{"id":"W4392681555","doi":"10.22318/icls2023.831011","title":"Data Comics: Using Narratives to Engage Students in Data Reasoning","year":2023,"lang":"en","type":"article","venue":"Proceedings.","topic":"Statistics Education and Methodologies","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"National Science Foundation","keywords":"Comics; Narrative; Curriculum; Qualitative property; Computer science; Thematic analysis; Storytelling; Mathematics education; Psychology; Pedagogy; Sociology; Qualitative research; Art; Literature; Social science; Artificial intelligence","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":[0.01044487,0.0008822801,0.0002944848,0.001697647,0.0024645,0.00750991,0.001418258,0.0009504656,0.004765024],"category_scores_gemma":[0.0257698,0.0004977894,0.0004555508,0.001280404,0.00475899,0.007239278,0.008851655,0.001834829,0.0008709489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00131547,"about_ca_system_score_gemma":0.002649893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006500187,"about_ca_topic_score_gemma":0.002031289,"domain_scores_codex":[0.9937069,0.004690215,0.0002805241,0.00044073,0.0005011539,0.0003804874],"domain_scores_gemma":[0.9697675,0.02204277,0.002287941,0.0032415,0.000903804,0.00175653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001979982,0.0004108632,0.01672165,0.0006115185,0.00003517067,0.0008988342,0.8022519,0.0006060183,0.009791125,0.04005573,0.006172933,0.1222462],"study_design_scores_gemma":[0.00009577945,0.0004673482,0.009455984,0.00081781,0.000066105,0.001894227,0.5725901,0.004466801,0.02262051,0.03793347,0.3494591,0.0001328119],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7955968,0.0004870743,0.1562269,0.00402796,0.0001849444,0.0006490854,0.0005858677,0.001097341,0.04114388],"genre_scores_gemma":[0.8976943,0.0004400065,0.09258563,0.0003786837,0.00002826895,0.0005397956,0.0002843636,0.0002127246,0.00783632],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01044487,"threshold_uncertainty_score":0.05523837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7323243029860248,"score_gpt":0.5840036994735623,"score_spread":0.1483206035124625,"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."}}