{"id":"W4401302950","doi":"10.1016/j.chbah.2024.100089","title":"Integrating generative AI in data science programming: Group differences in hint requests","year":2024,"lang":"en","type":"article","venue":"Computers in Human Behavior Artificial Humans","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"British Columbia Knowledge Development Fund; Canada Research Chairs; Canada Foundation for Innovation","keywords":"Generative grammar; Computer science; Visibility; Group (periodic table); Artificial intelligence; Generative model; Data science; Human–computer interaction","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002308472,0.0002094022,0.0003385262,0.0009418614,0.0004568282,0.002075741,0.0005566621,0.0006794251,0.003706013],"category_scores_gemma":[0.02848818,0.0002545192,0.0002068642,0.0004322275,0.0008810057,0.001673481,0.001864387,0.001120389,0.0007130726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003331876,"about_ca_system_score_gemma":0.0005156757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001269941,"about_ca_topic_score_gemma":0.001692888,"domain_scores_codex":[0.9977677,0.0007128502,0.0003203647,0.0003793147,0.0005242747,0.0002954923],"domain_scores_gemma":[0.977277,0.01399967,0.003720561,0.001548929,0.001452943,0.00200084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001799547,0.003564812,0.7797004,0.0002585305,0.0001766625,0.0004661412,0.08944582,0.0007978596,0.03126764,0.001547166,0.0006806707,0.09029473],"study_design_scores_gemma":[0.00005692037,0.001315396,0.952749,0.00009107029,0.00006688596,0.0004091924,0.03262645,0.002432927,0.004282119,0.00243179,0.00347694,0.00006126783],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985246,0.00004534414,0.0003148504,0.00004919249,0.000004341642,0.00001934309,0.00001895903,0.000006979441,0.001016566],"genre_scores_gemma":[0.9987426,0.00004472761,0.0003615826,0.00003471371,0.000002715731,0.0000394089,0.00004268284,0.00000887793,0.0007226381],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003706013,"threshold_uncertainty_score":0.01239783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09830740770571145,"score_gpt":0.3848576682036917,"score_spread":0.2865502604979802,"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."}}