Trust in AI: Building a Reliable Tool for Online Learners

New Study Reveals Reliable Measure of Student Trust in AI for Online Courses

A recent study has developed and validated a tool to assess how much students trust AI in online learning environments. The researchers began by synthesizing existing literature, then consulted experts to ensure each item’s relevance.

Methodology

• Sample: 837 students divided into three groups for exploratory and confirmatory analyses.
• Exploratory Factor Analysis (EFA): Identified five distinct themes explaining 63.20 % of response variance.
• Confirmatory Factor Analysis (CFA): Used an independent group; fit indices were excellent:
• CFI = 0.95
• TLI = 0.94
• RMSEA = 0.06

Reliability

Both Cronbach’s alpha and omega were high at 0.94, indicating strong internal consistency.

Key Findings

• The scale functions equivalently for male and female students.
• No significant relationship between trust levels and academic grades or AI usage frequency.

Implications

Trust appears to be a distinct mindset influencing how learners engage with AI tools. The 21‑question scale offers educators a dependable method to gauge trust and can inform the design of future AI‑enhanced learning experiences.