La inteligencia artificial en contextos del conocimiento técnico pedagógico del contenido (TPACK): Una revisión bibliográfica DOI Open Access

Miguel Paidicán Soto,

Pamela Arredondo Herrera

Panorama, Journal Year: 2024, Volume and Issue: 18(35)

Published: Dec. 14, 2024

The aim of this research was to examine the scientific production technical pedagogical content knowledge model (TPACK) in context artificial intelligence (AI). Nineteen articles were selected from following databases and/or repositories: DIALNET, DIMENSIONS, ERIC, Jstor, OpenAlex, PsycINFO, Redalyc, SCIELO, Scilit, SCOPUS and WoS, beginning TPACK 2006 until July 2024. inclusion criteria open access, only, full text, social sciences contexts. It can be concluded that is low, reaching 1.91% total number records analysed, mainly concentrated between years 2023 countries Asian continent show greatest development, with China accounting for more than a third production. studies focus on university teachers, specifically self-reporting knowledge, which instruments related AI are created, adapted, applied validated. results CK, PK TK-IA have little influence TPACK-IA. Finally, ethical aspects need considered when using AI.

Language: Английский

When TPACK meets artificial intelligence: Analyzing TPACK and AI-TPACK components through structural equation modelling DOI
Fatih Karataş, Bengü Aksu Ataç

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

Published: Nov. 25, 2024

Language: Английский

Citations

2

The impact of TPACK on teachers’ willingness to integrate generative artificial intelligence (GenAI): The moderating role of negative emotions and the buffering effects of need satisfaction DOI

Yiming Yang,

Qi Xia,

C. C. Liu

et al.

Teaching and Teacher Education, Journal Year: 2024, Volume and Issue: 154, P. 104877 - 104877

Published: Nov. 26, 2024

Language: Английский

Citations

2

Closing the divide: Exploring higher education teachers’ perspectives on educational technology DOI
Ahmad Samed Al‐Adwan, Rakesh Kumar Meet, Devkant Kala

et al.

Information Development, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 23, 2024

Incorporating technology into education has become a crucial component of contemporary teaching practices. Technological advancements have led to the development innovative tools and methodologies that promote active learning engagement among students. This study used modified version Technology Acceptance Model (TAM) analyze key factors impact integration in practice higher instructors. Among be included model are technostress tradition. These been rarely examined within mandatory settings. Partial Least Squares Structural Equation Modelling (PLS-SEM) is analyse empirical data collected from 657 teachers Jordan. Findings reveal teachers’ technological, pedagogical content knowledge (TPACK) played role facilitating effective boosted self-efficacy, personal innovativeness perceptions ease use usefulness. Additionally, TPACK negatively influenced their Indeed, tradition were identified as significant obstacles Significant implications for theory can derived findings this effectively incorporate education.

Language: Английский

Citations

1

Unveiling the Dynamic Mechanisms of Generative AI in English Language Learning: A Hybrid Study Based on fsQCA and System Dynamics DOI Creative Commons
Yang Zhang, Changqi Dong

Behavioral Sciences, Journal Year: 2024, Volume and Issue: 14(11), P. 1015 - 1015

Published: Oct. 31, 2024

The burgeoning development of generative artificial intelligence (GenAI) has unleashed transformative potential in reshaping English language education. However, the complex interplay learner, technology, pedagogy, and contextual factors that shape effectiveness GenAI-assisted learning remains underexplored. This study employed a novel mixed-methods approach, integrating qualitative comparative analysis (QCA) system dynamics (SD) modeling, to unravel multi-dimensional, dynamic mechanisms underlying impact GenAI on outcomes higher Leveraging sample 33 classes at Harbin Institute Technology, QCA results revealed four distinct configurational paths high low effectiveness, highlighting necessary sufficient conditions for optimal integration. SD simulation further captured emergent, nonlinear feedback processes among learner attributes, human-computer interaction, pedagogical practices, ethical considerations, shedding light temporal evolution GenAI-empowered language-learning ecosystem. findings contribute theoretical advancement intelligent education by constructing an integrative framework encompassing context dimensions. Practical implications are generated guide responsible design, implementation, optimization education, paving way learner-centric, adaptive experiences era.

Language: Английский

Citations

0

Gender and regional differences in technological pedagogical readiness among primary mathematics teachers in post-pandemic China DOI
Hongming Fan, Mao Li

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

Published: Dec. 17, 2024

Language: Английский

Citations

0

La inteligencia artificial en contextos del conocimiento técnico pedagógico del contenido (TPACK): Una revisión bibliográfica DOI Open Access

Miguel Paidicán Soto,

Pamela Arredondo Herrera

Panorama, Journal Year: 2024, Volume and Issue: 18(35)

Published: Dec. 14, 2024

The aim of this research was to examine the scientific production technical pedagogical content knowledge model (TPACK) in context artificial intelligence (AI). Nineteen articles were selected from following databases and/or repositories: DIALNET, DIMENSIONS, ERIC, Jstor, OpenAlex, PsycINFO, Redalyc, SCIELO, Scilit, SCOPUS and WoS, beginning TPACK 2006 until July 2024. inclusion criteria open access, only, full text, social sciences contexts. It can be concluded that is low, reaching 1.91% total number records analysed, mainly concentrated between years 2023 countries Asian continent show greatest development, with China accounting for more than a third production. studies focus on university teachers, specifically self-reporting knowledge, which instruments related AI are created, adapted, applied validated. results CK, PK TK-IA have little influence TPACK-IA. Finally, ethical aspects need considered when using AI.

Language: Английский

Citations

0