Case ReportPublished quantitative study2025
AAB-CASE-2025-RV-051
Learner perspectives on AI teacher effectiveness: The role of engagement, motivation, efficiency, and educational experience
UTAS Oman; learner-centered evaluation of AI teacher agents.
This page documents an AI literacy or AI education case for registry purposes. It is descriptive and does not imply AAB endorsement of any specific tool, provider, or intervention.
01
Implementation
University of Technology and Applied Sciences
02
Learning context
Private program
03
AI role
Tutor
04
Outcome signal
Engagement
Registry Facets
0
Education Level
- Higher education
Subject Area
- AI in education
Use Case Type
- Survey research
Stakeholder Group
- Students
AI Capability Type
- LLM/Chat
- Automation tool
Implementation Model
- Classroom-level
Evidence Type
- Post assessment
Outcomes Domain
- Engagement
- Satisfaction
Implementing Organization
1
Organization Type
University of Technology and Applied Sciences
Location
Muscat, Oman
Primary Facilitator Role
Researchers
Learning Context
2
Setting Type
- Private program
Session Format
AI-delivered course with structured questionnaire
Duration
Course context
Group Size
171 participants
Devices
AI teacher agent (instruction, Q&A, assessment support)
Constraints
- Technical and emotional limits of AI-only delivery
- Context-specific generalization
Learner Profile
3
Age Range
Adult learners (higher education band in study)
Prior AI Exposure Assumed
Increasing
Prior Programming Background Assumed
Not focal
Educational Intent
4
Primary Learning Goals
- Model perceived effectiveness of AI-led instruction
Secondary Learning Goals
- Highlight moderating role of human educator support
What This Was Not
- Not K-12 compulsory schooling sample
AI Tool Description
5
Tool Type
AI teacher (autonomous instructional agent)
AI Role
- Tutor
- Evaluator
- Automation tool
Languages
Oman HE context
User Interaction Model
- Delivers content; answers questions; evaluates understanding
Safeguards
- Human support pathways alongside AI delivery
- Transparency about limitations
Activity Design
6
Activity Flow
- Questionnaire
- Correlation and ordinal regression
Human Vs AI Responsibilities
- Educator support moderates outcomes despite AI-led delivery
Scaffolding Strategies
- Blend AI personalization with human mentorship
Observed Challenges
7
Educators Reported
- Efficiency paradox (correlation vs regression)
- Emotional limits of non-human instruction
Design Adaptations
8
Adaptations
- >80% variance explained in perceived effectiveness model
Reported Outcomes
9
Engagement
- Learners value personalization, clarity, flexibility
Learning Signals
- Educational experience strongest predictor
Educators Reflection
Supports human–AI collaboration designs over full replacement.
Ethical & Privacy Considerations
10
Privacy
- Learner data privacy
- Over-reliance on automation
Evidence Type
11
Evidence
- Post assessment
- Practitioner observation
Relevance to Research
12
Potential Research Use
- K-12 replication with safeguards
- Objective learning gains vs perceptions
Relevant Research Domains
- AI teacher
- Learner perceptions
- Human–AI teaming
Case Status
13
Case Status
- Completed
AAB Classification Tags
14
Age
Higher ed learners
Setting
Oman
AI Function
AI-led instruction
Pedagogy
Survey / regression
Risk Level
High if fully automated without support
Data Sensitivity
Medium
Registry Metadata
15
Case ID
AAB-CASE-2025-RV-051
Publication Status
Published quantitative study
Tags
caseHigher educationMuscat, OmanClassroom-levelLLM/ChatAI in educationSurvey research