{"id":"W2109268475","doi":"10.5539/jel.v2n2p8","title":"Comparing Student Engagement in Online and Face-to-Face Instruction in Health and Physical Education Teacher Preparation","year":2013,"lang":"en","type":"article","venue":"Journal of Education and Learning","topic":"Education and Learning Interventions","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Likert scale; Psychology; Face-to-face; Curriculum; Student engagement; Mathematics education; Significant difference; Medical education; Physical education; Perception; Class (philosophy); Blended learning; Pedagogy; Educational technology; Computer science; Medicine","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":[0.0006765489,0.00007476302,0.0001427453,0.0003823377,0.0001098699,0.0001826061,0.00008676312,0.00002234382,0.00001016412],"category_scores_gemma":[0.0001803165,0.00007285857,0.00001665686,0.0002249176,0.00001477999,0.0005482702,0.00004630566,0.0004468551,0.000002722151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000125401,"about_ca_system_score_gemma":0.0002941727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002025638,"about_ca_topic_score_gemma":0.00004103293,"domain_scores_codex":[0.9988688,0.0003916681,0.0003616787,0.0001528151,0.0001247152,0.0001003833],"domain_scores_gemma":[0.9993637,0.00005452132,0.0002792371,0.00006916776,0.00009142621,0.0001419013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000008517356,0.001361817,0.571145,0.00006525324,0.000009833037,9.749295e-8,0.1730538,0.003114626,0.0001514295,0.001558835,0.0004426506,0.2490881],"study_design_scores_gemma":[0.0003045581,0.0002459923,0.9187064,0.0002694713,0.000002289832,0.00002368879,0.06201486,0.01375971,0.000003919052,0.0001532771,0.004441467,0.00007437447],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909362,0.0004660973,0.002452123,0.005498732,0.0003216447,0.0001898253,2.806446e-8,0.0000081922,0.0001271389],"genre_scores_gemma":[0.9938059,0.0000778663,0.005127155,0.0002701201,0.0001039238,0.00001402351,0.000002223892,0.00000416084,0.0005946076],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3475614,"threshold_uncertainty_score":0.2971086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04067201679270861,"score_gpt":0.3958203870109224,"score_spread":0.3551483702182138,"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."}}