FOMO AI Tutor Accounting: Survey of 377 Accounting Students on AI Tutor Engagement

377 survey responses from accounting students using course-embedded AI tutors, collected by Gunawan Wibisono and last updated in May 2026. The data supports a study examining cognitive and affective pathways influencing strategic use versus overreliance on AI tutors in judgment-intensive subjects. Analysis was performed using partial least squares structural equation modelling and multigroup analysis.

Use Cases

• Modeling relationships between psychological factors (competence, autonomy, relatedness frustration) and AI tool engagement based on the study's theoretical framework.
• Analyzing the protective role of AI tutor limitation awareness on strategic use and overreliance as described in the findings.
• Comparing student engagement patterns across different course contexts where the structural relationships were tested.
• Investigating the distinction between cognitive FoMO and affective FoMO as pathways in technology-rich learning environments.

Strengths

• Survey data from 377 students provides a substantive sample for analysis.
• Data collection was tied to two specific accounting courses with embedded AI tutors, offering a controlled context.
• The dataset is openly licensed under CC-BY-4.0, facilitating reuse and sharing.

Limitations

• Row count and column-level documentation are unknown, limiting assessment of data structure and variable semantics.
• The dataset is very small at 62.3 KB, indicating limited scope and likely a summary or analysis dataset rather than raw responses.
• Geographic and institutional context of the students is unspecified, which may affect generalizability of findings.

Provenance

Source

Gunawan Wibisono via figshare.

Collection Method

Survey data collected from students in two accounting courses supported by course-specific AI tutors embedded in a Moodle-based learning management system.

Freshness

Last updated 2026-05-02 08:44:39; freshness should be verified.