The COVID-19 pandemic caused widespread disruption across the globe and compelled organizations to rapidly alter their operational methods. Higher education institutions (HEIs) worldwide confronted the challenge of maintaining educational continuity during the pandemic, which highlighted their shortcomings in adequately planning for a potential crisis, resulting in several negative impacts on both research and teaching activities (Shamsir et al., 2022). The responses of HEIs were very diverse, including measures such as space management, sanitation protocols, and, in more severe cases, lockdowns. However, the most prevalent solution was the shift to online classes (Furiv et al., 2021; Oleksiyenko et al., 2021). Some universities adapted swiftly to the new operational landscape, as exemplified by their rapid transition to online learning (Cordova et al., 2021).

The COVID-19 pandemic forced universities to embrace innovation and digitization, accelerating a rapid adaptation process that, while challenging, brought a range of tangible benefits to teaching and learning processes (Chukwuere, 2024). The shift to online education also posed significant organizational challenges, requiring adaptation from teachers, students, and administrative staff alike. The way classes were taught during the COVID-19 pandemic at HEIs worldwide later influenced students’ perceptions of those institutions. Some managed this situation more effectively than others.

The aim of this article is to explore the potential relationship between HEIs’ transition to online operations (including remote administration and remote classes) and student loyalty, as measured by the Net Promoter Score (NPS). The NPS is a well-established methodology that aids in assessing HEIs’ organizational performance and enhancing the quality of their offerings (Cruz et al., 2019). It has been effectively used, for example, in studies such as German and Lestari’s (2021) evaluation of teachers and students’ feedback on the Cambridge Learning Management System.

2. Literature review

The key determinants of service quality in higher education include the quality of academic services, facilities, lecturers, and programs (Kwarteng & Mensah, 2018). Bouranta et al. (2024) identified access, academic aspects, online learning, and program-related issues as critical factors influencing student satisfaction in Greek higher education. Guzmán Rincón et al. (2024) found that satisfaction with different elements of online higher education at HEIs in Colombia had a varying impact on overall satisfaction with the institution and dropout intentions. Such findings highlight the critical role of administrative and support services in shaping student satisfaction, suggesting that satisfaction with organizational aspects serves as a key indicator of students’ overall perception of the institution.

The COVID-19 pandemic led to a significant reduction in face-to-face interactions for a period, often limiting all interactions to conversations via webcams. Traditional study programs and courses, initially designed for in-person instruction, had to be adapted for online delivery. This abrupt shift presented significant challenges for academic staff, who needed to adapt the content and structure of their courses to a virtual environment. Given that the quality of academic staff and study programs are key elements in generating value for students (Lapina et al., 2016), these adaptations were crucial. Unfortunately, the transition to online education was not always successful for HEIs, as this process encountered numerous barriers, which were observed to varying degrees worldwide. Challenges in adopting this solution affected not only students but also HEIs’ academic staff and administrative personnel.

Cramarenco et al. (2023) and Zamora-Antuñano et al. (2022) highlight several obstacles that impeded this transition, such as inadequate equipment for both students and teachers, limited digital literacy, unstable internet access, increased demands for support services, student attitudes, and student attendance at class sessions. Revising courses, lectures, seminars, laboratory sessions, and assessments to integrate digital and mobile technologies often required additional work from faculty members (Cramarenco et al., 2023; Camilleri et al., 2021; Zizka & Probst, 2022). Conrad et al. (2022) further noted that factors such as information overload and the perceived technical skills required for online platforms adversely impacted satisfaction with the virtual learning environment, and that certain design elements – such as class structure and teaching quality – negatively influenced student experiences. Similarly, Turnbull et al. (2021) identified key barriers in the shift to online education, including issues with integrating synchronous and asynchronous tools, access to necessary technology, faculty and student digital competency, concerns over academic integrity, and privacy. Gonzalez-Ramirez et al. (2021) also noted challenges including connectivity and financial constraints, along with negative effects on social interactions, motivation, and health-related behaviors associated with this learning mode.

Research findings illustrate that, across various countries, the shift to online learning was not universally accepted or welcomed. Iqbal et al. (2022) found that Pakistani students were largely dissatisfied with online education during the COVID-19 pandemic, citing insufficient institutional support and low-quality online instruction. They also expressed little interest in continuing online learning once pandemic restrictions were lifted. Similar sentiments were observed among Indonesian students, who generally held negative views of their online learning experiences during the pandemic (Maydiantoro et al., 2020). In South Africa, research conducted at higher education institutions revealed a preference among students for face-to-face learning over online formats, which were hindered by various issues, such as limited data availability, unstable network connections, unconducive home environments, and feelings of isolation (Matarirano et al., 2021). Research in India by Kundu and Bej (2021) further suggests that students feared encountering significant challenges in the online learning environment and felt unprepared for virtual classes during the pandemic.

In certain instances, students initially viewed online learning as an innovative approach; however, over time, it often came to be perceived as monotonous. Zizka and Probst (2023) found that although students in Switzerland recognized the practical benefits of online education, their motivation gradually declined. Similarly, Alexa et al. (2022) reported that Romanian students initially exhibited high motivation in online classes, but this waned as this mode of instruction continued. Limited or absent interaction between the students and instructors in this study, as well as among the students themselves, further reduced motivation and adversely affected their mental health. Packmohr and Brink (2021) found that students expressed a stronger preference for blended learning formats over fully online courses, noting that shifts in course delivery modes hindered their learning outcomes. Due to methodological differences, not all courses could be delivered at a comparable level online – in laboratory-based classes, for example, some competencies can only be effectively developed in person. This is corroborated by Behera et al. (2023), whose findings revealed a marked preference among engineering students for face-to-face instruction, particularly in laboratory settings.

The findings presented in the literature underscore the diverse perceptions and outcomes associated with the shift to online learning during the COVID-19 pandemic, with numerous studies indicating that this teaching approach was not universally effective. While many studies revealed significant challenges, others highlighted potential benefits and neutral outcomes. For example, a study conducted in Portugal found that students’ perceptions of lecturer performance remained unchanged despite the transition from in-person to online education, with no significant differences between pre- and post-COVID-19 conditions (Alves dos Reis, 2021). Additionally, emergency remote education during the pandemic provided students with opportunities to gain new educational and learning experiences. Ukrainian students, for instance, primarily enhanced their digital literacy and communication skills (Mospan et al., 2022).

Interestingly, alongside computers and laptops, students also relied on smartphones to participate in online learning. Krishnan and Sharma (2021) identified smartphones as students’ preferred devices for this purpose. Similarly, Biswas et al. (2020) reported that most student respondents in Bangladesh viewed mobile learning (m-learning) positively during the COVID-19 pandemic. Consistent with these findings, research among female students in the United States also indicated a favorable perception of m-learning throughout the pandemic (Saleh and Jalambo, 2022).

Given the marked differences in how online studies are evaluated by students across various countries, as illustrated in the above literature review, further research on HEI stakeholders’ perceptions of online classes in additional contexts and countries is essential for understanding the factors that drive these differences. For instance, comparative research by K. Fuchs (2021) demonstrated striking contrasts between students in Thailand and Finland. While both groups agreed that complete courses could be delivered online, the Thai students – unlike their Finnish counterparts – did not perceive digital collaboration with their peers as beneficial. Similarly, Cranfield et al. (2021) found significant cross-country differences in students’ views on emergency online learning during the COVID-19 pandemic.
In Poland, after the COVID-19 outbreak was declared, the government announced the suspension of educational institutions’ activities starting on March 11, 2020 (NIK, 2021). Initially, and even later in the pandemic, no explicit guidelines were provided on how HEIs should operate, including how to conduct classes. As such, HEIs in Poland were granted considerable autonomy in deciding on operational formats. As the pandemic evolved, so did educational approaches, with some universities opting to conduct classes entirely online, while others adopted a hybrid model. Every university that continued its educational activities throughout the pandemic utilized online instruction for at least some period, enabling comparative studies on the satisfaction of HEI stakeholders in Poland with this mode of learning.

Research among first-year undergraduate students in Poland revealed a preference for distance learning over traditional in-person instruction, with enjoyment of the online format and a sense of self-efficacy being the primary factors contributing to that preference (Cicha et al., 2021). However, challenges associated with the abrupt transition were significant. A study conducted among Polish undergraduates suggests that the lack of information and dysfunctional communication that resulted in chaos were the most important ones (Kulikowski et al., 2021). Turbulent changes in the functioning of HEIs impacted perceptions of service quality, a critical determinant of student satisfaction, which, Borishade et al. (2021) have shown, can have a significant impact on student loyalty.

3. Research design

An empirical study was conducted to assess the readiness of Polish HEIs for the COVID-19 pandemic. The study employed the Computer-Assisted Web Interview (CAWI) technique, involving 2,832 students (N=2832) at six economic universities, the management faculties of two technical universities, and seven universities across Poland1. The proprietary research questionnaire covered several areas: the functioning of universities during the COVID-19 pandemic (17 variables), the organization and delivery of online classes during the COVID-19 pandemic (20 variables), the likelihood of students recommending their HEI to friends or acquaintances, as well as demographic data – such as gender, mode of study, type of degree program, and year of study.

The scope of the empirical study can be summed up as follows:

a) Subject – students from economic HEIs or departments with an economic profile at other HEIs.
b) Object – evaluation of crisis management at HEIs, focusing on aspects of the organization of higher education operations during the COVID-19 pandemic.
c) Spatial scope – Poland.
d) Temporal scope – the first half of 2021.

Table 1 presents the structure of the study population based on the following criteria: gender, mode of study, type of degree program, and year of study.

The PS IMAGO Pro 10 (IBM SPSS Statistics 29) statistical package was utilized to analyze the collected data. A five-point Likert scale was employed to evaluate students’ perceived preparedness of universities to conduct online classes during the COVID-19 pandemic, with values as follows: 1 – very poor preparation, 2 – rather poor preparation, 3 – average preparation, 4 – rather good preparation, and 5 – very good preparation. Assuming equal dis-tances between categories on the ordinal scale, mean values were calculated to rank aspects of university operations, as well as the organization and conduct of classes at the surveyed insti-tutions during the COVID-19 pandemic. Further methodological steps included exploratory factor analysis (EFA), analysis of variance (ANOVA), independent samples t-test, NPS and Spearman’s rank correlation coefficient.

4. Results

The analysis covered two primary sets of variables: the first encompassed those related to the functioning of universities during the COVID-19 pandemic, while the second included variables related to the organization and delivery of online classes at universities during this period. A list of variables along with their mean values is presented in Table 2.

