Knowledge Integration Model of Blockchain Technology in Higher Learning Institutions: A Rasch Measurement Model Approach for Pilot Study

Nur Ilyana Ismarau Tajuddin; Nurafifah Mohd Nor; Nor Aziyatul Izni; Nur Idayu Ah Khaliludin; Aeshah Mohd Ali

doi:10.33102/mjosht.527

Authors

Nur Ilyana Ismarau Tajuddin Tamhidi Centre, Universiti Sains Islam Malaysia, 71800 Nilai, Negeri Sembilan.
Nurafifah Mohd Nor Faculty of Science and Technology, Universiti Sains Islam Malaysia, 71800 Nilai, Negeri Sembilan.
Nor Aziyatul Izni Centre of Foundation Studies, Universiti Teknologi MARA, Cawangan Selangor, Kampus Dengkil, Dengkil, 43800, Selangor, Malaysia.
Nur Idayu Ah Khaliludin Tamhidi Centre, Universiti Sains Islam Malaysia, 71800 Nilai, Negeri Sembilan.
Aeshah Mohd Ali Faculty of Business and Management, UCSI University, 1 Jalan UCSI, UCSI Heights (Taman Connaught), Cheras 56000, Kuala Lumpur, Malaysia.

DOI:

https://doi.org/10.33102/mjosht.527

Keywords:

blockchain technology, instrument validation, higher education, knowledge integration model, Rasch Measurement Model

Abstract

Blockchain technology has emerged as a transformative tool in higher education, offering secure, transparent, and tamper-proof systems for credential verification, academic record management, and institutional data governance. Despite its potential, adoption remains limited due to technical, financial, and organizational barriers, alongside a lack of validated measurement tools to assess readiness and integration. This pilot study aims to validate an instrument grounded in the Knowledge Integration Model of Blockchain Technology for Higher Learning Institutions using the Rasch Measurement Model. A 50 item survey was administered to 31 purposively sampled stakeholders, including academics, researchers, and postgraduate students with blockchain related experience. Data analysis using WINSTEPS 3.92.1 assessed reliability, item-person fit, unidimensionality, and targeting through Wright Map analysis. The results showed satisfactory reliability (person = 0.82; item = 0.77). Four items (B5, B6, D8, C7) exceeded the acceptable outfit MNSQ threshold (>1.5) and were revised to enhance instrument quality. However, several items showed misfit and require refinement, and the Wright Map indicated a need for more challenging items to better target high ability respondents. Unidimensionality testing revealed a dominant construct with minor secondary dimensions, suggesting further refinement for conceptual clarity. These findings provide preliminary evidence the instrument’s potential for large scale application, providing a foundation for assessing blockchain knowledge integration and guiding policy and strategic implementation in higher education.

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