Teachers’ AI-TPACK: Exploring the Relationship between Knowledge Elements

Sustainability, Journal Year: 2024, Volume and Issue: 16(3), P. 978 - 978

Published: Jan. 23, 2024

The profound impact of artificial intelligence (AI) on the modes teaching and learning necessitates a reexamination interrelationships among technology, pedagogy, subject matter. Given this context, we endeavor to construct framework for integrating Technological Pedagogical Content Knowledge Artificial Intelligence Technology (Artificial Intelligence—Technological Knowledge, AI-TPACK) aimed at elucidating complex interrelations synergistic effects AI pedagogical methods, subject-specific content in field education. AI-TPACK comprises seven components: (PK), (CK), AI-Technological (AI-TK), (PCK), (AI-TCK), (AI-TPK), itself. We developed an effective structural equation modeling (SEM) approach explore relationships teachers’ knowledge elements through utilization exploratory factor analysis (EFA) confirmatory (CFA). result showed that six all serve as predictive factors variables. However, different varying levels explanatory power relation AI-TPACK. influence core (PK, CK, AI-TK) is indirect, mediated by composite (PCK, AI-TCK, AI-TPK), each playing unique roles. Non-technical have significantly lower teachers compared related technology. Notably, (C) diminishes PCK AI-TCK. This study investigates within its constituent elements. serves comprehensive guide large-scale assessment AI-TPACK, nuanced comprehension interplay contributes deeper understanding generative mechanisms underlying Such insights bear significant implications sustainable development era intelligence.

Language: Английский

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Enhancing teacher AI literacy and integration through different types of cases in teacher professional development

Computers and Education Open, Journal Year: 2024, Volume and Issue: 6, P. 100178 - 100178

Published: April 10, 2024

Integrating artificial intelligence (AI) into teaching practices is increasingly vital for preparing students a technology-centric future. This study examined the influence of case-based AI professional development (PD) program on integration strategies and literacy among seven middle school science teachers. Employing three distinct case problems, from well-structured to ill-structured, PD aimed stimulate teachers' reflection encourage construction problem-solving within various pedagogical contexts. Analysis video-recorded discussions revealed that teachers primarily drew personal experiences collaborative across cases. However, complexity problems influenced their approach knowledge co-construction, dealing with ill-structured promoted application new knowledge. Through analyzing survey data, we found marked increase in literacy, particularly domain knowing understanding AI, suggesting pivotal role direct instruction supports growth. this was limited during discussions, while other domains teacher were more frequently employed. The findings highlight importance combining AI-related programs bolster effectively. research has implications using learning short-term initiatives advocates ongoing need comprehensive facilitate subject-specific teaching.

Language: Английский

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Dual-contrast pedagogy for AI literacy in upper elementary schools

Learning and Instruction, Journal Year: 2024, Volume and Issue: 91, P. 101899 - 101899

Published: March 3, 2024

Language: Английский

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Exploring Factors That Support Pre-service Teachers’ Engagement in Learning Artificial Intelligence

Journal for STEM Education Research, Journal Year: 2024, Volume and Issue: unknown

Published: April 12, 2024

Abstract Artificial intelligence (AI) is becoming increasingly relevant, and students need to understand the concept. To design an effective AI program for schools, we find ways expose knowledge, provide learning opportunities, create engaging experiences. However, there a lack of trained teachers who can facilitate students’ learning, so focus on developing capacity pre-service teach AI. Since engagement known enhance it necessary explore how engage in This study aimed investigate teachers’ with after 4-week at university. Thirty-five participants took part reported their perception 7-factor scale. The factors assessed survey included (cognitive—critical thinking creativity, behavioral, social), attitude towards AI, anxiety readiness, self-transcendent goals, confidence We used structural equation modeling approach test relationships our hypothesized model using SmartPLS 4.0. results supported all hypotheses, attitude, anxiety, being found influence engagement. discuss findings consider implications practice policy.

Language: Английский

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Unpacking the role of AI ethics online education for science and engineering students

International Journal of STEM Education, Journal Year: 2024, Volume and Issue: 11(1)

