Blended Learning Using E-Courses in the Assessments of University Students: Decision Tree



The digital transformation of education is a sustainable international trend. Modern digital technologies allow universities to improve the quality of education through the development of digital competencies of students, individualization of learning, the introduction of e-learning courses and new learning formats. At the same time, there are a number of common opinions and prejudices about online learning in the digital environment of the university. The aim of the study is to compare students’ attitude to learning in the university digital environment at different levels of education and to identify their characteristic predictive opinions. We compared the opinions of students of master’s and second higher education programs (N = 161) and students of bachelor’s and specialty programs of the first higher education (N = 183) using a questionnaire that assesses students’ attitudes towards e-learning. For the questionnaire, using the CHAID analysis method, a decision tree was built and three predictors were identified: “Face-to-face meetings or webinars with a teacher are not needed at all, video recordings and contacts through forums are quite enough”, “It’s hard to get used to a new form of training in the EUL format” and “It’s high time to introduce e-learning”. Graduate and second-degree students are less likely to refuse face-to-face meetings with teachers and are less likely to agree that e-learning should be introduced, but more often they report that e-learning is easy to get used to. However, the overall percentage of correct predictions of the model was 65 % (52 % for graduate and second graduate students and 78 % for undergraduate and specialty students), which suggests little predictive power of the model and indicates that the results contradict the bias that older graduate students find it more difficult to get used to e-learning, that they are more challenged and more critical.

General Information

Keywords: digital educational environment, digital transformation of education, blended learning, e-learning course, scaffolding, flipped classroom model, CHAID analysis, decision tree

Publication rubric: Modeling and Data Analysis for Digital Education

Article type: scientific article

Funding. The reported study was funded by the Moscow State University of Psychology and Education (MSUPE) in the framework of the research project “Digital Technologies in Higher Education: Development of Technology for Individualizing Education Using E-Courses.

For citation: Sorokova M.G., Radchikova N.P. Blended Learning Using E-Courses in the Assessments of University Students: Decision Tree. Digital Humanities and Technology in Education (DHTE 2021): Collection of Articles of the II All-Russian Scientific and Practical Conference with International Participation. November 11-12, 2021 / V.V. Rubtsov, M.G. Sorokova, N.P. Radchikova (Eds). Moscow: Publishing house MSUPE, 2021., pp. 571–588.


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Information About the Authors

Marina G. Sorokova, Doctor of Education, PhD in Physics and Matematics, docent, Head of Scientific and Practical Center for Comprehensive Support of Psychological Research "PsyDATA", Head of the Department of Digital Education, Moscow State University of Psychology and Education, Moscow, Russia, ORCID:, e-mail:

Nataly P. Radchikova, PhD in Psychology, Leading Researcher of Scientific and Practical Center for Comprehensive Support of Psychological Research «PsyDATA», Moscow State University of Psychology & Education, Chief Specialist of the Laboratory of Biophysics of Excitable Media, Institute of Theoretical and Experimental Biophysics, Russian Academy of Sciences, Pushchino;, Moscow, Russia, ORCID:, e-mail:



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