Are They Ready to Teach? Generative AI as a Means to Uncover Pre-Service Science Teachers’ PCK and Enhance Their Preparation Program DOI Creative Commons
Ron Blonder, Yael Feldman-Maggor, Shelley Rap

и другие.

Journal of Science Education and Technology, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 18, 2024

Abstract Integrating generative artificial intelligence (GenAI) in pre-service teachers’ education programs offers a transformative opportunity to enhance the pedagogical development of future science educators. This conceptual paper suggests applying GenAI tool evaluate content knowledge (PCK) among teachers. By holding interactive dialogues with GenAI, teachers engage lesson planning way that reveals their understanding content, pedagogy, and PCK while facilitating practical application theoretical knowledge. Interpretation these interactions provides insights into teachers-to-be skills, enabling personalized learning experiences targeted program adjustments. The underscores need equip necessary competencies utilize effectively teaching practices. It contributes ongoing discourse on technology’s role teacher preparation programs, highlighting potential addressing existing challenges evaluating developing via GenAI. suggested research directions aim further investigate usage implications educational contexts.

Язык: Английский

Does ChatGPT enhance student learning? A systematic review and meta-analysis of experimental studies DOI Creative Commons
Ruiqi Deng,

Mingyu Jiang,

Xiao Yu

и другие.

Computers & Education, Год журнала: 2024, Номер unknown, С. 105224 - 105224

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

6

Teaching and learning computer programming using ChatGPT: A rapid review of literature amid the rise of generative AI technologies DOI
Manuel B. Garcia

Education and Information Technologies, Год журнала: 2025, Номер unknown

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

Towards a holistic integration of AI in EFL education: A mixed method empirical study DOI Creative Commons
Lihang Guan, John Chi‐Kin Lee, Yue Zhang

и другие.

Computers and Education Artificial Intelligence, Год журнала: 2025, Номер unknown, С. 100384 - 100384

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

Unveiling AI literacy in K-12 education: a systematic literature review of empirical research DOI
Qihua Tan, Xin Tang

Interactive Learning Environments, Год журнала: 2025, Номер unknown, С. 1 - 17

Опубликована: Март 28, 2025

Язык: Английский

Процитировано

0

How can we improve AI competencies for tomorrow's leaders: Insights from multi-stakeholders’ interaction DOI
Shashank Gupta, Rachana Jaiswal

The International Journal of Management Education, Год журнала: 2024, Номер 22(3), С. 101070 - 101070

Опубликована: Окт. 16, 2024

Язык: Английский

Процитировано

4

Pre-service science teachers’ perception on using generative artificial intelligence in science education DOI
Izida I. Ishmuradova, С. П. Жданов, Sergey V. Kondrashev

и другие.

Contemporary Educational Technology, Год журнала: 2025, Номер 17(3), С. ep579 - ep579

Опубликована: Март 27, 2025

The development of generative artificial intelligence (AI) has started a conversation on its possible uses and inherent difficulties in the field education. It becomes essential to understand perceptions pre-service teachers about integration this technology into teaching practices as AI models including ChatGPT, Claude, Gemini acquire popularity. This investigation sought create valid trustworthy instrument for evaluating science teachers’ opinions implementation educational settings related science. work was undertaken within faculty education at Kazan Federal University. total number participants is 401 undergraduate students. process scale encompassed expert evaluation content validity, exploratory factor analysis, confirmatory assessments reliability. resultant consisted four dimensions: optimism utility education, readiness openness integration, AI’s role inclusivity engagement, concerns skepticism demonstrated robust psychometric properties, evidenced by elevated reliability coefficients. Cluster analysis unveiled distinct profiles based their responses, encompassing spectrum from enthusiastic skeptical disengaged individuals. study provides comprehensive perceptions, thereby informing teacher programs professional initiatives regarding responsible AI. Recommendations entail validation across varied contexts, exploration longitudinal changes, subject-specific applications

Язык: Английский

Процитировано

0

The Role of Artificial Intelligence in Computer Science Education: A Systematic Review with a Focus on Database Instruction DOI Creative Commons

Alkmini Gaitantzi,

Ioannis Kazanidis

Applied Sciences, Год журнала: 2025, Номер 15(7), С. 3960 - 3960

Опубликована: Апрель 3, 2025

The integration of artificial intelligence (AI) into computer science (CS) education is evolving, yet its specific application in database instruction remains underexplored. This systematic review analyzes 31 empirical studies published between 2020 and 2025, examining how AI applications support teaching learning CS, with an emphasis on education. Following the PRISMA methodology, categorizes according to instructional design models, roles, actions, benefits, challenges. Findings indicate that tools, particularly chatbots, intelligent tutoring systems, code generators, effectively personalized instruction, immediate feedback, interactive problem-solving across CS database-specific contexts. However, challenges persist, including inaccuracies, biases, student dependency AI, academic integrity risks. also identifies a shift programming as reshapes software development practices, prompting need align curricula evolving industry expectations. Despite growing attention education, database-related research limited. highlights necessity for further investigations specifically more extensive addressing AI-driven pedagogical strategies their long-term impacts. results suggest careful tools can complement traditional emphasizing critical role human educators achieving meaningful effective outcomes.

Язык: Английский

Процитировано

0

Are They Ready to Teach? Generative AI as a Means to Uncover Pre-Service Science Teachers’ PCK and Enhance Their Preparation Program DOI Creative Commons
Ron Blonder, Yael Feldman-Maggor, Shelley Rap

и другие.

Journal of Science Education and Technology, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 18, 2024

Abstract Integrating generative artificial intelligence (GenAI) in pre-service teachers’ education programs offers a transformative opportunity to enhance the pedagogical development of future science educators. This conceptual paper suggests applying GenAI tool evaluate content knowledge (PCK) among teachers. By holding interactive dialogues with GenAI, teachers engage lesson planning way that reveals their understanding content, pedagogy, and PCK while facilitating practical application theoretical knowledge. Interpretation these interactions provides insights into teachers-to-be skills, enabling personalized learning experiences targeted program adjustments. The underscores need equip necessary competencies utilize effectively teaching practices. It contributes ongoing discourse on technology’s role teacher preparation programs, highlighting potential addressing existing challenges evaluating developing via GenAI. suggested research directions aim further investigate usage implications educational contexts.

Язык: Английский

Процитировано

2