• A Modern Approach to Transition Analysis and Process Mining with Markov Models in Education 

  Helske, Jouni; Helske, Satu; Saqr, Mohammed; López-Pernas, Sonsoles; Murphy, Keefe (Springer, 2024)

  This chapter presents an introduction to Markovian modelling for the analysis of sequence data. Contrary to the deterministic approach seen in the previous sequence analysis chapters, Markovian models are probabilistic ...

• Introductory Statistics with R for Educational Researchers 

  Tikka, Santtu; Kopra, Juho; Heinäniemi, Merja; López-Pernas, Sonsoles; Saqr, Mohammed (Springer, 2024)

  Statistics play a fundamental role in learning analytics, providing a means to analyze and make sense of the vast amounts of data generated by learning environments. This chapter provides an introduction to basic statistical ...

• Visualizing and Reporting Educational Data with R 

  López-Pernas, Sonsoles; Misiejuk, Kamila; Tikka, Santtu; Kopra, Juho; Heinäniemi, Merja; Saqr, Mohammed (Springer, 2024)

  Visualizing data is central in learning analytics research, underpins learning dashboards, and is a prime method for reporting results and insights to stakeholders. In this chapter, the reader will be guided through the ...

• Getting Started with R for Education Research 

  Tikka, Santtu; Kopra, Juho; Heinäniemi, Merja; López-Pernas, Sonsoles; Saqr, Mohammed (Springer, 2024)

  The R programming language has become a popular tool for conducting data analysis in the field of learning analytics. This chapter provides an introduction to the basics of R programming, with a focus on the Rstudio ...

• Simulating Counterfactuals 

  Karvanen, Juha; Tikka, Santtu; Vihola, Matti (AI Access Foundation, 2024)

  Counterfactual inference considers a hypothetical intervention in a parallel world that shares some evidence with the factual world. If the evidence specifies a conditional distribution on a manifold, counterfactuals may ...

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