Factors Influencing the Quality of Distance Learning—A Serbian Case

Abstract

This study examines the key factors influencing the quality of distance learning in higher education during the COVID-19 pandemic, a period when online learning became the dominant mode of education. Using a descriptive method and a 26-item questionnaire, data were collected from a representative sample of 360 students in Vojvodina, Serbia. The factors analyzed include computer literacy and technology access (Ph1), students’ ability to balance life obligations with study demands (Ph2), and their motivation for distance learning (Ph3). The results show that 89% of students had adequate IT access, 47% were able to reconcile study and personal obligations, and 70% reported strong motivation. Correlation analysis confirmed a statistically significant positive relationship between all three factors and students’ perceptions of well-organized distance learning, thus supporting the main research hypothesis. Beyond these findings, this study interprets digital literacy as adaptability, time management as resilience, and motivation as value orientation and future thinking—core dimensions of sustainability competences outlined in the European GreenComp framework. Distance learning is therefore positioned not only as an emergency response but also as a transformative pedagogy that integrates brain (knowledge), hands (skills), heart (values), and spirit (purpose), contributing to sustainable and resilient higher education.

1. Introduction

The COVID-19 pandemic led to a sudden and global transformation of educational systems and the shift to distance learning (DL) as the primary mode of instruction [1,2]. Information technologies and digital literacy proved to be key prerequisites for the continuity of teaching and the preservation of educational quality [3,4]. In the post-pandemic period, educational practices have stabilized into hybrid arrangements, where traditional, online, and blended learning coexist [5,6]). This raises new questions about sustainable quality and student experience under regular conditions, beyond crisis-driven responses.

Recent research in Serbia has shown that the quality of the teaching process (teaching process quality-TPQ) is a stronger predictor of student satisfaction and perceived usefulness than the technical quality of platforms (TQ), while the compatibility of DL with social and pandemic conditions (CSPC) remains a key dimension of perceived usefulness [7]. This aligns with the Technology Acceptance Model (TAM) and user satisfaction theories, where perceived usefulness is strongly shaped by pedagogical rather than purely technical factors [8].

Parallel findings in K-12 education highlight the role of motivation and self-regulation: students with higher academic achievement and stronger personal control report greater satisfaction and engagement [9]. These insights correspond with Self-Determination Theory (SDT; [10]), which emphasizes autonomy, competence, and relatedness as critical for intrinsic motivation. Gender and family context also influence these perceptions, which connects to the broader debate on the digital divide [11] and equity in e-learning.

In higher education, the pandemic has also accelerated the adoption of learning analytics (LA)—moving from descriptive to predictive and prescriptive models—to identify at-risk students, personalize learning, and enhance engagement [12,13]. These approaches resonate with contemporary theories of evidence-based teaching and adaptive learning, while simultaneously raising issues of ethics and data privacy. In STEM fields, the persistent challenge is the transfer of practical and laboratory skills into digital environments, reinforcing the importance of hybrid learning models supported by virtual labs [14]. Similar obstacles are noted in health sciences, where the lack of hands-on training and difficulties in fair assessment remain critical barriers [15,16].

Building on these insights, this study focuses on three groups of factors: (i) digital literacy and technical readiness (IP1), (ii) habits and time-management skills (IP2), and (iii) motivation for learning (IP3), and their relationship with the perceived quality of organized DL. This framework integrates findings with contemporary debates: digital literacy and access are understood in terms of the digital divide [11], motivation is analyzed through SDT [10], while the broader interpretation of competences draws on the European GreenComp framework [17]. Accordingly, digital literacy corresponds to adaptability, time-management to resilience and action competence, and intrinsic motivation and goal orientation to value-based and future-oriented thinking.

In this way, online/hybrid learning is conceptualized not only as a technological-organizational response, but also as a transformative pedagogy that integrates the “head–hands–heart–spirit” model [18] and contributes to the development of sustainable competences in higher education.

2. Materials and Methods

2.1. Computer Literacy (IP1)

Computer literacy is often equated with information literacy, although there are important differences between these terms. Information literacy implies the ability to recognize, locate, evaluate, and effectively use relevant information [19], while computer literacy refers to the knowledge and skills that enable the use of computer technology in everyday life and learning.