The aspects rated highest by respondents were as follows:

a) reorganization of classes to an online format (x̅₃ = 3.92), the organization of the recruitment process (x̅₉ = 3.90) and the general impression/perception of the university (x̅₁ = 3.87), among the variables related to the functioning of universities during the COVID-19 pandemic,
b) the opportunity to participate in online consultations (x̅₁₉ = 4.17), materials for online classes (x̅₁₃ = 4,12) and instructors’ attitude towards students (x̅₁₄ = 4.04), among the variables related to the organization and delivery of online classes at universities during the COVID-19 pandemic.

Due to the presence of multi-element sets of variables, Exploratory Factor Analysis (EFA) was employed to identify latent dependencies among the studied variables and reduce the number of original variables into newly defined components (Watkins, 2018; Reio & Shuck, 2015; Taherdoost et al., 2014). To assess data quality in the context of EFA, the Kaiser-Meyer-Olkin (KMO) coefficient and Bartlett’s test of sphericity were used – the test values are presented in Tables 3 and 4. In the process of extracting components, the VARIMAX orthogonal rotation was used (Lloret et al., 2017; Goretzko et al., 2021). The results of EFA within the set of variables related to the functioning of universities during the COVID-19 pandemic allowed for the reduction of 17 variables to 2 components 2. The first component includes variables associated with the administrative and organizational efficiency of the university, while the second encompasses variables relating to the offer of professional and academic development (Table 3).

Analysis of the mean values of the new components indicates a higher rating for variables relating to the administrative and organizational efficiency of the university (x̅ = 3.77) than for those addressing the evaluation of the professional and academic development offer (x̅ = 3.38).

EFA was subsequently applied to the variables relating to the organization and delivery of online classes at universities during the COVID-19 pandemic. This method allowed the original set of 20 variables to be reduced to 2 distinct components. The first encompasses factors related to technical and didactic support in remote education, while the second includes elements contributing to the atmosphere and practical value of online education (Table 4).

A comparison of mean values for the identified components indicates a higher rating for technical and didactic support in remote education (x̅ = 3.84) than for the atmosphere and practical value of online education (x̅ = 3.68).

Next, the mean values of components identified through EFA were compared based on selected characteristics of the respondents (including included gender, study mode, type of degree program, and year of study) and the likelihood of recommending their HEI to others (in line with the according to the Net Promoter Score framework). A ten-point scale developed by F. Reichheld was used to calculate NPS (Vélez et al., 2020; Reichheld, 2003; Rocks, 2016; Reichheld & Schefter, 2000), where a score of ‘1’ indicated a very low likelihood of recommendation and a score of ‘10’ indicated almost certain recommendation. Responses were categorized into three groups: detractors (scores 1–6), passively satisfied (scores 7–8), and promoters (scores 9–10). The NPS indicator was then calculated by subtracting the percentage of detractors from the percentage of promoters (NPS = P – D). Positive NPS values indicate a higher prevalence of promoters over detractors, signifying favorable evaluations of universities’ preparedness during the COVID-19 pandemic.

The independent samples t-test was applied when there were no more than two groups of respondents, whereas analysis of variance (ANOVA) was used for comparisons across three or more respondent groups (Armstrong et al., 2000; Ferreira et al., 2014). The comparison of university functioning components during the COVID-19 pandemic across selected respondent groups is presented in Table 5.

Analysis of these results reveals the following patterns regarding university functioning during the COVID-19 pandemic:

a) Female respondents rated both components higher than male respondents.
b) Part-time students rated both components higher than full-time students.
c) The highest rating for administrative and organizational efficiency was observed among master’s degree students.
d) First-year students, both at the first-degree and second-degree levels, rated both components higher than students in other years.
e) In terms of the NPS framework, promoters had the highest ratings, followed by passively satisfied respondents, whose ratings were higher than those of detractors.

The significance of the identified components related to the functioning of universities during the COVID-19 pandemic was then compared between female and male groups. The obtained results are presented in Table 6.

Analysis of the results for university functioning during the COVID-19 pandemic revealed the following patterns:

a) Among female students, part-time students rated both components higher than full-time students. For male students, no statistically significant differences were observed.
b) Female students in bachelor’s and master’s programs rated administrative and organizational efficiency higher than female students in engineering programs; no significant differences were found among male students.
c) First-year female students, at both undergraduate and graduate levels, rated both components higher than females in other years. Among male students, this pattern was observed only in administrative and organizational efficiency (for professional and academic development, the lowest ratings came from males in the final year of graduate studies).
d) In terms of the NPS framework, promoters rated both components highest, followed by passively satisfied respondents, whose ratings were higher than those of detractors. This pattern was consistent across both female and male groups.

Next, the ratings of components related to the organization and delivery of online classes at universities during the COVID-19 pandemic were compared across selected respondent groups. The results are presented in Table 7.

Analysis of these results concerning the organization of online classes during the COVID-19 pandemic revealed the following patterns:

a) Female respondents rated both components higher than male respondents.
b) Part-time students rated both components higher than full-time students.
c) In terms of technical and didactic support in remote education, master’s students provided the highest ratings, followed by bachelor’s students, with the lowest ratings from students in engineering degree programs. For atmosphere and practical value of online education, ratings from master’s and bachelor’s students were higher than those from engineering students.
d) First-year students, both undergraduate and graduate, rated both components higher than students in other years.
e) In terms of recommendation likelihood in the NPS framework, the highest ratings were given by promoters, followed by passively satisfied respondents, with the lowest ratings from detractors.

Additionally, the ratings of components related to the organization and delivery of online classes at universities during the COVID-19 pandemic were compared between female and male groups. The obtained results are presented in Table 8.

Analysis of the results based on the division into female and male groups evaluating the organization and delivery of online classes during the COVID-19 pandemic reveals the following patterns:

a) Part-time students rated both components higher than full-time students in both female and male groups.
b) Among female students, those in bachelor’s and master’s programs rated university preparedness higher than those in engineering programs. No statistically significant differences were observed among male students.
c) First-year students, both undergraduate and graduate, rated both components higher than students in other years in both gender groups.
d) Promoters gave the highest ratings, passively satisfied respondents gave moderate ratings, and detractors gave the lowest ratings, consistent across both female and male groups.

The final two steps of the research procedure involved assessing the likelihood of university students recommending their institutions to friends or acquaintances. An analysis of the distribution of responses regarding the likelihood of recommendation in selected respondent groups is presented in Table 9.

In the first part of Table 9, the distribution of responses regarding the likelihood of recommending their university is shown across groups of students overall, and separately by gender, study mode (full-time or part-time), type of degree program (engineering, bachelor’s, or master’s), and year of study. The analysis reveals positive NPS values in the following groups: overall (+0.9%), female students (+3.9%), part-time students (+5.0%), master’s students (+4.6%), and first-year students of both first-degree studies (+13.7%) and second-degree studies (+6.2%). It should be noted that these positive NPS values are relatively small – except for first-year first-degree students – which may suggest a declining tendency for students to recommend their universities as the duration of their studies increases.

In the final step of the analysis, Spearman’s rank correlation coefficients were calculated to verify the relationship between the level of student loyalty and components related to the functioning, organization, and delivery of online classes during the COVID-19 pandemic. The obtained results are presented in Table 10.

All Spearman’s rank correlation coefficients presented in Table 10 are statistically significant, confirming the presence of relationships between the level of loyalty (as measured using NPS) and the evaluated areas related to the functioning, organization, and delivery of online classes at the university during the COVID-19 pandemic. Among the components related to university functioning, higher correlation values with loyalty are generally observed for FC1 (“Administrative and organizational efficiency of the university”) than for FC2 (“Offer of professional and academic development”); an exception to this pattern is observed in the evaluations of students in the final year of second-degree studies.

Regarding the organization and delivery of online classes, the correlation values with loyalty are generally higher for OC1 (“Technical and didactic support in remote education”) than for OC2 (“Atmosphere and practical value of online education”).

5. Discussion

The study conducted assessed the functioning of higher education institutions in Poland during the COVID-19 pandemic, with a particular focus on university operations as well as the organization and delivery of online classes. Analysis of the results highlighted varied student opinions, which can be grouped into several key areas.

Firstly, in terms of administrative and organizational support, universities were rated relatively high (x̅ = 3.77); notably, female students and part-time students expressed higher satisfaction with the functioning of universities than male students and full-time students. This suggests that these demographic groups may have experienced better alignment between their expectations and the administrative responses of universities during the pandemic.

Similarly, technical and didactic support was also rated highly (x̅ = 3.84), particularly concerning access to materials, platform functionality, and instructor willingness to collaborate and provide responses. Lower ratings were observed for professional and academic development opportunities (x̅ = 3.38) and for the atmosphere and practical value of online classes (x̅ = 3.68), with master’s and bachelor’s students expressing greater satisfaction than engineering students.

In terms of student loyalty, NPS analysis suggests that first-year undergraduate and second-year graduate students exhibit higher loyalty levels. While NPS values were positive, they were generally relatively low, which may indicate a decline in satisfaction as studies progress. This trend warrants further empirical investigation to explore its causes and potential remedies. These observations are further supported by factors influencing loyalty levels – the strongest correlations with student loyalty were observed for FC1. Administrative and organizational efficiency of the university and OC1. Technical and didactic support in remote education. Notably, higher correlation values were found among female students and part-time students.

6. Limitations and future research directions

This study has a number of limitations. The first pertains to its geographic scope: the survey was carried out solely among Polish students; therefore, its findings may contribute to the scientific discussion on evaluating actions taken by HEIs during the COVID-19 pandemic, but the conclusions are only locally applicable. Additionally, the respondents were students of economics programs, which further narrows the scope. Expanding the study to include students from other disciplines and incorporating a broader set of variables is recommended to enhance the applicability of the findings.

A number of avenues remain open for future research. First, attention could be directed toward analyzing long-term relationships between online education and loyalty (especially considering the observed declines in loyalty in later years of study). Such longitudinal studies could provide insights into the potential for a lasting relationship between remote education experiences and students’ perceptions of their studies, and, consequently, their loyalty. Comparative studies focusing on differences between universities in Poland and abroad could also be beneficial, identifying the most effective practices in online education. Additionally, the role of social interactions and psychological support could be analyzed, particularly regarding the role of atmosphere and interaction in online education. Qualitative research would be especially suitable for exploring the impact of limited interaction on student motivation.

