Adaptive Learning Paths: Misconfiguration Badge for Adaptive Learning Sequences

1 Initial Problem

Adaptive Learning Sequences can contain complex input conditions. Authors may configure conditions that are technically valid on their own, but contradictory or impossible in the context of the complete Learning Sequence.

Without direct feedback in the adaptive content table, such configurations are hard to detect. Learners may later encounter blocked paths, unreachable objects or confusing navigation states, while authors do not immediately see which object is affected and why.

2 Conceptual Summary

The adaptive content table receives a misconfiguration badge for objects with conflicting or impossible static input configurations. The badge is shown directly in the table entry and is accompanied by a detail popover explaining the detected issue.

The detection covers static configuration problems that can be evaluated without learner-specific runtime data:

The feature does not replace runtime navigation checks. It supports authors while configuring adaptive paths and makes problematic static setups visible early.

3 User Interface Modifications

3.1 List of Affected Views

3.2 User Interface Details

If an adaptive table entry contains a conflicting static input configuration, a Misconfigured badge is displayed next to the affected object information.

Next to the badge, a help or details trigger opens a popover. The popover explains the concrete problem and may list affected or referenced objects. For points-related issues, it can also show which objects are referenced as points sources and which of them do not provide points output conditions.

3.3 New User Interface Concepts

No new user interface concept is introduced. The feature reuses badges and popovers to add contextual feedback to the existing adaptive content table.

3.4 Accessibility Implications

The badge text and popover content must be available textually and must not rely on color alone. The detail trigger needs an accessible label, and the explanation must identify the affected object and the reason for the warning in understandable language.

4 Additional Information

4.1 Involved Authorities

4.2 Technical Aspects

Static input configuration issues are collected for the adaptive content data and exposed to the adaptive table. The table decides per entry whether a misconfiguration badge and a detail popover must be rendered.

The analyzer evaluates input conditions and derives static constraints such as all completed, none completed and any completed. It also checks whether referenced objects are still part of the Learning Sequence and whether points-based conditions can be fulfilled with the configured output conditions.

Runtime learner data is not required for these checks. The feature is limited to static authoring-time configuration issues.

4.3 Privacy

The feature evaluates object configuration data and condition references. It does not introduce new processing of learner-specific personal data.

4.4 Security

No special security-relevant changes. The badge is shown only in the existing Learning Sequence administration context and follows the existing permission checks for managing adaptive content.

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'.

5 Discussion

6 Implementation

Feature has been implemented by the KPG team.

Related Feature Requests

6.1 Description and Screenshots

Implemented as been showed in the screenshot:

6.2 Test Cases

With regard to the integration of adaptive learning paths, all test cases for the learning sequence were revised. Below are all modified, new, or deleted test cases of the learning sequence.

Test cases completed at 26 OCT 2026 by Auerbach, Jeanine [jeanine.auerbach]

Modified testcases:

New testcases:

Deleted testcases:

6.3 Privacy

no change required

6.4 Approval

Approved at 28th OCT 2026 by Becker, Matthias [matthias.becker].