Conducting web lessons requires different preparation from the teacher than usual. In order to successfully organize studies, it is not enough to transfer the face-to-face learning to the web—lessons need to be adapted to the environment and possibilities, focusing on both the teaching methodology and the technology used (Guo et al., 2014; Trumm et al., 2020). Web lessons can be run both synchronously and asynchronously. In the first case, the lesson is conducted using a video conferencing application and all students are in the same (virtual) place at the same time. In the second case, the lesson is recorded in advance and students can access it through a video-sharing application. These approaches and the corresponding guidelines are very closely linked, for example, in both cases lessons should be clear, comprehensive, and engaging to avoid distractions (Mukan and Lavrysh, 2020), but there are also differences in the recommendations.

One of the main recommendations for conducting synchronous online lessons is that students should read or watch the materials at home in advance, and synchronous meetings should focus on discussing topics and consolidating what they have learned (Mukan and Lavrysh, 2020; Trumm et al., 2020; Luik et al., 2021). In order to keep the attention of students in a synchronous web lesson, they can be asked to keep the cameras on—this forces them to work more actively (Warden et al., 2013). However, as it is difficult to notice in a video when someone is preparing to ask or answer a question, limiting the number of participants can also make communication in an online lesson more convenient (Klonoski and Combs, 2009). It is recommended to use breakout rooms for group work in a web lesson, containing the optimal number of participants for the task, showing the time remaining for the work and enabling the participants themselves to enter and exit the room (Cornelius and Gordon, 2013). The need for instant messaging (chat) has also been pointed out, as it can be helpful in cases where the internet is bad or technology is failing (Bergdahl and Nouri, 2020; Mukan and Lavrysh, 2020).

Asynchronous web lessons require pre-recording of material. This is considered very important because recordings allow learners to process the material at a suitable pace (Luik et al., 2021), facilitate the acquisition of material in case of the absence (Coffey, 2010), and support independent learning (Trumm et al., 2020). There are several ways to record videos. One possibility is to record asynchronous web lessons in advance, where shorter videos are recommended at lower doses (Harrison, 2020; Massner, 2021). Synchronous web lesson can also be recorded, but in this case, their suitability must be assessed according to the content of the lesson (Cappiccie and Desrosiers, 2011) and permission must be sought to record the image and voice of the learners, as it is personal data (Trumm et al., 2020). In the case of asynchronous web lessons, there is no direct communication with students, so special attention should be paid to personality. Participants should be able to see the teacher's body language and facial expressions, and it would be good to increase eye contact (Guo et al., 2014; Gilardi et al., 2015). More enthusiastic and faster speakers help to make lessons more exciting (Guo et al., 2014). Saving a web lesson in a format where the teacher is in front of slides makes it easier for participants to focus on the slides and the teacher at the same time; in addition, a personal style, suitable animations, color and preference for images over long text blocks can all improve the presentation (Gilardi et al., 2015).

Screen sharing is considered to be a very important functionality in both synchronous and asynchronous web lessons, as it helps all parties to see the same part of the slide show simultaneously and facilitates better explanation of more complex tasks (Li, 2014). Sharing the screen with the ability to draw or write on it is also important for presentations (Correia et al., 2020). The on-screen writing and drawing function can usually be used without slides, mimicking the use of a whiteboard, which can make it easier to explain the subject (Correia et al., 2020). Freehand writing and drawing have also been shown to be more exciting than showing slides or writing code on the screen (Guo et al., 2014).

In addition to the technical side of teaching, it is also important to think about teaching methods where there is a partial overlap between web lessons and face-to-face learning. In order to take into account students' different levels and learning preferences, teachers can vary activities (Cornelius and Gordon, 2013), offer alternative tasks or provide different levels of difficulty (Mukan and Lavrysh, 2020; Luik et al., 2021) or send supportive tasks privately only to those who need them (Mukan and Lavrysh, 2020). To support learners, teachers can, at the beginning of the lesson, provide a recap of previous learning and explain what is being learned now and why (Luik et al., 2021). It is also important to engage learners, which can be done in many different ways. For example, self-assessment questions or tasks can be presented between different parts of the lesson to support learning (Harrison, 2020; Luik et al., 2021). As online lessons make it more difficult for a teacher to understand students due to a lack of non-verbal communication (Coffey, 2010), short feedback surveys on pace, material complexity, or comprehensibility could be included in suitable places (Luik et al., 2021) and learners can be often asked verbally if everything is clear (Coffey, 2010). It is also recommended to avoid giving lectures and instead allow students to contribute through presentations, comments, and interactions (Mukan and Lavrysh, 2020). The various functionalities of the applications, such as surveys, polls, hand-raising functions, emoticons, and instant messaging, can be used to increase interactivity and excitement and monitor active participation (Cappiccie and Desrosiers, 2011; Correia et al., 2020; Peper et al., 2021). It is also recommended to include regular movement or stretching breaks to increase excitement (Peper et al., 2021).