From the perspective of recommendation likelihood, an interesting research direction could involve evaluating the effectiveness of various hybrid education models. This could be informed by variations in satisfaction based on the type of degree program (engineering, bachelor’s, and master’s), with specific attention to verifying how different hybrid models cater to student needs according to the nature of their study programs. Furthermore, applying loyalty indicators to assess specific universities could provide deeper insights: the results from ANOVA analyses and statistically significant correlation findings suggest the utility of NPS in evaluating university preparedness. Exploring diverse educational environments unique to different higher education institutions could be insightful in this regard.

Conducting further research in these areas would enable higher education institutions to better tailor management strategies and online class organization to student expectations, ultimately increasing loyalty toward universities in evolving educational contexts.

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The housing market in university cities is characterised by high dynamics and a classic economic response to external factors. The occurrence of the COVID-19 pandemic meant that it began to change rapidly with the introduction of the first restrictions. The transition of students to a remote form of education, often the loss of a job were the biggest factors affecting the demand and supply of residential real estate. The loss of additional income from work during their studies meant that students were forced to change their place of residence and often return to their family home. One would expect that with reduced demand, the availability of premises would increase, but after a short 'shock’, the situation on the rental housing market in university cities stabilised and the real estate market returned to normal functioning with all its advantages and disadvantages. Interest in the presence of students in academic cities and their impact on the transformations taking place in them is consistently growing (Brooks, 2006; Munro et al., 2009). This is because, the demand reported by this social group concerns many areas of socio-economic life. The presence of students in cities primarily generates traffic in the real estate market, which is associated with the need to find a place to live for the duration of their studies. The demographic structure of cities and the local labour market is also not indifferent to the influx of young people to the city. With the constant number of students in the city, the demand for goods and services is changing, mainly in terms of living conditions, consumption, and participation in culture (Holdsworth, 2006). As a consequence, for several years, the literature on the subject has been discussing the multi-area impact of students on academic cities, which is referred to as studentification (Grzywińska-Rąpca et al., 2021; Nakazawa, 2017). The comprehensive, holistic impact of students on cities was written about at the beginning of the twenty-first century by m.in. Allinson (2006), and further developed, among others, by Kinton et al. (2018 ).

The aim of the study was to demonstrate the relationship between respondents’ assessments regarding: (1) changes in place of residence, (2) changes in the level of apartment rental fees, and (3) the impact of the pandemic on changes in the level of apartment rental fees. The study examined the relationships between respondents’ demographic characteristics and their assessments of their housing situation. As part of the main objective, the following research questions were asked: (1) What is the structure of assessments regarding changes in place of residence, taking into account the demographic characteristics of respondents? (2) What is the structure of assessments regarding changes in the level of apartment rental fees, taking into account the demographic characteristics of respondents? (3) What is the structure of assessments regarding the impact of the pandemic on changes in the level of apartment rental fees, taking into account the demographic characteristics of respondents? (4) Do demographic characteristics and economic activity of respondents differentiate their assessments of their housing situation?

This study, both in its cognitive and application parts, can be a source of knowledge and popularisation of research and can be a source of inspiration for in-depth scientific considerations and discussions. The analysis of the relationship between respondents’ demographic characteristics and their assessments of their housing situation presented in the publication may complement existing studies on the impact of respondents’ characteristics on subjective assessments of market behaviour. Subjective assessments of the housing situation may be taken into account to monitor and shape the housing market in academic centres.

Literature Review

As young people move to strong, academic urban centres, brain drain occurs (Docquier & Rapoport, 2012) in peripheral areas. On the other hand, many students after finishing their education decide to stay in the academic city to continue their professional activity here. Winters (2010) even states that the influx of young people affects the development of smart specialisations, contributing to the sustainable development of cities, making them even smarter.

As mentioned above, the influx of students into cities shapes demand in the local housing market. In general, the choice of a place to live boils down to two possibilities. The first is the housing stock at the disposal of the university. However, as the number of students increased, the housing base usually remained stable. Therefore, in the long run, not everyone interested in living in a student dormitory received such an opportunity. This is a global problem (see m.in. La Roche et al., 2010; Morris et al., 2020; Sotomayor et al., 2022). As a consequence, increased interest was observed in the open housing market, mainly in the rental market. Here, in turn, students usually have the choice of living independently in a rented apartment or co-living in one apartment with several people. The most popular are usually properties located in the immediate vicinity of the university, well connected with the place of education and public transport centres (stations, multi-modal transport transfer points, etc.) (Głuszak & Małkowska 2017).

The presence of students in cities translates into stable housing demand. Living costs, including apartment rentals, are part of the strategies of universities located in individual cities (Domański, 2022). Despite the primacy of private property in the Polish real estate market, academic cities are the places where surplus financial resources are invested in real estate. Properties are then intended for rent. In developed economies, the rental housing market is an important part of the market, dynamising, as Cesarski (2013) emphasises, the economy thanks to the multiplier effect. A wide range of apartments for rent (not only for 'students’) promotes the mobility of the workforce and improves the decisions of households when they are unable to meet their housing needs based on ownership.

The coronavirus pandemic has radically changed the situation of cities and the students living in them. A kind of 'closure’ of economies, minimising the functioning of many industries and moving away from traditional, stationary learning to remote learning caused many perturbations in academic life. Many students living in student dormitories or apartments for rent faced the decision to return to their family home or stay there (Birmingham et al., 2021). In view of online education and in most cases, the lack of earning opportunities, many of them decided to return to their towns (AMRON, 2021; Źróbek-Różańska, 2021, 2022). Researchers of the pandemic period attempted to diagnose the situation of students during this period. Farris et al. (2021) described students’ concerns about the possibility of becoming infected, the impact on the quality of education, which was related to the loss of employment and the need to make housing decisions. Similar results were presented by Iglesia and Lu (2021) in a review of studies documenting the distractors of student life during the COVID-19 pandemic. Long-term isolation and the need for many household members to stay in one apartment (even after returning to the family home) generated both positive and negative consequences (Kajta et al., 2023).

The outflow of students from academic cities has affected local markets, both real estate and the labour market. Rental rates on the rental market have decreased (Borzym, 2022; Mohammed et al., 2021), and the location of real estate near the university headquarters was not an important attribute during the pandemic (Głuszak & Belniak, 2020; Tomal & Helbich, 2022; Tomal & Marona, 2021; Źróbek-Różańska, 2022). The continuing time of the pandemic and isolation caused the loss of job among a large part of students (Oleszczyk, 2022; Rutkowski, 2020; Wronowska, 2021). This was a consequence of students leaving the academic city or closing the entities employing them (Wronowska, 2021).

Bearing the above in mind, the aim of this article is to indicate the relationship between students’ decisions related to residence and their activity on the labour market. According to the best knowledge of the authors, such a relationship has not been verified empirically in Poland so far.

Research Methods

Statistical analysis of data from the survey was carried out using correspondence analysis. This method is useful as an exploratory technique for revealing profiles in data and determining the nature of relationships. It belongs to one of the many specialised methods of data mining. The method is characterised by a wide range of applications and the possibility of a graphical presentation of test results. The statistics obtained as a result of the research procedure enable accurate recognition of the coexistence of categories of variables or objects. The most important steps in the correspondence analysis procedure are:

• Verification of hypotheses about independence adopted for the analysis of features (rejection of the hypothesis of independence),
• Determination of row and column profiles and parameters describing the quality of dependencies,
• Presentation of row (column) profiles in the space generated by columns (rows) of the correspondence matrix, and

1. Reduce the dimension of the space and create a common profile of rows and columns (Stanisz, 2007). Due to the minimal assumptions regarding the measurement properties of data and the possibility of using it on small data sets, this analysis is common in marketing analyses (study of similarities and associations between attributes and brands, market segmentation (Gursoy & Chen, 2000), brand positioning (Berthon et. al., 2001), positioning of a product or service in promotion, sales and advertising (Javalgi et al., 1995), and the separation of consumer profiles (Areni et al., 1998) and social sciences (Hoffman & Franke, 1986). The advantage of this method is the ability to describe relationships between two or more categorical variables (Beldona et al., 2005, Calantone et al., 1989, Malhotra et al., 2004). Polish researchers include, m.in: Stanimir (2005) in economic research, Górniak (2000) in social and marketing research, and Trzęsiok (2016), which used this method in measuring the confidence of financial institutions.

In this study, the analysis of correspondence was used to determine the correlations between the characteristics of respondents and their assessments regarding changes in residence, expectations regarding provisions in lease agreements, and changes in the level of housing fees caused by the pandemic situation.

One of the aims of the study is to demonstrate the relationship between the situation in the labour market of students (employment or lack of employment), gender, and changes in their housing situation. To mine the primary data from the questionnaire, the correspondence analysis used allowed to identify the structure of relationships between the studied variables and to present, without distortion in two-dimensional space, the original configurations of points representing the studied variables. The survey questions concerned the socio-economic situation of students with particular emphasis on the housing situation. First of all, they wanted to know the housing conditions of students and the changes caused by the pandemic. Then, the share of housing expenses in the students’ household budget was taken into account and, again, the changes that were triggered by the COVID-19 pandemic. As a consequence, students’ preferences related to the choice of place and method of residence and preferred provisions in lease agreements were learned.

Results and Discussions

The research was conducted in May 2021 on a sample of 391 students of the University of Warmia and Mazury in Olsztyn. The estimated values of basic macroeconomic indicators for this period prove that the crisis caused by the COVID-19 epidemic may cause many adverse changes in various areas of life. It can therefore be assumed that the date of the study is an appropriate date for analyses allowing for the diagnosis of students’ behaviour regarding changes in the housing market, labour market, and changes in shopping behaviour.
A study on changes in student behaviour regarding changes in the housing market, labour market, and changes in shopping behaviour was conducted in May 2021 among students of the University of Warmia and Mazury in Olsztyn. The respondents were undergraduate, engineering, and graduate students. The research tool was the author’s questionnaire. The frequency of responses in the area of the respondents’ housing situation indicates that there is a variation both by employment and gender of the survey participant (Table 1).

The majority part of students came to Olsztyn from the region and surrounding cities and towns. Only for some, it was associated with taking possession of real estate, for the vast majority, it was related to the search for a flat offered from university resources (mainly, student houses with a limited number of places) and apartments for rent available on the open market. The latter option made it possible to search for apartments on the rental market exclusively for personal use, and to settle the stock together with other landlords, where at that time, a room remained at the exclusive disposal (sometimes, even shared), while rooms such as a kitchen, dining room, or bathroom were available to all co-residents. It is still a popular form of residence during studies.

