Preservice teachers’ behavioural intention to use artificial intelligence in lesson planning: A dual-staged PLS-SEM-ANN approach
In the ever-changing landscape of education, the integration of technology has become an inevitable force that reshapes the foundations of teaching and learning. Amidst this transformative wave, the concept of Artificial Intelligence (AI) has taken center stage, promising innovative approaches, and...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
|
| Series: | Computers and Education: Artificial Intelligence |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666920X24001103 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850123161961496576 |
|---|---|
| author | Bernard Yaw Sekyi Acquah Francis Arthur Iddrisu Salifu Emmanuel Quayson Sharon Abam Nortey |
| author_facet | Bernard Yaw Sekyi Acquah Francis Arthur Iddrisu Salifu Emmanuel Quayson Sharon Abam Nortey |
| author_sort | Bernard Yaw Sekyi Acquah |
| collection | DOAJ |
| description | In the ever-changing landscape of education, the integration of technology has become an inevitable force that reshapes the foundations of teaching and learning. Amidst this transformative wave, the concept of Artificial Intelligence (AI) has taken center stage, promising innovative approaches, and increased efficiency. Within this context, the exploration of preservice teachers' behavioural intention to employ AI in lesson planning has emerged as a critical issue for examination. This study used a descriptive cross-sectional survey design and employed a purposive sampling technique to recruit 783 preservice teachers. By employing a cutting-edge dual-staged partial least squares structural equation modelling-artificial neural network (PLS-SEM-ANN) approach, this study investigated the influence of the following essential variables on preservice teachers' intentions to incorporate AI into their lesson planning endeavours: performance expectancy, effort expectancy, habit, hedonic motivation, social influence, and facilitating conditions. Social influence emerged as the most significant positive predictor of preservice teachers' behavioural intention to use AI in lesson planning. Additionally, habit, performance expectancy, effort expectancy, and facilitating conditions substantially positively influenced preservice teachers' behavioural intention to use AI in lesson planning. Conversely, hedonic motivation did not significantly affect preservice teachers’ behavioural intention to use AI in lesson planning. This study not only enhances our understanding of technology integration in pedagogy from a theoretical standpoint but also provides practical recommendations for refining educational curricula and instructional strategies that promote effective AI integration. |
| format | Article |
| id | doaj-art-06fbcc69c9a343b29aede302b4e8187d |
| institution | OA Journals |
| issn | 2666-920X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computers and Education: Artificial Intelligence |
| spelling | doaj-art-06fbcc69c9a343b29aede302b4e8187d2025-08-20T02:34:40ZengElsevierComputers and Education: Artificial Intelligence2666-920X2024-12-01710030710.1016/j.caeai.2024.100307Preservice teachers’ behavioural intention to use artificial intelligence in lesson planning: A dual-staged PLS-SEM-ANN approachBernard Yaw Sekyi Acquah0Francis Arthur1Iddrisu Salifu2Emmanuel Quayson3Sharon Abam Nortey4Department of Business and Social Sciences Education, University of Cape Coast, Cape Coast, GhanaDepartment of Business and Social Sciences Education, Faculty of Humanities and Social Sciences Education, University of Cape Coast, Cape Coast, Ghana; Corresponding author.Centre for Coastal Management- Africa Centre of Excellence in Coastal Resilience, Department of Fisheries and Aquatic Sciences, University of Cape Coast, Cape Coast, GhanaDepartment of Business and Social Sciences Education, Faculty of Humanities and Social Sciences Education, University of Cape Coast, Cape Coast, GhanaDepartment of Business and Social Sciences Education, Faculty of Humanities and Social Sciences Education, University of Cape Coast, Cape Coast, GhanaIn the ever-changing landscape of education, the integration of technology has become an inevitable force that reshapes the foundations of teaching and learning. Amidst this transformative wave, the concept of Artificial Intelligence (AI) has taken center stage, promising innovative approaches, and increased efficiency. Within this context, the exploration of preservice teachers' behavioural intention to employ AI in lesson planning has emerged as a critical issue for examination. This study used a descriptive cross-sectional survey design and employed a purposive sampling technique to recruit 783 preservice teachers. By employing a cutting-edge dual-staged partial least squares structural equation modelling-artificial neural network (PLS-SEM-ANN) approach, this study investigated the influence of the following essential variables on preservice teachers' intentions to incorporate AI into their lesson planning endeavours: performance expectancy, effort expectancy, habit, hedonic motivation, social influence, and facilitating conditions. Social influence emerged as the most significant positive predictor of preservice teachers' behavioural intention to use AI in lesson planning. Additionally, habit, performance expectancy, effort expectancy, and facilitating conditions substantially positively influenced preservice teachers' behavioural intention to use AI in lesson planning. Conversely, hedonic motivation did not significantly affect preservice teachers’ behavioural intention to use AI in lesson planning. This study not only enhances our understanding of technology integration in pedagogy from a theoretical standpoint but also provides practical recommendations for refining educational curricula and instructional strategies that promote effective AI integration.http://www.sciencedirect.com/science/article/pii/S2666920X24001103Artificial neural networkArtificial intelligenceBehavioural intentionLesson planningPerformance expectancyPreservice teachers |
| spellingShingle | Bernard Yaw Sekyi Acquah Francis Arthur Iddrisu Salifu Emmanuel Quayson Sharon Abam Nortey Preservice teachers’ behavioural intention to use artificial intelligence in lesson planning: A dual-staged PLS-SEM-ANN approach Computers and Education: Artificial Intelligence Artificial neural network Artificial intelligence Behavioural intention Lesson planning Performance expectancy Preservice teachers |
| title | Preservice teachers’ behavioural intention to use artificial intelligence in lesson planning: A dual-staged PLS-SEM-ANN approach |
| title_full | Preservice teachers’ behavioural intention to use artificial intelligence in lesson planning: A dual-staged PLS-SEM-ANN approach |
| title_fullStr | Preservice teachers’ behavioural intention to use artificial intelligence in lesson planning: A dual-staged PLS-SEM-ANN approach |
| title_full_unstemmed | Preservice teachers’ behavioural intention to use artificial intelligence in lesson planning: A dual-staged PLS-SEM-ANN approach |
| title_short | Preservice teachers’ behavioural intention to use artificial intelligence in lesson planning: A dual-staged PLS-SEM-ANN approach |
| title_sort | preservice teachers behavioural intention to use artificial intelligence in lesson planning a dual staged pls sem ann approach |
| topic | Artificial neural network Artificial intelligence Behavioural intention Lesson planning Performance expectancy Preservice teachers |
| url | http://www.sciencedirect.com/science/article/pii/S2666920X24001103 |
| work_keys_str_mv | AT bernardyawsekyiacquah preserviceteachersbehaviouralintentiontouseartificialintelligenceinlessonplanningadualstagedplssemannapproach AT francisarthur preserviceteachersbehaviouralintentiontouseartificialintelligenceinlessonplanningadualstagedplssemannapproach AT iddrisusalifu preserviceteachersbehaviouralintentiontouseartificialintelligenceinlessonplanningadualstagedplssemannapproach AT emmanuelquayson preserviceteachersbehaviouralintentiontouseartificialintelligenceinlessonplanningadualstagedplssemannapproach AT sharonabamnortey preserviceteachersbehaviouralintentiontouseartificialintelligenceinlessonplanningadualstagedplssemannapproach |