University Students’ Autonomous Learning Behaviors in Three Different Modes of ICT-Based Instruction in the COVID-19 Era: A Case Study of Lockdown Learning

Mátyás Bánhegyi, Budapest Business School University of Applied Sciences, Hungary

Balázs Fajt, Budapest Business School University of Applied Sciences, Hungary

Bánhegyi, M., & Fajt, B. (2022). University students’ autonomous learning behaviors in three different modes of ICT-based instruction in the COVID-19 era: A case study of lockdown learning. Studies in Self-Access Learning Journal, 13(1), 5–30. https://doi.org/10.37237/130102

Abstract

This paper explores Hungarian university students’ autonomous learning behaviors during the first wave of the COVID-19 pandemic in Hungary (March-June 2020). A self-developed questionnaire was used to explore some aspects of learner autonomy relying on the action-oriented dimensions of Tassinari’s (2015) dynamic model of learner autonomy. The present paper aimed to investigate how university students in Hungary regulated their learning processes during the first wave of the COVID-19 epidemic in 2020 with regards to three Information and Communication Technology (ICT)-based teaching modes. Based on a quantitative study of the constructs of goal setting, management of the learning process and monitoring of efficiency, the researchers examine to what extent students were capable of adapting, through the exercise of learner autonomy, to challenges posed by the altered learning environment. Results of the study also show that participants had different perceptions of the three teaching modes and that students’ exercise of learner autonomy influenced their perception of these ICT-based teaching modes.

Keywords: COVID-19, digital education, digital transformation, higher education, learner autonomy

By spring 2020, the COVID-19 outbreak had grown into a worldwide pandemic (WHO, 2020), and in order to slow the rapid spread of the virus, several countries adopted strict protocols: lockdowns, compulsory working from home, more flexible working hours and closing institutions including ones in education such as schools and universities (Bozkurt & Sharma, 2020). As a consequence, from March 2020 forward, numerous countries worldwide announced lockdowns and shutdowns of primary and secondary schools as well as higher educational institutions (UNESCO, 2020). On March 11th, 2020, the Hungarian government also decided to close Hungarian higher educational institutions, so colleges and universities pivoted to online, digital education from the very next day. The sudden change caused by these measures required substantial work and effort on the part of both students and teaching staff.

At the end of the 2020 spring semester, numerous higher education institutions collected student feedback on the perception of the digitization of university courses. This feedback was considered important because it was anticipated that in case a switch to (emergency) digital education was necessary again in the future (e.g., in September 2020) as a result of any subsequent wave of COVID-19, such information would be quite valuable. Feedback collected this way was hoped and envisaged to allow for and generate further methodological changes in an attempt to make digital education even more efficient and student-friendly.

With reference to the first wave of the COVID-19 pandemic in Hungary (March-June 2020), this research explores university students’ autonomous learning behaviors in different teaching modes and examines their perceptions of such teaching modes. For that purpose, a self-developed questionnaire was administered to explore some aspects of learner autonomy relying on the action-oriented dimensions of Tassinari’s (2015) dynamic model of learner autonomy: The authors of the present study investigated how university students regulated their learning processes during the first wave of the COVID-19 epidemic in 2020. More precisely phrased, with respect to an educational setting hitherto unknown and unprecedented to students, the present research explores, on the one hand, Hungarian university students’ autonomous learning behaviors in three Information and Communication Technology (ICT)-based teaching modes and, on the other hand, their perceptions of such teaching modes in an exceptional situation requiring a relatively high level of learner autonomy. Relying on a quantitative study based on Tassinari’s (2015) dynamic model, the researchers examined to what extent university students had been capable of adapting, by way of harnessing learner autonomy, to challenges posed by an abruptly altered learning environment.

