{"id":"W2894784890","doi":"10.1007/978-3-319-95059-4_20","title":"Learning to Program a Humanoid Robot: Impact on Special Education Students","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Affordance; Coding (social sciences); Variety (cybernetics); TRACE (psycholinguistics); Task (project management); Computer science; Mathematics education; Exploratory research; Psychology; Data collection; Humanoid robot; Robot; Human–computer interaction; Pedagogy; Engineering; Artificial intelligence; Sociology","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":[0.0003671103,0.000800696,0.0003826656,0.0004334592,0.0005314978,0.00226364,0.0008399112,0.0007815824,0.06124924],"category_scores_gemma":[0.001539088,0.0001428422,0.0004898949,0.0003766038,0.0003913413,0.001634809,0.001881513,0.001468292,0.01290463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006382534,"about_ca_system_score_gemma":0.0012879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008165147,"about_ca_topic_score_gemma":0.002116166,"domain_scores_codex":[0.9997912,0.00002921405,0.000004248886,0.00003835126,0.00009343237,0.00004346393],"domain_scores_gemma":[0.9991405,0.0001911278,0.00003653231,0.00003881952,0.0001586968,0.0004343388],"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":[0.0001497884,0.0008161847,0.001210717,0.0003146692,0.000008283617,0.0001780922,0.001178396,0.0004180027,0.00365797,0.006175301,0.1238156,0.8620771],"study_design_scores_gemma":[0.0000815242,0.001768566,0.01896088,0.001332137,0.00005917413,0.001942471,0.004941947,0.00232819,0.01168214,0.02852355,0.9283228,0.00005657409],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1404253,0.02132548,0.01768828,0.01061675,0.003510343,0.0001452288,0.0005513343,0.002537384,0.8031999],"genre_scores_gemma":[0.1632213,0.01789786,0.01721305,0.001766648,0.000614793,0.000153197,0.001066894,0.0007444695,0.7973218],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06124924,"threshold_uncertainty_score":0.2048991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0216156915178248,"score_gpt":0.3458379643118781,"score_spread":0.3242222727940533,"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."}}