{"id":"W3084243275","doi":"10.21432/cjlt27857","title":"Computational Thinking in Classrooms: A Study of a Professional Development for STEM Teachers in High Needs Schools","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Learning and Technology","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Maryland Higher Education Commission","keywords":"Thematic analysis; Mathematics education; Professional development; Psychology; Faculty development; Qualitative research; Pedagogy; Multimethodology; Process (computing); Content analysis; Semi-structured interview; Sociology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006947999,0.0004702749,0.0007790709,0.001955483,0.01218236,0.005851547,0.001455224,0.00159682,0.00174359],"category_scores_gemma":[0.01483831,0.001148009,0.000401641,0.000915329,0.006475461,0.002613176,0.005187028,0.003728502,0.0005833519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00414867,"about_ca_system_score_gemma":0.008567859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009131412,"about_ca_topic_score_gemma":0.03245658,"domain_scores_codex":[0.9936379,0.003737106,0.0001841014,0.0005854844,0.0007744546,0.001080963],"domain_scores_gemma":[0.9882498,0.005349618,0.0008526198,0.0004738389,0.001420693,0.003653519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00003807788,0.001103629,0.01037667,0.000092453,0.00000363417,0.000608551,0.9746368,0.00003422836,0.001114323,0.0005866294,0.0003468702,0.01105818],"study_design_scores_gemma":[0.00003462844,0.0004546048,0.01543409,0.0000931131,0.000008181572,0.0007482715,0.969282,0.0001683319,0.0008082183,0.000466003,0.01247713,0.00002549506],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996083,0.0001426342,0.000661969,0.0005811388,0.00001923648,0.0001002517,0.00001259691,0.00001217707,0.002386917],"genre_scores_gemma":[0.9949125,0.0002675487,0.001482254,0.0002684025,0.00001060495,0.0001017529,0.00001836108,0.00001673457,0.002921881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01218236,"threshold_uncertainty_score":0.03674495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01804343049322795,"score_gpt":0.2539151421843611,"score_spread":0.2358717116911332,"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."}}