{"id":"W2141042780","doi":"10.24908/pceea.v0i0.5893","title":"Assessing Class Performance and Progress using Grade Self-Estimation in Undergraduate Embedded Systems Courses","year":2015,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Experimental Learning in Engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; University of Calgary","keywords":"Computer science; Class (philosophy); Process (computing); Term (time); Mathematics education; Software; Modal; Software engineering; Artificial intelligence; Programming language; Psychology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005395783,0.0001927283,0.0001991212,0.0003761968,0.00008766406,0.0002684489,0.000166689,0.0001474388,5.396949e-7],"category_scores_gemma":[0.00026579,0.0002119818,0.00002863533,0.0005390898,0.00001766138,0.0007560653,0.00002126563,0.0002797537,0.000001567535],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003951563,"about_ca_system_score_gemma":0.0003182327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008943873,"about_ca_topic_score_gemma":0.0001544199,"domain_scores_codex":[0.9988424,0.00001061635,0.0003196744,0.0001628782,0.0003234133,0.0003410207],"domain_scores_gemma":[0.9992916,0.00003444844,0.0001726301,0.00008150518,0.000217373,0.0002024435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[7.424529e-7,0.00002801895,0.1254874,0.0005619234,0.00005357082,1.522196e-7,0.001599057,0.8680834,0.002259809,0.0009315053,0.0007306081,0.0002638083],"study_design_scores_gemma":[0.0001947969,0.000008624394,0.0295912,0.0004097391,0.00002646374,0.00001157292,0.000732339,0.9658781,0.002088613,0.00001916126,0.0007957364,0.0002436016],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964315,0.0005000269,0.0000792608,0.0002456716,0.001414443,0.0003273524,0.000002720022,0.0002351644,0.0007638529],"genre_scores_gemma":[0.9947708,0.0000134215,0.004952162,0.000009708778,0.00007785246,0.00004921555,0.000004808111,0.00005883692,0.00006320523],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0977948,"threshold_uncertainty_score":0.9998721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01226872026575444,"score_gpt":0.2466425322404117,"score_spread":0.2343738119746572,"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."}}