{"id":"W3198198404","doi":"10.5539/jel.v10n5p76","title":"Systematizing ICT Education Curriculum for Developing Computational Thinking: Case Studies of Curricula in the United States, Australia, and the United Kingdom","year":2021,"lang":"en","type":"article","venue":"Journal of Education and Learning","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Curriculum; Information and Communications Technology; Computational thinking; Curriculum framework; Sociology; Pedagogy; Curriculum development; Perspective (graphical); Social studies; Engineering ethics; Mathematics education; Political science; Psychology; Engineering; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003671989,0.00009893165,0.0002178062,0.0003348196,0.0005081176,0.0002812083,0.0001810642,0.00003246433,5.232291e-7],"category_scores_gemma":[0.001678596,0.00006083534,0.00004873225,0.000762682,0.00007169553,0.0002138158,0.00004829437,0.0004816279,1.247501e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005350521,"about_ca_system_score_gemma":0.0003283531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00048347,"about_ca_topic_score_gemma":0.00001167855,"domain_scores_codex":[0.9978849,0.001150446,0.0004960212,0.000128066,0.0002200403,0.0001205471],"domain_scores_gemma":[0.9967493,0.001644099,0.0006959309,0.00009027204,0.0007879693,0.0000324273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003159168,0.0005241883,0.03022123,0.001532287,0.0002749895,0.00006838683,0.3683774,0.09028581,0.00001528442,0.4257491,0.000878074,0.08204161],"study_design_scores_gemma":[0.003644585,0.000363972,0.01252007,0.008100301,0.0002978517,0.02413083,0.6790805,0.1634213,0.00002343345,0.01204961,0.09574723,0.0006203524],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9171252,0.001572429,0.07686122,0.003875245,0.0004003643,0.0001520169,1.371194e-7,0.000009477308,0.000003891692],"genre_scores_gemma":[0.9307529,0.00004735903,0.0687835,0.0002740492,0.00008332395,0.00001096906,0.00001085951,0.000004861837,0.00003215631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4136995,"threshold_uncertainty_score":0.3908081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07280025120308513,"score_gpt":0.3839454795709631,"score_spread":0.3111452283678779,"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."}}