{"id":"W2909847347","doi":"10.24908/pceea.v0i0.13086","title":"DEFINING THE APPROPRIATE COURSE PROJECT FOR FOSTERING THE EXPECTED COGNITIVE COMPETENCIES: EBD APPROACH TO AN ENGINEERING DESIGN COURSE","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":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia","keywords":"Course (navigation); Project-based learning; Curriculum; Set (abstract data type); Engineering management; Computer science; Engineering; Knowledge management; Mathematics education; Psychology; Pedagogy","routes":{"ca_aff":false,"ca_fund":true,"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":[0.005289921,0.0006226437,0.0002927506,0.001704262,0.00161416,0.003554334,0.001247632,0.001334908,0.002130159],"category_scores_gemma":[0.00643881,0.0003817995,0.0003451444,0.0009840342,0.002460093,0.001652624,0.003551049,0.00131719,0.0003827054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004109377,"about_ca_system_score_gemma":0.007457763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004974185,"about_ca_topic_score_gemma":0.01167594,"domain_scores_codex":[0.995752,0.002763632,0.0002226928,0.000354194,0.0006456457,0.00026186],"domain_scores_gemma":[0.9968925,0.001295574,0.0004039355,0.0002824449,0.0006659841,0.0004595623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002014878,0.002585523,0.01753553,0.001756318,0.00003818117,0.001408485,0.02537115,0.03815972,0.03257271,0.27535,0.004110521,0.6009103],"study_design_scores_gemma":[0.0004253316,0.00280237,0.03622291,0.00362295,0.0001737686,0.002783022,0.0621294,0.3931509,0.05757593,0.16017,0.2806064,0.0003369788],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1031917,0.0003561246,0.8468987,0.001815458,0.0000521773,0.002518621,0.0001134846,0.000238923,0.04481483],"genre_scores_gemma":[0.2501036,0.0002025332,0.745039,0.0001319211,0.000006905394,0.001091894,0.00007844048,0.00001813652,0.003327422],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005289921,"threshold_uncertainty_score":0.02981579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01627839700010135,"score_gpt":0.2395627310474161,"score_spread":0.2232843340473148,"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."}}