# 5. Assessment Analytics User Type: **Super Administrator** Source: *Mi Digital Academy - Education CRM Features Document* --- ## 5. Assessment Analytics ### 5.1 Time Spent per Question **What it does:** Tracks the time a learner spends on each question in an assessment: the duration per question, so the assessment's pacing is analyzed. The Super Administrator reviews the time-per-question data to identify the questions that are too slow (confusing, hard to parse) or too fast (trivial, or guessed), informing both the content and the question quality. **Sub-features:** - Time tracking: the duration per question recorded for each attempt - Per-question average: the average time per question across attempts - Slow-question flag: a question with an unusually high average time flagged - Fast-question flag: a question with an unusually low average time flagged - Learner view: a learner's own time per question (their pacing) - Correlation: the time correlated with the correctness (slow-and-wrong signals difficulty) - Audit/logging of the analytics reviews (where applicable) **Super Administrator User Journey:** 1. Super Admin opens the assessment analytics and reviews the time spent per question: the average duration per question across the attempts. 2. Identifies a slow question (an unusually high average time); it is flagged for review. 3. Correlates the time with the correctness: a slow-and-wrong question signals genuine difficulty (the learners struggle); a slow-and-right question signals a parsing issue (the question is hard to read). 4. For a parsing issue (a confusingly worded question), Super Admin routes a question fix (a clearer phrasing); the change is recorded. 5. For a genuine difficulty (the concept is hard), Super Admin notes it (the content may need a clearer explanation, or the question's difficulty tag is confirmed). 6. Identifies a fast question (an unusually low average time): a trivial question (too easy) or a guessed one (the learners are not engaging); it is reviewed. 7. For a learner, the time-per-question view shows their pacing (where they spent the time), so they can self-assess their approach. 8. The analytics reviews are logged where applicable (the assessment, the question, the action, the timestamp). **Rules & Edge Cases:** - The time per question is recorded per attempt; the average is across the attempts. - A slow question is correlated with the correctness; the cause (difficulty vs. parsing) is distinguished. - A fast question is reviewed (trivial or guessed); it is not assumed fine. - The time data informs the question quality (a phrasing fix) and the content (a concept that needs clearer teaching). - The learner's own time-per-question is visible; it supports their self-assessment. - Analytics reviews are logged where applicable. ### 5.2 Topic-Wise Accuracy **What it does:** Measures the accuracy per topic: the proportion of correct answers for the questions in each topic, so the learners' mastery by topic is visible. The Super Administrator reviews the topic-wise accuracy to identify the weak topics (the ones the learners struggle with) and the strong ones, informing the teaching and the content focus. **Sub-features:** - Topic-wise accuracy: the correct-answer proportion per topic - Per-topic metric: the accuracy measured for each topic - Weak-topic flag: a topic with a low accuracy flagged for review - Strong-topic identification: the topics with a high accuracy - Trend: the topic accuracy over time (improving or declining) - Correlation: the accuracy correlated with the content (the topic's teaching) - Audit/logging of the analytics reviews (where applicable) **Super Administrator User Journey:** 1. Super Admin reviews the topic-wise accuracy: the correct-answer proportion for the questions in each topic. 2. Identifies a weak topic (a low accuracy); it is flagged for review. 3. Puts the accuracy in context: the topic's difficulty and the questions' difficulty (a hard topic has a naturally lower accuracy than an easy one). 4. Reviews the trend: the topic accuracy over time (a decline suggests a recent teaching issue; a stable low accuracy suggests an inherent difficulty). 5. Correlates the accuracy with the content: the topic's teaching (the video, the explanation) — a weak topic with weak content confirms a content problem. 6. Routes the weak topic for a content/teaching review (a clearer explanation, more practice, a re-teach); the action is tracked. 7. Identifies the strong topics (a high accuracy): the learners master them, so the teaching can move on (or the questions can be made harder). 8. The analytics reviews are logged where applicable (the topic, the accuracy, the action, the timestamp). **Rules & Edge Cases:** - The topic-wise accuracy is the correct-answer proportion per topic; it measures mastery by topic. - The accuracy is read in context (the topic's difficulty, the questions' difficulty); a raw low accuracy is not automatically a failure. - The trend is over time; a single snapshot is not the whole picture. - A weak topic is correlated with the content; the cause (teaching vs. inherent difficulty) is distinguished. - A weak-topic flag marks the topic for review; the flag is a signal, not an automatic action. - Analytics reviews are logged where applicable. ### 5.3 Peer Comparison (Anonymous) and Historical Performance Trends **What it does:** Provides the learner's performance in context: the anonymous peer comparison (how the learner's result compares to the group, without identifying individuals) and the historical performance trend (the learner's results over time). The Super Administrator configures and reviews these so the learner sees their standing and progress, and the platform's overall performance is understood — all with the peer data kept anonymous. **Sub-features:** - Peer comparison: the learner's result compared to the group (anonymous) - Anonymity: the peer data does not identify individuals - Comparison metric: the relative standing (the percentile, the band) - Historical trend: the learner's results over time (the progression) - Trend direction: the trend improving, stable, or declining - Learner visibility: the comparison and trend shown to the learner - Group visibility: the aggregate (anonymous) performance shown to the Super Admin - Audit/logging of the configuration (where applicable) **Super Administrator User Journey:** 1. For an assessment, Super Admin enables the peer comparison: the learner's result compared to the group, anonymously (the percentile/band, not the individuals). 2. Confirms the anonymity: the peer data does not identify any individual learner; only the aggregate and the learner's own standing are shown. 3. A learner sees their standing (the percentile/band relative to the group) and their historical trend (their results over time). 4. For a learner with a declining trend, the platform surfaces it (the learner sees the decline); a support/review path is available. 5. For a learner with an improving trend, the progress is visible (the motivation); the improvement is acknowledged. 6. Super Admin reviews the group's aggregate performance (anonymous): the overall accuracy, the distribution, so the platform's performance is understood. 7. For a group with a low aggregate on a topic, Super Admin routes a teaching/content review (the topic needs attention for the group). 8. The configuration is logged where applicable (the assessment, the setting, the timestamp). **Rules & Edge Cases:** - The peer comparison is anonymous; the peer data does not identify individuals (only the aggregate and the learner's own standing). - The comparison metric is the relative standing (the percentile/band); it is a context, not a ranking of named individuals. - The historical trend is the learner's results over time; the direction (improving, stable, declining) is visible. - A declining trend is surfaced to the learner; a support/review path is available (it is not a silent decline). - The group aggregate is anonymous; the platform's performance is understood without exposing individuals. - The configuration is logged where applicable.