{"id":"W4366596271","doi":"10.1145/3544548.3581364","title":"Understanding Personal Data Tracking and Sensemaking Practices for Self-Directed Learning in Non-classroom and Non-computer-based Contexts","year":2023,"lang":"en","type":"article","venue":"","topic":"Mobile Learning in Education","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Sensemaking; Computer science; Tracking (education); Variety (cybernetics); Qualitative property; Human–computer interaction; Multimedia; Psychology; Artificial intelligence; Pedagogy; Machine learning","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":[0.007738987,0.0003200675,0.0002387888,0.001963124,0.002083152,0.006309143,0.000903331,0.0008629699,0.001403603],"category_scores_gemma":[0.01913515,0.0003517916,0.0003575965,0.001179531,0.003799385,0.009357317,0.003284021,0.0008813379,0.0001924303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002141064,"about_ca_system_score_gemma":0.002648124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00518101,"about_ca_topic_score_gemma":0.007505319,"domain_scores_codex":[0.9964287,0.002004572,0.0002247286,0.0005571386,0.0004435126,0.0003413275],"domain_scores_gemma":[0.9846111,0.009831256,0.002265497,0.001188433,0.001143231,0.0009605617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003978897,0.0001881529,0.1092956,0.0003243679,0.00002477547,0.0003266114,0.8150928,0.0002097629,0.00253104,0.00748735,0.0004843426,0.06399547],"study_design_scores_gemma":[0.00001766012,0.000165981,0.1662262,0.0007604062,0.00005446137,0.0004569955,0.7860934,0.003907286,0.002467934,0.01115423,0.02861237,0.00008300694],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9798381,0.000522938,0.009259339,0.001260701,0.00001911332,0.000100156,0.00005284206,0.00004629888,0.008900327],"genre_scores_gemma":[0.9969335,0.0001988334,0.002262399,0.00006047029,0.000002556538,0.00002878197,0.00001824485,0.000008050272,0.0004871594],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007738987,"threshold_uncertainty_score":0.04092818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1124520284362227,"score_gpt":0.339335491732201,"score_spread":0.2268834632959783,"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."}}