{"id":"W4392721292","doi":"10.22318/icls2023.622494","title":"Transforming Learning Data into a Machine Learning Model to Help STEM students Transition to University","year":2023,"lang":"en","type":"article","venue":"Proceedings.","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Office of Science","keywords":"Mindset; Learning analytics; Computer science; Metacognition; Machine learning; Artificial intelligence; Classifier (UML); Mathematics education; Psychology; Cognition","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":[0.002652398,0.0009722942,0.0006349431,0.001412219,0.0002596214,0.002342101,0.0008032194,0.0009933008,0.002925702],"category_scores_gemma":[0.01763563,0.0002843371,0.0006684312,0.00109661,0.0002459958,0.001932768,0.0005882218,0.002062196,0.001875156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008964899,"about_ca_system_score_gemma":0.001197432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004431325,"about_ca_topic_score_gemma":0.007948673,"domain_scores_codex":[0.9992347,0.0003903033,0.00005362808,0.0001669501,0.0001141741,0.00004032728],"domain_scores_gemma":[0.9923212,0.00607733,0.0004420929,0.0003928881,0.0006278334,0.00013871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005264669,0.004041127,0.2020608,0.0004389455,0.0004841975,0.0002015992,0.0006307217,0.2881851,0.004652842,0.005102954,0.01119625,0.482479],"study_design_scores_gemma":[0.00003022723,0.0004732986,0.012588,0.0001405037,0.00006939707,0.00004869534,0.0002798927,0.9674718,0.002614543,0.01303777,0.00320194,0.00004398259],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4367298,0.0008622755,0.535011,0.008881793,0.0003241564,0.0007260714,0.004905044,0.006262901,0.006297024],"genre_scores_gemma":[0.8656805,0.0004821084,0.1265746,0.0005110513,0.00007789782,0.0004087459,0.003863735,0.00009685651,0.002304481],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004431325,"threshold_uncertainty_score":0.01402736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04206148069067382,"score_gpt":0.2981443381925481,"score_spread":0.2560828575018743,"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."}}