{"id":"W4280592718","doi":"10.1007/s10639-022-11068-7","title":"Dropout prediction in Moocs using deep learning and machine learning","year":2022,"lang":"en","type":"article","venue":"Education and Information Technologies","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Artificial intelligence; Machine learning; Dropout (neural networks); Computer science; Deep learning; Big data; Learning analytics; Context (archaeology); Educational technology; Educational data mining; Predictive analytics; Active learning (machine learning); Data science; Mathematics education; Psychology; Data mining","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":[],"consensus_categories":[],"category_scores_codex":[0.0002626763,0.00006673465,0.00007161005,0.000461085,0.0003910321,0.0001329666,0.000129828,0.00004140729,0.000008793276],"category_scores_gemma":[0.0002126462,0.00006957903,0.000009940785,0.0004665943,0.00003277637,0.001308224,0.0002538504,0.0004342668,0.000002889384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000625033,"about_ca_system_score_gemma":0.00005253031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003280338,"about_ca_topic_score_gemma":0.000001480395,"domain_scores_codex":[0.9994375,0.00004395964,0.0001910839,0.0001012961,0.0001224578,0.0001036776],"domain_scores_gemma":[0.9997138,0.00002514632,0.0001270904,0.00008366471,0.00003495966,0.00001533656],"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":[0.000002631178,0.0000390639,0.09675474,0.00002936253,0.000004265828,2.371531e-7,0.003382138,0.01281719,0.00005359628,0.0304667,0.00003340677,0.8564167],"study_design_scores_gemma":[0.0001365706,0.00007631415,0.002862557,0.00001079306,0.000002271747,0.00002456881,0.01483761,0.9351939,0.00005366357,0.001895484,0.04481817,0.00008809741],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8573351,0.002207551,0.125796,0.009722322,0.0005375196,0.0002644287,0.000003044279,0.002053191,0.002080877],"genre_scores_gemma":[0.990513,0.000293167,0.008899886,0.00007109862,0.000008077638,0.00001389694,0.00002228678,0.000002626802,0.0001759358],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9223767,"threshold_uncertainty_score":0.3007542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008235233686771091,"score_gpt":0.2477563655477561,"score_spread":0.239521131860985,"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."}}