{"id":"W128295504","doi":"","title":"Analysis of students' actions during online invention activities - seeing the thinking through the numbers","year":2010,"lang":"en","type":"article","venue":"International Conference of Learning Sciences","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Schulze method; Computer science; Domain (mathematical analysis); Tracing; Intelligent tutoring system; Cognition; Mathematics education; Human–computer interaction; Cognitive science; Artificial intelligence; Psychology; Epistemology; Mathematics; Programming language","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":[0.0002977404,0.0002667115,0.00020466,0.00120553,0.0002113063,0.0005527309,0.0002068264,0.0003345119,0.00342506],"category_scores_gemma":[0.002316254,0.00008731704,0.0002320273,0.0006161979,0.0001791502,0.0002945446,0.0003838468,0.0003553829,0.0008787966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001674698,"about_ca_system_score_gemma":0.0001927611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001116206,"about_ca_topic_score_gemma":0.002114224,"domain_scores_codex":[0.9996456,0.00006293031,0.00002358748,0.0000828212,0.0001421322,0.0000428516],"domain_scores_gemma":[0.9986243,0.0008087498,0.0001511155,0.00008914091,0.0001783367,0.0001483655],"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":[0.001194221,0.0006677399,0.2428927,0.000457931,0.00009443716,0.001199932,0.01393435,0.003250812,0.1603442,0.001488176,0.002803178,0.5716723],"study_design_scores_gemma":[0.00003471675,0.0009779598,0.8947027,0.00008376161,0.00009389896,0.00138148,0.005420035,0.02929159,0.05575317,0.001350547,0.01083198,0.00007818304],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9846355,0.0001090329,0.009676474,0.00004187147,0.00001373381,0.00004886818,0.0005031318,0.0002067882,0.00476454],"genre_scores_gemma":[0.9896679,0.0001077432,0.006758912,0.00000997589,0.000004538907,0.0000306261,0.0003710591,0.0000235998,0.003025791],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00342506,"threshold_uncertainty_score":0.01145798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06604494723067422,"score_gpt":0.3536346666652556,"score_spread":0.2875897194345813,"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."}}