{"id":"W2476708502","doi":"10.1145/2930674.2930725","title":"Studying situated learning in a constructionist programming camp","year":2016,"lang":"en","type":"article","venue":"","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Situated; Strict constructionism; Constructionism; Documentation; Computer science; Situated learning; Artifact (error); Coding (social sciences); Scratch; Observational study; Exploit; Data science; Artificial intelligence; Mathematics education; Psychology; Epistemology; Sociology; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007412016,0.0001218654,0.0001390852,0.0001681619,0.0002862774,0.0002943246,0.0003711136,0.00005053717,0.0000152298],"category_scores_gemma":[0.0002517509,0.00008418945,0.00004100777,0.0004498513,0.000060102,0.0004047117,0.0001590659,0.0002863421,0.00007781328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007633892,"about_ca_system_score_gemma":0.0000537165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001736321,"about_ca_topic_score_gemma":0.0000603825,"domain_scores_codex":[0.9985879,0.0001959122,0.0002274344,0.0003918658,0.0001956109,0.0004012602],"domain_scores_gemma":[0.9994044,0.000164986,0.00008043267,0.0002390094,0.00003753126,0.00007361841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001952199,0.00002834717,0.05126777,0.000003458996,0.000004825339,0.00001526309,0.001305321,0.00005581433,0.0006274669,0.006594072,0.000008645585,0.9400871],"study_design_scores_gemma":[0.008627317,0.001229137,0.07831143,0.001317896,0.00002784943,0.0006834749,0.00723679,0.02383921,0.002815113,0.001302469,0.8716826,0.00292666],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1766409,0.00003522217,0.8196676,0.001210427,0.0002022751,0.0001467505,4.058578e-8,0.00126221,0.0008345057],"genre_scores_gemma":[0.8728624,0.000001983798,0.1258211,0.00002721674,0.0000264644,0.00001754868,2.896924e-7,0.000008686064,0.001234259],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9371604,"threshold_uncertainty_score":0.3433146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01711580143195026,"score_gpt":0.2482042891737154,"score_spread":0.2310884877417652,"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."}}