{"id":"W1772603559","doi":"10.24908/pceea.v0i0.4914","title":"ExCEL: A Unique Approach to Providing Experiential Learning Opportunities","year":2013,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Experiential learning; Discipline; Experiential education; Sustainability; Active learning (machine learning); Open learning; Engineering education; Learning sciences; Educational technology; Work (physics); Knowledge management; Engineering management; Engineering; Computer science; Engineering ethics; Cooperative learning; Pedagogy; Teaching method; Psychology; Sociology; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0002558262,0.0001923601,0.000172176,0.0003930714,0.0001412762,0.0001687855,0.0003016496,0.0001829949,0.00005087915],"category_scores_gemma":[0.0004262906,0.0001913043,0.00007131268,0.0005741986,0.00001487814,0.0003269595,0.00002709382,0.000319097,0.00002288293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001539532,"about_ca_system_score_gemma":0.0002932603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003678584,"about_ca_topic_score_gemma":0.0001666696,"domain_scores_codex":[0.9988102,0.000005545765,0.0002943928,0.0001778864,0.0003015498,0.0004104019],"domain_scores_gemma":[0.9990041,0.00002603427,0.00009413251,0.00009619893,0.0003660407,0.0004134972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005151944,0.0003832259,0.02010354,0.005575048,0.000564479,2.093264e-7,0.03040257,0.08229264,0.0882576,0.04502857,0.7024708,0.02491615],"study_design_scores_gemma":[0.0005932485,0.00009111436,0.1005734,0.001051657,0.0001446851,0.00002445992,0.009211378,0.1781056,0.02904179,0.0005611243,0.6782564,0.002345181],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9394723,0.0002126296,0.001289657,0.00567701,0.005272053,0.001472489,0.00001468347,0.001002318,0.0455869],"genre_scores_gemma":[0.9933397,0.00001388915,0.002316335,0.0001466159,0.0003072093,0.0004312714,0.00001565783,0.00006182666,0.003367466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09581298,"threshold_uncertainty_score":0.7801163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009324556376789757,"score_gpt":0.177258445761927,"score_spread":0.1679338893851372,"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."}}