Therefore, in the situation of suspension of full-time teaching and the transition to remote learning, only a few (determined by factors other than learning) decided to stay in the previously inhabited resources. As can be seen from Table 1, the professional activity of students did not play a significant role here, because very often, the place of employment (trade, services, and catering) of students was also closed. For this reason, the vast majority of students decided to return to their hometowns. This unusual situation caused by the pandemic forced the need to terminate lease agreements satisfying both parties. For this reason, respondents in their declarations pointed to the need to adapt to the lease agreements constructed so far to future, undesirable, and unexpected events. In this case, as shown in Table 1, students who are not professionally active showed greater sensitivity, relatively more often indicated the possibility of efficient recovery of the deposit and other financial outlays incurred earlier.

The results of the correspondence analysis together with generalised singularities and eigenvalues are summarised in Table 2.

Based on the results presented in Table 2, it can be seen that successive dimensions (which are orthogonal to the others) explain smaller and smaller parts of the total value of the chi-squared statistic (and thus inertia). The first dimension allows 76.16% of total inertia to be reproduced, and the included second dimension increases the percentage of explained inertia to 99.87% of total inertia. Therefore, on the basis of this criterion, it is advisable to place the profiles in two-dimensional space. The row and column coordinates presented in Table 3 indicate that the highest value of mapping quality was obtained in the case of the group of women who were not employed during the pandemic (0.999) and for the group declaring the variant of change of residence caused by the pandemic: I returned to my family home (leaving the student dormitory/rented apartment/room) (0.999).

High-quality values (Table 3) for all coordinates (row and column) indicate that there is a high representation of rows and columns by points in two-dimensional space and this means that the original configurations of points have undergone minimal distortion in factorial space. The points representing gender and employment as well as changes in housing conditions declared by respondents were placed in a space defined by two dimensions (Figure 1).

The points near the centre of the system (centroid) represent profiles similar to the average profiles in the entire dataset. The most typical groups of women who were not employed during the pandemic can be considered as the most typical in terms of declared changes of residence. The closest to this row point is the column point: return to the family home.

Another analysis concerned the interdependence of respondent’s characteristics (employees and gender) and expected changes in the provisions of the lease agreement. The first dimension allows 59.97% of total inertia to be reproduced and the second dimension increases the percentage of explained inertia to 100% of total inertia (Table 4).

Therefore, on the basis of this criterion, the location of profiles in twodimensional space is doomed. The further part of the correspondence analysis presented in Table 5 provides information on the role of individual objects and variables in creating the system of the first two factorial axes and the quality of mapping the original configuration of points representing objects and variables by these factors. The quality values presented in Table 5 provide information about the relative amount of information that rows and columns contribute to the data set. The values of the quality level were recorded in all cases equal to unity, which means that in this case, the original point configurations did not undergo any distortion in the factorial space. Relative inertia values indicate the share of row and column points representing individual respondents (rows) and variants of expected changes in provisions in contracts (columns). By far, the largest shares are employed here by women. The values of relative inertia in the column indicate that the expectation of a shorter notice period had the greatest contribution to the formation of factorial space. The points representing row and column profiles are presented in a graphic form in the form of a two-dimensional factorial space (Figure 2), which indicates that the most typical profiles are unemployed women waiting for provisions in contracts excluding reservation fees (answer variant: no reservation fee).

An important issue in the context of the housing situation of students during the pandemic is the level of housing expenses. Another analysis concerned the observed changes in housing fees taking into account the employment and gender of respondents. For the purpose of verifying the assumption about the dependence of the characteristics of changes in the level of housing charges, the following hypotheses were formulated: H0: the assessment of the level of changes in housing charges does not depend on the presence of employment and the gender of the respondent, and H1: the assessment of the level of changes in housing charges depends on the presence of employment and the gender of the respondent. The value of the c2 statistic, the significance level, and the critical value allowed to reject the null hypothesis, and the determined eigenvalues (Table 6) indicated the possibility of presenting the relationship between the characteristics of the level of changes in housing charges and the characteristics of the respondent in a two-dimensional system (dimension 1: 86.95%, dimension 2: 13.05%). After rejecting the null hypothesis, the coordinates and contribution to inertia for rows and columns were determined (Table 7).

The values presented in Table 7 are the relative amount of information that rows and columns contribute to the data set. The determined values, both for row coordinates and column coordinates, indicate that the original point configurations have not been distorted in factorial space. The points representing row and column profiles are presented graphically in the form of a two-dimensional factorial space (Figure 3).

Based on the scatter analysis, 'similar’ respondents were grouped according to the aspect considered. In the third figure, the following groups can be identified: Women employed, unemployed men indicating no change in the level of housing charges; Unemployed women citing lower fees than before the pandemic; Men employed during the pandemic indicating a level of fees higher than before the pandemic. The points closest to the centre of the projection are the first group (employed women, unemployed men indicating no change in the level of housing charges). This group can be considered typical.

Conclusions

Changes in the rental housing market caused by the COVID-19 pandemic can be considered short-term changes. The reason for this may be the fact that the housing market in Poland is characterised by a constant shortage of apartments, high purchase prices, and interest rates unfavourable to borrowers. As reported by Lis (2019), housing needs and their changes are key determinants of setting the main objectives of housing policy. The assessment of housing needs from the perspective of housing policy is made from the outside in an aggregated manner, and not by taking into account the individual needs of tenants. As a consequence, a disconnect may arise between individual expectations and the housing needs of a given community. As early as 1995, Levine (1995) emphasised that expectations regarding rental housing should be closely related to the possibility of choice. In the area of satisfying housing needs, there may be some restrictions of choice due to wealth (Lee et al., 2022). Conducting a survey on the identification of demographic and economic characteristics of respondents aimed at demonstrating differences in expectations regarding changes in the rental market. The results of the analysis of responses representing students showed that, in terms of declared changes of residence, a group of women not employed during the pandemic can be considered indicating the variant of the answer: return to the family home. An important issue in the context of the housing situation of students during the pandemic was the level of housing expenses. Students working during the pandemic expected fees at a level similar to those before the pandemic. Only, the group of unemployed women indicated the level of fees as lower than more than 50% of respondents before the pandemic. The analysis of expectations of changes in the provisions in lease agreements due to the occurrence of the pandemic, taking into account the employment and gender of the respondent, showed that they expected that there was no provision in the lease agreement regarding the occurrence of reservation fees.

The analysis indicates that the introduction of restrictions and the transition to remote education has forced many students to reorganise their lives. A common practice when concluding housing lease agreements is supply-side security, which includes, for example, a deposit made for possible damages or delays in timely payment of fees. According to students (over 50% of respondents) renting a room or apartment, it would be reasonable to include provisions in the contract that would allow for the refund of part of the monthly fee in exceptional situations, which undoubtedly include the pandemic (Martin et al., 2021). A provision expected by respondents in lease agreements is also the concept of a shorter notice period in exceptional situations.

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The COVID-19 pandemic is a phenomenon that has caused a lot of uncertainty, leading to changes in everyday life, social behaviour and economies worldwide. Consequently, most countries have introduced restrictions to ensure the health and safety of their citizens. The impact of the COVID-19 pandemic on the activities of the scientific sector in Poland has also become the subject of analysis and research.

The aim of this article is to discuss the significance and impact of the COVID-19 pandemic on the activities of research institutes in Poland. The data obtained on the basis of questionnaire surveys completed by research institutes in Poland and interviews with representatives of research institutes allowed to identify the main problems faced by research institutes in Poland and how their market situation changed during the pandemic. The article comprises four parts. In the first part, a brief introduction on the current situation of research institutes in Poland, their place and role in scientific policy of the state and the principles of their operation are described. The second part presents an analysis of conducted surveys, wherein the third section is a summary of their results. The last part includes conclusions and an attempt to systematise the main problems encountered by research institutes as a result of the COVID-19 pandemic.

The Outlined Problems

At present, there is a growing need for comprehensive research related to the impact of the pandemic on the functioning of research institutes in Poland. Research regarding the activities of research institutes in the pandemic period and their results may provide guidance for governmental institutions responsible for allocating public funds for scientific activities and may be helpful in developing the principles of the future scientific and innovation policy of the state (Czerniak, 2013).

One of the major challenges in the science policy of the state is the effective allocation of public funds to acquire new knowledge. Research institutes are an essential element of the system of science in Poland. Due to their supervision by competent ministers, research institutes are often referred to as 'departmental institutes’. Not only do they constitute an important source of scientific knowledge, but they are also entities managing research equipment and educating qualified personnel (Daszkiewicz, (2008). This is the only sector of science that was thoroughly restructured in the 1990s. The main direction of restructuring was consolidation. Currently, the framework for the research institutes operation is set out in the Act of law of 30 April 2010 on research institutes.¹

Research institutes, as defined in Art. 1 item 1, are state organisational units, identifiable in legal, organisational, economic and financial terms, which conduct scientific research and development work aimed at their implementation and application in practice. (Dz.U. z 2010 r. Nr 96 poz. 618). In December 2016, an Act was implemented that amended the existing Act of law on research institutes. The amended Act regulates the procedures for the appointment and dismissal of directors of state research institutes and the composition of their scientific councils, including the method of appointing the chairman of the council and the deputies. Subsequently, the new Constitution for Science (https://konstytucjadlanauki.gov.pl) was passed and the Łukasiewicz Research Network was established. (https://lukasiewicz.gov.pl).

A smaller network was also established to strengthen the potential of research institutes to carry out large research projects, both for the development of the economy and the competitiveness of enterprises in the area of land transport.² Currently in Poland there are 99 research institutes, including 32 belonging to the Łukasiewicz Research Network (Kwieciński, 2020) and 3 institutes belonging to the POLTRIN network. The establishment of research networks in Poland was inspired by solutions found in other European countries, such as the Fraunhofer Fraunhofer Gesellschaft in Germany.(https://www.fraunhofer.de/en/aboutfraunhofer. html) (Beise & Stahl, 1999). The research networks that were established in Poland associating research institutes are a necessary and inspiring project for the development of the Knowledge-Based Economy (Barcikowska, 2018).

Public research institutes are diverse and complex scientific units, located throughout the entire country. Each of them has a unique management and organisational culture. They operate in the areas of industry, transport, energy, medicine, agriculture, public services, infrastructure and defence. The main objective of the institutes is to cooperate with the economy and business, and encourage entrepreneurs to implement modern technologies (Matyjas & Bohdanowicz, 2018). At the same time, these units are obliged, like other branches of science, to demonstrate their achievements in research and publication areas. Reconciling these two fundamental objectives of their activities and finding an optimal solution is a difficult and complicated process (Gullbrandsen, 2011).