Published: Aug. 2, 2024

Abstract Background As artificial intelligence (AI) technology rapidly advances, it becomes imperative to equip students with tools navigate through the many intricate ethical considerations surrounding its development and use. Despite growing recognition of this necessity, integration AI ethics into higher education curricula remains limited. This paucity highlights an urgent need for comprehensive initiatives in AI, particularly science engineering who are at forefront these innovations. Hence, research investigates role online explicit-reflective learning module fostering graduate students' knowledge, awareness, problem-solving skills. The study’s participants included 90 specializing diverse tracks. Employing embedded mixed-methods approach, data were collected from pre- post-intervention questionnaires closed-ended open-ended questions. Results study's results indicate that significantly enhanced knowledge ethics. Initially, exhibited a medium–high level perceived which saw modest but statistically significant enhancement following participation. Notably, more distinct increase was observed actual awareness issues before after intervention. Content analysis students’ responses questions revealed their ability identify articulate concerns relating privacy breaches, utilization flawed datasets, biased social representation. Moreover, while initially displayed limited abilities ethics, considerable competencies evident post-intervention. Conclusions study highlight important preparing future professionals skills necessary decision-making. placing emphasis not only on AI-related also capacity resolve perhaps mitigate impact such dilemmas.

Language: Английский

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Integrating generative artificial intelligence in K-12 education: Examining teachers’ preparedness, practices, and barriers

Computers and Education Artificial Intelligence, Journal Year: 2025, Volume and Issue: unknown, P. 100363 - 100363

Published: Jan. 1, 2025

Language: Английский

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STEM teachers' perceptions, familiarity, and support needs for integrating generative artificial intelligence in K‐12 education

School Science and Mathematics, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 28, 2025

Abstract We applied a mixed‐method survey approach to explore STEM teachers' perceptions, familiarity, and the support needed for integrating generative artificial intelligence (GenAI) in K‐12 education. The study collected 48 responses from Idaho, USA, predominantly White, female teachers servicing rural schools. analyzed data using both descriptive inferential statistics, along with thematic content analysis. findings revealed diverse perceptions among regarding impact of GenAI on education, an almost equal split between those who viewed positively it negatively. Similarly, familiarity integration varied widely, over half lacking user experience. A significant positive correlation was found their its integration. Despite these views, there strong consensus importance equipping students AI‐related knowledge skills. While professional development identified as most crucial integration, pointed own resistance lack awareness school leadership major challenges implementing GenAI‐focused development. discussed implications developing systems that can better facilitate

Language: Английский

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How Can Emerging Technologies Impact STEM Education?

Journal for STEM Education Research, Journal Year: 2023, Volume and Issue: 6(3), P. 375 - 384

Published: Nov. 16, 2023

Language: Английский

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Pre‐service teachers' inclination to integrate AI into STEM education: Analysis of influencing factors

British Journal of Educational Technology, Journal Year: 2024, Volume and Issue: 55(6), P. 2574 - 2596

Published: May 3, 2024

Abstract In the ever‐evolving AI‐driven education, integrating AI technologies into teaching practices has become increasingly imperative for aspiring STEM educators. Yet, there remains a dearth of studies exploring pre‐service teachers' readiness to incorporate their practices. This study examined factors influencing willingness integrate (WIAI), especially from perspective attitudes towards application in teaching. study, comprehensive survey was conducted among 239 teachers, examining influences and interconnectedness Technological Pedagogical Content Knowledge (TPACK), Perceived Usefulness (PU), Ease Use (PE), Self‐Efficacy (SE) on WIAI. Structural Equation Modeling (SEM) employed data analysis. The findings illuminated direct TPACK, PU, PE, SE TPACK found directly affect SE, while PE PU also influenced SE. Further analysis revealed significant mediating roles relationship between WIAI, highlighting presence chain mediation effect. light these insights, offers several recommendations promoting Practitioner notes What is already known about this topic? potential enrich learning experiences improve outcomes education been recognized. Pre‐service practice crucial shaping future environment. TAM frameworks are used analyse teacher technology‐supported environments. Few have context education. paper adds? A designed developed WIAI its relationships with including impact identified as variables Two sequential effects, → teachers were further identified. Implications and/or policy encouraged explore utilize technology enhance confidence self‐efficacy Showcasing successful cases practical essential fostering awareness integration It recommended introduce courses training programs. Offering internship practicum opportunities related can skills

Language: Английский

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Exploring the relationship between teachers’ competencies in AI-TPACK and digital proficiency

Education and Information Technologies, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 19, 2024

Abstract In recent years, there has been a growing emphasis on integrating Artificial Intelligence (AI) applications in educational settings. As result, it is essential to assess teachers’ competencies Technological, Pedagogical, and Content Knowledge (TPACK) as pertains AI examine the factors that influence these competencies. This study aims analyze impact of digital proficiency AI-TPACK The utilized correlational survey model involved 401 teachers from various provinces departments Turkey. data collection tools included personal information form, an scale, scale. collected were analyzed using structural equation modeling. research findings revealed below average, whereas their levels above average. Furthermore, significant relationship between was identified, with predictor Based findings, recommendations for future studies are provided.

Language: Английский

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