Theoretical Background

ICT-Based Solutions to Teaching and Learning

For some time now, traditional classroom instruction has been supplemented with different forms of digital education. Concerning available ICT solutions in different modes of instruction and with respect to the application of ICT in language teaching. Pojulà (2020) distinguishes four different kinds of teaching involving ICT tools: 1) web-enhanced teaching, 2) blended teaching, 3) hybrid teaching and 4) online teaching. 1) Web-enhanced teaching involves traditional face-to-face learning coupled and supported by online course components that would otherwise not be available to students. Such components merely supplement the course. 2) In the case of blended teaching, in addition to traditional face-to-face learning, a part of the education takes place through online instruction using digital platforms, where online instruction forms a fully integrated part of the course. 3) In hybrid teaching, synchronous online live instruction is provided to remote students, which is coupled with asynchronous activities. These two components and their integration make up the entire course. 4) Finally, online teaching refers to a teaching method carried out through a synchronous or an asynchronous approach, or their combination. In this scenario education is delivered without any on-campus student activity, typically through some specifically designed and integrated educational platform that fully supports the entire range of learning activities.

Blended Learning

In the pre-COVID-19 era, a combination of traditional classroom instruction with some form of digital education was the most typical form of instruction in higher education institutions (Dziuban, 2018; Graham, 2014; Spring & Graham, 2017; Spring et al., 2016). Ubell (2017) defines this education as blended learning; a form of education in which online, digital education is mixed or blended with the traditional classroom-based form of education. According to Ubell (2017), during blended learning, 70% of education typically takes place online in a digital form, while the remaining 30% takes place in the usual classroom setting. Previous research points out that the advantage of blended learning lies specifically in that it effectively and systematically combines digital and classroom teaching methods and seeks to harness the strengths of each, thereby supporting the learning process (Ho et al., 2016; Jesus et al., 2017; McCutcheon et al., 2015; Powell, 2015).

Concerning higher education, some previous papers claim that in the majority of these learning environments the combination of different online and digital teaching modes with traditional teaching methods has a positive effect on students’ learning processes (Donnelly, 2010; Jesus et al., 2017; Nguyen, 2015; Woltering et al., 2009). On the other hand, some other studies seem to question this interpretation and discuss disadvantageous trends. A study conducted in the United States of America has shown that the digital form of education has lost its popularity in higher educational institutions in recent years (Allen et al., 2016) because the incorporation of different digital tools, methods and content into traditional lessons may cause difficulties for course instructors (Kelly et al., 2009; Ubell, 2017). Digitization, and thus the increased workload caused by a new and previously unknown mode of instruction, may also add complications. Likewise, another problem is the lack of personal contact between students and teachers (Ubell, 2017). In addition, previous research examining teacher feedback and teacher-student interactions revealed that such interactions are not only important for students but also greatly contribute to the success of the learning process (Garrison & Cleveland-Innes, 2004; Rovai & Jordan, 2004). Moreover, these types of interaction do not seem to be present in online courses as much as they are at hand in traditional lessons (DeLacey & Leonard, 2002).

Learner Autonomy

In the extraordinary situation caused by the COVID-19 pandemic, the majority of students were suddenly exposed to a new learning environment. Even if through the Internet they were connected to peers and their teachers under the altered circumstances, students’ own learning more extensively depended on themselves than before: learner autonomy was crucial to their survival and success in their studies. In the scope of the present paper, based on Ruelens’ (2019) work, learner autonomy is defined as a state in which “the learner is aware of the various aspects of the learning process, and is able and willing, to different extents, to use strategies to initiate and regulate their own learning process” (p. 376). The ways autonomous learning takes place is contested in the literature. Viewed collectively, there seems to be agreement on the presence of certain aspects that describe the autonomous learning process, and researchers also agree that some regulation of learning does take place. After having examined what the literature (more specifically, Bolhuis, 1996; Cotterall, 2000; Dam, 1995; Hammond & Collins, 1991; Holec, 1981; Knowles, 1975; Machaal, 2015; Oxford, 1990; Reinders, 2010; Tassinari, 2012; Zimmerman & Pons, 1986) has in common concerning the different regulatory activities (called aspects in Ruelens, 2019) involved in the autonomous learning process, Ruelens (2019) concludes: “Generally, the aspects of the learning process that are discussed [in the literature] are orienting and goal-setting, selecting resources and activities, planning, executing the plan, monitoring the learning process, evaluating the learning outcome and adapting the plan” (p. 377, emphases by the authors). Within the scope of the present research and through the application of the quantitative research paradigm used for the present study, the authors examined students’ autonomous learning behaviors and focused on the perception of three modes of university-level ICT-based instruction. The researchers also intended to collect data from students concerning the ways the perception of their learning process was influenced by the teaching environment they were suddenly exposed to. With a view to this, the researchers focused on three of the above aspects – spanning across the entire learning process – that students were to manage exclusively on their own during the first wave of the COVID-19 period: goal setting, monitoring of the learning process and evaluating the learning outcome. These aspects all reflect students’ decision-making mechanism concerning their studies, which surface as autonomous learning behaviors.

