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More than high, medium, and low: Pre-service teacher TPACK profiles and intentions to teach with technology.

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Title: More than high, medium, and low: Pre-service teacher TPACK profiles and intentions to teach with technology.
Authors: Cheng, Jiaming1 (AUTHOR), Hall, Jacob A.2 (AUTHOR) jacob.hall@cortland.edu, Wang, Qiu3 (AUTHOR), Lei, Jing3 (AUTHOR)
Source: Education & Information Technologies. Dec2024, Vol. 29 Issue 18, p24387-24413. 27p.
Subject Terms: *Student teachers, *Pedagogical content knowledge, *School integration, Technology Acceptance Model, Multivariate analysis
Abstract: Using pre-service teachers' (PSTs) technological, pedagogical, content knowledge (TPACK) survey responses, this study's cluster analysis identified five distinct learning profiles: Pedagogical Content Knowledge Specialists, Technological Forerunners, Pedagogically Minded, Balanced Integrators, and TPACK Lingerers. Instead of using a single timepoint or a single TPACK domain for identifying high or low PST clusters, this study identified five distinct TPACK clusters by analyzing TPACK perception scores before and after a technology integration course. MANOVA, ANOVA, t-tests, and Chi-square tests were then employed to further examine how TPACK domains changed within and between clusters. The MANOVA results indicated that the five profiles exhibited distinct learning trajectories, and the Chi-square results confirmed that cluster membership was independent of PST's programs and majors. After completing the course, all profiles significantly improved their technological knowledge and technological content knowledge, yet only the Technological Forerunner and Pedagogically Minded profiles significantly increased self-perceptions in all TPACK domains. The study furthermore examined the relationship between the TPACK clusters and Technology Acceptance Model (TAM) variables, and results revealed significant differences across learner groups in TAM after taking the technology integration course. The profiles in this study present fine-grained patterns of technology integration development that may inform future TPACK/TAM research, application of cluster analysis methods, and the design of technology integration coursework. [ABSTRACT FROM AUTHOR]
Copyright of Education & Information Technologies is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: More than high, medium, and low: Pre-service teacher TPACK profiles and intentions to teach with technology.
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  Data: <searchLink fieldCode="AR" term="%22Cheng%2C+Jiaming%22">Cheng, Jiaming</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hall%2C+Jacob+A%2E%22">Hall, Jacob A.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> jacob.hall@cortland.edu</i><br /><searchLink fieldCode="AR" term="%22Wang%2C+Qiu%22">Wang, Qiu</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lei%2C+Jing%22">Lei, Jing</searchLink><relatesTo>3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Education+%26+Information+Technologies%22">Education & Information Technologies</searchLink>. Dec2024, Vol. 29 Issue 18, p24387-24413. 27p.
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  Data: Using pre-service teachers' (PSTs) technological, pedagogical, content knowledge (TPACK) survey responses, this study's cluster analysis identified five distinct learning profiles: Pedagogical Content Knowledge Specialists, Technological Forerunners, Pedagogically Minded, Balanced Integrators, and TPACK Lingerers. Instead of using a single timepoint or a single TPACK domain for identifying high or low PST clusters, this study identified five distinct TPACK clusters by analyzing TPACK perception scores before and after a technology integration course. MANOVA, ANOVA, t-tests, and Chi-square tests were then employed to further examine how TPACK domains changed within and between clusters. The MANOVA results indicated that the five profiles exhibited distinct learning trajectories, and the Chi-square results confirmed that cluster membership was independent of PST's programs and majors. After completing the course, all profiles significantly improved their technological knowledge and technological content knowledge, yet only the Technological Forerunner and Pedagogically Minded profiles significantly increased self-perceptions in all TPACK domains. The study furthermore examined the relationship between the TPACK clusters and Technology Acceptance Model (TAM) variables, and results revealed significant differences across learner groups in TAM after taking the technology integration course. The profiles in this study present fine-grained patterns of technology integration development that may inform future TPACK/TAM research, application of cluster analysis methods, and the design of technology integration coursework. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Education & Information Technologies is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: School integration
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              Text: Dec2024
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