategies and enhance their task assignments and assessments to foster deep learning, self‐regulated learning and metacognitive skills in the age of GenAI. Policymakers should update teacher education curriculum to include AI competency, strengthen content and pedagogical knowledge, especially in social emotional learning, formative and authentic assessment methods and establish guidelines for selecting GenAI tools that support human intelligence and mitigate over‐reliance.

Abstract Despite increasing interest in using Generative Artificial Intelligence (GenAI) in education, little is known about how students with disability engage with GenAI to support their own learning. This study investigates the potential of ChatGPT to support the learning agency of adolescents with disability in a secondary science classroom in Australia. Guided by sociocultural and socio‐material conceptualisations of agency, the study explored the mediated choices and capabilities of three students with disability to use ChatGPT to facilitate their learning. The study was conducted in a class comprising students of varying ages clinically diagnosed with diverse learning needs. Data sources included student interviews, the students' conversations with ChatGPT, teachers' lesson worksheets and video recordings of the lesson. Thematic analyses reveal that while students expressed clear and meaningful choices to use ChatGPT to support their learning, they faced metacognitive challenges and cognitive constraints, resulting in a misalignment between their choices and actual capability. The findings identify key theoretical perspectives and practical considerations for supporting students with disability in using GenAI to develop their learning agency. The study recommends customising GenAI for specific learning needs in line with its function as a cognitive prosthesis for students with disability and for better alignment with Universal Design for Learning, thereby supporting students' learning agency. Practitioner notes What is already known about this topic The development of students' learning agency has been widely explored in the secondary context, but not for students with disability. There is increasing interest in using Generative AI (GenAI) to support inclusive education. Current theoretical frameworks can inform the exploration of the learning agency of students with disability using GenAI. What this paper adds Foregrounds the learning choices of students with disability as indicators of their emergent learning agency. Identifies learning challenges facing students with disability that misalign their learning choices and capabilities. Examines GenAI's potential as a socio‐material mediator facilitating the material and relational agency of students with disability. Implications for practice and/or policy Consulting students with disability on how GenAI can support their learning, providing opportunities for them to express their learning preferences. Customising GenAI tools in line with the Universal Design for Learning guidelines to address the specific learning challenges of students with disability. Clarifying the roles of teachers and education assistants in facilitating the learning agency of students with disability in light of customising GenAI to mediate their learning agency.

Abstract This study explored the impact of high‐immersion virtual reality (VR) as an innovative andragogical tool in undergraduate biology education. Amidst concerns about traditional lecture‐based teaching methods, VR can offer interactive hands‐on experiences. The study hypothesized that students who opt in for a supplementary VR experience will outperform the students presented with text‐based lectures and the students presented with video‐assisted content in content‐related quizzes and assignments. The study involved 456 students of an undergraduate contemporary biology course. Three conditions were presented over four semesters: a VR activity focused on teaching genetics and Punnett squares that supplemented a video lecture, video lecture only and long‐form text‐based materials only. Pre‐ and post‐VR activity tests were conducted to assess knowledge gains and perceptions of the VR experience of the 49 students who chose the additional VR experience. Results suggest significant improvements in the immediate content‐related post‐test scores, delivered in multiple‐choice format. A significant difference was observed in the mean scores of the genetics module assignments (delivered in long‐form text format) among the three groups (ie, VR‐and‐video‐assisted group; video‐assisted group; text‐only materials group). The text‐only group scored the lowest, while the video‐and‐VR‐assisted group scored the highest, but only marginally higher than the video‐assisted group. The results suggest that VR provides a viable, scalable and cost‐effective complement to traditional laboratory practice. Rather than outperforming lecture‐based approaches, VR offers an accessible way to practical experiences that would otherwise require specialized facilities or costly equipment. Our findings provide a baseline and highlight a need for further research to investigate the full potential and limitations of integrating VR in biology education. Practitioner notes What is already known about this topic Virtual reality (VR) has emerged as an increasingly viable method of engaging users in educational experiences. VR as a medium can engage users in ways traditional media struggle to achieve, such as fostering empathy and delivering immersive experiences. Hands‐on learning opportunities remain highly relevant to STEM education, an area highly appropriate for exploration in VR. VR has gained considerable traction in biology education. What this paper adds Evidence for the integration of VR into a high‐enrollment, accredited curriculum implemented in a naturalistic, ecologically valid context. A comparison of VR‐assisted biology lessons with more traditional, video‐ or text‐based lecture in high‐enrollment undergraduate courses. VR experiences may be more beneficial than lecture‐based instruction for complex topics in undergraduate education. Implications for practice and/or policy VR is particularly useful in addressing typically challenging learning concepts. The integration of VR technology with large‐enrollment undergraduate courses is possible. The availability of VR experiences and equipment remains necessary for the successful integration of VR.

