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Factors Influencing Technology Integration among Mathematics Educators in South Africa: A Modified UTAUT2 Perspective

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  • Author(s): Antony Musasa (ORCID Antony Musasa (ORCID 0009-0006-5671-0097); Jameson Goto (ORCID Jameson Goto (ORCID 0000-0002-7102-8911); Geoffrey Lautenbach (ORCID Geoffrey Lautenbach (ORCID 0000-0001-7099-095X)
  • Language:
    English
  • Source:
    Contemporary Educational Technology. 2025 17(2):564.
  • Publication Date:
    2025
  • Document Type:
    Journal Articles
    Reports - Research
  • Additional Information
    • Availability:
      Contemporary Educational Technology. Faculty of Communication Sciences, Anadolu University, Yunus Emre Campus, Eskisehir 26470, Turkey. e-mail: editor@cedtech.net; Web site: http://www.cedtech.net
    • Peer Reviewed:
      Y
    • Source:
      21
    • Subject Terms:
      Educational Technology; Technology Integration; Mathematics Education; Mathematics Teachers; Mathematics Instruction; Teaching Methods; Foreign Countries; Technological Literacy; Pedagogical Content Knowledge; Social Influences; Teacher Attitudes; Educational Benefits; Predictor Variables; Intention
    • Subject Terms:
      South Africa (Johannesburg)
    • Abstract:
      Educators must effectively integrate technology into their teaching practices in today's technology-driven world. This study investigated factors influencing technology integration into teaching among mathematics educators in Gauteng secondary schools in South Africa. The unified theory of acceptance and use of technology, extended by adding the technological pedagogical content knowledge (TPACK) framed the study. Data was collected using an online questionnaire from 309 mathematics educators. Exploratory and confirmatory factor analyses were used to validate and verify the measurement model. The structural equation modelling analyses indicated that hedonic motivation (HM), performance expectancy (PE) and TPACK influenced behavioral intention (BI) to integrate technology. TPACK, facilitating conditions (FC), effort expectancy (EE), social influence (SIN), descriptive norms (SID) and habit (HT) influenced the behavioral use (BU) of technology integration. The second-order structural modelling indicated that all the constructs contributed to technology integration. Still, TPACK was the most important, with the highest explained variance of 64.4%, followed by EE, FC, HM and HT, which all had explained variances above 50%. BI and BU, PE and social influence contributed less than 50% of the explained variance. Our findings could provide insights into future interventions for effective technology integration for in-service educator training.
    • Abstract:
      As Provided
    • Publication Date:
      2025
    • Accession Number:
      EJ1470009