{"id":"W2201189832","doi":"10.14742/ajet.1869","title":"Blending for student engagement: Lessons learned for MOOCs and beyond","year":2015,"lang":"en","type":"article","venue":"Australasian Journal of Educational Technology","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"University of Alberta; University of Central Florida","keywords":"Immediacy; Student engagement; Agency (philosophy); Mathematics education; Educational technology; Pedagogy; Higher education; Blended learning; Qualitative research; Digital learning; Psychology; Computer science; Sociology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01052662,0.0008545512,0.0007673407,0.000951706,0.003001384,0.00899594,0.003222398,0.002820414,0.003749837],"category_scores_gemma":[0.01635919,0.0003144056,0.001157471,0.0007077533,0.003571727,0.009312454,0.006737579,0.004116256,0.001151779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001994152,"about_ca_system_score_gemma":0.0034092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001782346,"about_ca_topic_score_gemma":0.003333509,"domain_scores_codex":[0.9933582,0.003836558,0.000227593,0.0006056582,0.001084793,0.0008871131],"domain_scores_gemma":[0.9854621,0.009337701,0.0003224741,0.001226232,0.0009573753,0.002694028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002234175,0.00155063,0.007587543,0.001334093,0.00005488092,0.0005014643,0.04969199,0.001041609,0.003008492,0.02278828,0.01416417,0.8980534],"study_design_scores_gemma":[0.0002338157,0.003750796,0.02147253,0.00641232,0.0001405052,0.001304137,0.1687628,0.009007025,0.01051534,0.1875303,0.5905347,0.0003357769],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5283133,0.02870947,0.1513677,0.1569624,0.004635973,0.002745872,0.000316047,0.002128917,0.1248204],"genre_scores_gemma":[0.8454593,0.009819515,0.1226291,0.005126681,0.0007078888,0.001629988,0.0002604013,0.0004054451,0.0139617],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01052662,"threshold_uncertainty_score":0.05567074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08092950516696247,"score_gpt":0.4096362372722358,"score_spread":0.3287067321052733,"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."}}