{"id":"W2908691693","doi":"10.24908/pceea.v0i0.12983","title":"Using a common course syllabus as part of the quality control loop and accreditation data collection process","year":2018,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Engineering Education and Curriculum Development","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Syllabus; Accreditation; Control (management); Process (computing); Quality (philosophy); Computer science; Mandate; Course (navigation); Engineering management; Medical education; Engineering; Mathematics education; Psychology; Political science; Medicine; Artificial intelligence; Programming language","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06977849,0.001077015,0.001366208,0.01520193,0.003213949,0.004844223,0.001745039,0.0008274785,0.006788716],"category_scores_gemma":[0.1514767,0.001148542,0.0006745558,0.008442277,0.001397568,0.002648771,0.0036224,0.001805338,0.005885113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005251064,"about_ca_system_score_gemma":0.01892212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02024898,"about_ca_topic_score_gemma":0.02208629,"domain_scores_codex":[0.9361649,0.02477045,0.01247879,0.007543226,0.01745854,0.001583989],"domain_scores_gemma":[0.6690125,0.0851328,0.03237588,0.05053745,0.1551852,0.007756166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008313748,0.001373879,0.09393757,0.00160075,0.0001309484,0.0001647618,0.006947733,0.002498406,0.03703346,0.005545875,0.04318662,0.8067486],"study_design_scores_gemma":[0.0003107318,0.002721895,0.4072014,0.001226618,0.0002496122,0.0003906845,0.004636229,0.06442202,0.1506124,0.007738394,0.3597288,0.0007611155],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.135778,0.0005540593,0.7369635,0.002640034,0.0009601978,0.04852162,0.01720771,0.03030813,0.02706681],"genre_scores_gemma":[0.2202557,0.0002691855,0.7295138,0.0008501982,0.0003835105,0.02440829,0.0126732,0.001674533,0.009971655],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06977849,"threshold_uncertainty_score":0.3690283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01959756013748607,"score_gpt":0.2853589548981002,"score_spread":0.2657613947606141,"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."}}