Computer literacy includes the ability to work with operating systems (Windows, Mac, Linux), use standard applications (word processors, spreadsheets, databases, Internet browsers, e-mail), and understand the basic principles of computer systems, without necessarily knowing technical details [20,21]. In modern education, computer literacy has become a key competence that enables active participation in distance learning and lifelong learning [22]. During the COVID-19 pandemic, it became clear that a high level of digital literacy was a prerequisite for successfully following online classes [23], while students with stronger digital competences achieved better results and expressed higher satisfaction with distance learning [24].

In this study, dimension IP1—computer literacy and technological equipment—was operationalized through five items (ST1–ST5). Details about internal consistency and validity are presented in Chapter 3.

2.2. Personal Life Habits and Learning Organization (IP2)

Distance learning is a more complex process than traditional teaching, as it requires a high level of independence, self-regulation, and time management from students [25]. Distance learning students are often employed, have family responsibilities, and must balance learning with other life responsibilities [22]. Isolation, lack of direct contact with peers and teachers, as well as challenges in using technology further complicate this process [23].

Adapting personal habits, developing the ability to plan independently, and managing time effectively are crucial for successful distance learning [26]. Students who successfully overcome these challenges develop high levels of motivation for this type of education [27]. Key factors include:

• ability to allocate time for distance learning;
• planning and coordination of all responsibilities;
• overcoming the lack of face-to-face interaction;
• willingness to seek help when needed [24,26].

In this study, dimension IP2—personal lifestyle habits and time management—was measured through five items (ST6–ST10). Reliability and validity tests are described in Chapter 3.

2.3. Motivation in the Learning Process (IP3)

Motivation is one of the most important factors influencing success in distance learning [28]. Even among students with a high level of knowledge and skills, lack of motivation can significantly reduce educational achievements [29].

Motivation has three key dimensions: direction, intensity, and persistence [30]. Students must clearly identify goals, be willing to make an effort, and maintain consistency in learning over time. In the context of distance learning, self-motivation is particularly important, as daily contact with teachers and colleagues is absent [23]. Students must develop abilities such as:

• recognition of their own goals and educational needs,
• maintaining self-confidence when facing challenges,
• actively seeking contact with peers and mentors,
• working with content linked to practical examples [22].

In this study, dimension IP3—motivation for distance learning—was operationalized through five items (ST11–ST15). The assessment of scale consistency and construct validity is discussed in Chapter 3.

3. Methodology

The aim of this research is to examine the impact of three key factors on the quality of distance learning through quantitative analysis:

• the level of computer literacy and technological equipment of students (IP1),
• personal life habits and the ability to organize time (IP2),
• motivation for distance learning (IP3).

In addition, the study sought to contribute to a better understanding of the conditions for the successful implementation of distance learning and to provide recommendations for the improvement of educational practice in this domain.

3.1. Research Questions

The research was guided by the following questions:

• IP1: Is there a statistically significant positive correlation between the IT equipment and literacy of students and the quality of organized distance learning?
• IP2: Is there a statistically significant positive correlation between students’ ability to organize the time needed for learning and the quality of organized distance learning?
• IP3: Is there a statistically significant positive correlation between the level of motivation of students and the quality of organized distance learning?

The results of this research are expected to contribute to:

• a better understanding of the key factors of successful distance learning,
• recognizing the challenges and needs of students in this form of education,
• improving educational strategies and providing concrete recommendations for practice—for teachers, educational institutions and policymakers.

3.2. Research Sample

The research was conducted on a representative sample of 360 students from several faculties in Vojvodina (Serbia). The students were between the ages of 19 and 22 and the survey was conducted during the 2020/2021 academic year, at the peak of the COVID-19 pandemic.

The sample was constructed to reflect the structure of the student population in terms of gender, age, and study program (

Table 1. Descriptive statistics of the sample.

Dimension	Min.	Max.	Mean	Std. Dev.
Age	1	4	2.04	1.04
Gender	1	2	1.72	0.45
Department	1	3	1.83	0.62
Valid N				360

). The target population consisted of approximately 5000 students. The sample size provides a confidence level of 95%, with a confidence interval of ±5%.

