{"id":"W4205700957","doi":"10.22215/etd/2021-14677","title":"Modelling Programming Problem Solving in Python ACT-R","year":2021,"lang":"en","type":"dissertation","venue":"","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Python (programming language); Computer science; Programming language; Cognitive model; Software engineering; Think aloud protocol; Programming paradigm; Artificial intelligence; Cognition; Human–computer interaction; Usability; Psychology","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":[0.001586692,0.000660528,0.0002584732,0.0006766265,0.0007732773,0.002168918,0.001641605,0.0009869824,0.006676163],"category_scores_gemma":[0.00564086,0.0005319703,0.001251432,0.0004919569,0.002797196,0.001883119,0.001752753,0.001897226,0.001174933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002077089,"about_ca_system_score_gemma":0.002826652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01115787,"about_ca_topic_score_gemma":0.01254862,"domain_scores_codex":[0.9987406,0.0006976859,0.00007669155,0.0001520874,0.0002420369,0.00009094381],"domain_scores_gemma":[0.9970187,0.001988526,0.0002930987,0.0002958768,0.0002806244,0.0001232278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000141583,0.0002039701,0.00399739,0.0004315026,0.00005563978,0.000443552,0.006587223,0.3162699,0.00271083,0.6385019,0.004132156,0.0265244],"study_design_scores_gemma":[0.00005986985,0.00008177964,0.001191047,0.0001295496,0.00003474756,0.0001994056,0.0007827639,0.8373561,0.002415998,0.1213711,0.03633117,0.00004649285],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07908327,0.00009879739,0.8562737,0.001068174,0.00004961718,0.000704154,0.0008084348,0.002513382,0.05940052],"genre_scores_gemma":[0.3747591,0.0001902514,0.6078151,0.0002452422,0.00001456878,0.001539475,0.0007667862,0.0002975829,0.01437186],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01115787,"threshold_uncertainty_score":0.02233398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02099950625949499,"score_gpt":0.2723803025703498,"score_spread":0.2513807963108548,"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."}}