Distractor rationale generation is a job in Item Bank Health Check (IBHC) that generates explanatory text for correct and incorrect choices in multiple choice and “fill in the blanks” question types.

These rationales provide learners with meaningful feedback by clarifying the specific misconceptions associated with a distractor, transitioning assessments from simple evaluation tools into rich learning opportunities.

Integrating these rationales provides actionable insights at the moment of feedback, ensuring learners understand the reasoning behind incorrect selections and reducing the likelihood of future guessing.

When to use this job

The distractor rationale generation job is recommended when you need to:

• Support formative assessment: Provide detailed guidance for learners in practice environments where pedagogical feedback is critical.
• Optimize authoring workflows: Quickly generate rationales across diverse assessment materials to meet institutional standards.
• Scale content enhancement: Efficiently update large Item banks containing multiple-choice or fill in the blanks questions that lack feedback.

Running the job

• Open the Learnosity Console and navigate to Item Bank Health Check.
• Create a Collection or select an existing one with the Item bank you want to analyze.
• Click on Create and select Distractor rationale generation from the menu of available job types.
• Select either Multiple choice or Fill in the blank (Cloze). The Fill in the blank option covers Cloze with drag & drop, Cloze with drop down, and Cloze with text.
• Initiate the process by clicking Run job.

The time required for completion depends on the volume of content within the Collection.

Reviewing results

Following the analysis of the Collection, a review space provides a list of each Item where new rationales were proposed. In this space, you can:

• Evaluate the AI-generated rationale recommendations for each possible answer.
• Preview the rationales in an assessment environment.
• Choose to accept, refine, or discard the suggestion prior to completing the job and saving changes.

We recommend reviewing results to ensure the AI suggestions match your organization's specific terminology and pedagogical style.