{"id":"W2594276145","doi":"10.24908/pceea.v0i0.6484","title":"GRADUATE ATTRIBUTE ASSESSMENT IN SOFTWARE ENGINEERING PROGRAM AT UNIVERSITY OF OTTAWA – CONTINUAL IMPROVEMENT PROCESS","year":2017,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; University of Ottawa","keywords":"Rubric; Grading (engineering); Visualization; Computer science; Process (computing); Software engineering; Scale (ratio); Graduate students; Software; Data science; Engineering management; Data mining; Engineering; Mathematics education; Civil engineering; Cartography; Programming language; Medical education; Psychology","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":[],"consensus_categories":[],"category_scores_codex":[0.0004936859,0.0001179718,0.0001771298,0.0001910797,0.000218812,0.0001300969,0.0008510779,0.00008717399,0.000002350515],"category_scores_gemma":[0.0008567921,0.0001286081,0.00006999431,0.000268232,0.00001626204,0.0003533709,0.0001085079,0.0002416278,0.000001247166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001565475,"about_ca_system_score_gemma":0.0007167574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004780646,"about_ca_topic_score_gemma":0.007856729,"domain_scores_codex":[0.9989753,0.00000399089,0.0002200633,0.0002024303,0.0003236745,0.0002745149],"domain_scores_gemma":[0.9985046,0.00002942783,0.0005907686,0.0001790111,0.0005684361,0.0001277582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000001114915,0.0001645454,0.9797969,0.0003866396,0.00008087,4.643666e-7,0.001374576,0.004682172,0.0007115458,0.006898938,0.00209225,0.003809999],"study_design_scores_gemma":[0.0003368881,0.00004939826,0.9222772,0.0002471691,0.00002698555,0.000001167287,0.0001757993,0.07100751,0.001646346,0.00008768918,0.003906518,0.0002373524],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910915,0.00001503982,0.0003654065,0.007091,0.0006208715,0.0003911316,0.0000181642,0.00009888827,0.0003080248],"genre_scores_gemma":[0.9909706,0.000003485789,0.008040141,0.00001844892,0.00004273901,0.000007652318,0.000004699235,0.00001142266,0.0009008552],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06632534,"threshold_uncertainty_score":0.7226939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008633109793604455,"score_gpt":0.246346333240242,"score_spread":0.2377132234466375,"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."}}