3.3. Research Instrument and Procedure

For the purposes of the research, a questionnaire (Table 2) was distributed to students online (web-survey) as part of the teaching process. Students had previously received clear instructions from teachers on how to complete the survey.

The questionnaire consisted of 26 items, divided into two groups:

• First group (15 items)—evaluation of factors:
  • IP1—computer literacy and technological equipment (items ST1–ST5),
  • IP2—personal lifestyle habits and ability to organize time (items ST6–ST10),
  • IP3—motivation for distance learning (ST11–ST15).
• Second group (11 items)—students’ attitudes and perceptions about the quality of organized distance learning (DE items).

Responses were collected using a five-point Likert scale (from “absolutely agree” to “absolutely disagree”), and a three-point scale to assess the experience and quality of distance courses.

Table 2. Descriptive statistics of questionnaire items.

Statement	Descriptive Statistics
	Short Name	N	Min	Max	Mean	Std. Dev.
I have technology necessary for distance education (computer and Internet access).	ST1	360	1	2	1.89	0.31
How do you rate your own ability to download and install the software?	ST2	360	1	5	3.67	1.40
I understand basic operations related to working with files: creation, renaming, recording, finding.	ST3	360	1	5	3.56	1.50
How do you rate your own ability to communicate via e-mail, forums and chat rooms?	ST4	360	1	5	3.65	1.49
I possess strong writing and reading skills, in English language.	ST5	360	1	5	3.13	1.18
Assess your ability to balance the obligations related to the course of distance education and beyond.	ST6	360	1	5	3.26	1.50
I am able to dedicate the time required for the DE course (2–10 h).	ST7	360	1	5	4.14	1.14
How do you rate your ability to assess your needs for learning and understanding the material?	ST8	360	1	5	3.83	1.03
I am able to take the responsibility for getting the necessary help—by asking questions.	ST9	360	1	5	4.53	0.99
Interaction “face to face” is not important to me.	ST10	360	1	5	3.09	1.12
I always persist in achieving my goals.	ST11	360	1	5	3.99	1.15
I am organized, motivated and self-disciplined student.	ST12	360	1	5	4.06	1.30
I think it makes no sense to plan a lot ahead.	ST13	360	1	5	2.70	1.22
One should have a clearly defined goal—at any time.	ST14	360	1	5	4.21	1.20
It is important for me to point out my success.	ST15	360	1	5	4.11	1.13
I have valuable experience in learning from DE courses.	DE1	360	1	3	2.78	0.57
Course materials are appropriate and concise.	DE2	360	1	3	2.74	0.62
The examples and tasks are relevant and useful.	DE3	360	1	3	2.70	0.67
Workload is appropriate to the length of DE class time.	DE4	360	1	3	2.56	0.80
Testing procedures and evaluations are done fair.	DE5	360	1	3	2.66	0.70
The expectations are clearly stated orally or in the program.	DE6	360	1	3	2.64	0.72
The instructors encouraged me to become actively involved in the course’s discussions.	DE7	360	1	3	2.82	0.44
The instructors provided me feedback on my work through comments.	DE8	360	1	3	2.71	0.67
I was able to interact with the instructors during the course’s discussions.	DE9	360	1	3	2.75	0.64
The instructors treated me individually.	DE10	360	1	3	2.70	0.68
The instructors informed me about my progress periodically.	DE11	360	1	3	2.84	0.48
Valid N		360

Table 2. Descriptive statistics of questionnaire items.

