{"id":"W3163485689","doi":"10.1111/bjet.13122","title":"Creating technology‐enabled lifelong learning: A heutagogical approach","year":2021,"lang":"en","type":"article","venue":"British Journal of Educational Technology","topic":"Educational Leadership and Innovation","field":"Social Sciences","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"Athabasca University; Université de Sherbrooke; University of Calgary","funders":"","keywords":"Lifelong learning; Experiential learning; Blended learning; Educational technology; Computer science; Synchronous learning; Competence (human resources); Context (archaeology); Learning sciences; Active learning (machine learning); Instructional design; Cooperative learning; Knowledge management; Pedagogy; Teaching method; Psychology; Multimedia; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009491483,0.000101597,0.0002486413,0.0005902918,0.00078311,0.0001379281,0.0003995823,0.0003906371,0.0009501134],"category_scores_gemma":[0.009929961,0.0001288188,0.00008854269,0.00249562,0.0005615362,0.0003202191,0.00004706894,0.0009730547,0.0000215157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002257333,"about_ca_system_score_gemma":0.002750789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005854037,"about_ca_topic_score_gemma":0.00005605296,"domain_scores_codex":[0.998246,0.0001762605,0.0005566526,0.0002337298,0.0004475052,0.0003398837],"domain_scores_gemma":[0.9970199,0.0003027397,0.0004572094,0.0001077593,0.002014628,0.00009777793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000008314424,0.000722224,0.06492898,0.00001687227,0.00007713791,0.00004204429,0.001613685,0.00003938412,0.0006964558,0.9088383,0.005770343,0.01724629],"study_design_scores_gemma":[0.001063455,0.0002028741,0.02884764,0.0005427456,0.00006283603,0.009068057,0.1898733,0.00002796652,0.00126849,0.4566067,0.3118278,0.0006080203],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7027197,0.006917897,0.0004974267,0.2260941,0.0008819858,0.0001485409,0.000002616879,0.00009834507,0.06263928],"genre_scores_gemma":[0.9738626,0.0005998347,0.01843714,0.0003279517,0.001056891,0.00002122007,0.00002161297,0.00001457813,0.005658201],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4522315,"threshold_uncertainty_score":0.9999632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03444393188524944,"score_gpt":0.3311113132048453,"score_spread":0.2966673813195958,"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."}}