{"id":"W2942549445","doi":"10.19173/irrodl.v20i2.3730","title":"Exploring Demographics and Students’ Motivation as Predictors of Completion of a Massive Open Online Course","year":2019,"lang":"en","type":"article","venue":"The International Review of Research in Open and Distributed Learning","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Massive open online course; Affect (linguistics); Reputation; Logistic regression; Higher education; Psychology; Demographics; Medical education; Distance education; Mathematics education; Computer science; Medicine; Demography; Sociology","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":[0.003748421,0.00006652752,0.0002611302,0.0001342062,0.0000555315,0.0001139893,0.001761215,0.00002045164,0.0000147062],"category_scores_gemma":[0.001316069,0.00004932596,0.00002823817,0.0005935735,0.0001293661,0.0004568098,0.001946225,0.0003631738,0.000001084486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002388798,"about_ca_system_score_gemma":0.0001065686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003207295,"about_ca_topic_score_gemma":0.000007558118,"domain_scores_codex":[0.998175,0.0003872311,0.0003775548,0.0001910773,0.0007522281,0.0001168723],"domain_scores_gemma":[0.9982533,0.0007204967,0.0002887558,0.0001990904,0.0004984548,0.00003992809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004554208,0.0002920145,0.9622458,0.00100714,0.00007417953,0.000002435602,0.0002912079,0.0007290558,0.0001455161,0.0271118,0.00005446492,0.008000823],"study_design_scores_gemma":[0.001823212,0.0007040053,0.9127678,0.02095908,0.00002727909,0.00001031866,0.003849087,0.05312344,0.0001543903,0.003170729,0.003244824,0.0001657867],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990898,0.001451555,0.000718257,0.00603359,0.00004550263,0.0005182428,0.00002673363,0.000004531176,0.0003036517],"genre_scores_gemma":[0.9860203,0.01328689,0.0004837658,0.00003232076,0.00001253591,0.00001129772,0.00008326746,0.000003781732,0.00006581225],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05239439,"threshold_uncertainty_score":0.3272804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1768374017492916,"score_gpt":0.4568437125411388,"score_spread":0.2800063107918472,"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."}}