In order to describe the learning process and support this research with a theoretical underpinning, the authors needed to locate a theoretical model of learner autonomy that is capable of capturing decision-making as a distinct part of the model. For this reason, Tassinari’s dynamic model of learner autonomy has been selected as the theoretical framework of the present research, which is supported by the fact that Tassinari (2012) developed and then refined (2015) a dynamic model of learner autonomy capable of evaluating attained levels of learner autonomy. The latter newer model describes autonomy along 4 components: 1) the cognitive and metacognitive component, 2) the affective and motivational component, 3) the social component and 4) the action-oriented component. Briefly put, the cognitive and metacognitive component is concerned with structuring knowledge, whereas the affective and motivational component addresses diverse feelings and motivations influencing learning. In turn, the social component is about co-operating with others during the learning process, while the action-oriented component describes decision-making associated with actions during the learning process. The action-oriented component comprises and extends to the aspects of “planning, choosing materials and methods, completing tasks, monitoring, evaluating, co-operating and managing my own learning (Tassinari, 2015, p. 74; emphases by the authors).

The present research focuses on the most commonly accepted (for a further discussion on these most commonly accepted aspects, cf. Ruelens, 2019) aspects of the autonomous learning process: i.e., goal setting, monitoring of the learning process and evaluating the learning outcome, which feature as ‘planning’, ‘managing my own learning’ and ‘evaluating’ in Tassinari’s (2015) model. According to Tassinari (2015), planning is learners’ design of their own learning process according to their needs and goals, whereas, managing one’s own learning is one’s ability to control and to be in charge of one’s own learning. Evaluating is students’ perception and assessment of their effectiveness in their studies. This model examines attitudes to and behavior along the four components of the model. This feature, in turn, enables Tassinari’s (2015) model to suitably function as a theoretical background for gauging students’ attitude to, and attained behavior along, the aspects included in the model.

Switch to ICT-Based Teaching

Due to the pandemic situation caused by the COVID-19 outbreak, educational institutions in Hungary had practically no other choice but to have students and teaching staff switch to fully online education within a few weeks in March 2020 and manage education remotely. The situation was resolved differently by various higher education institutions: they inevitably had to select from among diverse modes of instruction that involve some ICT solution, and the same is true to language teaching offered by such education institutions.

The Switch to Emergency Digital Instruction in Hungary

Reacting to the COVID-19 challenge in mid-March 2020, Budapest Business School University of Applied Sciences’ (BBS) Institute of Foreign Languages and Communication opted for three different teaching modes of language teaching at each of the University’s three Faculties. All students of each Faculty participated in 2 times 90-minute-long language classes during the term in question.

The Faculty of Finance and Accountancy decided in favor of online teaching relying exclusively on asynchronous language teaching activities, which were made complete with online live synchronous or asynchronous consultation sessions. Working at their own pace and keeping deadlines for submission, students completed the asynchronous activities set out for them in the new learning environment. Students received feedback on their submissions on a regular basis and could participate in consultations at their request.

The Faculty of Commerce, Hospitality and Tourism used online teaching involving synchronous online live instruction during one of the weekly two 90-minute-long sessions of language instruction. For the other 90-minute slot, compulsory asynchronous tasks were assigned, coupled with optional asynchronous activities. This in practice meant that one of the classes was based on instructor-led synchronous activities, while the other session included asynchronous activities that students completed at their own pace observing deadlines for submission. These asynchronous activities were set each week and corresponded to the materials covered during the synchronous online live instruction sessions. Concerning submissions, students received regular feedback and had the opportunity to participate in online or offline consultations at their request.

The Faculty of International Management and Business opted for hybrid teaching in the form described earlier. This meant that the weekly 2 times 90 minutes of language instruction was provided through synchronous online live instruction to remote students, and to a very limited extent asynchronous activities were also used. This teaching meant instructor-led classes utilizing the potentials afforded by the online space primarily through synchronous activities. Table 1 below shows the different modes of instruction at BBS’s three Faculties.

