Pre-service Teachers' Digital Competence Survey Across a 16-Week Semester

23 pre-service teachers completed a 23-item digital competence survey three times during a 16-week semester at a Chinese normal university. The dataset contains Likert-scale responses measuring six dimensions of digital competence, plus demographic variables. It was collected by Zhou, Rui to examine the effects of an Instructor–Student–AI Collaborative model.

Use Cases

• Conduct repeated measures analysis based on three measurement points (T1, T2, T3).
• Examine divergent development trajectories between technical and ethical competence dimensions.
• Link quantitative survey data to qualitative data like reflection journals and interview transcripts.
• Analyze the relationship between demographic variables and digital competence development.

Strengths

• Longitudinal design with three measurement points over a 16-week semester.
• Survey measures six distinct dimensions of digital competence.
• Dataset is part of a convergent mixed-methods design, enabling linkage to qualitative data.

Limitations

• Small sample size of 23 participants.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Harvard Dataverse, author Zhou, Rui.

Collection Method

Quantitative survey responses collected via the Pre-service Teacher Digital Competence Scale.

Time Range

Data gathered over a single 16-week semester.

Freshness

Last updated 2026-05-11 14:33:42; freshness should be verified.

Geography

Data collected at a Chinese normal university.