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Google BigQuery for Education: Framework for Parsing and Analyzing edX MOOC Data.

, , , , и . L@S, стр. 181-184. ACM, (2017)

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Другие публикации лиц с тем же именем

Navigating the Local Modes of Big Data: The Case of Topic Models., , и . Computational Social Science, Cambridge University Press, (2016)Designing Adaptive Assessments in MOOCs, , , , , и . Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale, стр. 233--236. New York, NY, USA, ACM, (2017)Which Planning Tactics Predict Online Course Completion?, , , , и . LAK, стр. 360-370. ACM, (2024)MOOC Dropout Prediction: How to Measure Accuracy?, , , , и . L@S, стр. 161-164. ACM, (2017)Widening Access to Applied Machine Learning with TinyML., , , , , , , , , и 14 other автор(ы). CoRR, (2021)TopicCheck: Interactive Alignment for Assessing Topic Model Stability., , , , , , и . HLT-NAACL, стр. 175-184. The Association for Computational Linguistics, (2015)Google BigQuery for Education: Framework for Parsing and Analyzing edX MOOC Data., , , , и . L@S, стр. 181-184. ACM, (2017)Adaptive Learning Open Source Initiative for MOOC Experimentation., , , , , , , и . AIED (2), том 10948 из Lecture Notes in Computer Science, стр. 307-311. Springer, (2018)Adaptive Assessment Experiment in a HarvardX MOOC., , , , , , и . EDM, International Educational Data Mining Society (IEDMS), (2017)The effects of adaptive learning in a massive open online course on learners' skill development., , , , , , , и . L@S, стр. 6:1-6:8. ACM, (2018)