Table 1

Teaching Modes at Faculties and Expected Level of Learner Autonomy

Methods

Prompted by Qian‐Hui and Ying’s (2020) suggestions that in this exceptional period good teaching practices concerning online teaching platforms, live broadcast systems, synchronous classrooms and online teaching should be gathered and shared amongst both researchers and practitioners, the authors of this paper investigated students’ autonomous learning behaviors and their perception of three modes of ICT-based instruction at BBS.

In this context, the following research question guided this study: What were the participants’ autonomous learning behaviors like in the three modes of instruction applied at the three Faculties of BBS, and what characterized their perception of these modes of instruction?

This perception by students was assessed with the help of the quantitative research paradigm and a questionnaire focusing on the three aforementioned aspects of students’ learning process: goal setting, management of the learning process, and monitoring of efficiency.

Participants

The researchers collected data from students attending BBS at the time of administering the questionnaire, i.e., in the spring term of the 2019-2020 academic year. A total of 982 participants were recruited from the three Faculties. Females outnumbered males (80.1%, n=787) and the mean age of the participants was 20.7 (SD =1.71) with a range of 18 to 42 years of age. The distribution of participants by Faculties was as follows: 26% (n=255) was from the Faculty of Finance and Accountancy, 48.5% (n=476) from the Faculty of Commerce, Hospitality and Tourism, and 25.5% (n=251) from the Faculty of International Management and Business, which reflects a slightly uneven distribution of participants from the Faculties in comparison with the total number of students in each Faculty. All participants were enrolled full-time in one of the programs offered by BBS. The participants were required to indicate which foreign language they were studying at the time of the administration of the questionnaire: the answers are shown in Table 2.

Table 2

Foreign Languages Studied at BBS

Research Instrument

For data collection, a self-constructed questionnaire consisting of three questions and 32 statements was developed by the researchers. The items of the research instrument were based on the relevant literature (Tassinari, 2015) and the results of previous empirical research (Asztalos et al., 2021; Fajt, Török & Kövér, 2021). In the scope of the development of the questionnaire, a think-aloud protocol was also used to identify ill-worded items, which was followed by the finalization of the research instrument. The questionnaire was administered in Hungarian, as Hungarian was the first language of the participants. In the scope of the research, participants were asked to what extent they agreed with the statements appearing in the questionnaire, and their behavior – based on their own evaluation – was measured on a five-point Likert-scale (1 = Strongly Disagree; 5 = Strongly Agree). The statements in the questionnaire belong to altogether eight scales related to the learning process’ three aspects (goal setting, management of the learning process, monitoring of efficiency). The questionnaire features in the Appendix to this study in an English translation. The examined aspects and the eight scales belonging to them are as follows.

Aspect: goal setting

Scale:

1. Goal setting (5 items): the extent to which participants were able to set their own learning goals. Sample item: “When I studied in the online digital teaching mode, I was always aware of my daily learning goals.”

Aspect: management of the learning process

Scales:

2. Organization and control of learning (8 items): participants’ capacity to oversee possibilities and opportunities to design and facilitate their own learning and progress. Sample item: “I enjoyed having to organize my own learning.”

3. Controlling environments for home study (3 items): to what extent participants were able to ensure optimal conditions of learning for themselves. Sample item: “I preferred to stay and study at home even if I had had the opportunity to go back to the old ways and go to the university in person.”

4. Requesting help from peers (3 items): to what extent participants asked for help from fellow students when encountering difficulties while completing assignments. Sample item: “I asked my fellow students for help when I didn’t know how to do a task.”

5. Need for personal social contact (2 items): to what extent participants missed being present in their classroom in person. Sample item: “I would have been happier if we had been able to study in person with the other students in a classroom.”

6. Amount of course work for individual completion (3 items): to what extent participants deemed the workload to be completed as part of preparation for classes manageable. Sample item: “I was able to complete the tasks assigned by my teacher in time.”

7. Requesting help from instructors (2 items): to what extent participants asked for help from their course instructor when encountering difficulties while completing assignments. Sample item: “I tried to use all the consultation opportunities offered by the teacher.”

