{"id":"W4307302859","doi":"10.52041/iase.icots11.t8a1","title":"The Big Picture: A Family of Instruments for Understanding University-Level Statistics and Data Science Attitudes","year":2022,"lang":"en","type":"article","venue":"Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics","topic":"Statistics Education and Methodologies","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Saint Vincent University","funders":"National Science Foundation","keywords":"Scope (computer science); Expectancy theory; Data science; Set (abstract data type); Computer science; Big data; Value (mathematics); Survey instrument; Data set; Mathematics education; Psychology; Statistics; Applied psychology; Mathematics; Data mining; Social psychology; Artificial intelligence; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"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":[0.03471639,0.001177003,0.000916991,0.01165178,0.001536663,0.002986386,0.001310231,0.00133587,0.005364189],"category_scores_gemma":[0.1266028,0.0008402598,0.00262751,0.01008515,0.002095166,0.01107472,0.00466111,0.002299403,0.001123769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001692564,"about_ca_system_score_gemma":0.003062648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001478368,"about_ca_topic_score_gemma":0.003130588,"domain_scores_codex":[0.9861835,0.007961345,0.001688097,0.0009758002,0.002881961,0.0003093417],"domain_scores_gemma":[0.852032,0.1069197,0.01581365,0.01140647,0.01146021,0.00236791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003601224,0.0003209915,0.2184061,0.002946701,0.0009228498,0.00007297064,0.01352836,0.0009089969,0.001479071,0.03726188,0.01011989,0.7136722],"study_design_scores_gemma":[0.0003489313,0.002008004,0.5145451,0.005731981,0.001917578,0.0005954008,0.02607111,0.009650256,0.004083214,0.2982911,0.1362761,0.0004812322],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2406178,0.01274415,0.6459469,0.0072628,0.000879068,0.007001914,0.01178301,0.003806032,0.06995828],"genre_scores_gemma":[0.4254058,0.006670872,0.5358533,0.002128103,0.0002257875,0.02076822,0.004986241,0.0003657803,0.003595875],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03471639,"threshold_uncertainty_score":0.1836001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3292477968378236,"score_gpt":0.4374442161397055,"score_spread":0.1081964193018818,"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."}}