This study investigates how three language teachers with diverse instructional backgrounds, professional experiences, and levels of familiarity with generative artificial intelligence (GenAI) integrated GenAI, particularly ChatGPT as a conversational tool to support oral practice, into speaking instruction in a community-based English language program. Using a multiple-case design, the study examines how teachers planned and implemented GenAI-supported speaking activities and how their pedagogical beliefs, prior experiences, and technological confidence shaped their instructional decisions. Findings reveal three distinct facilitation profiles: Strategic Facilitator who used GenAI to redistribute attention across learners with different proficiency levels; Progressive Integrator who customized prompts and designed interactive GenAI-driven tasks; and Technology Adapter who gradually incorporated GenAI to support structured speaking practice. Despite these differences, teachers continued to draw on core practices of traditional language instruction, such as modeling, monitoring, and emotional support; however, these practices were reconfigured as teachers actively shaped and mediated GenAI-supported interaction, with GenAI automating aspects of conversational scaffolding and allowing teachers to focus more on facilitating student interaction. Across cases, variations in teachers’ experiences as language learners and teachers, as well as their levels of familiarity with GenAI, also informed their classroom practices. These findings suggest that reflective professional development that integrates both pedagogical and technological dimensions may support teachers in adapting GenAI to their instructional goals, especially for those with limited prior experience with such tools. The findings call for future research on long-term teacher learning, student outcomes in GenAI-enhanced classrooms, and instructional designs that advance beyond simple augmentation in language education.

Self-regulated learning is essential in online environments, where learners must manage large amounts of information, resulting in increased cognitive load and reduced task performance. While metacognitive prompts can support self-reflection and self-management, their classroom integration remains challenging. Recent advancements in generative AI, such as customised ChatGPT, provide new opportunities for more practical integration. To explore this potential, we conducted a study with 40 South Korean university students randomly assigned to either an experimental or a comparison group. All participants watched Python programming video lectures and completed problem-solving tasks using ChatGPT, but only the experimental group received metacognitive prompts. Cognitive load and self-efficacy were assessed through self-reported surveys, and task performance was evaluated based on problem-solving processes, outcomes, and retention tests. The results revealed significant group differences in problem-solving processes, with the experimental group showing a tendency towards lower cognitive load, higher self-efficacy, and improved task performance.

Since the introduction of ChatGPT’s voice functionality, new research opportunities in speaking activities have emerged. This exploratory qualitative study investigates the perceptions of English language learners (ELLs) on the use of generative artificial intelligence (GenAI), particularly ChatGPT, in speaking classes. A focus group interview with six ELLs indicated that their initial curiosity and skepticism about ChatGPT shifted to recognizing its usefulness for ongoing language practice. Additionally, learners differentiated the roles of ChatGPT from human teachers, appreciating its constant availability as a practice tool while noting its inability to replace the motivational support and facilitation of human teachers. Factors influencing their experiences included the relevance of ChatGPT-assisted activities to their daily lives, teachers’ pedagogical approach, teachers’ technological comfort, and challenges like practice time and targetedness of questions. The study outlines new directions for future research on its scalability and potential long-term impacts across different proficiency levels in various educational contexts.

This study explores how elementary teachers interact with generative AI in student-centered lesson design, comparing differences by teaching experience and AI proficiency. Ten teachers' interactions with AI were analyzed using CORDTRA diagrams, revealing seven patterns: direct adoption, elaborated adoption, initial rejection, revised adoption, follow-up guided use, complex interaction, and bypassing AI. Experienced and proficient teachers critically adapted AI responses to classroom contexts, while less experienced or low-proficiency teachers relied more on AI's suggestions. The findings emphasize the need for differentiated support to foster teachers' effective and reflective use of AI in promoting student-centered learning.

