Differential Item Functioning of Preservice teachers' Digital Competency in Indonesia

Published: 29 April 2024| Version 1 | DOI: 10.17632/dgj4s3rtpb.1
Muhammad Luthfi Hidayat


The findings stem from a comprehensive survey conducted among 1400 preservice teachers spanning six departmental clusters across 23 Muhammadiyah universities in Indonesia throughout the academic years 2021–2022. Utilizing Winsteps software, the dataset underwent thorough analysis employing Differential Item Functioning (DIF) within the Rasch model framework. DIF, a methodological approach, delves into the nuanced performance variations of specific test items across diverse demographic groups. Specifically, in the context of evaluating preservice teachers' digital competency in Indonesia, DIF meticulously examines whether certain test items demonstrate bias influenced by factors such as gender, demographic backgrounds, or other relevant variables. Its primary aim is to ensure fairness, equity, and impartiality in the assessment of preservice teachers' digital proficiency.


Steps to reproduce

Data gathered from a digital questionnaire and analyzed using Winsteps software


Universitas Muhammadiyah Surakarta, Persyarikatan Muhammadiyah


Numerical Analysis, Rasch Analysis