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Learner satisfaction-based research on the application of artificial intelligence science popularization kits

The application of artificial intelligence science popularization kits in maker courses has promoted the rapid development of maker education. However, there exist few theoretical and empirical studies on the application of artificial intelligence science popularization kits in maker education. The...

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Autores principales: Ling, Yingfei, Jin, Zhou, Li, Yingxin, Huang, Jieya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9343763/
https://www.ncbi.nlm.nih.gov/pubmed/35928423
http://dx.doi.org/10.3389/fpsyg.2022.901191
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author Ling, Yingfei
Jin, Zhou
Li, Yingxin
Huang, Jieya
author_facet Ling, Yingfei
Jin, Zhou
Li, Yingxin
Huang, Jieya
author_sort Ling, Yingfei
collection PubMed
description The application of artificial intelligence science popularization kits in maker courses has promoted the rapid development of maker education. However, there exist few theoretical and empirical studies on the application of artificial intelligence science popularization kits in maker education. The theory of learner satisfaction can be used to explain learner motivation and outcomes with regard to participation in maker education using the artificial intelligence suite. Therefore, taking advantage of the opportunity the Zhejiang Action Plan for Promoting the Development of New Generation Artificial Intelligence (2019–2022) has provided, this study first conducted semi-structured interviews based on the results of a literature review and a questionnaire survey and then performed Pearson correlation analysis and regression analysis using SPSS 24.0 to explore the influencing factors of students’ satisfaction with the use of artificial intelligence science popularization kits in education. The following results were obtained. (1) The correlation between grades and learners’ satisfaction is not significant. (2) The use of a high-quality artificial intelligence science suite in the classroom will positively impact learners’ satisfaction. (3) The degree of interaction with the artificial intelligence suite is negatively correlated with learners’ satisfaction. (4) Teaching adaptability is significantly positively correlated with learner satisfaction. (5) Learners’ individual characteristics have no significant positive correlation with learner satisfaction. Therefore, this study recommends focusing on suite quality, improving human–computer interaction, adopting a student-centered strategy, and aiming at improving the suitability of the curriculum.
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spelling pubmed-93437632022-08-03 Learner satisfaction-based research on the application of artificial intelligence science popularization kits Ling, Yingfei Jin, Zhou Li, Yingxin Huang, Jieya Front Psychol Psychology The application of artificial intelligence science popularization kits in maker courses has promoted the rapid development of maker education. However, there exist few theoretical and empirical studies on the application of artificial intelligence science popularization kits in maker education. The theory of learner satisfaction can be used to explain learner motivation and outcomes with regard to participation in maker education using the artificial intelligence suite. Therefore, taking advantage of the opportunity the Zhejiang Action Plan for Promoting the Development of New Generation Artificial Intelligence (2019–2022) has provided, this study first conducted semi-structured interviews based on the results of a literature review and a questionnaire survey and then performed Pearson correlation analysis and regression analysis using SPSS 24.0 to explore the influencing factors of students’ satisfaction with the use of artificial intelligence science popularization kits in education. The following results were obtained. (1) The correlation between grades and learners’ satisfaction is not significant. (2) The use of a high-quality artificial intelligence science suite in the classroom will positively impact learners’ satisfaction. (3) The degree of interaction with the artificial intelligence suite is negatively correlated with learners’ satisfaction. (4) Teaching adaptability is significantly positively correlated with learner satisfaction. (5) Learners’ individual characteristics have no significant positive correlation with learner satisfaction. Therefore, this study recommends focusing on suite quality, improving human–computer interaction, adopting a student-centered strategy, and aiming at improving the suitability of the curriculum. Frontiers Media S.A. 2022-07-19 /pmc/articles/PMC9343763/ /pubmed/35928423 http://dx.doi.org/10.3389/fpsyg.2022.901191 Text en Copyright © 2022 Ling, Jin, Li and Huang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Ling, Yingfei
Jin, Zhou
Li, Yingxin
Huang, Jieya
Learner satisfaction-based research on the application of artificial intelligence science popularization kits
title Learner satisfaction-based research on the application of artificial intelligence science popularization kits
title_full Learner satisfaction-based research on the application of artificial intelligence science popularization kits
title_fullStr Learner satisfaction-based research on the application of artificial intelligence science popularization kits
title_full_unstemmed Learner satisfaction-based research on the application of artificial intelligence science popularization kits
title_short Learner satisfaction-based research on the application of artificial intelligence science popularization kits
title_sort learner satisfaction-based research on the application of artificial intelligence science popularization kits
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9343763/
https://www.ncbi.nlm.nih.gov/pubmed/35928423
http://dx.doi.org/10.3389/fpsyg.2022.901191
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