Due to the ongoing pandemic caused by COVID-19 worldwide, there is a significant danger of reducing the scientific and research capacity of research institutes. Therefore, in 2020, the General Council of Research Institutes — (Rada Główna Instytutów Badawczych — RGIB) conducted a quantitative survey twice using a survey questionnaire among research institutes, the aim of which was to identify the problems the institutes were facing and how much their market situation changed in the initial period of the pandemic, after the first half of 2020 (Christensen & Raynor, 2003).

Analysis of the Impact of COVID-19 on the Activities of Research Institutes

Source material and research method

In March 2020, the Office of the General Council of Research Institutes sent out for the first time a survey questionnaire on the impact of the COVID-19 pandemic on the functioning of research institutes in Poland. A total of 62 institutes responded to the survey, which is about 62% of all institutes in Poland. The survey consisted of five questions concerning the economic situation of the surveyed unit, the conditions for fulfilling undertaken commitments, the impact of the closure of the economy on the functioning of the unit and reduction in employment (https://www.rgib.org.pl/start/dokumenty/329-ankieta-w-sprawie-wplywu-epidemii-covid-19-nasytuacjefinansowo-ekonomiczna-instytutow).

In July 2020, all research institutes were again asked to fill in an extended survey, the aim of which was to find out the opinion of the institutes on how COVID-19 affected the functioning of the units after the first half of 2020 and 61% of them responded. Each question had three possible answers to choose from. After collecting the answers, the RGIB office prepared synthetic information on the results and sent it to the Ministry of Education and Science (https://www.rgib.org.pl/start/ dokumenty/338-informacja-o-wynikach-ankiety-o-wplywie-epidemii-covid-19nafunkcjonowanieib-po-i-polroczu-2020-r).

Analysis and discussion of research results

On the basis of the data collected and published by the RGIB, the results of the survey of research institutes on the impact of the COVID-19 pandemic on their functioning beyond the first half of 2020 are presented below. In this stage, the institutes answered eight research questions.³

The first question, Have you noticed any deterioration in the economic and financial situation of your Institute?, was responded to by 64% of the surveyed institutes, who noted that their economic and financial situation had deteriorated, 3% noticed a significant deterioration, whereas in one in three institutes the situation had not deteriorated. The results are shown in Figure 1.

The second question, How does the implementation of previously signed contracts as well as national and international commitments look like?, was answered by 26% of the institutes, who stated that during the pandemic period no problems occurred with the implementation of previously signed contracts and national and international commitments, 64% of the institutes faced problems with the implementation of previously signed contracts, while 6% answered that it was not possible to implement contracts (Figure 2).

The third question, Were there any other adverse impacts directly or indirectly related to the pandemic which affected the operation of the Institute?, was answered by 39% of the institutes in the affirmative, 38% reported no adverse action and 23% described the difficulties as minor (Figure 3).

The fourth question, Has the current situation caused, or is it likely to cause, redundancies in the Institute?, was replied by 13% of the institutes surveyed in the affirmative, 80% in the negative and 7% were unable to predict whether redundancies would occur (Figure 4).

The fifth question, Do you think the ongoing situation may negatively affect the institute’s economic performance in the current year?, was answered by as many as 80% of the institutes in the affirmative, 16% in the negative and 4% replied that it was difficult to estimate (Figure 5).

The sixth question, Has the institute benefited from assistance under the Anti-Crisis Support Shield?, was answered in the affirmative by 28% of the surveyed institutes and in the negative by as many as 72% of respondents (Figure 6).

The seventh question, Is the existing support for research institutes within the framework of the Anti-Crisis Support Shield sufficient?, was
answered by 6% of the surveyed institutes in the affirmative, 51% in the negative and 43% were unable to give a definite answer (Figure 7)⁴

The eighth question, Do you see any need to extend the Anti-Crisis Support Shield with additional solutions targeted at research institutes?,
was answered by almost 100% of research institutes in the affirmative.

Interpretation

The answers obtained to the eight questions of the survey questionnaire encourage the following reflections:

• there is clear concern among research institutes about their economic and financial situation in the first half of 2020, but many also express their concern about the future, with more than half of those surveyed reporting a deterioration in their financial and economic situation during the COVID-19 pandemic;
• despite significant problems due to delays in the implementation of signed contracts and commitments, most institutes met their
  obligations;
• delays and changes in contract schedules, delays due to the delivery of equipment from abroad, have become a fairly obvious problem;
• the majority of institutes are unlikely to plan staff reductions (it should be added that some institutes decided to make temporary changes to working conditions, reduce raises, reduce working time or reduce basic salary);
• for more than half of the institutes surveyed, the introduced AntiCrisis Support Shield was not sufficient and not many institutes took advantage of it. Moreover, the information received during the 4th meeting of the RGIB5 shows that the main reasons for the
  deterioration in the economic situation of the institutes resulted from the inability to carry out field research in a timely manner and limitations in obtaining new orders. Lack of trainings, scientific seminars and conferences which impeded professional development opportunities, and increased market prices for certain raw materials necessary for research works were also observed. However, most institutes maintain financial liquidity. The main reasons for the deterioration of the institutes’ economic situation are due to the economic slowdown. Significant costs were generated by expenditure on ensuring safe and hygienic work, as well as purchasing additional equipment necessary for remote work. There were also time delays in cooperation with domestic and foreign contractors.

The recommendations and guidelines made by the General Council of Research Institutes, after consultations with representatives of research institutes, to the Ministry of Education and Science to reduce the impact of the COVID-19 pandemic included the following solutions:

• direct reference in the legislation to research institutes as entities covered by the Anti-Crisis Support Shield;
• the creation of a special-purpose financial reserve for research institutes at the disposal of supervising ministers, the purpose of which would be to provide ad hoc support for institutes in the most difficult situation caused by COVID-19;
• regulation of the remote working mode contained in the Labour Code; 􀁺 the possibility for research institutes to obtain additional funding to support the IT infrastructure;
• increase the annual subsidy by a significant percentage;
• the allocation of more funds by the Ministry of Education and Science to research and development work carried out by the institutes;
• introduction of legal solutions allowing for the extension of the implementation period of projects financed by National Centre of Research and Science (NCBR).

It was also proposed by NCBR to launch the IN4IN programme, targeted at real economic and social needs, taking into account the capabilities of entrepreneurs, with higher than so far co-financing from NCBR. The proposed programme would include in particular technical, technological and medical solutions (Biuletyn Rady Głównej Instytutów Badawczych, 2020).

On the positive side, there have been significant advances and developments in the technological processes necessary to carry out online work, and a significant increase in scientific publications. Research institutes have coped reasonably well with the pandemic period and have adapted their activities to the prevailing conditions. In the future, it will be reasonable to continue with this research and to present it after the end of the pandemic time. It is also worth considering undertaking research related to the issue of research institutes and their management, internal regulations and organisational structures, which undoubtedly have a huge impact on their operation in Poland (Biuletyn Rady Głównej Instytutów Badawczych, 2021).

Conclusions

The COVID-19 pandemic proved to be a disruptor of the existing order of things and a catalyst for change in many areas of life, although often sudden and unexpected. The need to limit contacts with other people forced and accelerated changes in the technological sphere, which not everyone was or is ready to accept. The disruption of supply chains, the inertia of adaptation processes and uncertainty in markets have led to a significant increase in interventionism and levels of inflation not seen for many years. Finally, the imminent threat to human life and health, resulting in overburdened health systems in many countries, was, on the other hand, accompanied by a wave of scepticism. Today’s world is becoming increasingly complex and multidimensional (Smith, 2006). It is difficult to avoid risks, meet challenges and exploit opportunities without coordinated efforts and the use of talents and resources. It also seems impossible to solve any civilisational problem without cooperation between science, administration and business.

In the crisis that COVID-19 caused, the need for research and innovation development is clear. The way work was organised, managed and collaborated revealed the interdependence between research and policy. Compared with universities, the issues related to research institutes are much less addressed and described in the literature. Quite often, they are treated holistically as a scientific and research system without focusing on the specifics of their activities. Their functioning is influenced by the scientific and innovation policy of the state, appropriate legal regulations facilitating their operation and financial resources dedicated to these institutions. In order to function properly, they need stability and predictability of actions of the government administration, the Ministry of Education and Science, state agencies such as the NCBR and the National Centre of Science (NCN). It is necessary to create institutional, organisational and information solutions, support tools in which they could develop and their activity would have an effective impact on the scientific and economic development of the country. The analysis and conclusions in this article in relation to the impact of the COVID-19 pandemic will be an indication for the development of appropriate legal and economic solutions (Gryzik, 2017).

Endnotes

1 The provisions of the Act shall not apply to research institutes of higher education and research centres of the Polish Academy of Sciences.
2 Polska Sieć Instytutów Badawczych Transportu–POLTRIN.
3 For the analysis, the author chose a questionnaire with the largest number of questions.
4 The question was answered by research institutes that benefited from the Anti-Crisis Support Shield.
5 The meeting was held on-line on 1 July 2021 and the author participated in it. For more information see Bulletin of the General Council of Research Institutes No. 2 July 2021.

References

Literature of the problem

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2. Beise, M., & Stahl, H. (1999). Public research and industrial innovations in Germany. Policy, 28, 377–422.
3. Biuletyn Rady Głównej Instytutów Badawczych. (2020, December). Instytuty badawcze w rzeczywistości zmienionej przez pandemię COVID-19. Bulletin of the General Council of Research Institutes Research Institutes in a Reality Changed by the COVID-19 Pandemic, 1(107), 1–4
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Education is the key determinant of socioeconomic and cultural wellbeing. In the era of globalization, innovation and competitiveness in various areas of economic and social life, education remains high on the list of priorities, and lifelong learning has become an established paradigm. Education plays a major role in the life of every human being, starting from compulsory education in primary school,1 through secondary school, the choice of university studies, the acquisition of professional skills and further qualifications, all the way to self-development and the pursuit of passions and interests.

At the same time, education is — alongside healthcare — among the areas of socioeconomic life that have been particularly strongly affected by the COVID-19 pandemic. School closures caused by COVID-19 affected over 90% of the world’s enrolled learners (Strauss, 2020), which upended the education landscape. The effects have been experienced by learners in all types of education institutions: from pre-primary schools to universities (United Nations, 2020). In addition, the pandemic has impacted those planning to study abroad (Dhungana, 2020).

