{"id":"W2390567443","doi":"10.15388/infedu.2016.05","title":"Data Mining of Undergraduate Course Evaluations","year":2016,"lang":"en","type":"article","venue":"Informatics in Education","topic":"Evaluation of Teaching Practices","field":"Social Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Course (navigation); Computer science; Set (abstract data type); Regression analysis; Quality (philosophy); Mathematics education; Course evaluation; Linear regression; Higher education; Data science; Psychology; Machine learning; 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":[0.004777795,0.0005843772,0.0008259506,0.006261894,0.0004358171,0.001500413,0.0009125808,0.0006370072,0.0008727828],"category_scores_gemma":[0.04511634,0.0001957714,0.0005387238,0.00726232,0.0003171624,0.001078058,0.0007593437,0.001010104,0.0006401376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007813988,"about_ca_system_score_gemma":0.0008484292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004172766,"about_ca_topic_score_gemma":0.005514023,"domain_scores_codex":[0.9940128,0.001996613,0.0008680063,0.000978105,0.001782508,0.0003619769],"domain_scores_gemma":[0.9600061,0.02213247,0.006309517,0.003161485,0.007156943,0.001233537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003759146,0.0007184727,0.7572396,0.0003892219,0.0003000998,0.0002733496,0.0008094099,0.006917126,0.00175348,0.001104467,0.01300062,0.2171181],"study_design_scores_gemma":[0.00004197249,0.0004249429,0.9200367,0.0001353165,0.000103787,0.0003407151,0.001228958,0.05514465,0.00373777,0.003935295,0.01479467,0.00007525321],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9486242,0.001253276,0.02276918,0.0009095828,0.000107931,0.0003092571,0.02063007,0.0004124964,0.004984143],"genre_scores_gemma":[0.9592469,0.0002816574,0.01408299,0.00009401837,0.0000891101,0.0003231668,0.02458452,0.00003941564,0.001258287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006261894,"threshold_uncertainty_score":0.02526766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2471596697972253,"score_gpt":0.5448979039769878,"score_spread":0.2977382341797624,"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."}}