Lecturers should also take into account the specifics of the subject, as it has been found that different subjects may require the use of particular functionalities (Loch and Reushle, 2008). For example, teaching programming would benefit from the ability to share the screen and take control of the student's screen to find errors in the code more quickly (Coffey, 2010) whereas in mathematics, it is useful to mimic writing solutions on the whiteboard (Loch and Reushle, 2008).

In summary, although it is necessary to conduct web lessons differently than in face-to-face learning, advanced technology still allows students to be connected and feel involved (Li, 2014). At the same time, it must be remembered that videoconferencing alone is not a miracle—it is the lecturers who need to unlock its potential with their activities and creativity (Martin, 2005).

The opinion of students is very important in distance learning. Decades ago, the potential of distance learning, and especially web lessons, was seen when students in a 1992 survey at the University of Iowa said that distance learning courses met their educational needs, and one student mentioned that videotape courses would be important in the future (Miller and Honeyman, 1993). Students' perceptions of distance and face-to-face learning have been repeatedly compared and different results have been obtained. In some cases, distance learning courses are preferred, where students have perceived that they are more complex and time-consuming, but at the same time teach more and are of higher quality (Hannay and Newvine, 2006). In other cases, students have considered face-to-face and distance learning courses to be equally effective (Horspool and Lange, 2012). Face-to-face meetings are also preferred because they are more interactive and engaging than distance learning and allow for a lively discussion (Klonoski and Combs, 2009).

In addition to problems with communication, problems with motivation and fatigue have been identified as shortcomings of distance learning and web lessons. Students find that distance learning makes it difficult to interact with fellow students (Horspool and Lange, 2012; Fidalgo et al., 2020) and limited interaction and socializing among students may heighten the risk of feeling isolated (Ferri et al., 2020; Putri et al., 2020). In addition, when learning at home students can feel stressed and unproductive, and this can negatively affect their ability to concentrate on learning activities, stay present while taking web classes, and lower motivation (Di Pietro et al., 2020; Peper et al., 2021). In an Active Minds survey among college students, 85% of students reported that focusing on school has been the most difficult thing and 80% of respondents said that COVID-19 has negatively impacted their mental health (Active Minds, 2020). Furthermore, students can experience congestion (Sowan and Jenkins, 2013) and loss of attention, especially when they are multitasking (Peper et al., 2021). Distance learning and web lessons also increase the time spent in front of screens (Dushkevych et al., 2020), which is tiring and exhausting for students (Trumm et al., 2020; Oducado et al., 2021). During synchronous web lessons, students also noticed the new phenomenon of feeling exhausted during or after video conferencing, known as videoconference fatigue or “Zoom fatigue” (Bailenson, 2021).

According to students, teachers can do a lot to improve web lessons. Students feel that engagement and perceived learning are most influenced by the presence of the teacher, including humor and personal examples (Hibbert, 2014). Student engagement strategies like allocating time for student questions is considered beneficial in synchronous communication with a teacher (Abou-Khalil et al., 2021), and questions asked during web lessons are considered to support learning (Harrison, 2020). In addition, it has been suggested that asynchronous web lessons can improve students' overall experience and satisfaction with distance learning where synchronous learning does not take place, as they allow closer contact with the teacher and are more similar to face-to-face learning (Harrison, 2020). This also increases engagement and motivation (Scagnoli et al., 2019).

It appears that students' perceptions of distance learning and web lessons have been studied in the past, but the results have been mixed. This may be due in part to differences in disciplines. The goal of this research is to find out how students from different disciplines rate the importance of engagement strategies in web lessons in relation to students' concentration difficulties, motivation problems, and screen fatigue. Three research questions were posed:

The University of Tartu, where the study was carried out, had quite a long track record in distance learning even before the coronavirus pandemic situation. In 1991, the first video lecture was recorded at the university, and since 1998 online learning environments for conducting lectures and workshops have been used (TÜ e-õpe ajajoonel). After that, distance learning has been applied in online in-service training (42.9% of fully web-based online in-service training courses in 2019) and also in regular education, with 69% of fully or partially web-based courses in 2019 (Pilt, 2020).

