Learner Choice Attempt
Learner Choice Attempt
Introduction
A Learner Choice Attempt is the record of a learner’s response to a multiple-choice question (Choice Task). It stores which answers they selected, tracks their status, and holds any AI or manually assigned score. This makes it easy for instructors or the AI to review correctness, provide feedback, and analyze patterns.
Key highlights:
Status Lifecycle: Pending → Submitted → Scoring → Scored → Expired.
Scoring: The system can automatically determine correctness if the question has a “CorrectResponsesPattern.” Instructors or AI can refine or override the final mark if needed.
Reflection: Learners may include a short reflection, offering insight into why they chose a particular set of answers.
Properties
LearningChoiceTaskId
Links to the multiple-choice question this attempt pertains to.
ContactId
Identifies the learner who submitted these choices.
Status
The stage of the attempt: “Pending” if the learner hasn’t finalized, “Submitted” if it’s in the system, “Scoring” if an AI or manual evaluation is in progress, “Scored” if a final result is assigned, or “Expired” if the window closed.
PendingDate
When the attempt was first created or moved to pending.
SubmittedDate
The time the learner officially pressed “submit.”
ScoringDate
When the system or an instructor started reviewing or scoring the attempt.
ScoredDate
The moment final scoring wrapped up.
ExpiredDate
If the attempt is no longer valid (e.g., missed a deadline), it’s marked expired here.
AttemptPattern
A comma-separated list of which answers the learner picked (e.g., “2,4”).
AttemptReflection
(Optional) The learner’s notes on why they chose those answers or what thought process they followed.
Score
A numeric outcome, potentially auto-calculated if it matches the question’s correct response.
ScoreReason
Text explaining or justifying the assigned score. E.g., “Only 2 out of 3 answers correct.”
ScoreInstruction
General guidance or next steps (“Review Chapter 2 for more on product vs. place in the marketing mix”).
ScorePersonalInstruction
Personalized feedback, e.g., “Consider the difference between ‘People’ and ‘Promotion’ in context.”
CreatedDate
Date/time automatically set when this attempt record is created.
ModifiedDate
Date/time automatically updated with any changes to the attempt or the score.
Example
A student named Chris answers “Which are the 4 Ps of Marketing?” with choices 1 and 3 only. The system sees AttemptPattern = “1,3.” Since the correct pattern is “1,3,4,” the AI might assign partial credit. The ScoreReason states “Missed Promotion,” and the ScoreInstruction suggests reviewing the 4 Ps concept again.
Use Case
In a professional compliance training, employees take short multiple-choice quizzes. Each attempt is recorded as a Learner Choice Attempt. Supervisors can see who answered incorrectly and follow up with additional training resources. The system can aggregate attempts to gauge how well the company comprehends critical policies.
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