{"id":"W3206988405","doi":"10.1093/iwc/iwab026","title":"Design Strategies for Collaborative Learning in Tangible Tabletops: Positive Interdependence and Reflective Pauses","year":2021,"lang":"en","type":"article","venue":"Interacting with Computers","topic":"Innovative Teaching and Learning Methods","field":"Psychology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Pacific Institute for Climate Solutions","keywords":"Set (abstract data type); Computer science; Collaborative design; Collaborative learning; Human–computer interaction; Control (management); Psychology; Knowledge management; Artificial intelligence; Systems design","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001123532,0.0002120631,0.0003150369,0.0001973109,0.0002079819,0.0002232844,0.0001072517,0.00007736764,0.00003553671],"category_scores_gemma":[0.0007964839,0.0001941455,0.00002438193,0.0005620284,0.00008305729,0.0003201096,0.0000637835,0.0007716867,0.000003476759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001106772,"about_ca_system_score_gemma":0.0001850451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001511568,"about_ca_topic_score_gemma":0.00005788487,"domain_scores_codex":[0.9971557,0.001611876,0.0002553075,0.0005313953,0.000104276,0.000341441],"domain_scores_gemma":[0.9922057,0.006956193,0.0002276203,0.0001307053,0.0004419833,0.00003776353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.006983718,0.0006603357,0.02608099,0.000157618,0.001722657,0.001687528,0.6772696,0.05736684,0.05190887,0.02628897,0.004558299,0.1453145],"study_design_scores_gemma":[0.01095451,0.01277267,0.0522509,0.009867523,0.0002346789,0.002272516,0.8096786,0.0401162,0.04037939,0.007132427,0.01093584,0.003404805],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1894444,0.0001442205,0.8042607,0.0003196892,0.0009433585,0.0002817919,0.000002557399,0.00009825556,0.004504994],"genre_scores_gemma":[0.8259123,0.000001754182,0.173084,0.0002316861,0.00006801804,0.00005648693,0.000008127292,0.000027577,0.0006101056],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6364679,"threshold_uncertainty_score":0.7917022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05286182832201891,"score_gpt":0.3916423774957033,"score_spread":0.3387805491736844,"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."}}