This article explores emerging epistemic practices when students engage with generative AI tools as cognitive partners. Such partnerships enable students to accomplish tasks they could not complete without technological support and transform how they learn. Drawing on focus group interviews from a one-year action and design-based research project, this qualitative study identifies epistemic practices of reflective thought arising from students' process-oriented engagement with AI. Notably, theoretical and empirical reflection appear through cognitive partnerships with AI. The article offers insights for teachers on how to scaffold these practices and support students in realizing the potential of AI as a cognitive partner. An implication for educational practice is not to ban AI but to cultivate students' abilities to engage with AI as instruments for reflective thought.
This design-based research study examines how the Go-Show-Flow-Glow (GSFG) framework supports elementary students' engagement with ISTE Standards for Students through participatory game design. Twenty-three third-grade students designed educational games about the Dust Bowl during a five-day implementation. Thematic analysis of 540 coded instances revealed differential engagement across ISTE Standards: Innovative Designer dominated (34%), followed by Knowledge Constructor (16%) and Creative Communicator (14%), while Digital Citizen received minimal attention (<1%). Findings indicate structured classroom design, such as the GSFG framework, can support standards-based learning while maintaining student agency, contributing empirical evidence that design constraints scaffold rather than limit elementary students' creative engagement.
This study investigates the instructional roles teachers perceive and enact when integrating immersive virtual technologies in K-12 classrooms, comparing low-immersive desktop VR (DVR), immersive rooms (IR), and fully immersive virtual reality (VR). Drawing on 31 teacher interviews and 42 classroom observations, teacher degree of centrality was analyzed using the teacher prototypes framework (sage, facilitator, guide, partner). Three case studies combined with quantitative comparisons revealed distinct patterns: DVR uniquely supported partner roles; IR emphasized structured facilitation; and VR positioned teachers as sages, contrasting with their self-perception as facilitators or guides. Findings highlight both alignment and gaps between teachers' pedagogical beliefs and practices, shaped by immersion levels and technological constraints. Supporting teachers through professional development is essential for creating immersive environments that enable student-centered practices and flexible instructional roles.
This study aims to examine the structural relationships of GitHub Copilot AI-powered programming education with students' AI literacy, metacognitive awareness, satisfaction, learning strategies, and self-regulation skills. The research was carried out with the participation of 167 undergraduate students and AI literacy, metacognitive awareness, satisfaction, learning strategies, and self-regulation skills scales were used in the data collection process. The analyses conducted using structural equation modeling revealed that learning strategies positively influenced both metacognitive awareness and self-regulation skills. It was determined that metacognitive awareness significantly enhanced AI literacy and satisfaction. Self-regulation skills were found to have a positive impact on both AI literacy and satisfaction. This study reveals that AI tools are not merely supportive instruments that facilitate code writing but also pedagogical components that reshape learning-processes.
This phenomenographic study identified six qualitatively distinct conceptions of GenAI-mediated learning among 15 Taiwanese undergraduates through interviews: (1) answer acquisition, (2) cognitive offloading, (3) future competency development, (4) question-driven exploration, (5) critical judgment engagement, and (6) collaborative creativity. Notably, "answer acquisition" emerged as the most common conception. These conceptions form a hierarchical spectrum, varying along dimensions of interaction mode with GenAI, perceived GenAI roles, and learner agency, and illustrate a progression from instrumental use toward collaborative knowledge construction. Understanding these variations could inform pedagogical strategies that encourage learners to move beyond surface-level engagement. Consequently, educators could promote deeper learning through critical reflection and collaborative co-construction, which are essential for supporting the responsible and transformative use of GenAI in educational contexts.
This study investigates how 299 Greek sixth graders (ages 11-12 years) visually represent artificial intelligence (AI) through draw-and-write methodology. Qualitative content analysis across five dimensions suggests students primarily depict AI as anthropomorphic robots (64%) or technological tools (28%). Attitudes ranged from positive (42%) to negative (16%), with ethical concerns. Most drawings (68%) lacked environmental context, and 81% showed no human interaction, indicating decontextualized conceptualization. Students attributed both superhuman capabilities and mundane tasks to AI. Findings suggest concrete yet multifaceted mental models merging functional, imaginative, and affective elements, providing insights for developing primary AI literacy programs addressing anthropomorphism, clarifying capabilities, incorporating ethics, and emphasizing real-world contexts.
The rapid emergence of generative artificial intelligence (GenAI) has introduced both opportunities and challenges for education systems worldwide. Educational stakeholders are grappling with fundamental questions of how to guide students on whether and when, and in what ways, they should use GenAI. In this study, a framework was developed to guide K-12 policies and guidelines on the use of GenAI. Using the Delphi technique and collective writing, expert perspectives were gathered from participants across 20 countries and six continents. The analysis identified eight key topic areas for K-12 GenAI policy and guideline development: (1) data privacy and security, (2) ethical and responsible use, (3) equitable access, (4) academic integrity, (5) human oversight, (6) GenAI literacy, (7) curriculum integration, and (8) governance and review. A complementary six-part framework was also constructed to support policy relevance and currency through multi-stakeholder governance, continuous review, ongoing training, awareness of external developments, outcome monitoring, and transparent communication. Together, these frameworks advance the scholarly and practical understanding of how GenAI policies can be designed and maintained in schools.
