Investigating in-service teachers’ views on ChatGPT integration DOI
Zeina Hojeij, Mohammad Amin Kuhail, Areej ElSayary

и другие.

Interactive Technology and Smart Education, Год журнала: 2024, Номер unknown

Опубликована: Июль 26, 2024

Purpose This study aims investigate in-service teachers’ perspectives on the integration of ChatGPT, an artificial intelligence (AI)-driven chatbot, into United Arab Emirates (UAE) private schools. As UAE progresses towards a knowledge-based economy, aligning with goals 2030 vision, this research assesses capacity ChatGPT to enhance educational experience within framework technological pedagogical content knowledge. Design/methodology/approach A mixed-methods approach is used, combining survey assessing attitudes and thematic analysis open-ended responses, explore effectiveness, challenges implications ChatGPT’s use in classroom. Findings reveal that teachers value for its potential individualize learning streamline creation materials, shift student-centred approaches demands 21st-century skills. However, significant are noted, including ethical concerns, need reliable necessity extensive professional development fully realize benefits. Practical While transforms teaching practices, realizing requires addressing critical issues through adaptive policy-making, continuous educator training thoughtful curriculum. Originality/value The highlights importance collaborative dealing details AI education, ensuring advancements like align evolving paradigms UAE.

Язык: Английский

Exploring the AI competencies of elementary school teachers in South Korea DOI Creative Commons
Keunjae Kim, Kyungbin Kwon

Computers and Education Artificial Intelligence, Год журнала: 2023, Номер 4, С. 100137 - 100137

Опубликована: Янв. 1, 2023

Although the importance of K–12 artificial intelligence (AI) education grows, lack teacher readiness hinders integration AI in schools. To address this issue, study aimed to explore South Korean elementary school teachers' experiences teaching curricula and examine their competencies. A survey interviews were conducted with 67 teachers who have been working AI-leading schools Korea. The results indicated that least confident content knowledge, followed by technological knowledge pedagogical relevant AI. Additionally, 13 revealed five themes regarding education: (1) emphasizing instructional design education; (2) redesigning learning environment promote experiences; (3) lowering anxiety acknowledging limitations knowledge; (4) extending based on computer science (CS) principles; (5) acquiring literacy codes, data, technologies, ethical issues. Based findings, 22 competencies for derived categorized (TPACK) framework. provide a practical framework acquire necessary skills education. contributes understanding practices Korea revealing teachers’ perspectives identifying essential practicing

Язык: Английский

Процитировано

70

Design and validation of the AI literacy questionnaire: The affective, behavioural, cognitive and ethical approach DOI Creative Commons
Davy Tsz Kit Ng,

Wenjie Wu,

Jac Ka Lok Leung

и другие.

British Journal of Educational Technology, Год журнала: 2023, Номер 55(3), С. 1082 - 1104

Опубликована: Дек. 13, 2023

Artificial intelligence (AI) literacy is at the top of agenda for education today in developing learners' AI knowledge, skills, attitudes and values 21st century. However, there are few validated research instruments educators to examine how secondary students develop perceive their learning outcomes. After reviewing literature on questionnaires, we categorized identified competencies four dimensions: (1) affective (intrinsic motivation self‐efficacy/confidence), (2) behavioural (behavioural commitment collaboration), (3) cognitive (know understand; apply, evaluate create) (4) ethical learning. Then, a 32‐item self‐reported questionnaire (AILQ) was developed measure students' development dimensions. The design validation AILQ were examined through theoretical review, expert judgement, interview, pilot study first‐ second‐order confirmatory factor analysis. This article reports findings using preliminary version among 363 school Hong Kong analyse psychometric properties instrument. Results indicated four‐factor structure revealed good reliability validity. recommended as reliable measurement scale assessing foster inform better instructional based proposed affective, behavioural, (ABCE) framework. Practitioner notes What already known about this topic has drawn increasing attention recent years been an important digital literacy. Schools universities around world started incorporate into curriculum young Some studies have worked suitable tools, especially outcomes programmes. paper adds Develops terms Proposes parsimonious model ABCE framework addresses skill set Implications practice and/or policy Researchers able use guide Practitioners assess development.

Язык: Английский

Процитировано

54

Teachers’ AI-TPACK: Exploring the Relationship between Knowledge Elements DOI Open Access
Yimin Ning, Cheng Zhang, Binyan Xu

и другие.

Sustainability, Год журнала: 2024, Номер 16(3), С. 978 - 978

Опубликована: Янв. 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.

