{"id":"W4400410907","doi":"10.1109/educon60312.2024.10578709","title":"Enhancing Students' Performance in Computer Science Through Tailored Instruction Based on their Programming Background","year":2024,"lang":"en","type":"article","venue":"","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Queen's University; Queen's University Belfast","keywords":"Computer science; Multimedia; Computer aided instruction; Mathematics education; Computer architecture; Psychology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001693291,0.0002099011,0.0001616929,0.0004073973,0.0003886253,0.001946362,0.001128643,0.00005656321,0.00000620884],"category_scores_gemma":[0.00001836916,0.0001663607,0.00005871098,0.001794281,0.000142574,0.001681315,0.0002747755,0.0005406641,0.00005305412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000238465,"about_ca_system_score_gemma":0.0001784529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007288645,"about_ca_topic_score_gemma":0.00002008287,"domain_scores_codex":[0.9975911,0.00009183026,0.0002929064,0.0008013845,0.0006673988,0.0005553729],"domain_scores_gemma":[0.999222,0.0001272992,0.00004989103,0.0004830202,0.00004570816,0.00007205083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005840844,0.00008905659,0.003404316,0.00006189533,0.000005090051,0.00001232915,0.004374401,0.007761775,0.0001569731,0.00408234,0.000003827202,0.9800422],"study_design_scores_gemma":[0.0004684038,0.000459347,0.01328709,0.0006580456,0.000002618303,0.00002511401,0.0003063644,0.9645976,0.002128661,0.00007255317,0.01761202,0.0003822129],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4047404,0.00002814038,0.5934302,0.00016412,0.0007788033,0.000143041,5.735937e-8,0.0005698499,0.0001453643],"genre_scores_gemma":[0.7485737,0.000002139117,0.251114,0.0001452529,0.00009502578,0.00001990342,0.000001033263,0.00001171443,0.00003729642],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9796599,"threshold_uncertainty_score":0.9990897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02108921862656898,"score_gpt":0.2886747494229081,"score_spread":0.2675855307963391,"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."}}