Statement	Descriptive Statistics
	Short Name	N	Min	Max	Mean	Std. Dev.
I have technology necessary for distance education (computer and Internet access).	ST1	360	1	2	1.89	0.31
How do you rate your own ability to download and install the software?	ST2	360	1	5	3.67	1.40
I understand basic operations related to working with files: creation, renaming, recording, finding.	ST3	360	1	5	3.56	1.50
How do you rate your own ability to communicate via e-mail, forums and chat rooms?	ST4	360	1	5	3.65	1.49
I possess strong writing and reading skills, in English language.	ST5	360	1	5	3.13	1.18
Assess your ability to balance the obligations related to the course of distance education and beyond.	ST6	360	1	5	3.26	1.50
I am able to dedicate the time required for the DE course (2–10 h).	ST7	360	1	5	4.14	1.14
How do you rate your ability to assess your needs for learning and understanding the material?	ST8	360	1	5	3.83	1.03
I am able to take the responsibility for getting the necessary help—by asking questions.	ST9	360	1	5	4.53	0.99
Interaction “face to face” is not important to me.	ST10	360	1	5	3.09	1.12
I always persist in achieving my goals.	ST11	360	1	5	3.99	1.15
I am organized, motivated and self-disciplined student.	ST12	360	1	5	4.06	1.30
I think it makes no sense to plan a lot ahead.	ST13	360	1	5	2.70	1.22
One should have a clearly defined goal—at any time.	ST14	360	1	5	4.21	1.20
It is important for me to point out my success.	ST15	360	1	5	4.11	1.13
I have valuable experience in learning from DE courses.	DE1	360	1	3	2.78	0.57
Course materials are appropriate and concise.	DE2	360	1	3	2.74	0.62
The examples and tasks are relevant and useful.	DE3	360	1	3	2.70	0.67
Workload is appropriate to the length of DE class time.	DE4	360	1	3	2.56	0.80
Testing procedures and evaluations are done fair.	DE5	360	1	3	2.66	0.70
The expectations are clearly stated orally or in the program.	DE6	360	1	3	2.64	0.72
The instructors encouraged me to become actively involved in the course’s discussions.	DE7	360	1	3	2.82	0.44
The instructors provided me feedback on my work through comments.	DE8	360	1	3	2.71	0.67
I was able to interact with the instructors during the course’s discussions.	DE9	360	1	3	2.75	0.64
The instructors treated me individually.	DE10	360	1	3	2.70	0.68
The instructors informed me about my progress periodically.	DE11	360	1	3	2.84	0.48
Valid N		360

3.4. Instrument Reliability and Validity

Internal consistency of the scales was estimated using Cronbach’s alpha coefficient:

• IP1—α = 0.81
• IP2—α = 0.79
• IP3—α = 0.80
• DE—α = 0.82

Values above 0.70 indicate satisfactory reliability of the scales [31].

To assess construct validity, an exploratory factor analysis (EFA) was conducted. The KMO index was 0.83, and Bartlett’s test of sphericity was significant (p < 0.001), confirming the adequacy of the data. Results indicated a dominant one-factor structure, suggesting that items from IP1, IP2, and IP3 were strongly interrelated and reflected a broader, integrative concept of digital competence in the context of distance learning.

This finding suggests that although the questionnaire was originally designed to measure three distinct aspects, students perceived them as interconnected dimensions of a single competence. Such results align with research that conceptualizes digital competence as a unified construct essential for effective online education [11,17,20,22].

3.5. Statistical Data Processing

The collected data were analyzed using descriptive statistics and Pearson’s correlation coefficient, with the help of the statistical software package IBM SPSS 20.

The goal of the statistical analysis was to determine:

• the existence of a positive correlation between the analyzed factors and students’ attitudes towards the quality of organized distance learning,
• the level of statistical significance of the identified links.

4. Results

The results of the correlation analysis of the participants’ relevant answers are presented in this section. Statistically significant correlations are bold and marked as: * p < 0.05; ** p < 0.01.

4.1. Results of the First Research Question

Below are the results of the analysis of the correlation between the level of computer literacy and technological equipment of students with their attitudes towards the quality of organized distance learning.

Table A1. Respondents’ answers on the level of computer literacy and technological equipment (in percentage).

Attitude	Absolutely Agree	Agree	No Opinion	Disagree	Absolutely Disagree
ST1	89	0	0	0	11
ST2	42	14	21	12	11
ST3	41	16	18	9	16
ST4	48	8	19	12	13
ST5	11	31	30	15	13

(Appendix A) presents an overview of the results related to the assessment of the level of computer literacy and technological equipment of students. The data obtained confirms that the majority of students have the technical conditions and digital skills necessary for successful distance learning.

