{"id":"W7127288362","doi":"10.1109/ccece64018.2025.11364473","title":"SEDM: A Multi-Modal Deep Learning Approach for Detecting Student Engagement","year":2025,"lang":"","type":"article","venue":"","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Student engagement; Deep learning; Mode (computer interface); Face (sociological concept); Online learning; Student activities; User engagement; Key (lock)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001925017,0.0003757634,0.0004100007,0.0003939403,0.0009367004,0.0001583077,0.0002610983,0.0003666352,0.001431895],"category_scores_gemma":[0.0002722615,0.000388482,0.0003359116,0.000374453,0.00006318071,0.00007169298,0.0001967406,0.0009154845,0.0001488804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000167389,"about_ca_system_score_gemma":0.00005784789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004457837,"about_ca_topic_score_gemma":0.00006093082,"domain_scores_codex":[0.9964866,0.0008848631,0.0007513511,0.0009435582,0.000215498,0.0007181197],"domain_scores_gemma":[0.9987435,0.0003740521,0.0002289528,0.0003186756,0.0002056273,0.0001291711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004387197,0.00537502,0.00574581,0.0008960658,0.001778164,0.000006489405,0.02023241,0.002854236,0.002066377,0.008350454,0.0007971741,0.9514591],"study_design_scores_gemma":[0.0423531,0.002658499,0.03244037,0.0004754473,0.001839443,0.00003106214,0.2452365,0.573146,0.005434222,0.0004713271,0.09368861,0.002225385],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02478414,0.000559623,0.8009824,0.0002342039,0.002105546,0.002331592,0.000003580567,0.000204276,0.1687946],"genre_scores_gemma":[0.8989199,0.00007903365,0.04169683,0.0008576105,0.0002241129,0.0006370085,0.00005082915,0.00004475363,0.05748988],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9492337,"threshold_uncertainty_score":0.9998567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07514444020838791,"score_gpt":0.3870130277168705,"score_spread":0.3118685875084826,"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."}}