{"id":"W2147417908","doi":"10.19173/irrodl.v11i1.794","title":"Using mobile phones to improve educational outcomes: An analysis of evidence from Asia","year":2010,"lang":"en","type":"article","venue":"The International Review of Research in Open and Distributed Learning","topic":"Mobile Learning in Education","field":"Computer Science","cited_by":405,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mobile phone; Developing country; Information and Communications Technology; Educational technology; Mobile technology; Business; Economic growth; Computer science; Multimedia; Mobile device; Psychology; Telecommunications; Pedagogy; World Wide Web; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01689368,0.0006984876,0.002415176,0.006148555,0.0004693284,0.002471002,0.0009787178,0.0009079215,0.002922116],"category_scores_gemma":[0.04458922,0.0004727222,0.00317581,0.01139212,0.001215148,0.001593449,0.002003121,0.001198543,0.0004018802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001965713,"about_ca_system_score_gemma":0.005112177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006563074,"about_ca_topic_score_gemma":0.01165201,"domain_scores_codex":[0.9887284,0.004709695,0.003278855,0.0006254884,0.002286756,0.0003708504],"domain_scores_gemma":[0.9188481,0.05791208,0.0138989,0.0009266968,0.007519779,0.0008943552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003631613,0.0005120054,0.1678033,0.2320067,0.0216381,0.000852283,0.004549994,0.0005629765,0.0007565971,0.001127488,0.002093493,0.5644654],"study_design_scores_gemma":[0.001506284,0.005691308,0.5864348,0.2686319,0.07679563,0.002015896,0.01195903,0.0005563205,0.002746791,0.001158501,0.04235476,0.000148779],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1647395,0.8172618,0.0007699361,0.004144585,0.0001481665,0.0004994108,0.001218331,0.00001867097,0.01119958],"genre_scores_gemma":[0.3950386,0.6016077,0.0009776326,0.001350571,0.00008002549,0.0002744639,0.0003889492,0.00001636249,0.0002656377],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01689368,"threshold_uncertainty_score":0.08934343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1593056640524872,"score_gpt":0.5117964893059193,"score_spread":0.352490825253432,"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."}}