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Adaptive Learning Paths: Extenstion of Object Conditions – Point Allocation
Page Overview
[Hide]- 1 Initial Problem
- 2 Conceptual Summary
- 3 User Interface Modifications
- 4 Additional Information
- 4.1 Involved Authorities
- 4.2 Technical Aspects
- 4.3 Privacy
- 4.4 Security
- 4.5 Contact
- 4.6 Funding
- 5 Discussion
- 6 Implementation
- 6.1 Description and Screenshots
- 6.2 Test Cases
- 6.3 Privacy
- 6.4 Approval
1 Initial Problem
Currently, ILIAS does not offer native core solutions for adaptive learning paths within the learning sequence. Existing approaches using preconditions or external plugins are complex and difficult to maintain. For true adaptivity, more flexible conditions are required that go beyond a purely linear sequence.
2 Conceptual Summary
As part of Phase 1, the "Learning Sequence" component will be supplemented with extended object conditions. The goal is to make path control more dynamic. As a next expansion, point allocation will be introduced. Meaning, there will be conditions based on scores achieved.
This allows decisions to be determined based on points or scores achieved.
Examples:
- “If score ≥ 80%, proceed directly to the next module”
- “If score < 50%, unlock supplementary material”
3 User Interface Modifications
3.1 List of Affected Views
- Property page of objects in the learning sequence.
- Editor for conditions/preconditions.
- Tutor view (object table).
3.2 User Interface Details
- New area for logic links in the condition editor.
- Input fields for score thresholds and minimum number of passed objects.
- New column in the object table of the tutor view to display dead ends.
3.3 New User Interface Concepts
Visual editor for conditions (preparation for full visualization in Phase 2).
3.4 Accessibility Implications
The implementation utilizes Kitchen Sink elements to ensure accessibilty
4 Additional Information
4.1 Involved Authorities
- Authority to Sign off on Conceptual Changes: Großkopf, Katrin [katrin.grosskopf]
- Authority to Sign off Code Changes: Großkopf, Katrin [katrin.grosskopf], Auerbach, Jeanine [jeanine.auerbach], Clausen, Keven [keven.clausen]
4.2 Technical Aspects
- Extension of the precondition logic in the core of the learning sequence.
- Database adjustments for storing logic gates and threshold values.
4.3 Privacy
Learning progress data is processed to evaluate the conditions. No new categories of personal data are introduced.
4.4 Security
No special security-relevant changes beyond the standard.
4.5 Contact
Person to be contacted in case of questions about the feature or for funding offers: Auerbach, Jeanine [jeanine.auerbach]
4.6 Funding
Funding status and funding parties are listed in the block 'Status of Feature' in the right column of this page.
If you are interested to give funding for this feature, please get into contact with the person mentioned above as 'Contact'.
Implementation requires funding of 5,000 Euro
5 Discussion
6 Implementation
Feature has been implemented by {Please add related profile link of this person}
6.1 Description and Screenshots
{ Description of the final implementation and screenshots if possible. }
6.2 Test Cases
Test cases completed at {date} by {user}
- {Test case number linked to Testrail} : {test case title}
6.3 Privacy
Information in privacy.md of component: updated at {date} by {user} | no change required
6.4 Approval
Approved at {date} by {user}.
Last edited: 26. May 2026, 12:25, Auerbach, Jeanine [jeanine.auerbach]