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  • Learning analytics methods and tutorials = a practical guide using R /
  • 紀錄類型: 書目-電子資源 : Monograph/item
    正題名/作者: Learning analytics methods and tutorials/ edited by Mohammed Saqr, Sonsoles López-Pernas.
    其他題名: a practical guide using R /
    其他作者: Saqr, Mohammed.
    出版者: Cham :Springer Nature Switzerland : : 2024.,
    面頁冊數: xxxiv, 736 p. :ill. (some col.), digital ;24 cm.
    內容註: Chapter. 1. Capturing the Wealth and Diversity of Learning Processes with Learning Analytics Methods -- Part. I. Getting started -- Chapter. 2. A Broad Collection of Datasets for Educational Research Training and Application -- Chapter. 3. Getting started with R for Education Research -- Chapter. 4. An R Approach to Data Cleaning and Wrangling for Education -- Chapter. 5. Introductory Statistics with R for Educational Researchers -- Chapter. 6. Visualizing and Reporting Educational Data with R -- Part. II. Machine Learning -- Chapter. 7. Predictive Modelling in Learning Analytics using R -- Chapter. 8. Dissimilarity-based Cluster Analysis of Educational Data: A Comparative Tutorial using R -- Chapter. 9. An Introduction and R Tutorial to Model-based Clustering in Education via Latent Profile Analysis -- Part. III. Temporal methods -- Chapter. 10. Sequence Analysis in Education: Principles, Technique, and Tutorial with R -- Chapter. 11. Modeling the Dynamics of Longitudinal Processes in Education. A tutorial with R for The VaSSTra Method -- Chapter. 12. A Modern Approach to Transition Analysis and Process Mining with Markov Models in Education -- Chapter. 13. Multichannel Sequence Analysis in Educational Research Using R -- Chapter. 14. The Why, the How, and the When of Educational Process Mining in R -- Part. IV. Network analysis -- Chapter. 15. Social Network Analysis: A Primer, a Guide and a Tutorial in R -- Chapter. 16. Community Detection in Learning Networks Using R -- Chapter. 17. Temporal Network Analysis: Introduction, Methods, and Analysis with R -- Chapter. 18. Epistemic Network Analysis and Ordered Network Analysis in Learning Analytics -- Part. V. Psychometrics -- Chapter. 19. Psychological Networks: A Modern Approach to Analysis of Learning and Complex Learning Processes -- Chapter. 20. Factor Analysis in Education Research using R -- Chapter. 21. Structural Equation Modeling with R for Education Scientists -- Chapter. 22. Why educational research needs a complex system revolution that embraces individual differences, heterogeneity, and uncertainty.
    Contained By: Springer Nature eBook
    標題: Education - Data processing. -
    電子資源: https://doi.org/10.1007/978-3-031-54464-4
    ISBN: 9783031544644
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