Despite the growing interest in using Virtual Reality (VR) for educational purposes, few studies have explored the connection between empathy and situational interest in the context of VR-supported history education. This study explored the relationship between empathy and situational interest in a history learning VR task. We recruited 49 undergraduate and graduate students to watch a 5-min VR movie, Defying the Nazi , from Life VR. Following, participants completed a survey battery capturing their empathy and situational interest. We employed multidimensional scaling to reveal nuanced relationships between the constructs. Overall, we found a strong relationship between empathy and situational interest following the VR historical empathy task, with an emphasis on emotional engagement. Our findings suggest that emotional engagement plays a crucial role in sustaining student interest and supporting learning outcomes in VR history learning environments, highlighting the importance of designing VR experiences that foster empathy and situational interest to enhance the efficacy of history education.

In an online environment, learners control various factors related to learning. However, a closer examination is necessary to identify the factors that impact their sense of control within online learning. This study aims to explore the factors that constitute learners’ sense of control in online classes and to develop a tool for measuring this construct. To achieve this, we prepared a structured questionnaire to identify the elements that learners believe they can control. Written interviews were conducted with 53 participants via an online platform. Through analysis of the responses, we extracted and categorized the elements that informed the development of a preliminary draft of the measurement tool. After refining and validating the draft, the main survey was conducted with 506 participants. The data were analyzed using content analysis, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA). The findings revealed that learners’ sense of control in online classes could be broadly categorized into two domains: class activities and environment. Within class activities, factors related to course delivery, attitude, and participation were identified, whereas the class environment encompassed factors such as time, space, and media. The measurement tool was developed based on these factors, including specifics such as sequencing, feedback provision, group activities, and device accessibility. Both EFA and CFA were conducted to validate the tool, and the final version was confirmed. This study is significant as it highlights learners’ sense of control as a crucial psychological factor in online learning, which instructors should consider when designing online learning experiences.

Given the importance of self-regulated learning (SRL) in flipped learning in higher education, this study explored the role of a mobile-based artificial intelligence (AI) chatbot in enhancing SRL among university students enrolled in a flipped business course. The chatbot supported students by providing SRL prompts in the forethought, performance, and reflection phases. An explanatory sequential mixed-methods design was employed to examine the effectiveness of the chatbot and students' conversation patterns. Survey data from 43 participants revealed that low prior-SRL students significantly benefited from chatbot interaction, while high prior-SRL students surprisingly exhibited a decrease in their SRL scores. Qualitative analysis of extreme cases revealed evident differences in interaction patterns between students whose SRL scores decreased and increased after chatbot use. The findings contribute valuable insights to the expanding field of mobile-based AI chatbots in flipped learning and emphasize the importance of adaptive and personalized interventions for students according to their prior SRL skills.

This study investigated the usage of conversational artificial intelligence (CAI) to support learners in foreign language classrooms. It employed Google Assistant and focused on the interactions between the teacher, learners, and CAI, as well as the teacher's collaboration with CAI. Using social network and content analyses of two 50-minute language classes and group interviews, this study revealed that the teacher and CAI played a significant role during classroom interactions. The teacher employed various talk moves to facilitate interactions between the students and CAI. There were several instances of collaboration between the teacher and CAI during classroom facilitation. This study highlights the implications of the collaboration between human teachers and CAI in classrooms for teaching foreign languages and suggests avenues for future research.

Design thinking and virtual reality continue to infiltrate the K-12 landscape, with incredible promise for fostering deeper engagement with content. Design thinking in particular embodies maker education’s beliefs in learning through building, but with the added caveat of solving real-world problems with the consideration of others’ perspectives. For leveraging the benefits of design thinking, understanding the perspective of the other person can be crucial. In this phenomenological study, thirteen high school students participated in a Design Thinking class which used two different media— one immersive virtual reality video, and one non-immersive traditional documentary— as a means to kickstart the design thinking process. Results showed that the traditional documentary allowed students to brainstorm problems to solve, while a more immersive media evoked stronger feelings in students and prompted more action; both media appear to help gain perspective. This research provides implications on how media immersion influences problem solving with design thinking.

This exploratory case study investigates student interaction patterns and teacher facilitation in an artificial intelligence (AI)-integrated foreign language learning classroom. The study focuses on small-group activities using Google Assistant as a conversational AI system. Six adult learners in two groups interacted with Google Assistant in a 50-minute English-speaking class facilitated by a teacher. Social network analysis was employed to examine the overall interaction patterns and showed that an intelligent personal assistant and a teacher played central roles in classroom interactions. Community detection analysis also revealed distinct communities formed within the network. Qualitative analysis revealed more prominent peer support in Group B where community was formed among students and more frequent teacher facilitation in Group A during a small group activity where community was not detected. The findings suggest that language teachers must consider learners’ attitudes, prior experiences, and perceptions when integrating AI technologies into language classrooms to provide effective guidance and support.