However, even before the outbreak of the pandemic, interest in new technologies in education had already been visibly on the rise. Global investments in educational technology (EdTech) reached USD 18.66 billion in 2019, and the overall online education market is expected to reach USD 350 billion by 2025. Since the outbreak of the pandemic, however, there has only been even faster growing interest in language applications, virtual tutoring, video conferencing tools and online learning software (Li & Lalani, 2020).

When the COVID-19 pandemic first arose in March 2020, in-person learning became mostly impossible in many places, including in Poland. As public and non-public schools suspended their traditional activities, the education system shifted towards e-education, with various methods and forms of distance education being rapidly implemented. Schools were forced to shift to the online mode of teaching virtually overnight, which caused numerous difficulties and posed an enormous challenge to the Polish digitalization programme. Legitimate questions arose about whether online education could provide all learners with the right conditions to advance their knowledge and obtain results similar to the ones that would have been achieved during traditional learning. Some of the opinions that were expressed were enthusiastic, while others were sceptical.

Access to the Internet and the quality of the connections, as well as access to such devices as desktop computers, laptops, tablets, and smartphones were important issues. This problem has manifested itself in many countries, in myriad ways. For example, 95% of students in Switzerland, Norway, and Austria have a computer to work on, compared with only 34% in Indonesia, according to OECD data. In the United States, there are considerable differences in access to a computer between students from more privileged vs more disadvantaged backgrounds (Li & Lalani, 2020). In Poland, certain inequalities of opportunity were driven by the fact that not all children, adolescents, and students had access to the Internet and/or the necessary hardware. However, many authorities (including local governments), celebrities, and even schools at various levels of education took initiatives to counteract this situation.

Since the situation in the next school/academic year, 2021–2022, remains uncertain at the time of writing this article, the question arises of whether e-education or its selected elements can continue to be used in the teaching process and whether hybrid learning is possible. There is no doubt that learning new solutions in the sphere of e-education is not merely a matter of expedience but a necessity. However, this requires the development of new skills and new student-teacher relationships. In the words of Paweł Poszytek, director general of the Foundation for the Development of the Education System (FRSE), „the pandemic is not only a crisis. It is a tremendous opportunity to test both new educational tools and our competencies” („Edukacja w czasach pandemii,” 2020).

This study reported herein sought to explore the current state of affairs in the Polish e-education market, as perceived by the owners of companies providing commercial educational services and by secondary school and university students who consume educational services. The study was carried out in May 2020, which means early on during the COVID-19 pandemic, and it had a twofold nature. Firstly, to set the stage and gain an overview of the market, in-depth interviews were carried out with eight owners of companies offering e-education services. Next, an extensive online survey was carried out among secondary school and university students concerning their degree of experience with e-education and their satisfaction or dissatisfaction with such services. By surveying two groups of students from different age groups, we sought to compare their behaviour and motivations both before and during the COVID-19 pandemic.

Before these two parts of the present study are presented in detail, however, the next section of this paper sets the current e-learning situation into a broader historical context.

Some History: From Correspondence Courses to Modern E-Learning

In the pre-Internet era, distance education involved sending educational materials by regular post between the education institution and its students. This was called „correspondence education” and it is first attested in the early half of the eighteenth century (Penkowska, 2010, pp. 9–10, 14–15). It is assumed that correspondence education started in 1728 in the United States, when the Boston Gazette advertised a correspondence course for the residents of Boston. Those who enrolled in the course had several lessons sent to them by regular post on a weekly basis. The classes were organized by Caleb Phillips, a shorthand teacher. A similar model was noted in Poland in 1776, when the University of Kraków started to offer „vocational courses for craftsmen” (Agnieszka, n.d.).

In the nineteenth century, the method gained increasing popularity. In England, correspondence courses started to include not only shorthand but also English and German language courses. Lessons in the transcription of Bible passages initiated by Isaac Pitman, regarded as the pioneer of distance education (Penkowska, 2010, pp. 14–15), eventually rose to fame. The students were required to transcribe selected chapters into shorthand and send the results to the instructor by letter for grading. The instructor would then add his comments and send the materials back to the students, also by regular post. These can be recognized as early counterparts to today’s methods that involve submitting a draft assignment online using an e-learning platform for subsequent grading by the teacher/lecturer.

As distance education flourished, universities and other higher education institutions became the main centres offering correspondence courses. Their scope was broadened, and the lessons were modernized and modified. Important figures in the field of correspondence education included Anna Eliot Ticknor, who founded the Society to Encourage Studies at Home (SH) in the United States in 1873. The organization offered distance courses in 24 subjects (Penkowska, 2010, p. 15).

With the development of technology, remote education underwent successive transformations. The distance education market grew rapidly in the twentieth century, characterized by a number of new inventions enabling the transmission of information, such as radio, television, computers and the Internet. In the United States and Australia, educational radio started to be used, which facilitated education in sparsely populated regions and in rural areas, where no traditional schools operated (Dąbrowska et al., 2013, p. 30). The year 1945 witnessed the emergence of what was called educational television, and the 1960s marked the beginning of the computer age, with computers gradually starting to take centre stage at numerous universities around the world, with the United States being the leader in this field.

Once computers became commonplace, it was only a matter of time before e-learning gained popularity. The first e-learning platform, called PLATO (Programmed Logic for Automatic Teaching Operations), was created in 1965 at the University of Illinois and continued to operate until 2006. Many of today’s multi-user concepts (such as forums, online testing, e-mail, chat rooms for real-time conversations, instant messaging, screen sharing and multiplayer video games) were originally developed on PLATO. By the standards of its times, PLATO was a highly innovative system (Dąbrowska et al., 2013, p. 30).

The 1990s witnessed the rapid global expansion of the Internet. Exploring the opportunities it offered made education possible in almost every place in the world with network access. The Internet enabled unrestricted communication, real-time conversations and interactions between teachers and students, an immediate transfer of knowledge and the removal of the barriers of time and space. E-learning developed largely thanks to advancements in digital telecommunication, as well as multimedia and satellite technology. Educational institutions and universities were established that offered fully remote studies ending in the awarding of a diploma. Radio and television courses were replaced by videoconferences, which were later displaced by online education (Penkowska, 2010, pp. 17–18, 62–63).

The next step in the expansion of e-learning is related to the development of mobile technology. Opportunities offered by the ubiquity of mobile phones and smartphones, which are much smaller in size than computers, contribute to the growing popularity of such devices in e-education. A phenomenon referred to as media convergence has changed the existing framework of the use of basic education tools, primarily the Internet. It can now be accessed using various devices, not only computers, and e-learning with the help of mobile phones, pocketsize tablets and smartphones is rapidly gaining popularity, which necessitates the adaptation of educational courses to continually shifting mediums.

Numerous inventions in the field of data transmission and their various applications have pushed down the costs of education, thus making it more accessible. Inequal opportunities in access to knowledge among various social groups have been gradually reduced.

Some of the ways e-education (also referred to as e-learning, online education, and distance education) has been defined in the literature are as follows:

• as a form of education conducted via electronic media, including computer networks, as well as satellite, radio and television broadcasts. Here e-education is understood as an interactive method of education based on the use of the latest developments in information technology (IT), with the teaching content and related information being transmitted primarily through the Internet, but also through local area networks (LANs), often with the use of audio-visual materials, DVDs, etc. On this approach, e-education comprises a wide range of learning technologies and methods; it combines self-directed learning with the use of selected electronic tools and traditional methods by which students learn from lecturers (Stecyk, 2006, p. 295–300);
• as „a teaching process that takes place in a non-school environment (derived from the concept of distance learning/distance education) and aims to create new quality in learning by using modern multimedia ICT solutions in the education process” (Kuźmicz, 2012, p. 130). Here e-education is understood as a process conducted using various tools, in particular desktop computers and laptops, notebooks, tablets, graphics tablets, mobile phones, PDAs (Personal Digital Assistants)2 and smart TVs;
• as a type of teaching and learning process that represents the whole of the educational model applied or a part thereof with the use of new information and communication technologies that enable communication, interaction and remote access to educational materials. Here, e-education is seen as promoting the acceptance of new approaches to education and its development (Szczepaniak-Sobczyk,
  2018, p. 66).

The COVID-19 pandemic that began in 2020 has necessitated an unprecedented and vast increase in the transfer of knowledge through e-education. In this mode of teaching, it is chiefly the student, not the teacher, who is required to plan the process of acquiring knowledge and achieving the desired results. Young people are increasingly eager to explore new educational opportunities, online content and educational computer games. Teachers and authors of curricula are trying to adapt the educational process to these new opportunities. There is a visible tendency to increase effectiveness, optimize time management and focus on the most important activities, namely work and leisure time.

The most popular consumer trends currently observed in e-learning include:

• blended learning (Penkowska, 2010, pp. 106–107);
• mobile learning (Hejduk, 2009, p. 43);
• augmented reality (the physical world is combined with electronic data and images; Szczepaniak-Sobczyk, 2018, pp. 168–169),
• artificial intelligence (such as homework solving and speech recognition applications), machine learning (such as coding, language learning, supporting teachers by aggregating student data in one place), and MOOCs (massive online access courses, which target an unlimited number of users and allow open access via the Web; Kwiatkowska, 2018, pp. 51–52);
• MOOCs (massive online access courses, which target an unlimited number of users and allow open access via the Web); (Kwiatkowska, 2018, pp. 51–52);
• open educational resources (open databases offered increasingly frequently by higher education institutions); (Dąbrowska et al., 2013, p. 53);
• intelligent multimedia textbooks (for example the Semantic Web); (Banachowski, 2013, p. 11);
• personalized education programmes (in both non-public and public schools, especially in higher education institutions); (Madej et al., 2016, p. 15),
• popular information sources (the ability to search for and find relevant information; (Banachowski, 2013, p. 15),
• social learning (acquiring individual, professional, practical and emotional skills through collaboration with other group members);(Dąbrowska et al., 2013, p. 43); and
• gamification (learning through games); (Margulis, 2005).

Materials and Methods

This study, seeking to examine the situation in the Polish e-education market in the post-COVID-19 realities, comprised two parts. Firstly, to set the stage, a qualitative survey was conducted among owners of companies who provided educational services. Secondly, an extensive quantitative survey on was carried out among consumers of educational services (secondary school and university students); by surveying both service providers and two groups of students from different age groups, we could study their behaviour and motivations both before and during the COVID-19 pandemic. Each of these two sources of information will now be described in turn.

Qualitative survey among education service providers

The qualitative survey was conducted among owners of companies that provide educational services: online tutoring, video courses, email courses, webinars and dedicated e-learning platforms. Eight such individuals were selected in a targeted sample, with whom in-depth interviews of this sort were conducted. The interviews were structured around the objective of addressing questions relating to the situation their companies found themselves in during the COVID-19 pandemic. Some of the interviewees’ companies had previously provided traditional in-person educational services but due to lockdown measures had been forced to temporarily suspend this form of teaching.

