{"id":"W2588240791","doi":"10.24059/olj.v20i2.802","title":"Using Learning Analytics to Identify Medical Student Misconceptions in an Online Virtual Patient Environment","year":2015,"lang":"en","type":"article","venue":"Online Learning","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Western Hospital; McGill University; University Health Network","funders":"","keywords":"Formative assessment; Computer science; Learning analytics; Analytics; Domain (mathematical analysis); Inclusion (mineral); Chart; Data science; Machine learning; Psychology; Mathematics education; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007783655,0.0005450615,0.0005499861,0.005437142,0.0005854557,0.002894596,0.001083936,0.0008881142,0.0004505234],"category_scores_gemma":[0.07161927,0.0002545815,0.0004046742,0.002121915,0.0004949131,0.002769621,0.001582472,0.0008471737,0.0002806291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007617286,"about_ca_system_score_gemma":0.001143832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001702522,"about_ca_topic_score_gemma":0.002459546,"domain_scores_codex":[0.9924693,0.004040779,0.0007826866,0.0007550224,0.001691339,0.0002609691],"domain_scores_gemma":[0.8821232,0.09637748,0.01135423,0.004108103,0.004923272,0.001113663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001032494,0.001118762,0.6750754,0.0004710881,0.0002458017,0.0007929106,0.0172169,0.004751848,0.005541044,0.0004628161,0.001338723,0.2919523],"study_design_scores_gemma":[0.0001576818,0.003287884,0.5708433,0.0008799833,0.0006949466,0.00465016,0.0320788,0.3124912,0.05053352,0.009679909,0.01426077,0.0004418993],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9863577,0.0002145832,0.01150597,0.0003229645,0.00001376744,0.0001102876,0.0004662501,0.0004052939,0.0006033011],"genre_scores_gemma":[0.9762282,0.0001106221,0.02249774,0.00009033922,0.00001764551,0.00005959429,0.0007402783,0.00002189585,0.0002337387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007783655,"threshold_uncertainty_score":0.0411644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0817676672790888,"score_gpt":0.3954793453496462,"score_spread":0.3137116780705574,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}