To understand three-dimensional modeling and printing (3DMP) technology, pre-service mathematics teachers (PMTs) need to experience it within their education program. This technology can be used to solve model-eliciting activities (MEAs). The present qualitative study aimed to investigate the challenges and opportunities of PMTs in integrating 3DMP while solving one MEA. To this end, the qualitative data-the researchers' field notes and the PMTs' written, digital, and physical work-were collected from 20 PMTs in a single session of the 3D printing in school course as part of a teacher education program in Austria. The results indicated that the participants encountered both challenges and opportunities concerning 3DMP and collaboration. These findings can provide insights into the use of 3DMP-integrated MEAs in mathematics education and teacher education.
Online learning has become a dominant mode of education in the digital era. However, students' low levels of motivation and engagement in online learning continue to undermine its effectiveness. It is important to identify the motivation and engagement components that are most critical and should be prioritized for intervention. Furthermore, the extent to which the critical motivation and engagement components differ across genders remains underexplored. Drawing on the Motivation and Engagement Wheel, this study employs network analysis to examine the central features of online learning motivation and engagement among 21,545 college students. Results indicated that the perceived value of online learning and task management were the most central components. This suggests that helping students realize the real-world value of what they are learning and scaffolding their ability to manage their tasks could be high-leverage intervention targets. Focusing on these constructs could have broader positive effects on other motivational factors. Notable gender differences also emerged. Enhancing self-belief was more important for females, whereas reducing uncertain control was more crucial for males. This study advances the literature by adopting a holistic, systems-oriented approach to understanding online motivation and engagement. It surfaces key gender differences that could help personalize interventions and highlights high-leverage targets for instructional design.
As generative AI (GenAI) becomes increasingly integrated in project-based learning (PjBL), understanding the dynamic student-AI collaboration is essential. This study employed an integrated data analysis framework (e.g., sequence analysis, process mining) to identify strategic collaboration patterns with GenAI among 40 undergraduates in a semester-long PjBL course. Three patterns emerged, each with unique characteristics. Pattern 1 (strategic balanced collaborator), associated with the highest performance, involved initial autonomous exploration followed by an "assistance-evaluation" loop, whereas pattern 3 (dependent support-seeker) showed reliance on direct assistance with the lowest performance. Findings suggest that GenAI's pedagogical value depends not on usage frequency but on the timing, quality, and intentionality of engagement, highlighting the need to cultivate relevant literacies that leverage GenAI while safeguarding core traits fundamental to meaningful PjBL.
This mixed-methods study reported how teaching core CS concepts through coordinated unplugged and plugged activities improved elementary students' coding performances. Through collaborative design with elementary teachers, we developed 14 activities focusing on data, conditional logic, and variables and implemented them with 13 fourth- and fifth-grade students in Spring 2025. Using a convergent mixed methods approach, we analyzed students' pre-, mid-, and post-test scores on a coding task and responses in cognitive interviews. Quantitative results revealed a statistically significant difference in coding performance from pretest to post-test. Meanwhile, qualitative findings revealed a progressive development in students' conceptual understanding.
Information and communication technologies (ICTs) encompass the use of digital tools including computers, mobile devices, online platforms, and interactive software for enhancing communication, learning, and productivity. Most studies focus on participation, communication, and learning experience, leaving a critical gap in understanding how intercultural constructs shape digital engagement and learning outcomes in multicultural ICT-mediated contexts. Many digital learning environments continue to reflect Western-centric assumptions about monochronic time management, communication patterns, and learner autonomy, which can marginalize students from high-context or polychronic cultural backgrounds. This systematic review examines three underrepresented cultural dimensions: Hall's high- and low-context communication styles, which explain differences in direct and indirect communication; polychronic-monochronic time orientations, which explain differences in flexible and linear approaches to time; and Hofstede's concept of power distance, which explains differences in expectations about authority and participation in ICT-supported higher education. The review seeks to identify the broader patterns through which these cultural factors influence access to information, digital literacy, communication, collaboration, and learning behavior in multicultural digital environments. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 22 relevant articles were retrieved from ProQuest, IEEE Xplore, ScienceDirect, Web of Science, and Google Scholar databases. The findings indicate that these cultural dimensions shape how students participate in ICT-supported learning, with many digital environments implicitly favoring low-context communication, monochronic time management, and low-power-distance interaction norms. This may place additional organizational and cognitive demands on students from other cultural orientations, although current evidence remains limited regarding whether culturally responsive adaptations improve academic performance as distinct from participation and learning experience.