The results of the survey show that 89% of students have computer technologies and access to the Internet (see Table A1, ST1). Given that a large number of students have high-speed internet at home, they have no problem downloading materials and installing software. A large number of respondents (56%) believe that they are able to download material and install software, the number of those who do not feel confident in this matter is 23%, while 21% have no opinion (ST2). The basic procedures over files (copying, deleting, renaming files and folders) are also known to the vast majority of students (57% agree and absolutely agree), 9% disagree, 16% absolutely disagree, while 18% are still left without an attitude (ST3). The fact is that today almost everyone has computer equipment and smart mobile phones, which, through appropriate applications, can access distance learning courses and allow you to download materials. At the same time, interaction with other students and instructors takes place via email, forums, and chat (56%). A smaller number of students prefer verbal communication (25%), while 19% did not have an opinion (ST4). 42% of respondents possess strong English reading and writing skills (ST5).

The results of the research show that the respondents have a computer and access to the Internet, as well as developed computer literacy. A statistically significant positive correlation (

Table 3. Correlation between computer literacy and equipment and attitudes towards distance learning quality (Pearson correlation).

	DE1	DE2	DE3	DE4	DE5	DE6	DE7	DE8	DE9	DE10	DE11
ST1	0.47 **	0.49 **	0.51 **	0.58 **	0.49 **	0.48 **	0.24 **	0.61 **	0.03	0.68 **	0.21 **
ST2	0.14 **	0.34 **	0.35 **	0.34 **	0.30 **	0.35 **	0.14 **	0.20 **	0.24 **	0.26 **	0.03
ST3	−0.02	0.32 **	0.37 **	0.23 **	0.13	0.20 **	0.17 **	0.11 *	0.24 **	0.11 *	−0.02
ST4	−0.00	0.09	0.11 *	0.26 **	0.16 **	0.15 **	0.23 **	0.09	0.34 **	0.13 *	0.02
ST5	−0.03	0.02	0.25 **	0.01	0.15 **	0.09	0.08	0.10	0.16 **	0.07	−0.01

) can be observed between item ST1 and items DE1 (0.47 significance level p < 0.01), DE2 (0.49 ** significance level p < 0.01) and DE3 (0.51 ** significance level p < 0.01). Thus, students are able to effectively participate in distance learning and have a positive experience.

They are able to download all the material and tasks that the courses offer them, to install the necessary software, as well as to create, record and find the desired files—which is confirmed by the statistically significant positive correlation between the items ST2 and DE2 (0.34 ** significance level p < 0.01); DE3 (0.35 ** significance level p < 0.01), as well as ST3 and DE2 (0.32 ** significance level p < 0.01); DE3 (0.37 ** significance level p < 0.01).

Given that students have a positive experience working with computer equipment, the use of e-mail, forums and chat is not a problem for them. This form of communication is used to consult with teachers and other students regarding any ambiguities during the learning process—a positive correlation between item ST4 and DE7 (0.23 ** significance level p < 0.01) is confirmed; DE9 (0.34 ** significance level p < 0.01).

Based on the above results, it can be concluded that students do not show significant obstacles in the use of digital technologies that require distance learning, which is confirmed by the existence of a statistically significant positive correlation between the factors of computer literacy and equipment with the quality of organized distance learning.

Based on the presented results, the first research question was confirmed—computer literacy and student equipment statistically significantly contribute to the quality organization and efficiency of distance learning

4.2. Results of the Second Research Question

An analysis of the results related to the second research question (

Table A2. Respondents’ responses to personal life habits and time management skills (in percentage).

Attitude	Absolutely Agree	Agree	No Opinion	Disagree	Absolutely Disagree
ST6	32	15	20	14	19
ST7	53	23	12	8	4
ST8	22	57	7	9	5
ST9	75	13	5	3	4
ST10	13	21	35	24	7

, Appendix A) indicates that 47% of students believe that they are able to successfully reconcile the obligations related to distance learning with other life obligations (ST6). A total of 33% of students disagree or absolutely disagree with the statement, while 20% of respondents remained neutral (they do not have a clear opinion on this statement).

