Dataset on Digital Competence Practices in Indonesian Universities
Description
This dataset contains anonymised individual responses from 519 lecturers at public (n = 142) and private (n = 377) higher education institutions in Indonesia, collected through an online Google Forms questionnaire (administered in Bahasa Indonesia) between 21 August and 19 September 2025. Each record includes profile variables (gender, type of institution, academic discipline, perceived institutional support, teaching-mode preference, and the frequency, nature and perceived effectiveness of collegial collaboration on digital teaching), the Attitude toward Computer Technology scale (12 items) and the Self-Efficacy with Computer Technology scale (25 items), both rated on a four-point agreement scale, and the DigCompEdu Check-In self-assessment (21 items, five proficiency statements each). Files: (1) Dataset_Digital_Competence_Indonesia_HE_v3.xlsx with three sheets, namely README, Data (519 rows × 73 columns) and Codebook; (2) Data.csv and Codebook.csv, the same content in CSV format; (3) Research_Instrument_ID.pdf and Research_Instrument_EN.pdf, the questionnaire in Bahasa Indonesia and English; (4) Informed_Consent_EN.pdf, the consent text shown to participants. Version 3 converts all response columns to numeric format, adds one value omitted in version 2 (respondent 308, teaching mode), separates the codebook from the data sheet, and adds the questionnaire and consent text. The study was approved by the Research Ethics Committee (KEPK-FIK) of Universitas Muhammadiyah Surakarta (No. 913/KEPK-FIK/II/2025).
Files
Steps to reproduce
1. Survey: a cross-sectional online questionnaire was built in Google Forms and administered in Bahasa Indonesia from 21 August to 19 September 2025. The link was distributed online to lecturers at Indonesian higher education institutions (non-probability convenience sampling). All items were required, and completion took less than 10 minutes. Respondents gave electronic consent before answering. No names or e-mail addresses were collected. 2. Instruments: the profile and collaboration questions were developed by the authors. The Attitude toward Computer Technology scale (12 items) and the Self-Efficacy with Computer Technology scale (25 items) were adapted from Milbrath and Kinzie (2000). The DigCompEdu Check-In (21 items) follows Horváth et al. (2024). The full wording is provided in the questionnaire files and the Codebook. 3. Pre-processing: responses were exported from Google Forms to Microsoft Excel, converted to numeric codes as listed in the Codebook, and assigned a sequential respondent ID (1–519). Multiple-response answers on the nature of collaboration are stored as a letter string and as six 0/1 indicators. No records were removed, no values were imputed, and no items were reverse-scored in the data files (ACT3–ACT6 are negatively worded). 4. Checks: completeness, value ranges, frequency distributions and Cronbach's alpha were examined in IBM SPSS Statistics version 29. ACT3–ACT6 were reverse-scored for the alpha computation only. 5. To reuse: open Data.csv (or the Data sheet) in any statistical package and use the Codebook to label variables and value codes. The README sheet lists response patterns (identical, uniform or inconsistent responses) that users may wish to screen.
Institutions
- Muhammadiyah University of SurakartaCentral Java, Surakarta