However, the coronavirus pandemic that began in 2020 affected distance learning at the University of Tartu. A case study (Trumm et al., 2020) found that the number of distance learning courses in the Moodle environment did not increase significantly due to the emergency, but the number of Panopto video lectures and BigBlueButton webinars increased significantly. According to the authors, the reason for the increase was the introduction of digital solutions in order to conduct lessons in a situation of forced distance learning. In the same study, it was found that both teachers and students generally coped with the situation.

The sample of the study consisted of the students of the Faculty of Sciences and Technology and the Faculty of Social Sciences at the University of Tartu, representing two different disciplines [STEM (science, technology, engineering, and mathematics) and social science], who answered the questionnaire. A total of 430 students from the University of Tartu formed the sample (325 of them rated all engagement strategies and they are used in the comparison test). Of these, 199 (46.3%) studied at the Faculty of Sciences and Technology and 231 (53.7%) at the Faculty of Social Sciences including 2 colleges. Narva College is a part of the Faculty of Social Sciences, which includes divisions of Civic Studies, Psychology and Pedagogy, Estonian Language and Literature, Russian Language and Literature, and Foreign Languages. Pärnu College is a part of the Faculty of Social Sciences, which includes departments of Entrepreneurship, Tourism Studies and Social Work Administration. All the institutes with teaching responsibilities were represented in the study and the distribution of respondents by institute is presented in Table 1.

Two hundred and seventy-seven of the respondents (64.4%) were bachelor students, 125 (29.1%) were master's students, 23 (5.3%) were applied higher education students and 5 respondents (1.2%) were integrated bachelor's and master's students. Three hundred and twenty-one of the respondents (74.7%) were women, 100 (23.3%) were men, and nine respondents (2.1%) did not want to disclose their gender. Regarding age, 13.5% of the sample were aged up to 19, 48.8% were aged 20–24, 10.7% were aged 25–29, 6.3% were aged 30–34 and 20.7% were aged 35 and over.

Data were gathered using an anonymous questionnaire, which was administered to the students of the Faculty of Sciences and Technology (FST) and the Faculty of Social Sciences (FSS) of the University of Tartu through the mailing lists of respective institutes in December 2020. Respondents had to rate 15 items on a 5-point Likert scale [ranging from a score 1 (“not important at all”) to 5 (“very important”)], indicating the student engagement strategies that they consider important when participating in web lessons (see Figure 1). The items were composed according to previous studies (Klonoski and Combs, 2009; Sowan and Jenkins, 2013; Luik et al., 2021). Also, students rated their own perceptions of using screens and web lessons with three items: (1) it is harder for me to concentrate; (2) it is harder for me to motivate myself, (3) I feel screen fatigue. The prefacing statement to all these items was “Participating in web lessons” and the items were rated by students on a 5-point Likert scale (1-totally disagree … 5-totally agree). The questionnaire ended with a background data section.

To ensure validity of the questionnaire, two students from the sample piloted it before it was distributed. The students in the pilot study were a 3rd-year undergraduate from the Institute of Computer Science and a 3rd-year undergraduate from the Institute of Psychology, thus representing the Faculty of Sciences and Technology and the Faculty of Social Sciences, respectively. The activities of the students were monitored while participating in the pilot study in filling in the questionnaire and more specific questions were asked if necessary. As the questionnaire was not significantly modified after the piloting, the answers of these two students were also included in the sample.

Statistical analyses were carried out as follows (see Figure 1): First, descriptive statistics on students' ratings of the importance of student engagement strategies and perceptions of students about difficulties were investigated. Answering the first research question, the multivariate analyses of variance (repeated measures ANOVA) with the Bonferroni adjustment for multiple comparisons were used to identify differences between the ratings of the different strategies. For the second research question, the MANCOVA multivariate analysis of variance test was used to compare the ratings of student engagement strategies between students from the two faculties, controlling the influence of screen fatigue. In the last phase, Spearman correlation coefficients were calculated to investigate the relationship between concentration difficulties, students' motivational problems, screen fatigue and the ratings of student engagement strategies for web lessons. As the aim was to know which ratings of 15 student engagement strategies are related to the evaluations on concentration difficulties, we used Bonferroni correction dividing p-value to 15. The same division was conducted with the evaluations on motivational problems and evaluations on screen fatigue.