Table 4. Correlation between students’ personal life habits and ability to organize their time with their perceptions of the quality of distance learning, (Pearson correlation).

	DE1	DE2	DE3	DE4	DE5	DE6	DE7	DE8	DE9	DE10	DE11
ST6	0.41 **	0.11 *	0.25 **	0.15 **	0.12 *	0.09	0.10	0.14 **	0.15 **	0.17 **	0.03
ST7	0.36 **	0.43 **	0.43 **	0.35 **	0.41 **	0.35 **	0.27 **	0.35 **	0.06	0.42 **	0.23 **
ST8	0.30 **	0.41 **	0.35 **	0.65 **	0.37 **	0.37 **	0.14 **	0.33 **	−0.03	0.36 **	0.07
ST9	0.25 **	0.30 **	0.23 **	0.24 **	0.23 **	0.27 **	0.52 **	0.30 **	0.09	0.36 **	0.19 **
ST10	0.21 **	0.08	0.12 *	0.18 **	0.07	0.13 *	0.08	0.49 **	0.00	0.48 **	0.41 **

presents the data on the personal life of the respondents.

The majority of students (53%) say they can set aside more than 10 h per week for distance learning, while 23% set aside about 8 h, 12% 6 h, 8% 4 h, and 4% only 2 h per week (ST7).

More than a fifth of students (22%) believe they are extremely capable of assessing their learning needs and understanding of the material, while 57% believe they are capable and 7% are hesitant. Only 14% of students disagree with this statement (9% disagree, 5% disagree absolutely) (ST8).

The vast majority of students (88%) have no problem actively seeking help, either from colleagues or from professors via email or forums. A smaller number of students (3% disagree, 4% absolutely disagree), while 5% have no opinion on this statement (ST9).

When it comes to the importance of face-to-face contact with teachers, students’ attitudes are divided: for 34% the lack of such contact is a problem, 35% have no attitude, while for 31% of students it is not a problem (ST10).

Table 4 shows that there is a statistically significant positive correlation between different aspects of personal life habits and the ability to organize time and perception of the quality of distance learning.

In particular, there is a correlation between the ability to reconcile life and educational obligations (ST6) and the overall positive experience with distance learning (DE1; r = 0.41 **, p < 0.01). Students who successfully balance their responsibilities show a more positive attitude towards the quality of online teaching.

Also, students who successfully set aside enough time for learning (ST7) achieve positive correlations with almost all dimensions of course quality, including the content of the material (DE2; r = 0.43 **) and relevance of examples and tasks (DE3; r = 0.43 **).

The ability to properly assess one’s own learning needs (ST8) shows the highest correlation with the adequacy of the course load (DE4; r = 0.65 **) and with the clarity of the teaching materials (DE2; r = 0.41 **), which emphasizes the importance of self-regulation skills in the distance learning process.

Students who are willing to actively seek help (ST9), as well as those for whom the lack of face-to-face communication (ST10) is not an obstacle, have positive correlations with dimensions such as encouraging active participation (DE7; r = 0.52 **) and receiving feedback from teachers (DE8; r = 0.49 **).

Based on these results, it can be concluded that personal life habits and the ability to organize time are significantly associated with a positive experience and perception of the quality of distance learning, thus confirming the second research question.

4.3. Results of the Third Research Question

The results of the research show that students are largely organized, motivated and self-disciplined in the distance learning process. In fact, 70% of students estimate that they have developed organizational skills and the ability to manage learning independently (

Table A3. Respondents’ answers about IP3—motivation for distance learning (in percentage).

Attitude	Absolutely Agree	Agree	No Opinion	Disagree	Absolutely Disagree
ST11	45	25	18	8	4
ST12	57	13	17	5	8
ST13	11	14	27	31	17
ST14	61	14	15	5	5
ST15	50	26	12	8	4

, ST11, Appendix A). Although 12% of students express some doubts about their organizational abilities, and 18% do not have a clear position on this issue, the majority still successfully plan their activities.

Although less than half of respondents (48%) believe that it is necessary to plan ahead (ST13), as many as 75% of students state that they have clearly defined learning goals (ST14), which further encourages their motivation to achieve these goals—70% declare themselves motivated and engaged (ST12).

