Purpose: In order to initialize a student model in intelligent tutoring systems, some form of initial knowledge test should be given to a student. Since the authors cannot include all domain knowledge in that initial test, a domain knowledge subset should be selected. The paper aims to discuss this issue. Design/methodology/approach: In order to…

Three studies were conducted to explore machine learning support of novel learning problems. The first was a study of a computer-supported online learning website, which was designed to support teachers improving their pedagogy and this work created a data-first approach for Linguistic pedagogy, and to support improved pedagogy delivery and…

The widespread adoption of online courses opens opportunities for analysing learner behaviour and optimising web-based learning adapted to observed usage. Here, we introduce a mathematical framework for the analysis of time-series of online learner engagement, which allows the identification of clusters of learners with similar online temporal…

In recent years, computer science has become a cornerstone of modern society. As a result, enrollment in undergraduate computer science programs has expanded rapidly. While the influx of talent into the field will undoubtedly lead to countless technological developments, this growth also brings new pedagogical challenges. Educational resources,…

At the examination of a patient, a doctor evaluates clinical picture of the disease that manifests itself by a great number of various general and local symptoms caused by an etiological factor and pathogenesis changes of the different organs and systems of the organism. A purpose of the surgical patient examination is making of early, correct and…

Although immediacy is one of the necessary criteria to show strong evidence of a causal relation in SCDs, no inferential statistical tool is currently used to demonstrate it. We propose a Bayesian unknown change-point model to investigate and quantify immediacy in SCD analysis. Unlike visual analysis that considers only 3-5 observations in…

Social media can contribute to an inclusive society, but they are also asymmetrical and polarised communication spaces. This requires competent teachers to build critical digital citizenship. The aim of this article is twofold: to present web scraping and text analytics as tools that define teachers' digital competences, and to investigate which…

Causal search algorithms have been effectively applied in different fields including biology, genetics, climate science, medicine, and neuroscience. However, there have been scant applications of these methods in social and behavioral sciences. This article provides an illustrative example of how causal search algorithms can shed light on…

Large-scale assessments are supported by a large item pool. An important task in test development is to assign items into scales that measure different characteristics of individuals, and a popular approach is cluster analysis of items. Classical methods in cluster analysis, such as the hierarchical clustering, K-means method, and latent-class…

This study aims to investigate the effect of using the Harezmi education model, which has been widely used in Turkey in recent years, in social studies teaching regarding computational thinking skills. Interviews were held with students and teachers seven months after the applications to determine the conceptual knowledge levels of students for…

The COVID-19 epidemic had caused one of the most significant disruptions to the global education system. Many educational institutions faced sudden pressure to switch from face-to-face to online delivery of courses. The conventional classes are no longer the primary means of delivery; instead, online education and resources have become the…

Digital technologies can be used to support the inclusion of diverse student groups in education in a number of ways including enhancing accessibility of educational content, increasing personalisation and providing distance learning opportunities, as was the case during the COVID-19 pandemic. However, persistent digital inequalities can undermine…

This dissertation presents various machine learning applications for predicting different cognitive states of students while they are using a vocabulary tutoring system, DSCoVAR. We conduct four studies, each of which includes a comprehensive analysis of behavioral and linguistic data and provides data-driven evidence for designing personalized…

This dissertation focuses on elite efforts to restructure work and education in the Russian data sciences. Russia has long had a strong national program in theoretical mathematics, but has been substantially less successful at applying this expertise to develop modern computational science, infrastructure, and business. As the Russian extraction…

Syntactic structures are unobserved theoretical constructs which are useful in explaining a wide range of linguistic and psychological phenomena. Language acquisition studies how such latent structures are acquired by human learners through many hypothesized learning mechanisms and apparatuses, which can be genetically endowed or of general…