{"id":"W3117666975","doi":"","title":"Digital literacies and competencies: Examining teacher candidates’ achievement, engagement, attitudes, and personalized learning in technology enhanced environments","year":2020,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Digital literacy in education","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mathematics education; Student engagement; Educational technology; Personalized learning; Psychology; Computer science; Pedagogy; Multimedia; Medical education; Teaching method; Medicine; Cooperative learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002095819,0.0002842981,0.0002858564,0.0004414245,0.0001924555,0.001009527,0.0007144034,0.000107502,0.000006762703],"category_scores_gemma":[0.0001057238,0.0003323343,0.00002919319,0.0005799238,0.0002042249,0.005109081,0.001109442,0.0005856676,0.00003978705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001439428,"about_ca_system_score_gemma":0.00004486023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000010141,"about_ca_topic_score_gemma":0.00002332343,"domain_scores_codex":[0.9981397,0.0001632451,0.0002546576,0.0007796502,0.0002640661,0.0003987041],"domain_scores_gemma":[0.9992027,0.0001083383,0.0001706225,0.000281723,0.00002736695,0.0002092522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002613193,0.00008287226,0.9812248,0.00004337973,0.00003118816,0.00005447234,0.005066797,0.000007973561,0.002781301,0.0003279548,1.148342e-7,0.01035295],"study_design_scores_gemma":[0.001402132,0.0003687725,0.9864846,0.0001992354,0.00001704936,0.00001870716,0.001707085,0.00002473663,0.0009258742,0.0001168913,0.008238524,0.0004963726],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925202,0.0001719256,0.005702811,0.0005908028,0.00005492747,0.0002310365,0.000006628891,0.0001715878,0.000550041],"genre_scores_gemma":[0.9963328,0.00006429723,0.0004764943,0.0002672776,0.00002205168,0.000003040119,0.00002309269,0.00001966434,0.002791317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009856582,"threshold_uncertainty_score":0.9999129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0622375693969062,"score_gpt":0.2931836028522048,"score_spread":0.2309460334552986,"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."}}