Also, the sense of achievement is expressed: 76% of students say that they are proud of their success and want to share it and present it to others (ST15). These data indicate a high level of intrinsic motivation and a positive attitude of students towards distance learning.

Based on the results obtained, it can be concluded that students are organized, motivated, and self-disciplined, and that they are able to realistically assess their learning needs. Most of them successfully plan and allocate enough time for distance learning, effectively organize their obligations, and despite the lack of constant direct contact with teachers, manage to work efficiently with teaching materials and the online environment. These findings indicate that intrinsic motivation and developed self-regulation strategies significantly contribute to quality distance learning and strengthen students’ engagement.

Table 5. Correlation between the degree of motivation and the quality of organized distance learning.

	DE1	DE2	DE3	DE4	DE5	DE6	DE7	DE8	DE9	DE10	DE11
ST11	0.30 **	0.46 **	0.44 **	0.41 **	0.48 **	0.45 **	0.26 **	0.36 **	0.13 *	0.43 **	0.13 *
ST12	0.33 **	0.54 **	0.56 **	0.48 **	0.41 **	0.48 **	0.26 **	0.40 **	0.20 **	0.48 **	0.18 **
ST13	0.08	0.02	0.22 **	−0.14 **	0.06	−0.10	0.05	0.31 **	−0.01	0.30 **	0.31 **
ST14	0.34 **	0.43 **	0.55 **	0.39 **	0.43 **	0.43 **	0.31 **	0.42 **	0.28 **	0.51 **	0.15 **
ST15	0.35 **	0.42 **	0.42 **	0.35 **	0.40 **	0.34 **	0.27 **	0.34 **	0.08	0.42 **	0.23 **

shows the correlation between the level of motivation of students and their perceptions of the quality of organized distance learning.

The results show that students are highly motivated, organized, and self-disciplined for distance learning. Having effective learning strategies and setting realistic and clearly defined goals contributes significantly to their success, as confirmed by the following statistically significant positive correlations:

• ST11 (persistence in achieving goals) and DE6 (clarity of expectations)→r = 0.45, p < 0.01;
• ST12 (organization, motivation and self-discipline) and DE6→r = 0.48, p < 0.01;
• ST14 (clearly defined targets) and DE6→r = 0.43, p < 0.01.

Further, the desire to achieve success and positively valuing one’s own achievements (ST15) is associated with a better overall distance learning experience:

• ST15 and DE1 (positive distance learning experience)→r = 0.35, p < 0.01.

Also, the feedback students receive from their teachers—during courses, through comments, and interaction in forums—has an additional positive effect on their motivation and engagement in distance learning.

In conclusion, the results of the research confirm that IT equipment and literacy, personal time management habits, as well as motivation for distance learning, are statistically significantly related to the quality of organized distance learning. Thus, the main hypothesis of the research is fully confirmed.

4.4. Summary of Findings

In summary, the results consistently demonstrate that computer literacy and equipment, personal lifestyle habits and time management, and student motivation are all statistically significantly related to the quality of organized distance learning. Full descriptive statistics are provided in Appendix A, while correlation analyses presented in the main text highlight the most important relationships.

5. Discussion

The analysis confirmed that digital literacy, time management, and motivation are strongly related to the perceived quality of distance learning, which supports the main hypothesis of the study. The results also allow for interpretation in light of broader frameworks, such as theories of e-learning, motivation, and sustainability competences.

The first research question (IP1) confirmed that a high level of digital literacy and access to computer technology enable students to effectively navigate the online environment. Students with stronger digital competences manage learning more easily, show greater satisfaction, and achieve better results. These findings are consistent with [22,23,24], who emphasize digital skills as foundational for online learning. At the same time, some correlations found in this study were weak (r < 0.30), which indicates that digital literacy alone does not fully determine learning quality, but interacts with other conditions such as institutional support and pedagogy. This nuance aligns with recent debates about the digital divide [11], which stress that access is necessary but not sufficient for high-quality learning.