Abstract Self‐regulated learning (SRL) is an active process involving multiple interacting components that evolve over time, exhibiting characteristics of complex systems such as non‐linearity, emergent behaviour, self‐organization, and hierarchy. These interactions unfold at different temporal levels, each warranting a dedicated lens to capture their distinct dynamics. In this study, we apply a complex dynamic systems lens to analyse the longitudinal dynamics of SRL. We map how different SRL processes interact with each other across time and scales: (1) the stable between‐person level, which represents the dominant approach to learning or roughly the trait of SRL, (2) the contemporaneous level, which maps how SRL processes influence each other within the same time and (3) the temporal level, which captures how processes predict or influence each other in the future. Data were collected through a weekly survey administered over 4 weeks in five courses at two institutions, complemented by LMS behavioural engagement data. A panel vector autoregression model was employed to examine the structure and dynamics of SRL and LMS behavioural engagement at the three levels. The findings suggest that central SRL processes, such as planning and adapting, take place in separate stages, in accordance with the classic SRL models, whereas other processes, like effort regulation, are more pervasive, co‐occurring with most other regulatory processes. At the aggregate level, adjusting was the most central process that drove students' SRL. As such, our results align with the main characteristics of complex systems, including non‐linearity and hierarchy. These findings have implications for the design of SRL interventions, where effort can benefit from real‐time prompts, whereas metacognitive processes might require long‐term scaffolding. Furthermore, the weak association between LMS engagement and SRL processes across all levels highlights the limitations of relying solely on behavioural trace data to infer regulation. Practitioner notes What is already known about this topic? Self‐regulated learning (SRL) is an important driver of academic success and can be influenced through targeted interventions. Most SRL research is based on group‐level data, often using static, cross‐sectional designs that overlook temporal dynamics. Recent work has highlighted that SRL can and should be modelled as a complex dynamic system. What this paper adds? There is evidence of complex systems characteristics in SRL such as hierarchy, non‐linearity and feedback loops. SRL processes follow distinct temporal phases, with some processes persisting throughout all phases. Metacognition is the most central process at the between‐person level, whereas effort is central at the within‐person level. LMS behavioural data is weakly linked to self‐reported SRL. Implications for practice and/or policy SRL interventions should consider how regulatory processes unfold over time, rather than treating SRL as a static trait. Interventions targeting effort regulation and metacognition have the potential to be the most consequential. Caution must be exerted when using average or between‐person data to inform individualized support. LMS metrics should be interpreted with care and ideally complemented by self‐report or observational data.

