Monitoring
Where do I currently stand?Current points, grades, completed activities, progress and status.
← Back to Current Research
AIVA — AI VIRTUAL ADVISOR
Personalised learning guidance grounded in course context
AIVA is an AI Virtual Advisor integrated into Moodle. It combines teacher-defined course rules with authorised information from the student's actual course situation to provide personalised guidance about progress, requirements and next steps.
LEARNING SUPPORT
From “Where am I?” to “What should I do next?”
Goal-setting
What do I need to achieve my goal?Remaining requirements, desired outcomes and possible paths toward them.
Decision support
What should I do next?Guidance based on the student's situation, course rules and available options.
Clarification
How does this requirement work?Procedural and informational questions about requirements, assessments and activities.
PEDAGOGICAL FOUNDATION
Designed to support self-regulated learning
AIVA was not designed around conversational AI for its own sake. Its educational concept is grounded in Self-Regulated Learning and is intended to help students understand their current situation, identify remaining work, consider paths toward their goals, make informed decisions and reflect on progress.
Empirical research is ongoing; the Lab does not yet claim demonstrated effects on self-regulated learning or learning outcomes.- 01Plan
Identify goals and requirements
- 02Monitor
Understand current progress
- 03Decide
Choose appropriate next steps
- 04Reflect
Review progress and outcomes
HOW IT WORKS
How AIVA works
Course context+Student context+Generative AI→Personalised, contextual guidance
MOODLE INTEGRATION
Built where learning already happens
AIVA operates directly within Moodle rather than as an unrelated external chatbot. Its integration combines conversational AI with relevant course context and authorised student information inside the learning environment.
View AIVA on Moodle Marketplace ↗AIVAAI Virtual Advisor
Authorised course dataEDUCATOR CONTROL & RESPONSIBLE AI
AI that works within teacher-defined rules
A central design principle is that the educator defines the educational context in which AIVA operates. The advisor supports students within that structure rather than inventing academic requirements, policies, grades or decisions. AIVA's design centres on educator-defined educational context, authorised student information, a clearly defined advisor role, institutional and teacher control, privacy-aware system design and transparency about the context behind generated guidance.
- Teacher-defined course rules
- Course-specific configuration
- Explicit assessment requirements
- Role boundaries
- Authorised educational context
- Rules connected to guidance
COLLABORATION
Educational research meets Moodle development
AIVA was developed through collaboration between EduTech Lab at the University of Zagreb Faculty of Organization and Informatics and GTN Solutions in Austria. EduTech Lab contributed the educational concept, pedagogical framework, functional requirements and research evaluation, while GTN Solutions implemented and develops the Moodle plugin and its technical integration.
EduTech Lab
Research · Pedagogy · Concept · Evaluation- Educational concept and vision
- Pedagogical framework
- Functional requirements and use cases
- Educational scenarios
- Authentic course deployment
- Research design, testing and evaluation
GTN Solutions
Software Development · Moodle Integration- Moodle plugin implementation
- Software engineering
- Moodle integration
- Technical development
- Maintenance and compatibility
↓ AIVA / Exabis AI Chat
CURRENT RESEARCH
Studying how students use context-aware AI guidance
AIVA provides a research platform for studying how students interact with context-aware AI learning support in authentic educational settings. Current research examines how students use the advisor, how they perceive its usefulness and quality, and how interaction patterns relate to learner characteristics and engagement.
These are current research topics, not findings. There are currently no AIVA-specific published research papers.
DOCTORAL RESEARCH
Marko Matus
AI-based learning support in LMS environmentsAIVA provides the central research and development context for this doctoral research.
ThesisDesign and Evaluation of an AI-Based Virtual Advisor for Learning Support in an LMS Environment