{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008568731,0.00008750104,0.0002469698,0.001119044,0.0001569649,0.00004596192,0.0003614994,0.0001026898,0.000001368488],"category_scores_gemma":[0.0002971545,0.00008424334,0.00001872978,0.0007537187,0.00003668828,0.0001081105,0.00004802592,0.001092087,3.480603e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000936694,"about_ca_system_score_gemma":0.0008961401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002181468,"about_ca_topic_score_gemma":0.000945503,"domain_scores_codex":[0.9989312,0.0001411355,0.0004144859,0.000146645,0.000134427,0.0002321018],"domain_scores_gemma":[0.9993533,0.0001104475,0.0002601013,0.0000497836,0.00008677806,0.0001395543],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001067066,0.00005358775,0.713239,0.00001902571,0.00002537612,0.00006128422,0.05161247,0.008674481,0.000008564253,0.002551366,0.00001751733,0.2237266],"study_design_scores_gemma":[0.01942196,0.009720126,0.2355429,0.002680264,0.0000524044,0.0005303361,0.5548626,0.04707663,0.0001001785,0.006697902,0.1219453,0.001369498],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9706942,0.0002007606,0.02458096,0.004259453,0.00009712717,0.0001386939,1.485716e-7,0.00002499656,0.000003687345],"genre_scores_gemma":[0.9626777,5.893922e-7,0.0372383,0.00002746471,0.00001354853,0.000006884469,4.735923e-7,0.00000678585,0.00002828551],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5032501,"threshold_uncertainty_score":0.4744633,"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."}}