Generative AI presents a profound challenge to the existing structures and purposes of education. It forces us to reconsider not only how we teach and learn but also, more fundamentally, what education is for. This conceptual paper argues that, in order to integrate AI into education in a way that can meet the major challenges facing humanity, ranging from ecological crisis to the future of democratic societies, we must reframe education. Drawing on the nature and potential of generative AI in conjunction with educational theory, we propose a double dialogic pedagogy that recognises education as both teaching thinking through dialogue and inducting students into participation in the long‐term powerful dialogues of culture. We relate this double dialogic pedagogy with AI to education for collective intelligence. This pedagogy positions AI not as a replacement for human thinking, but as a partner in expanding the space of dialogue. By articulating this theoretical foundation, we offer a basis for the future design of educational practices and technologies that can support human flourishing in an age of accelerating technological change. Practitioner notes What is already known about this topic The rise of generative AI, particularly large language models, poses both opportunities and challenges for education. While existing research highlights AI's potential to support personalised learning through intelligent tutoring systems, concerns remain about its possible negative impact on students' critical and creative thinking. Previous studies have also noted the need for educational theory to keep pace with technological developments, yet little work has been done to articulate a pedagogical framework that addresses the broader societal and environmental challenges of the AI era. What this paper adds This paper proposes a double dialogic pedagogy as a theoretical foundation for integrating AI into educational design. It situates current developments in AI within a historical and philosophical context, drawing on dialogic theory and the concept of the pharmakon to argue that AI is neither inherently beneficial nor harmful, but depends on pedagogical framing. The paper advances the field by explicitly linking AI‐supported learning to education for collective intelligence, offering concrete illustrations of how AI can support both dialogic learning and induction into long‐term cultural dialogues. Implications for practice and/or policy This paper suggests that educational practice should shift from focusing on individual knowledge acquisition towards cultivating collective intelligence through dialogic pedagogy. Policymakers and educators are encouraged to design AI‐supported learning environments that promote collaborative problem‐solving and critical engagement with real‐world challenges, such as those posed by the Anthropocene. Assessment policies should be re‐evaluated to reward collaborative inquiry and ethical reasoning, rather than individual content reproduction. This reconceptualisation positions education as a key enabler of planetary‐level self‐regulation and human flourishing in the face of technological and environmental disruptions.

This paper explores the use of a shared tablet within the context of collaborative learning among a teacher and upper‐secondary students (aged 16–17). We analyse how various resources are mobilised for joint meaning making. Drawing on video‐recorded episodes, this qualitative case study shows how human and digital resources emerge when students collaboratively make meaning of body‐related concepts using a shared tablet and how these resources support learning. The findings identify seven types of resources that were used when making meaning of body concepts while interacting with an application related to muscles and kinesiology. These resources include: 3D visualisations, students' prior knowledge, personal narratives, instructional video, the app's side menu, tactile functionalities and bodily representations. This paper offers insights for designing collaborative learning instructions involving tablets to support the co‐creation of meaning in small groups. Practitioner notes What is already known about this topic Extensive research has indicated that the use of shared tablets can support collaborative learning when students take active roles, benefit from access to resources and develop problem‐solving skills by interacting with learning materials. Although there is a growing recognition that tablets can engage students in deep cognitive processes—such as analysing, evaluating and creating—current research has not yet explored how students mobilise and simultaneously use human and digital resources for joint meaning making. What this paper adds 3D visualisations displayed on a shared tablet play a crucial role in interpreting abstract concepts such as body injuries, thereby facilitating meaning making among students. Yet, students still need to mobilise additional resources for interpretation and learning. By analysing three video interactional episodes, this case study shows how resources emerge when students collaboratively make meaning of body‐related concepts using a shared tablet and how these resources support learning. The findings identify seven types of resources that served to support student learning: 3D visualisations, students' prior knowledge, personal narratives, instructional video, the app's side menu, tactile functionalities and bodily representations. Implications for practice and pedagogy The study offers educational implications regarding collaborative learning and co‐creation of meaning in students' small group involving a shared tablet. It sheds light on the design of tablet‐mediated learning instructions and the need to consider tasks that engage problem‐solving and dialogical pedagogies, allowing for interactive discussions and the co‐creation of meaning. Teachers should give attention to the multiple resources at play in such learning settings and be sensitive to how they are combined when students engage in making meaning together. This sensitivity would enable teachers to use such resources to guide students' reasoning and engagement.

Abstract Social presence has been hypothesized to facilitate successful learning in digital and online learning environments. Instructor presence in instructional videos is suggested to enhance learners' social presence. However, research is still relatively rare regarding the elementary school learner population. The current experimental study investigated whether embedding an animated human‐like artificial pedagogical agent in an instructional video compared to having only a voice could evoke a sense of social presence and improve learning in a sample of primary school learners. The study confirmed that a sense of social presence of a virtual instructor can be fostered through a digital animated pedagogical agent; however, there was no effect on learning performance, nor did social presence mediate a relationship between learning with a pedagogical agent and learning performance.