Aspect: monitoring of efficiency

Scale:

8. Monitoring of efficiency (6 items): participants’ perceived effectiveness of online education compared to traditional education. Sample item: “In my perception, digital and online teaching was more effective than traditional face-to-face lessons.”

Data Collection and Data Analysis

The researchers explored participants’ autonomous learning behaviors and perceptions of the three modes of instruction applied at the three Faculties of BBS. The anonymous data collection process took place online between the middle of May and early July 2020, and Google Forms was used for data collection. The data were coded quantitatively and imported into SPSS 27.0 statistical analysis software. Besides descriptive statistics, one-way analysis of variance (one-way ANOVA) was used to find statistically significant differences between the averages of scores. The level of statistical significance was set at p<.05.

Results

The reliability of the research instrument was ensured by testing its internal consistency. The researchers calculated the Cronbach alpha internal consistency reliability coefficients with respect to the different scales: these are presented in Table 3.

Table 3

Cronbach Alpha Reliability Coefficients of Scales

The eight scales were found to be reliable as their Cronbach Alpha coefficient reached the .6 threshold (Dörnyei & Taguchi, 2010). Then principal component analysis (varimax rotation) was performed to identify potential further dimensions within scales. The results of the analysis revealed that all scales loaded onto one dimension each allowing for further statistical analyses.

The results, i.e., data on participants’ autonomous learning behaviors, are presented in Table 4. In order to investigate potential differences in participants’ autonomous learning behaviors in the different modes of instruction, one-way analysis of variance (one-way ANOVA) was run: in the scope of the analysis, with respect to each scale, statistically significant differences between participants’ mean scores were identified in order to gain insights into differences between students’ behavior during the three teaching modes.

Table 4

Results of One-way ANOVA Showing Statistically Significant Differences between Three Teaching Modes

For the eight scales, statistically significant differences were found in the case of a total of seven scales; however, since ANOVA alone is not suitable to uncover which subgroups demonstrate statistically significant differences, post-hoc analysis was also run. The Student-Newman-Keuls (SNK) post-hoc analysis revealed that in case of the first variable, goal setting, there is a statistically significant difference between the three modes of education. For the second variable, organization and control of learning variable, there is a statistically significant difference between the three modes of education. The third variable, controlling the environment for home study, also demonstrates a statistically significant difference between the first two and the third modes of education of. For the fourth variable – requesting help from peers – no statistically significant difference between the different modes of education was identified. In contrast, for the variable need for personal social contact, a statistically significant difference between all three forms of education was found. As for the sixth variable, the amount of course work for self-completion, a statistically significant difference was found between the second and the first modes of education. In the case of the seventh variable, requesting help from instructors, a statistically significant difference between all three variables was identified. Regarding the monitoring of efficiency, there is a statistically significant difference between the first two and the third modes of education.

Discussion

With respect to students’ autonomous learning behaviors, the following can be established along the scales of this research. Concerning goal setting, it seems that students learning in the asynchronous teaching mode were more capable of establishing their own learning goals and became less dependent on their teachers’ help than their peers learning in the other teaching modes. Given this, students perceived the asynchronous teaching mode as a setting more easily enabling them to become goal-oriented and goal-conscious.

As far as learners’ management of their own learning process is concerned, students using the asynchronous teaching mode seemed more relaxed about managing their learning and exhibited less anxiety about and frustration with the situation. This is important because, as Chang et al. (2020) point out, students may experience symptoms of depression and anxiety due to lockdown caused by the COVID-19 pandemic: the alleviation of these symptoms should also be one of the priorities during digital education.

Also, the participants using the asynchronous teaching mode felt more in control of their learning environment than their peers. It is also true, however, that all students – irrespective of teaching mode – missed their instructors’ more extensive guidance on learning, which is in complete agreement with the literature on the importance of teacher-student interaction and feedback (Garrison & Cleveland-Innes, 2004; Rovai & Jordan, 2004). Relying on these findings, it can be concluded that the asynchronous teaching mode helped students become more relaxed about their studies and also more in control of their learning.

