{"id":"W3002447953","doi":"10.24908/pceea.vi0.13768","title":"DEVELOPING A FRAMEWORK TO EVALUATE INDIVIDUAL LEARNING IN ENGINEERING DESIGN PROBLEMS – PART 1: TEACHING THROUGH SIMULACRA OF REAL-WORLD PROBLEMS","year":2019,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Engineering Education and Curriculum Development","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba","keywords":"Cornerstone; Capstone; Dilemma; Context (archaeology); Problem-based learning; Engineering education; Computer science; Mathematics education; Engineering design process; Preference; Simple (philosophy); Engineering management; Engineering; Mathematics; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.00139968,0.0003283957,0.0003980933,0.0008005484,0.00008726295,0.000107104,0.000476077,0.0002133004,0.00003253386],"category_scores_gemma":[0.001230038,0.0003569798,0.00008837711,0.001529722,0.00000738608,0.0003322091,0.00005154055,0.0007558142,0.00001918108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003498148,"about_ca_system_score_gemma":0.0007346442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001828322,"about_ca_topic_score_gemma":0.00110232,"domain_scores_codex":[0.9977674,0.00001977243,0.000732024,0.0003072454,0.0005662245,0.000607345],"domain_scores_gemma":[0.9988335,0.0001842309,0.0002693783,0.0001633828,0.0003490128,0.0002004738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.000001064001,0.00002795905,0.04161536,0.0008597703,0.00009003861,4.253089e-8,0.005336256,0.9395931,0.001276983,0.009632262,0.001211223,0.0003559691],"study_design_scores_gemma":[0.001577677,0.0001667941,0.4767607,0.01648077,0.0002367957,0.000009760383,0.002818129,0.3513337,0.0166795,0.002209606,0.1279347,0.003791776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9782749,0.0002648645,0.006524051,0.002261377,0.005112588,0.002808118,0.00001655809,0.0006610619,0.004076513],"genre_scores_gemma":[0.9672294,0.00003266946,0.03145587,0.00009069165,0.0001017083,0.0002476681,0.00001200567,0.0001036318,0.0007263691],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5882593,"threshold_uncertainty_score":0.9998882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01669677142628352,"score_gpt":0.2430823749507485,"score_spread":0.2263856035244649,"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."}}