Quantitative study among education service consumers

The quantitative survey among consumers was carried out among two groups: final-year secondary school students (group I) and university students (group II). The questionnaire survey was carried out using Computer-Assisted Web Interviewing (CAWI) — an Internet surveying technique in which the interviewee follows a script provided on a website — on 10–25 May 2020. It is perhaps worth stressing that this was a time when the use of e-education during the COVID-19 pandemic was still an largely unstudied phenomenon.

The questionnaire survey was correctly completed by a total of 803 respondent Of this number, 30% (243 respondents) were members of group I and 70% (560 respondents) belonged to group II. The survey was conducted using the CAWI method (computer-assisted web interviewing) and purposive sampling. The study questionnaire comprised 20 thematic questions, including 17 closed-ended questions and three open-ended questions. In addition, the questionnaire included five demographic questions related to: the type of education institution (public/non-public), the type of studies or the class curriculum profile in secondary school, the mode of studies (full-time/part-time studies), the city in which the respondent learnt and gender. Filter questions were used to find out whether respondents had used e-learning during the coronavirus pandemic and whether they had done so before its outbreak. In this way, we selected a group of respondents that met the sampling criteria.

Among the respondents in group I, 65% attended general secondary schools, 33.3% attended technical secondary schools, and the remaining 1.6% indicated the answer „other.” Group I was characterized by a significant prevalence of women (86.4%) over men (13.6%).

In the survey of university students, 97.5% of the respondents studied at public universities, compared with 2.5% enrolled at private universities. Among those surveyed, 61% pursued first-cycle programmes (bachelor’s/engineer’s degree), 27.5% pursued second-cycle programmes (master’s degree), and 11.5% pursued long-cycle programmes. Among the respondents, 495 were full-time students, and 65 were part-time students. Group II was likewise characterized by a significant prevalence of women (82%) over men (18%). Among the cities in which the respondents learnt, the most frequently provided answer was Warsaw (190 respondents), followed by Wrocław (124), Kraków (93), Toruń (88), Rzeszów (18) and Lublin (7). Other cities received single answers from the respondents. The surveys were conducted in May 2020.

Results

E-Education From the Perspective of Service Providers

The qualitative interviews carried out with providers of education services revealed that after the COVID-19 pandemic broke out, they noted an increase in interest in products aimed at secondary school students. Moreover, they attributed this situation to the upcoming final exams and students’ dissatisfaction with online education organized by schools, which prompted learners to search for additional sources of knowledge. In addition, such services also provided a way for young people to spend their free time during the lockdown. However, the respondents also stressed that the demand for online education among adults had dropped during the pandemic, which they in turn blamed on the uncertain situation in the labour market, concerns about job stability and job loss and cost-cutting, including at the companies that had financed such services for their employees. When asked about the prevailing trends in the education market before the COVID-19 pandemic, the respondents consistently pointed to a growing interest in in-person tutoring. As for online education, however, they provided highly diversified answers, pointing to a steady rise in the popularity of online tutoring and e-learning platforms, as well as a decline in the popularity of email and video courses.

The respondents listed the following reasons for the increased demand for online tutoring: wishing to save time on commutes, being accustomed to using computers/mobile devices to work and do various other activities, an easier time overcoming the language barrier for shier people and enjoying greater anonymity. They argued that students found it a lot easier to „open up” when interacting via Skype, for instance, than when interacting in person, in direct contact with people who might be seen as judging them.

As for the advantages of e-learning platforms, the owners surveyed pointed out the accumulation of knowledge presented in different forms (such as text, audio, video and image files) in one place, as well as uniform ways of tapping into them, which translated into intuitive navigation.

The respondents also pointed to growing competition. Before the pandemic, many companies knew very little about digital marketing, which meant higher conversion rates in advertising campaigns on Facebook and those using Google Ads. Internet marketing is now much more popular, and email marketing campaigns are a lot less effective for reasons related to the oversaturation of this form of communication, which impacts on the possibility of winning customers. In addition, the market is increasingly saturated with online courses, which are relatively easy and inexpensive to organize. Mounting price competition is pushing down the profitability of businesses.

According to a majority of the respondents, the devices predominantly used by their customers for e-learning are laptop computers. At the same time, the percentage share of those using mobile phones (smartphones) in the education process is a lot greater than five years ago. The rising curve of the use of mobile devices and the gradually declining curve of the use of desktop computers in the e-education process is evidence of a trend known as mobile learning.

E-Education From the Perspective of Final-Year Secondary School Students

Secondary school students, including final-year secondary school students, reported that they are particularly motivated to use educational services outside of school for reasons related to their secondary school graduation exams (known as the matura in Poland) — not only to pass the exams, but also to prepare for them as well as possible and obtain good results, which will help them get into their target universities. University students, on the other hand, reported that they are motivated by the prospect of mid-term and final exams, the desire to change their study path, interest in increasing their knowledge capital and the acquisition of additional skills, which they will be able to use on the labour market in Poland and abroad.

A vast majority of the secondary school students we surveyed (92.6%) said that they participated in online lessons provided by their schools, which demonstrates not only that students participate in online education but also that schools do organize and conduct such classes. Among the respondents, 2.5% provided negative answers, i.e. they did not attend remote classes, despite the fact that such lessons were provided by their schools. Reasons for this could include not only reluctance to participate, but also the absence of adequate technical infrastructure. According to data from Statistics Poland (GUS), 84.2% of Polish households had access to the Internet in 2018 (Orczykowska, 2018), compared with 90.4% in 2020 (Wegner, 2020), which translates into a rise of 6.2 percentage points. In the study, 4.9% of the respondents declared that their schools did not provide additional distance education, so they had to learn by themselves, using available sources or paid forms of e-education services to pass their exams with good results.

The respondents were then asked about the forms of e-education provided by their schools. The most frequently used tools included textbased materials sent by email (197 responses), live online classes (149 responses) and education platforms (97 responses). Audio and video materials, e-books and educational games were less likely to be used. The respondents who answered that they participated in live online classes were asked about the tools most commonly used by teachers in communication with students to conduct lessons. The most popular platform for live online classes was Microsoft Teams, followed by Zoom, Skype and Discord. Other tools that were mentioned included Facebook Messenger, Google Hangouts, Google Meet, WhatsApp and Webex. Participants in online school education were asked to rate their satisfaction with the classes they attended and the methods of conducting them on a seven-point Likert scale (one — strongly dissatisfied, two — dissatisfied, three — somewhat dissatisfied, four — no opinion, five — somewhat satisfied, six — satisfied, seven — strongly satisfied). The most frequently indicated ratings were „four” and „five” (22.9% of all answers each), which means that secondary school students were, on balance, moderately satisfied with this form of education.

Secondary school students were also asked to identify the advantages and disadvantages of e-learning. The advantages they named included: flexible learning hours, the possibility of lengthening or shortening lessons without waiting for the school bell to ring, delayed start times compared with traditional education, teacher engagement, no need to commute to school, the possibility of assuming any posture or position during remote lessons, no need to show one’s face, greater understanding on the part of teachers, a relaxed atmosphere, less stress, a greater ease of obtaining good grades, autonomy, the ability to review the material at one’s own pace, no time pressure and the possibility of getting up later. The list of the disadvantages they named included: a lot of time spent in front of a computer screen, a lower motivation to learn, too wide a variety of the programmes used, no access to all materials on a single platform, no direct contact with teachers and peers, a low level of engagement on the part of some teachers, no access to selected technologies or problems with using them, such as poor sound quality during live classes and connectivity issues due to the poor quality of the Internet connection, difficulties in providing access to electronic devices for all students and teachers, no individual approach to students in case of problems, difficulties in contacting teachers, failure to explain the topics under study — only the submission of assignments and answers, easier distraction, the need to devote some time to organizational issues, which means that less time is left for actual learning, and too much homework. Many respondents pointed to difficulties especially in learning mathematics, because teachers focus mainly on speaking and there is no possibility of simultaneously writing anything down on the blackboard. The list of the disadvantages mentioned appears to be longer than the benefits that were observed.

Respondents were also asked whether they used e-learning services outside of school (including paid services) during the 2019–2020 school year. Affirmative answers were given by 61% of those surveyed, of which one-in-three had used commercial e-education, compared with 39% who did not use paid services. Online tutoring and video courses proved to be the most frequently named forms of e-education (Fig. 1).

In order to compare the behaviour of final year secondary school students before and during the COVID-19 pandemic, we asked them whether they had used paid forms of e-education before the pandemic. Among the respondents, 21% answered affirmatively, while 79% answered negatively. Importantly, the share of positive answers was 33% before the pandemic, which implies growth in the demand for paid e-learning services. Once the pandemic ends, schools may return to traditional teaching methods, but some of the elements of e-learning will become a permanent part of education. It could be said that many people have realized that harnessing the latest technologies creates new opportunities in the education process and allows the transition to remote learning, thus causing a transformation of the existing education model.

When respondents were asked to rate their satisfaction with the paid elearning services on a seven-point Likert scale, the answers were clearly dominated by favourable opinions: 39.8% of the respondents were satisfied (six points) and 16.1% were very satisfied (seven points). By contrast, the ratings of four (no opinion) and five (somewhat satisfied) were most frequently selected when the respondents were asked to rate their satisfaction with e-education provided by their schools.

We also analysed the use of free out-of-school e-learning services by the respondents. The results we obtained indicate that those services were dominated by text and video materials, which received more than twice as many answers as audio materials and free e-learning platforms (Fig. 2). Single responses pertained to open webinars, as well as tutoring on television.

The main reasons why the respondents used paid e-learning services were: a desire to better prepare for exams (60% of answers), insufficient education at school (41%), the possibility of individual teaching (34.5%), a desire to get into a specific university programme (34%), better efficiency (25%), better adjustment to needs (23%), round-the-clock access (20%) and self-paced learning (20%).

Secondary school students who used paid e-learning services perceived video materials as the most effective form of online education, listing such advantages as better efficiency of learning/working, reduced effort and a lot simpler explanations of specific problems.

Interesting results were obtained regarding the devices used by secondary school students for e-learning purposes. Respondents’ answers were dominated by computers (including laptop computers), which accounted for 61% of the responses, followed by mobile phones and smartphones (26% of responses), whereas the use of a tablet was indicated by a mere 3% of respondents. Computers may be the most popular devices for reasons related to larger screen sizes, which translates into easier access to a variety of functions and bookmarks without the need to swipe. Ease of navigation is also a very important factor behind the choice of learning tools.