As for students’ perceptions of their own learning efficiency during online teaching, it appears that students perceived the asynchronous teaching mode as more effective in comparison with the other modes even if they struggled with goal setting and the management of their learning. This is in line with the study of Lall and Singh (2020), who also found that the participants of their research had an overall positive attitude towards online education. In light of this, asynchronous teaching seemed the most strenuous but also the most effective out of the three examined modes.

Looking at the findings more in detail, it can be established that those studying with the help of synchronous online live instruction coupled with asynchronous tasks or hybrid teaching were more dependent on their teachers’ learning goals setting than students learning through asynchronous activities. This may well have been caused by students’ continued dependence on teacher guidance even after the switch to online education had taken place. This is further underscored by the following finding: asynchronous instruction was less favorably received by the participants than either of the other two teaching modes. This finding is in line with the results of previous research: guidance from the teacher and learning conditions play a critical role in the formation of different dimensions of learner autonomy (Zhong, 2018). It also seems to suggest that students were not fully prepared or unready to assume exclusive responsibility for their own learning and were dependent on their teachers’ guidance. Apparently, instruction using asynchronous activities caused students to be less goal oriented. This finding implies that students’ level of preparedness for autonomy was, in this case, less than what might have been desired. This reassures the findings of pervious research in that it is necessary to foster students’ autonomy and responsibility in the scope of language learning (Al Ghazali, 2020). At the same time, it is also true that students studying with the help of asynchronous activities still missed their course instructors’ guidance, which suggests they could not fully cope with the new and unexpected situation and were probably not suitably trained and prepared to manage such a situation at the time of the first lockdown. In other words, asynchronous activities – which offered less teacher guidance – accompanied by a lack of proper preparation of students for increased autonomy proved to be less favored by students. Even if this way students were given more freedom and enjoyed a less stressful environment, they ultimately had to decide about their learning thereby assuming increased responsibility for their studies, which seemed to be daunting for them. This concurs with the findings of Marcelo and Yot-Domínguez (2019), who found that digital education and education in general are still teacher-centered rather than student-oriented. Moreover, it is noteworthy that according to Campos et al. (2020) it is important to make a point of purposefully training students in diverse skills for learning. Campos et al. (2020) also drew attention to the reality that students cannot simply be expected to become autonomous without external help and gradual preparation.

Another intriguing observation is that students using asynchronous activities preferred controlling their environments for home study and also demonstrated more positive perceptions of digital education. This confirms our previous research carried out in the Hungarian higher educational context (Asztalos et al., 2021; Fajt et al., 2021). At the same time, students who took part in synchronous online live instruction complete with asynchronous tasks or hybrid teaching exercised a lower level of control of their environments and showed less enthusiasm for digital education. This seems to show that the use of asynchronous activities pushed students towards increased control of their learning environments, which contributed to the formation of a more favourable judgment of their studies.

In addition, it can also be stated that students had difficulty finding the right balance between their home duties and university commitments, and this was felt particularly by those who had only asynchronous activities. Our understanding is that students struggled with time management problems and had difficulty separating their private lives from their academic work in the absence of a weekly timeframe offered by the university. But once they engaged in studying, they felt they were in charge and could successfully cope. When considering the possible directions of future developments in tertiary education, Chang et al. (2020) recommend that students should be offered options and freedom of choice in selecting the teaching mode they prefer. Furthermore, it is likewise desirable that autonomous learning and related best practices should be promoted amongst students more extensively, probably in the scope of skills development courses.

All in all, based on students’ autonomous learning behaviors, a general trend of differences between the three examined modes of education was identified. Our results revealed that a clear division line exists between the perception of the asynchronous teaching mode, on the one hand, and synchronous online live instruction complete with asynchronous tasks and hybrid teaching, on the other hand.

It follows from the above that students at the examined university are apparently not autonomous enough to solely manage their own learning. For remedying this shortcoming, self-access language learning centers, which foster autonomy, develop skills of self-directed learning, offer ample language learning opportunities and equip learners with the skills necessary to continue language learning after completing formal studies, provide a viable solution. Typically, self-access learning centers teach students how to tailor their own learning process as well as how to manage content, speed, strategies and resources for their learning, and how to reflect on their learning. With reference to Japan, Mynard (2019) describes numerous self-access learning centers initiatives, which might easily be adapted and adjusted to the needs and characteristics of self-access language learning centers. It is anticipated that once students’ autonomy increases thanks to such self-access language learning centers, they will be less teacher-dependent and will also be able to more easily and effectively cope with those teaching modes that require increased learner autonomy.

