{"id":"W4391562192","doi":"10.18260/1-2--40598","title":"WORK IN PROGRESS Understanding Student Learning Profiles in Second Year Problem-Solving Engineering Classes","year":2024,"lang":"en","type":"article","venue":"","topic":"Problem and Project Based Learning","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Toronto","funders":"","keywords":"Computer science; Work (physics); Engineering education; Mathematics education; Artificial intelligence; Data science; Engineering management; Engineering; Mathematics; Mechanical engineering","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":[0.006120858,0.0004890255,0.0006317861,0.001661339,0.0007423731,0.002236925,0.0009110164,0.0005964246,0.004158334],"category_scores_gemma":[0.01414498,0.0002058156,0.0007601783,0.001663953,0.0003325165,0.002267854,0.0009943699,0.0007896112,0.000994539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007229366,"about_ca_system_score_gemma":0.002040817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006263752,"about_ca_topic_score_gemma":0.007747927,"domain_scores_codex":[0.9968185,0.001336192,0.000246809,0.000461613,0.0007017149,0.0004351516],"domain_scores_gemma":[0.9771494,0.009392037,0.002767547,0.00155162,0.005430419,0.003708876],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001920869,0.001847235,0.8938392,0.0001796815,0.00007250287,0.00004679977,0.008503078,0.0003301693,0.001012021,0.0001127241,0.001054942,0.09280944],"study_design_scores_gemma":[0.00001214058,0.0008347636,0.9876503,0.00007731099,0.00002937009,0.00004448442,0.00640102,0.001072383,0.0009235282,0.0001309204,0.00279188,0.00003183144],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961739,0.0001790653,0.001313753,0.00022499,0.00001788298,0.0001577856,0.0003220915,0.00003718328,0.0015734],"genre_scores_gemma":[0.990765,0.0003068411,0.004905795,0.0001230091,0.00002694078,0.0003199442,0.001107021,0.0000261989,0.002419325],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006263752,"threshold_uncertainty_score":0.03237057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0295894747970118,"score_gpt":0.3135266936242811,"score_spread":0.2839372188272694,"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."}}