Aleksandra Kobicheva

The purpose of the current study is to identify the main factors influencing the intention of students to study in a blended learning environment and reveal whether gender and level of education moderate the students' blended learning continuance intention. For the research model we took as the basis an expectation-confirmation model and theory of planned behavior. A total of five key factors were identified: satisfaction, perceived utility, attitude, subjective norms, and perceived behavioral control. The study involved 487 undergraduate and postgraduate students studying in the blended learning format. According to the results, there is no significant difference between men and women regarding the five contributing factors. The intention of students to study in a blended environment among groups of different levels of education varies significantly. It turned out that the average scores of postgraduate students are higher than the scores of undergraduates in almost all factors. Multigroup confirmatory factor analysis showed that the effect of perceived utility was very significant for graduate students. A high influence of attitude on the intention of undergraduate students to study in a blended environment was also revealed, that is not in consistency with the previous studies which propose the satisfaction as the strongest predictors of continuance intention. Thus, university managers and teachers should pay more attention on building the positive attitude of students towards the blended learning format to enhance the efficiency of the educational process.

In the era of universal digitalization, new technologies and services are being created, among which we can highlight the development of chatbot technologies that can be effectively used in the educational process and that will be of interest to representatives of the younger generations. The current study aims to reveal the influence of artificial intelligence chatbot integration on students’ intention to learn and their academic performance in the blended learning environment. The research framework includes 7 key indicators: Satisfaction (SAT), Perceived Usefulness (PU), Attitude (ATD), Subjective Norms (SN), and Perceived Behavioral Control (PBC), Continuance Intention to Learn (CIL) and academic performance (AP), which are evaluated in traditional blended learning setting (N=104) and blended learning based on artificial intelligence chatbot (N=107). For comparison we used the average scores, standard deviations (σ) of students on 23 items and student’s t-test for independent samples. We also calculated Pearson correlation coefficient for all analyzed. The results of the current study confirmed the positive influence of artificial intelligence usage during the blended learning as it increases students’ attitude, satisfaction and perceived usefulness which directly and highly affects the intention to continue learning and academic performance.

In the current study, we evaluated the students’ foreign language lexical and grammatical skills in the course based on the peer teaching methodology and analyzed the effect of their altruistic and egoistic behaviors on learning results. This experiment was conducted in a groups of senior students majoring in linguistics. The total number of participants accounted for 197 students (101 students in reference groups and 96 in exposure groups); the difference between the reference and exposure groups was that the undergraduates in the latter were to prepare a fragment of a lesson, create exercises, and act in the capacity of a teacher during the course. To evaluate students’ foreign language lexical and grammatical skills, the diagnostic test was conducted at the beginning and at the end of the experiment. Apart from comparing the diagnostic and final tests, we also circulated a questionnaire which checked the students’ egoistic and altruistic tendencies. The data appeared to be quite noisy; therefore, we processed them with a tool which proves effective when it comes to solving such problems, i.e., neural networks. According to the results on learning outcomes, students improved their English proficiency in the exposure groups to a greater extent than in the reference groups. At the same time, the results of the psychological tests revealed that the higher the students’ training level, the less altruistic they are. Also, it was detected that the more altruistic learners’ progress in outcomes was higher than those of the more selfish students, regardless of the way in which the learning process was organized. Moreover, the statistical data proved the efficiency of the peer teaching methodology for students’ majoring in linguistics, despite their psychological characteristics.

Currently some studies that demonstrate the correlation between students' level of psychological security and their academic performance and engagement have been published. Many studies have examined the importance of the level of psychological safety among students, some of which have proposed a methodology for assessing this indicator. To assess students' level of psychological security in studying, there were conducted online surveys. The sample included 351 students between the ages of 19 and 21 (M = 19.57, SD = 0.59), predominantly female (57%). As a result of the survey, it was found that women showed a higher level of psychological safety. The same trend was found in levels of academic engagement and academic performance. Using linear regression analysis, psychological safety was found to positively affect academic performance and attainment, especially in an online educational environment.