Descriptive statistics of the student engagement strategies are presented in Table 2. As the values for asymmetry and kurtosis between −2 and +2 are considered acceptable in order to prove normal univariate distribution (George and Mallery, 2010), all the strategies indicated the univariate normality of the data and a parametric test was used. There was a statistically significant difference between the ratings of different strategies [F_{(1, 328)} = 11,431.263, p < 0.001, η2 = 0.735]. Multiply comparison with Bonferroni adjustment indicated that four engagement strategies (“Use of slides,” “Explaining what and why is being studied,” “Sharing the teacher's screen,” and “Recalling what has been learned before”) were evaluated significantly higher than the other strategies (comparison from the others all p < 0.05). There was also a statistically significant difference between the strategies “Use of slides” and “Recalling what has been learned before” (p < 0.01), but there were no other statistically significant differences between these four engagement strategies (all p > 0.05).

Of all other engagement strategies, “Presentation of article-based tasks,” “Second teacher answers questions in a chat,” and “Use of breakout rooms” were evaluated significantly lower (with Bonferroni adjustment all p < 0.05). There was also a statistically significant difference between the strategies “Presentation of article-based tasks” and “Use of breakout rooms” (p < 0.01), but there were no other statistically significant differences between these three engagement strategies (all p > 0.05).

At first, we present descriptive statistics for difficulties as perceived by students in web lessons (Table 3). Again all aspects showed skewness and kurtosis values between the −2 and 2 indicating the univariate normality of data. Comparing perceptions of students about experiences of screen fatigue, low motivation, and low concentration in web lessons from the two faculties with t-test, there was no statistically significant difference in the case of statements about concentration [t₍₄₂₇₎ = 0.499, p > 0.05, d = 0.048] and motivation [t₍₄₂₇₎ = −0.306, p > 0.05, d = −0.030]. However, a statistically significant difference was found in the statement about screen fatigue [t₍₄₂₃₎ = 5.734, p < 0.01, d = 0.558], which was higher ranked by students from the Faculty of Social Sciences (M = 3.77, SD = 1.284) compared with the students from the Faculty of Science and Technology (M = 3.04, SD = 1.333).

As the significant difference was found in the case of screen fatigue and this aspect could influence ratings on student engagement strategies, we used MANCOVA controlling by the screen fatigue ratings. Comparing the ratings given by students from the two disciplines, a significant statistical difference appeared in the case of five student engagement strategies, with F_{(15, 308)} = 11.245, p < 0.001, Wilks' Λ = 0.646 and partial eta-squared η2 = 0.254. “Sharing the teacher's screen” and “Drawing or writing on slides” were rated higher by the students of the Faculty of Sciences and Technology, while the statements “Conduction of short feedback surveys (about tempo, material complexity, comprehensibility),” “Taking stretching breaks,” and “Use of breakout rooms” were rated higher by the students from the Faculty of Social Sciences (see Table 4).

There were no significant relationships between concentration difficulties and the ratings of student engagement strategies, neither in the case of students from the Faculty of Sciences and Technology nor from the Faculty of Social Sciences (Table 5). However, the results indicated that the ratings of the strategy “Offering a selection of tasks of varying difficulty” was significantly related to the students' evaluations on motivation problems for students from both disciplines. The ratings of student engagement strategy “Presentation of article-based tasks” was significantly correlated with the students' evaluations on motivation problems only in the case of students from the Faculty of Sciences and Technology. The ratings of engagement strategies “Explaining what and why is being studied” and “Conduction of short feedback surveys (about tempo, material complexity, comprehensibility)” were significantly related to the evaluations on motivation problems only in the case of students from the Faculty of Social Sciences. As the third difficulty, relations of ratings of students' engagement strategies with the evaluations on perceptions on screen fatigue were explored. In the case of students from both faculties, evaluations on screen fatigue were significantly related to the ratings of the strategy “Presentation of article-based tasks”. In addition, in the case of students from the Faculty of Sciences and Technology, significant correlations with the ratings of “Taking a break from thinking” and “Taking stretching breaks” were found.