{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006655942,0.0001715449,0.0002065037,0.0003966621,0.0004723814,0.0002653682,0.00171742,0.00006179698,0.000001373621],"category_scores_gemma":[0.00006234097,0.0001878064,0.00004703775,0.001754588,0.00001146109,0.0008481938,0.0007462127,0.0004528232,0.0001556701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008455481,"about_ca_system_score_gemma":0.0000442011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004282703,"about_ca_topic_score_gemma":0.00001207924,"domain_scores_codex":[0.9982302,0.00001763757,0.0001803249,0.0006635382,0.0005269491,0.0003813672],"domain_scores_gemma":[0.9993598,0.00001983193,0.00005318941,0.0001978996,0.0001261435,0.0002430988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000150574,0.0002195774,0.01670654,0.0004074118,0.0001443384,0.00008460222,0.1277488,0.6533361,0.01657852,0.00697201,0.002259689,0.1753919],"study_design_scores_gemma":[0.0002536999,0.0001375136,0.0001503662,0.00009844961,0.00001882665,0.000003487091,0.002279677,0.9850734,0.0002765363,0.0001348977,0.0113301,0.0002430675],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5866246,0.00001761049,0.4052798,0.006106797,0.00007313102,0.0002427344,0.000004672869,0.001128652,0.0005220289],"genre_scores_gemma":[0.9773536,0.00003700546,0.01940438,0.0001872662,0.00006759632,0.000002280514,0.00002585975,0.00002253096,0.002899528],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.390729,"threshold_uncertainty_score":0.7658523,"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."}}