{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001597731,0.0001649037,0.0002277076,0.001125935,0.001549181,0.002854857,0.000329455,0.0004629847,0.002855497],"category_scores_gemma":[0.005957741,0.0001895118,0.0002258326,0.0005974449,0.0009316906,0.0008636679,0.002075608,0.0006854378,0.0005495544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000877133,"about_ca_system_score_gemma":0.001805037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006400288,"about_ca_topic_score_gemma":0.01264598,"domain_scores_codex":[0.9987742,0.0004005855,0.00009118849,0.00009903486,0.0002917286,0.0003432237],"domain_scores_gemma":[0.9968877,0.0006093913,0.0008947618,0.0001195312,0.0004939712,0.0009946137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001456574,0.001576894,0.834777,0.0001185384,0.00002371781,0.000641679,0.1217389,0.0001388914,0.002443336,0.0008171141,0.0004583914,0.03712002],"study_design_scores_gemma":[0.00001310491,0.0008019683,0.8088718,0.00008808096,0.00001868176,0.0004211636,0.1825637,0.0003807793,0.00138689,0.0001754411,0.005256311,0.0000219709],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99845,0.00001297862,0.00004521148,0.00004108747,0.000001336428,0.000008658561,0.000008472404,0.000001079189,0.001431164],"genre_scores_gemma":[0.9986334,0.00002749803,0.00008638322,0.00001484133,0.000001527379,0.00001431635,0.00002263897,0.000001010837,0.001198312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006400288,"threshold_uncertainty_score":0.01272607,"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."}}