@article {7448,
	title = {Model of student engagement in the distance learning process},
	journal = {Central European Management Journal},
	volume = {32},
	year = {2024},
	abstract = {Purpose {\textendash} We aimed to identify factors that influence student engagement in distance learning.
Design/methodology/approach {\textendash} The research involved a group of 671 students from economic and technical higher education institutions in Poland. We collected the data with the CAWI technique and an original survey. Next, we processed the data using principal component analysis and then used the extracted components as predictors in the induced smoothing LASSO regression model.
Findings {\textendash} The components of the students{\textquoteright} attitude toward remote classes learning conditions are: satisfaction with teachers{\textquoteright} approach, attitude to distance learning, the system of students{\textquoteright} values and motivation, IT infrastructure of the university, building a network of contacts and communication skills. The final model consisted of seven statistically significant variables, encompassing the student{\textquoteright}s sex, level of studies and the first five extracted PCs. Student{\textquoteright}s system of values and motivation as well as attitude toward distance learning, were those variables that had the biggest influence on student engagement.
Practical implications {\textendash} The research result suggests that in addition to students{\textquoteright} system of values and motivation and their attitude toward distance learning, the satisfaction level of teachers{\textquoteright} attitude is one of the three most important factors that influence student engagement during the distance learning process. Originality/value {\textendash} The main value of this article is the statistical model of student engagement during distance learning. The article fills the research gap in identifying and evaluating the impact of various factors determining student engagement in the distance learning process.},
	issn = {2658-0845 },
	doi = {10.1108/CEMJ-01-2024-0005}
}