Язык: Английский

Процитировано

47

Enhancing teacher AI literacy and integration through different types of cases in teacher professional development DOI Creative Commons
Ai-Chu Elisha Ding, Lehong Shi,

Haotian Yang

и другие.

Computers and Education Open, Год журнала: 2024, Номер 6, С. 100178 - 100178

Опубликована: Апрель 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.

Язык: Английский

Процитировано

45

Understanding K–12 teachers’ technological pedagogical content knowledge readiness and attitudes toward artificial intelligence education DOI Creative Commons

Miao Yue,

Morris Siu‐Yung Jong, Davy Tsz Kit Ng

и другие.

Education and Information Technologies, Год журнала: 2024, Номер 29(15), С. 19505 - 19536

Опубликована: Март 20, 2024

Abstract Artificial intelligence (AI) education is increasingly being recognized as essential at the K–12 level. For better understanding teachers’ preparedness for AI and effectively developing relevant teacher training programs, technological pedagogical content knowledge (TPACK) readiness attitudes toward teaching must be determined. However, limited research has been conducted on this topic. To address gap, we recruited 1,664 teachers to obtain a comprehensive view of in classrooms. These differed terms their gender, subject, grade, experience, experience AI. The findings study indicated that substantial gap exists AI-related teachers. Moreover, intriguing relationships were found between knowledge, effects demographic factors TPACK also examined. On basis study, recommendations formulated effective professional development programs field education.

Язык: Английский

Процитировано

38

A framework for inclusive AI learning design for diverse learners DOI Creative Commons
Yukyeong Song, Lauren Weisberg, Shan Zhang

и другие.

Computers and Education Artificial Intelligence, Год журнала: 2024, Номер 6, С. 100212 - 100212

Опубликована: Фев. 28, 2024

As artificial intelligence (AI) becomes more prominent in children's lives, an increasing number of researchers and practitioners underscored the importance integrating AI as learning content K-12. Despite recent efforts developing curricula guiding frameworks education, educational opportunities often do not provide equally engaging inclusive experiences for all learners. To promote equality equity society increase competitiveness workforce, it is essential to broaden participation education. However, framework that guides teachers designers into design tailored education lacking. Universal Design Learning (UDL) provides guidelines making across disciplines. Based on principles UDL, this paper proposes a guide learning. We conducted systematic literature review identify design-related articles synthesized them our proposed framework. Our new includes core component (i.e., five big ideas), anchored by three UDL (the "why," "what," "how" learning), six praxes with pedagogical examples Alongside this, we present illustrative example application context middle school summer camp. hope will designing experiences.

Язык: Английский

Процитировано

22

Enhancing Teachers’ AI Competencies through Artificial Intelligence of Things Professional Development Training DOI Open Access
Pornchai Kitcharoen, Suppachai Howimanporn, Sasithorn Chookaew

и другие.

International Journal of Interactive Mobile Technologies (iJIM), Год журнала: 2024, Номер 18(02), С. 4 - 15

Опубликована: Янв. 25, 2024

The rapid increase in new challenges of the combination Internet Things (IoT) and artificial intelligence (AI), which are emerging technologies, can play a compelling role prompting development (AIoT). Therefore, demand for AI competencies everyone will increase. Educational institutes focus on encouraging education because AI-literate workers industrial sector. However, teachers’ lack knowledge is significant barrier to education. Thus, developing teacher’s educating them about how use teach students critical. In this study, we proposed things professional (AIoT-PD) training prepare teachers ready teach. A quasi-experimental design with two-day workshop was conducted among 13 examine its impact competencies, including knowledge, skill, attitude. quantitative data were collected via pretest posttest after activity, while qualitative interviews. This study showed that significantly improved. These findings revealed AIoT workshop’s effectiveness enhancing help effectively

Язык: Английский

Процитировано

17

Artificial Intelligence in Teaching and Teacher Professional Development: A Systematic Review DOI Creative Commons
Xiao Jian Tan, Gary Cheng, Man Ho Ling

и другие.

Computers and Education Artificial Intelligence, Год журнала: 2024, Номер unknown, С. 100355 - 100355

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

10

Development and validation of the Artificial Intelligence Literacy Scale for Teachers (AILST) DOI
Yimin Ning, Wenjun Zhang, D Yao

и другие.

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

Опубликована: Март 15, 2025

Язык: Английский

Процитировано

1

Analysis of influencing factors on teachers' AI literacy under the SOR framework: An empirical study based on PLS-SEM and fsQCA DOI
Yimin Ning,

Hanyi Zheng,

Hsin‐Kai Wu

и другие.

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

Опубликована: Март 31, 2025

Язык: Английский

Процитировано

1