{"id":"W4414545589","doi":"10.38159/jelt.2025695","title":"Integrating Play-Based Learning with Coding for Early Childhood Mathematics Education in Under-Resourced Schools","year":2025,"lang":"en","type":"article","venue":"Journal of Education and Learning Technology","topic":"Child Development and Digital Technology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Education and Early Childhood Development","funders":"","keywords":"Experiential learning; Coding (social sciences); Curriculum; Axial coding; Perception; Thematic analysis; Early childhood; Discovery learning; Early childhood education; Connected Mathematics","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":[0.01109538,0.0004137438,0.0004950886,0.002690929,0.004388295,0.005624486,0.001727833,0.0006264753,0.001390663],"category_scores_gemma":[0.02119115,0.0005244161,0.0004357732,0.0022094,0.00736256,0.004429217,0.01062733,0.001567745,0.0002483847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004461648,"about_ca_system_score_gemma":0.01145894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007358696,"about_ca_topic_score_gemma":0.02298478,"domain_scores_codex":[0.9869606,0.009264786,0.0006617472,0.0005396518,0.001298622,0.001274541],"domain_scores_gemma":[0.9783667,0.01321191,0.002701487,0.00166689,0.001339411,0.002713558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009102565,0.0003726334,0.04026932,0.0008239753,0.00001845194,0.001286942,0.6633213,0.0006302088,0.004204823,0.009976565,0.001100585,0.2779042],"study_design_scores_gemma":[0.00003122178,0.0003391845,0.05784746,0.002301713,0.00005228634,0.001490067,0.8676963,0.001591039,0.00390971,0.01544682,0.04919903,0.00009520457],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9476781,0.001239911,0.03016194,0.004790026,0.00005864412,0.0003866524,0.00004090011,0.00008683884,0.01555695],"genre_scores_gemma":[0.9637781,0.0009105745,0.03357571,0.0001854157,0.00001184158,0.000290958,0.00002919649,0.00002566482,0.001192567],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01109538,"threshold_uncertainty_score":0.05867875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01001566905274421,"score_gpt":0.3061643901566345,"score_spread":0.2961487211038903,"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."}}