This report describes the use of electroencephalography (EEG) to collect online learners' physiological information. Recent technological advancements allow the unobtrusive collection of live neurosignals while learners are engaged in online activities. In the context of multimodal learning analytics, we discuss the potential use of this new technology for collecting accurate information on learners' concentration levels. When combined with other learner data, neural data can be used to analyze and predict self-regulated behaviors during online learning. We further suggest the use of machine learning algorithms to provide optimal live neurofeedback to train online learners' brains to improve their self-regulated learning behaviors. The challenges of EEG and neurofeedback in online educational settings are also discussed.

Despite the increasing use of conversational artificial intelligence (AI) in language learning, few studies explored how to develop collaborative partnership between AIs and humans. This systematic review examines empirical evidence of human-computer collaboration from 24 studies conducted in an AI-integrated language learning environment and published between 2015 and 2021. The roles of conversational AIs and teachers in each language learning phase with challenges of and suggestions for conversational AI-integrated language learning were identified. Although limited evidence for collaboration between conversational AIs and human teachers was found, future language education should integrate conversational AIs to promote intelligence amplification and decrease human teachers' workload through classroom orchestration. The study concludes with guidelines and recommendations for teachers and AI researchers.

Historical empathy may be enhanced by virtual reality (VR) technologies, which provide varying degrees of immersion into other time periods and places. This study explored the effects of combining semi-immersive and fully immersive VR with a follow-up writing task to promote historical empathy with adult learners. Thirty-six participants were randomly assigned to view a brief historical film on either a flatscreen or a head-mounted device (HMD). Afterward, participants were again randomly assigned to either a first-person perspective or a factual recall writing prompt before then responding to questionnaires gauging their situational interest. Quantitative and qualitative data were analyzed to provide a holistic interpretation of participants' development of historical empathy. Results suggest that although type of writing task remains instrumental in promoting historical empathy, immersive VR with an HMD also plays a promising role. Our findings pose important implications for post-secondary, museum, and teacher educators interested in scaffolding VR experiences to promote historical empathy.

Despite the common and growing use of and instruction on digital reading in schools, the ways in which reading comprehension may operate differently in paper and online environments are still underexplored. Using publicly available national datasets, we explore similarities and differences in how varied comprehension processes relate to each other in these spaces. Analyses using a Bayesian unidimensional graded response model found that paper-based reading performance involved hierarchical comprehension processes consistent with traditional theories of reading comprehension while digital hypermedia reading did not involve these same processes. This research provides usable knowledge for supporting researchers, and teachers in uncovering the unique educational benefits and challenges of online reading.

Background Immersive VR is still rarely used as an intervention for meeting the affective end goals of student learning despite its positive impact on affection. Also, studies regarding the use of immersive VR as an intervention for affective achievement in broader educational contexts are still lacking. Objectives: This study aimed to examine the effect of immersive VR and perspective-taking on presence and empathy. Methods A total of 148 pre-service teachers participated in experiments, using either a head-mounted display or a flat screen device to view two VR videos with different perspective-taking affordances. This study used a mixed design with one between-subject variable of immersion level and one within-subject variable of perspective-taking to explore how immersive VR experiences influenced participants' perceived level of presence and empathy. Results and Conclusions The results showed that the level of immersion affects perceived presence, but it was the type of perspective-taking that affects empathetic reactions. We also found an interaction effect between immersion levels and perspective-taking. The direct embodiment in VR combined with high immersion produced stronger empathy than with low immersion, while the perspective of an observer was better in evoking empathy when experienced with low immersion. Implications This study gives a guidance on how to take advantage of this new technology in educational settings, and apply it to instructional activities to enhance students' empathy. In addition, it could serve as a reference when developing or introducing educational contents with respect to the types of contents that are more effective in educational settings.