{"id":"W2739911667","doi":"","title":"Qualitative, quantitative, and data mining methods for analyzing log data to characterize students' learning strategies and behaviors","year":2010,"lang":"en","type":"article","venue":"International Conference of Learning Sciences","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Educational data mining; Data science; Learning analytics; Qualitative property; Quantitative research; Quantitative analysis (chemistry); Cognition; Artificial intelligence; Machine learning; Psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1084785,0.002040565,0.001754974,0.01309687,0.002321074,0.0070633,0.002686271,0.001846135,0.003291741],"category_scores_gemma":[0.131119,0.001132956,0.002462162,0.01016907,0.00541995,0.005939413,0.003033974,0.003327154,0.0008578018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004641361,"about_ca_system_score_gemma":0.00684903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00296894,"about_ca_topic_score_gemma":0.00486897,"domain_scores_codex":[0.898991,0.07553592,0.005365765,0.002830159,0.01660819,0.0006688705],"domain_scores_gemma":[0.7426808,0.2142055,0.01034691,0.01333274,0.01827942,0.001154595],"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":[0.0002007321,0.0008882946,0.02528274,0.00703416,0.0008615269,0.000213444,0.01464996,0.006647967,0.008457683,0.2842292,0.01358916,0.6379451],"study_design_scores_gemma":[0.0003816425,0.002071064,0.03850885,0.01069684,0.0008137728,0.001869039,0.03873938,0.09079877,0.02366258,0.5503699,0.2408642,0.001223977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004129572,0.002153052,0.983465,0.002363432,0.0003064794,0.001829829,0.0006213748,0.0002824517,0.004848874],"genre_scores_gemma":[0.05045556,0.002838515,0.9351985,0.0008546012,0.0001746344,0.008124287,0.0003832452,0.0001209368,0.001849772],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1084785,"threshold_uncertainty_score":0.5736958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3193778205409949,"score_gpt":0.5534960642674233,"score_spread":0.2341182437264284,"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."}}