Student Experiences with Blackboard AI Tool: A Qualitative Study Based on the AIDUA Model

A qualitative study of 360 conversation turns explores postgraduate student engagement with an AI tool in a learning management system. The research, authored by Fawzia Omer Alubthane and published in 2026, combines focus group interviews with master's and PhD students and a functional analysis of dialogue patterns. Findings indicate perceptions of anthropomorphism and hedonic motivation enhance initial appraisals, while cognitive fatigue can arise from AI verbosity and conversation loops.

Use Cases

• Analyzing drivers of student engagement with AI tools based on the AIDUA model framework mentioned in the description.
• Studying patterns of cognitive fatigue and user burnout based on observed AI verbosity and persistent conversation loops.
• Investigating the role of anthropomorphism and hedonic motivation in technology acceptance based on qualitative student feedback.
• Designing structured closure mechanisms for AI conversations based on the study's findings regarding open-ended design.

Strengths

• Qualitative findings are derived from a functional analysis of 360 conversation turns.
• The study employs a recognized theoretical framework, the AI device usage acceptance (AIDUA) model.
• Data is openly shared under a CC-BY-4.0 license, permitting reuse and redistribution.

Limitations

• The dataset is a 101.4 KB PDF document, which is a very small qualitative analysis report rather than a primary data corpus.
• Row count and column-level documentation for any underlying data are absent; field semantics must be inferred from the report.
• The study's scope is limited to a specific tool (Blackboard AI Conversation) and a postgraduate student population.

Provenance

Source

figshare

Collection Method

Qualitative design combining focus group interviews and functional analysis of conversation turns.

Freshness

Last updated 2026-05-29 06:15:08.