{"id":"W1935141251","doi":"10.24908/pceea.v0i0.5789","title":"ENGINEERS AS LIFE-LONG LEARNERS: PEDAGOGICAL TOOLS FOR ENGINEERING GRADUATE ATTRIBUTE DEVELOPMENT","year":2015,"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":"Carleton University","funders":"","keywords":"Toolbox; Experiential learning; Mathematics education; Bloom's taxonomy; Curriculum; Psychology; Taxonomy (biology); Computer science; Engineering education; Cognition; Pedagogy; Engineering; Engineering management","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007471027,0.0003689311,0.0003296898,0.0004505738,0.0001316646,0.0002589006,0.0004604574,0.0002528896,0.0000193258],"category_scores_gemma":[0.003285574,0.0003841149,0.0001421498,0.0007461364,0.00001173605,0.0004519475,0.00003369704,0.0003898031,0.00003913436],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004044618,"about_ca_system_score_gemma":0.001724246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003383136,"about_ca_topic_score_gemma":0.0002938733,"domain_scores_codex":[0.9978803,0.000004646918,0.0005730966,0.0002856415,0.0005841732,0.0006721659],"domain_scores_gemma":[0.9979324,0.0001038358,0.0001732665,0.0001539061,0.0008179979,0.0008185887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001793401,0.0003272659,0.02762236,0.00292288,0.001468705,0.000001093531,0.02849284,0.5942613,0.002950118,0.02048322,0.3115182,0.009934073],"study_design_scores_gemma":[0.00173211,0.00008570866,0.1016373,0.0008506161,0.0002343189,0.00003450886,0.006732598,0.05966156,0.01759802,0.0001121521,0.8086368,0.002684324],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9779926,0.0006198426,0.003093011,0.003548717,0.009266122,0.001647859,0.00004478037,0.001131515,0.002655531],"genre_scores_gemma":[0.9895282,0.00001927002,0.00724181,0.0001699852,0.0003882197,0.0004489948,0.00006540563,0.0001197078,0.00201841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5345998,"threshold_uncertainty_score":0.9998611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06439392543325248,"score_gpt":0.2610895494365659,"score_spread":0.1966956240033134,"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."}}