Proofing

This study examined how preservice teachers experience the transition from traditional to AI-assisted lesson planning in integrated mathematics and science education. Grounded in the technological pedagogical content knowledge framework, the Technology Acceptance Model, and Activity Theory, the study addressed two research questions concerning the transition process and factors influencing adoption. Thirty-four elementary preservice teachers completed a structured sequence of traditional and AI-assisted lesson planning using the 5E instructional model. Participants’ structured written reflections were analyzed using reflexive thematic analysis. Three themes were identified: (a) AI integration transformed professional practice, shifting participants from “content deliverers” to “learning facilitators”; (b) AI facilitated cross-curricular integration, though authentic connections required professional judgment; (c) AI’s differentiation capabilities required systematic quality assurance grounded in Critical AI Literacy. Findings suggest, from participants’ perspectives, AI integration has the potential to augment rather than replace human expertise, positioning human-AI collaboration as essential to realizing technology’s potential while preserving the fundamentally human core of mathematics and science teaching.

The discourse around technology in education over the past 2 decades has centered on the issue of barriers to explain why so few teachers continue to use technology in pedagogically transformative ways. Today, that discourse has been inverted by the outcry of overuse of technology in American schools leading to learning loss and teen mental health issues. Drawing on data collected in fall 2019 — on the eve of the COVID-19 pandemic and the arrival of generative AI — this study used video-cued multivocal ethnographic methods to reframe the discussion of technology in schools by attending to the new literacies practices of two secondary English teachers and how their personal engagement with technology shaped their classroom pedagogies. Findings revealed shared commitments from both participants: mentors who model innovative practice, social media as professional community, protocols that anticipate technology failure, and deliberate balance between digital and analog technologies. A theory of “teachers who tech” is developed to explain how personal and professional uses of technology informed pedagogical decisions related to English content. Implications consider what teachers who tech offer schools now working under district-mandated ed tech, including AI platforms, and how teacher preparation programs might support the “making” of teachers who tech.

Developing instructional materials is a cornerstone of teacher education, enabling future educators to translate pedagogical concepts into practical learning experiences. A quasi-experimental study evaluated preservice science teachers’ computational thinking (CT) skills and educational technology standards self-efficacy (ETSSE) in relation to a 14-week augmented reality (AR) material development process. Sixty-two preservice science teachers participated, comparing an experimental group designing AR-based materials using Unity and Vuforia with a control group developing traditional instructional materials (non-AR) on identical content. Within-group analyses revealed statistically significant pre-to-posttest gains in CT and ETSSE across both conditions. However, ANCOVA comparisons controlling for baseline scores indicated no statistically significant between-group differences, with post hoc sensitivity analysis suggesting the design was constrained to detecting medium to large effect sizes. In short, both 14-week interventions were associated with statistically significant pre-to-posttest gains in the investigated skills, though no significant difference was observed between the groups. Overall, engaging in structured, hands-on instructional material design was accompanied by improvements in technological self-efficacy and computational thinking, regardless of the specific technology employed, though a distinct AR-specific effect remains unisolated.