Case ReportPublished qualitative / ENA studySep. 2024
AAB-CASE-2025-RV-054
Understanding Student Perceptions of Artificial Intelligence as a Teammate
UniSA CChange; grade 9; human–AI teaming on complex problems.
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 + partner school
02
Learning context
In-school (K–12)
03
AI role
Co-creator
04
Outcome signal
Collaboration
Registry Facets
0
Education Level
- 9-12
Subject Area
- AI literacy
- STEM
Use Case Type
- Design research
Stakeholder Group
- Students
AI Capability Type
- Reasoning
- Co-creator
Implementation Model
- Classroom-level
Evidence Type
- Qualitative
Outcomes Domain
- Collaboration
- Trust
Implementing Organization
1
Organization Type
University + partner school
Location
Adelaide, Australia
Primary Facilitator Role
Researchers
Learning Context
2
Setting Type
- In-school (K–12)
Session Format
Collaborative problem solving with AI teammate
Duration
Task + focus groups
Group Size
59 students in 15 groups
Devices
AI teammate for space exploration scenario
Constraints
- Single region
- Specific task domain
Learner Profile
3
Age Range
Grade 9
Prior AI Exposure Assumed
Mixed
Prior Programming Background Assumed
Not required
Educational Intent
4
Primary Learning Goals
- Explore student perceptions of AI as collaborative partner
Secondary Learning Goals
- Inform Explainable AI and classroom integration
What This Was Not
- Not standardized test outcome study
AI Tool Description
5
Tool Type
AI teammate in collaborative learning task
AI Role
- Co-creator
- Tutor
Languages
English
User Interaction Model
- Teams solve complex problem with AI assistance
Safeguards
- Build trust via explainability
- Teacher facilitation of human–AI norms
Activity Design
6
Activity Flow
- Assign challenging problem
- AI teammate access
- Focus groups
- ENA visualization
Human Vs AI Responsibilities
- Students co-reason with AI; teachers set collaboration norms
Scaffolding Strategies
- Structured teaming roles
Observed Challenges
7
Educators Reported
- Trust and capability dominate student framing
Design Adaptations
8
Adaptations
- ENA quantifies thematic networks for design feedback
Reported Outcomes
9
Engagement
- Authentic complex problem context
Learning Signals
Educators Reflection
Practical strategies for trustworthy classroom AI teammates.
Ethical & Privacy Considerations
10
Privacy
- Student voice data
- Fair access to AI tools
Evidence Type
11
Evidence
- Activity documentation
- Practitioner observation
Relevance to Research
12
Potential Research Use
- Link perceptions to learning gains
- Other domains beyond space task
Relevant Research Domains
- Human–AI teaming
- Explainable AI
- Secondary STEM
Case Status
13
Case Status
- Completed
AAB Classification Tags
14
Age
Grade 9
Setting
Australia
AI Function
Collaborative agent
Pedagogy
Team problem solving
Risk Level
Medium
Data Sensitivity
Medium
Registry Metadata
15
Case ID
AAB-CASE-2025-RV-054
Publication Status
Published qualitative / ENA study
Tags
case9-12Adelaide, AustraliaClassroom-levelReasoningAI literacySTEMDesign research