E-Education From the Perspective of University Students

In the survey of university students, the study questionnaire was filled in by 560 respondents. As many as 99% of the respondents answered affirmatively to the filter question about the use of e-education services organized by their universities during the COVID-19 pandemic in the 2019–2020 academic year. Negative answers, which accounted for 1% all responses, may have resulted from technical problems of specific university units (no adequate hardware, no Internet access) or the independent decision made by the students who did not want to participate in this form of education, despite the fact that it was offered by their universities. Among those surveyed, 82% admitted to attending live classes, which resemble traditional education to the greatest degree. Respondents obtained study materials from a variety of sources (Fig. 3).

The results we obtained led us to the conclusion that universities used education platforms to offer remote education, which allowed them to place scientific content presented in different forms in a single place. This approach allowed better organization of work, reduced the time spent searching for required content, and allowed easier navigation of topics and information.

Live online classes were primarily conducted using: Microsoft Teams (54% of answers), followed by Zoom (19%), Skype (7%) and Google Meet (6.5%). As for other platforms, we noted significant interest in BigBlueButton (3%), Cisco Webex (3%) and Facebook Messenger (2.5%). For reasons related to the wide variety of products used, which were new to many students, we asked the respondents whether they had any problems using such programs during their first online class. Two thirds of the respondents declared that had no problems, which indicates that young people, raised in the era of the technological revolution and wide expansion of the Internet, learn to use new Internet communication tools very quickly and navigate them intuitively.

When asked about their attitudes towards e-education organized by their universities, two fifths of the respondents admitted that they were curious about classes taught in this form and one fourth were not satisfied with the change, whereas one sixth were of the opposite view. The remaining respondents felt indifferent.

Importantly, 60% of the students surveyed declared that they always participated in online classes, 27% stated that did so almost always, and only 3.5% did not participate in remote classes. The main reasons for high student participation in classes included mandatory attendance (checked by instructors), curiosity about e-learning courses and satisfaction with e-lessons.

The university students surveyed were also asked to rate their subjective satisfaction with distance learning organized by their universities on a seven-point Likert scale (one — strongly dissatisfied, seven — strongly satisfied). The responses were dominated by ratings on the higher side of the scale, which expressed satisfaction. Almost one third of the respondents gave distance learning a rating of five (somewhat satisfied), whereas the ratings of six (satisfied) and four (hard to say) were selected by one fifth of the respondents each. Six percent rated distance organized by their universities at seven (strongly satisfied), whereas 5.5% gave it a rating of one (strongly dissatisfied).

The respondents were also asked whether they availed themselves of any e-education services outside those offered by university. Among the university students surveyed, 36% answered affirmatively. As many as 91% of them used paid forms of online learning. The most common forms of commercial e-learning services they used were webinars (34.6%), followed by e-books (31.8%), e-learning platforms (29.6%) and video courses (28.5%). Less importance was given to audio- and videoconferencing (14.5%), email courses (14%), online tutoring (8.9%), MOOCs (6.7%), educational games (5.6%), audio courses (4.5%) and learning apps (2%).

Importantly, one in four university students made use of commercial e-learning services to pursue their passions and interests, pursue selfdevelopment and gain additional professional qualifications. The topics studied by students were primarily foreign languages. A substantially smaller respondents learnt computer skills via this medium, but some of them also expanded their knowledge in such fields as economics, psychology, mathematics, law, the Polish language and marketing.

The vast majority of respondents (80%) declared that the COVID-19 pandemic had affected their interest in e-learning. Before the pandemic, e-books were the most popular form of e-learning, but they were replaced by webinars. The position of e-learning platforms and video courses remained unchanged, but an increased interest in email courses was noted.

When choosing between various e-education services, the university students we surveyed reported that were mostly guided by a desire for self-development (55%), followed by the absence of traditional classes (29.5%), the possibility of choosing when they could learn (28%), the improvement of qualifications (27%), round-the-clock access (25%), selfpaced learning (25%), no need to commute (22%) and the possibility of individual teaching (21%). Students were satisfied with the paid eeducation services they used.

When asked about the effectiveness of specific e-education services, students primarily indicated video courses (28%), live classes (27%) and e-learning platforms (15%). Among the devices they used for e-education, 77% named a computer, whereas 21% indicated a mobile phone/smartphone.

Discussion

The spread of new technologies goes hand in hand with the development of e-education. Innovations in the IT sector, such as artificial intelligence, machine learning, virtual and augmented reality, are all changing the image of education and educational tools. At the same time, a significant increase in the use of mobile devices and other such factors are making it increasingly necessary to adapt educational products to the changing needs of consumers. On top of this already complex and changing e-learning landscape, the COVID-19 pandemic that began in early 2020 brought with it unexpected and quite significant dynamics in the educational setting in general, and the e-learning services market in specific.

Poland is certainly not unique in this respect. Based on a survey of students from the largest public universities in the United States, Aucejo et al. (2020) found that the pandemic affected all students, but its impact was more disruptive to lower-income students. The authors blame this situation on the fact that lower-income students are more financially vulnerable to the pandemic and more concerned about immediate virusrelated health risks. The students who completed the survey stated that their learning capacity in the spring semester had been affected negatively by the COVID-19 pandemic. Citing research by Kuhfeld et al. (2020), the authors argue that the declining educational value of universities amidst COVID-19 is consistent with new evidence regarding the situation of primary and secondary school students.

The study reported herein examined the situation in the Polish market of e-education services, seeking greater insight into the existing realities and perceptions in the wake of the onset of the pandemic. The study comprised two parts: a qualitative survey conducted among owners of companies that provide commercial e-educational services regarding their perceptions of the market, and a broader quantitative survey among consumers of educational services (secondary school and university students) concerning the degree to which they avail themselves of such services and their levels of satisfaction and dissatisfaction with e-education.

As for the qualitative survey of service providers, it found that they when the pandemic broke out, they — perhaps unsurprisingly — noted a surge in interest in online education. However, this surge was not across the board: while interest in products aimed at secondary school students and university students went up, the demand for online education among adults had dropped. Moreover, they reported that the market is quickly becoming increasingly difficult for reasons related to mounting competition, pushing down prices. The respondents reported that digital marketing and e-mail marketing had become less effective, and attributed the growing interest in online tutoring to the absence of direct contact between students and those who could evaluate them. Overall, the findings from the qualitative survey among service providers seem to indicate the COVID-19 pandemic brought the intensification of earlier trends (e.g. towards more on-line tutoring), while also brining considerable instability to the market.

As for the quantitative survey of secondary school students and university students, both groups were found to be characterized by a high level of participation in the classes organized by their schools, but this level was somewhat higher in the latter group (by six percentage points). The forms of e-education were dominated by text-based materials in secondary schools, compared with text-based materials and live classes in universities. The programme most commonly used for the purpose of live classes, in both secondary and university education was Microsoft Teams, followed by Zoom and Skype. The main reason behind the use of online learning was the desire to better prepare for secondary school graduation exams for secondary school students, and self-development for university students.

Compared with secondary school students, university students were more satisfied with e-learning offered by the educational institution they attended. A much higher percentage of secondary school students used out-of-school e-education services (61%, compared with 31% for university students). One in five respondents in each group had used selected forms of paid e-education before the pandemic, with COVID-19 clearly driving up demand for such services.

Both groups of students under study were generally satisfied with paid e-learning services, although they did also list numerous disadvantages of such forms of education. Importantly, however, the survey was conducted not long after the beginning of the pandemic (in May 2020), which means that the reactions of the respondents may also have been based on emotional reactions to some extent. In any case, the findings reported herein are coherent with international research suggesting that online learning helps students absorb information more quickly and takes less time, which means that the changes in the organization of education necessitated by the spread of the coronavirus may be here to stay. Other research (Li & Lalani, 2020) has shown that students retain 25–60% more material on average in e-learning settings (versus 8–10% in traditional learning); in addition, e-learning allows students to learn at their own pace and requires 40–60% less learning time than traditional education. In turn, McDougall et al. (2020) found that online classes could be as effective as traditional lessons, but a great deal depended on the use of „active learning” techniques by students.

However, it should be recognized that the pandemic has likewise been disruptive to teachers. Not all of them had even basic skills in the use of Internet and communication technologies or previous experience with providing high-quality online education. This has been confirmed by a study carried out in Latvia (Svence et al., 2020). Continued efforts are therefore necessary to improve the technological skills of all those involved in the education process.

Education is the foundation of the functioning and development of human beings and allows them to fulfil their needs for self-education and self-actualization. Moreover, e-learning has become an integral part of not only university studies but also at lower levels of education. The Internet can be used by learners around the world to immediately find information on practically any topic and access educational materials practically at no cost, and by teachers to share their knowledge and experience (Sharma, 2020). At the same time, a result of the uncertainty caused by the COVID-19 pandemic and its changeability over time, it is difficult to project changes in the demand for various forms of e-learning in the near future. Undoubtedly, e-learning, despite the criticism it has attracted, has made it possible to continue the educational process during the lockdown period. Numerous related topics are being discussed the literature — such as in Pyżalski (2020), a collection of articles on education during the COVID-19 pandemic, addressing such issues as remote education tools, wise education, teacher well-being, collaboration between teachers, digital inequalities, peer relationships, collaboration with parents/guardians, digital competence and student engagement.

The study reported herein may serve as a valuable point of reference in this ongoing research into the continually shifting e-learning landscape, as a certain snapshot of practices, attitudes and perceptions at a particular place and a particular moment in time (in Poland, in May 2020, during the first wave of the COVID-19 pandemic). As such, this study can be seen as a contribution to further research and observation. A great deal of space has recently been devoted to the assessment of the functioning of educational institutions, limited access to the Internet and by the same online education and organization of online classes. It can be assumed that the future waves of COVID-19 infections will encourage researchers to study in greater detail the behaviour of consumers (secondary school and university students) in the market of commercial e-education services.

Endnotes

1 Compulsory schooling in Poland is regulated in the Act of 14 December 2016 — Education Law (Journal of Laws 2020, Items 910 and 1378). Under Article 35(2), the period of compulsory education starts at the beginning of the school year in the calendar year in which a child reaches the age of seven years and continues until he or she completes primary school education, but no longer than until the child reaches the age of 18 years.
2 PDAs are very small, portable personal computers that fit into the palm of a hand or into a pocket and have a touch screen that is operated with the use of a stylus.

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