Examining Academics’ Perceptions of Technology Acceptance in Statistics Education: A Necessary Condition Analysis (NCA) and Structural Equation Modeling (SEM) Approach

Asyraf Afthanorhan (), Nur Zainatulhani Mohamad (), Sheikh Ahmad Faiz Sheikh Ahmad Tajuddin (), Nurul Aisyah Awanis A. Rahim (), Hamdy Abdullah () and Muhammad Takiyuddin Abdul Ghani ()
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Asyraf Afthanorhan: Faculty of Business and Management, Universiti Sultan Zainal Abidin
Nur Zainatulhani Mohamad: Universiti Sultan Zainal Abidin
Sheikh Ahmad Faiz Sheikh Ahmad Tajuddin: Faculty of Business and Management, Universiti Sultan Zainal Abidin
Nurul Aisyah Awanis A. Rahim: Faculty of Business and Management, Universiti Sultan Zainal Abidin
Hamdy Abdullah: Faculty of Business and Management, Universiti Sultan Zainal Abidin
Muhammad Takiyuddin Abdul Ghani: Faculty of Business and Management, Universiti Sultan Zainal Abidin

A chapter in Eurasian Business and Economics Perspectives, 2025, pp 39-67 from Springer

Abstract: Abstract The aim of this study is to evaluate the performance of a proposed model utilizing the Technology Acceptance Model (TAM) to forecast student perceptions of statistics education with advanced technology. A total of 379 undergraduate students from Malaysia’s East Coast region were recruited using a simple random sampling technique. The Pooled Confirmatory Factor Analysis (PCFA) was employed to assess the factor loadings and fitness of the model being tested. Moreover, the Composite Reliability (CR) and Average Variance Extracted (AVE) were established to assess their reliability and validity. The results from the PCFA method were further validated through Necessary Condition Analysis (NCA) to verify the consistency of the findings. The findings from both methods suggest that all constructs in the model are reliable, valid, and consistent. The NCA provided additional insights into the effect size of each variable, offering the researcher a deeper understanding of item quality, beyond the reliance on CFA alone. Furthermore, NCA’s less stringent assumptions make it suitable for a wide range of circumstances, further enhancing the robustness of the study’s outputs.

Keywords: Academic Perception; Technology Acceptance Model; Necessary Condition Analysis; Confirmatory Factor Analysis; Structural Equation Modelling (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/978-3-031-98398-6_3

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