The second research question (IP2) highlighted the importance of self-regulation and time management, showing that students who reconcile learning with other responsibilities, assess their own needs, and seek help, have a more positive experience with distance learning. This is consistent with [25,26], but also resonates with broader frameworks of sustainable learning, which stress responsibility and resilience as essential competences [17]. It should be noted, however, that not all students found time management equally easy, which indicates that personal lifestyle factors interact with socio-economic and family contexts. This reflects findings from post-pandemic studies showing that hybrid education requires institutional strategies to support equity and balance [32].

The third research question (IP3) showed that intrinsic motivation and organization are decisive for student engagement. Students with clear goals and persistence report higher satisfaction and course quality. These findings are aligned with [24,28], and can be interpreted through Self-Determination Theory [30], which stresses autonomy, competence, and relatedness as central to motivation.

Nevertheless, motivation was not uniform: while many students reported strong discipline, others expressed skepticism toward long-term planning (ST13). This suggests the need for pedagogical strategies that foster adaptive goal-setting and maintain student engagement in uncertain contexts.

From a broader perspective, these findings contribute to the understanding of post-pandemic higher education. During the pandemic, distance learning was the dominant form, but today it coexists with hybrid and blended models. The results of this study remain relevant in showing which factors (digital competences, time management, and motivation) consistently predict positive student experiences across modalities. This provides evidence for institutions designing sustainable hybrid systems that combine flexibility with pedagogical quality.

Finally, linking to sustainability competences (GreenComp), the three identified factors map onto essential competences:

• Digital literacy (IP1)→supports adaptive learning and lifelong digital inclusion.
• Time management and self-regulation (IP2)→reflect responsibility, resilience, and personal agency.
• Motivation and goal-setting (IP3)→connect to futures literacy and value-based decision-making.

Thus, distance education environments can support the development of competences needed for sustainable societies. By fostering not only technical skills (“brain”), but also resilience and responsibility (“hands”), motivation and values (“heart”), and long-term vision (“spirit”), distance learning can play a transformative role in higher education.

6. Conclusions and Recommendations

In the context of modern trends in education, distance learning is increasingly functioning as part of blended (hybrid) models, rather than as a temporary substitute for face-to-face teaching. The findings of this research show that digital literacy, the ability to organize time independently, and motivation are key factors for success in distance learning. The majority of students showed a high level of organization, self-discipline and clearly defined goals, which significantly contribute to positive experiences in the online environment. These findings are consistent with earlier studies emphasizing the importance of digital competences, self-regulation, and intrinsic motivation as foundations of effective online learning [22,23,24].

Based on the results obtained, the following recommendations for educational practice can be formulated:

• It is necessary to continuously develop digital competencies in students through formal and informal education.
• Teachers should further strengthen their presence in the digital space, providing clear feedback and encouraging active student participation.
• It is necessary to provide support to students in developing self-regulation strategies, time management and goal setting.
• Educational institutions should not only develop blended teaching models that encourage flexibility but also maintain high interactivity and personalized support.

While the results of this study offer valuable insights, there are some limitations:

• The research was conducted on a sample of students from one region, which may limit the applicability of the results to a wider population.
• A cross-sectional approach is used, which does not involve changes over time.
• Only self-assessment data were used, without including objective indicators of success or teachers’ attitudes.

Future research should include more diverse samples and the application of a combined method (quantitative and qualitative) in order to take a deeper look at the success factors in distance learning. It is also recommended to design longitudinal studies to examine the development of digital competences, motivation, and self-regulation over time, as well as to include the perspectives of teachers and institutional decision-makers [32,33].

In addition, this study highlights that the analysed factors—IT literacy, self-regulation, and motivation—can be interpreted as essential components of sustainability competence development. Digital literacy equips students with adaptive learning capacities for a fast-changing world; time management and responsibility reflect resilience and action competence, while motivation and clear goals connect to value thinking and future orientation [11,17].

Therefore, the findings support the argument that distance learning, if designed and implemented through transformative pedagogies, contributes not only to the efficiency of education but also to building a sustainability mindset. By fostering the integration of “brain” (knowledge), “hands” (skills), “heart” (values and motivation), and “spirit” (purpose and long-term vision), distance education can act as a transformative pathway within Education for Sustainability (ESD) in higher education [23].