Conclusion

By way of investigating students’ autonomous learning behaviors during the first wave of the COVID-19 pandemic, this paper offered some insight into students’ perceptions of three ICT-based teaching modes, and described ways university students regulated their learning processes in this novel online learning environment. Relying on the action-oriented dimensions of Tassinari’s (2015) dynamic model of learner autonomy, the study employed a self-developed questionnaire to explore certain aspects of learner autonomy. It was found that a divide lies between students’ perception of the asynchronous teaching mode and the other examined two teaching modes. As compared to the other examined two teaching modes, students find the asynchronous teaching mode to be more effective but also more demanding. At the same time and irrespective of the teaching mode, students miss their teachers’ guidance on learning and goal setting.

These findings suggest that online education can be made more effective if students are carefully schooled in participating in different online modes of teaching: students should be informed of the advantages and drawbacks of each teaching mode, and their contribution to their own learning must also be made clear to them as far as each of these modes is concerned. It is also obvious that student autonomy should be further increased in order to enable students to benefit even more extensively from online learning environments.

As for future research, further qualitative research could be carried out to explore causes behind students’ perceptions of different teaching modes, which may shed light on why certain modes were received more favorably than others, and what advantages such modes offer that remained unidentified in the present quantitative study. Besides, additional quantitative and qualitative studies could address students’ perceptions of teaching modes not tackled here. Such research may identify those aspects and features of teaching modes that students particularly value: related findings may also contribute to the development of so-far unknown teaching modes.

In addition, further quantitative and qualitative studies could also investigate the relationship between social isolation, learner autonomy, motivation and self-motivation, which may extend to the effects that isolated and other learning environments can potentially have on motivation and learner autonomy. Furthermore, investigating and collecting students’ best practices of goal setting, managing their learning process and monitoring their efficiency in online learning environments could also serve as insightful case studies for both educators and students as to the development of autonomous learning skills are concerned. Finally, other educational contexts, such as the primary and secondary educational contexts could also be investigated to discover if students’ perceptions at these levels of education are similar to those of tertiary students. Such studies could identify similarities and differences between students’ perceptions of diverse teaching modes at different levels of education and could thus provide information on the extent to which certain teaching modes benefit students at different levels of education. Such research projects could shed light on the interrelatedness and complexity of the COVID-19-induced switch to emergency digital education.

Notably enough, the present research project has its limitations. It is important to point out that the study investigated one particular higher education institution in one specific context, namely BBS in Hungary. In other higher education contexts, the data and the results might have been different. In addition, even though the study is a large-scale one, the findings may not necessarily be representative of the population of the higher educational institution where the study was conducted. The last limitation of the study concerns self-report measures: within the scope of such data collection, respondents may hide their real perception and report answers which they think are favored by the researchers.

Acknowledgements

We are grateful to Dr. Réka Asztalos, Dr. Ágnes Ibolya Pál and Dr. Alexandra Szénich, members of the Department of Languages for Business Communication of Budapest Business School University of Applied Sciences’ Faculty of Commerce, Hospitality and Tourism for contributing to the development of the questionnaire used for the present study.

We also wish to thank Dr. Beatrix Fűzi, Head of Budapest Business School University of Applied Sciences’ Research Coordination Office and Dr. Zsuzsanna Géring, Director of the Future of Higher Education Research Center for their valuable suggestions concerning our research.

Notes on the Contributors

Mátyás Bánhegyi (PhD) is full time associate professor and Acting Head of the Institute of Foreign Languages and Communication at Budapest Business School University of Applied Sciences. He currently offers ESP and skills development classes. His research areas include various issues in language pedagogy, methodology of ESP, translation studies and cultural studies.

Balázs Fajt is an assistant lecturer at Budapest Business School University of Applied Sciences. He is also a PhD student in language pedagogy. His research interests include EFL learning motivation and EFL learning beyond the classroom, especially through different extramural English activities including especially films, series, video games, music.

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Appendix (see PDF version)