Digital competency mapping dataset of pre-service teachers in Indonesia

This dataset used the Digital Competency Scale (DCS) to describe Indonesian pre-service teachers’ perceptions. The DCS instrument consisted of five constructs/dimensions, which are: 1) data and information literacy, 2) communication and collaboration, 3) digital content creation, 4) safety, and 5) p...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Data in brief 2023-08, Vol.49, p.109310-109310, Article 109310
Hauptverfasser: Hidayat, Muhammad Luthfi, Hariyatmi, Astuti, Dwi Setyo, Sumintono, Bambang, Meccawy, Maram, Khanzada, Tariq J.S.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This dataset used the Digital Competency Scale (DCS) to describe Indonesian pre-service teachers’ perceptions. The DCS instrument consisted of five constructs/dimensions, which are: 1) data and information literacy, 2) communication and collaboration, 3) digital content creation, 4) safety, and 5) problem-solving, with a total of 36 items using five-point agreement Likert scale. The data was gathered from 23 education and teacher training faculties at Muhammadiyah Universities in 14 provinces across Indonesia in the academic year 2021/2022. A total of 1400 students (18 to 23 years old) in their first to fifth years of study were recruited using the convenience sampling technique, where they participated in filling in the survey electronically using Google Form. The dataset was analysed with the Rasch model measurement approach using WINSTEPS version 5.2.3 software for data cleaning and validation, and reliability and validity testing of the instrument. This dataset analysis can help teacher-training institutions, or higher education policymakers design effective programmes to improve pre-service teachers' digital competencies. Furthermore, researchers can compare this dataset with more rigorous data from other countries.
ISSN:2352-3409
2352-3409
DOI:10.1016/j.dib.2023.109310