Addressing students' perceived value with the virtual university concept

Ryszard Ćwiertniak, Przemysław Stach, Katarzyna Kowalska-Jarnot, Karolina Worytkiewicz-Raś, Barbara Wachułka-Kościuszko

The outbreak of the pandemic related to the spread of the SARS-CoV-2 virus at the beginning of 2020 caused temporary restrictions on the functioning of educational institutions in many countries around the world. On March 30, 2020, as the pandemic was accelerating, educational institutions of all levels were closed in 167 countries. Schools were closed for the longest periods in India (60 weeks), Argentina (59 weeks), and the United States (58 weeks). In Poland, schools were closed for 43 weeks (UNESCO, n.d.). Due to the pandemic, the World Health Organization introduced a state of epidemic on March 11, 2020 (World Health Organization, 2020). On that day, the operations of HEIs in Poland were severely limited by government order, and thus institutions of higher education faced the difficult task of ensuring education continuity, which conveniently could be attained by the use of Internet-based, distance learning solutions1.

Distance learning and e-learning are well-known tools supporting the teaching process at universities and colleges, however, before the outbreak of the pandemic, they were not widely used (Zbarachewicz, 2020). According to the study "E-learning in European Higher Education Institutions", almost all higher education institutions offered digital learning. In Germany, Spain, Switzerland the United Kingdom, and Poland, more than 50% of students are involved in distance learning, whereas in Italy, France, and Turkey these activities are least popular (Gaebel et al., 2014). The same study also addressed students' motivation to engage in online learning. It was found that the most popular motive among students was the opportunity to combine work and study (69% of respondents).

A few months after the pandemic pushed many HEIs into launching virtual classes, many intuitions began to evaluate the students' online experience. A major Polish university specializing in training educators based in Cracow conducted a survey in May and June 2020 (n = 1927) to assess students' satisfaction among certain other issues (Długosz & Foryś, 2020). The researchers report that 40% of students evaluated the experience as good or very good, and 35% evaluated it as average. Only 25% of students described the experience as negative. However, when requested to compare the experience with traditional campus-based learning, only one in five students said that remote learning was better. The reason for this interesting discrepancy may lie in the survey students' replies regarding the pros and cons of remote learning. Predictably, the advantages included savings in time and money, and the safety and comfort of their homes. The disadvantages, however, include overload of study material and assignments, lack of motivational stimuli, and lack of direct contact with peers and professors. These findings illustrate clearly that online learning is not just about moving classes into cyberspace.

The authors' institution, the College of Economics and Computer Science (WSEI), just like other similar HEI in Poland and around the world, had to face the challenge of transferring their operations into cyberspace. Although the WSEI leadership had been planning to increase its digitalization even before the pandemic, the move online was earlier than anticipated. Nevertheless, the college was able to start providing most of the classes online in just three days. To support the seamless move into cyberspace, many training sessions for students and processors were offered just before the launch, as well as throughout the semester. Student support initiatives were also introduced, including psychological support and social engagement.

Although it is too early to attempt a meta-analysis of the remote learning experience forced upon students due to COVID-19, some already published research suggests that many students found the experience generally satisfying and that potential drawbacks of online learning can be effectively countered by substantial benefits (Fatani, 2020; Sharma et al., 2020; Surahman & Sulthoni, 2020; Zeng & Wang, 2021). The research proves that the introduction of distance and e-learning as the basic channel of the didactic process at a higher education institution is indeed a complex process. Understandably, the emergency launch of remote learning forced institutions to focus on the priorities they were able to deal with at short notice, resulting in varied evaluations of online learning. However, a college or a university wishing to fully capitalize on the benefits and possibilities of distance learning needs to realize early during the venture that it requires a profound digital transformation of organizational, managerial, didactic, and scholarly systems, with the aim to adapt to the environment and its changes and the needs of all stakeholders (Mazurek, 2019; Seres et al., 2018), as well as to improve, expand, and provide new functions or redesign the products or services already offered (Sandkuhl & Lehmann, 2017).

Conceptual framework

The transition of higher education institutions to remote teaching and, in many cases, their digital transformation forced upon them by the pandemic constitutes a significant organizational change that results from the need to adapt. Although the change is unprecedented, the contemporary HEIs had been, at least to some extent, prepared by the widespread use of the Internet and many examples of successful distance and e-learning initiatives (e.g., edX, Coursera, many universities globally already offering online degree programs). During just one generation, the Internet has become a resource supporting multidirectional communication, research, transactions, and co-creation of value (Goliński, 2011). The potential benefits of using digital technologies mean that a rethink is needed of HEI stakeholders' needs and that the value higher education has to offer needs to be redefined.

To sum up the considerations on the scope of distance learning and referring to the current situation caused by the pandemic, this kind of learning is not limited to an unconventional educational (training) service based on Internet technology. The discussion around the definition of distance learning touches on many aspects. Online learning is by definition a beneficial change in various areas of a university's activity (schools, training centers), established at the HEI or outside it, being a response to the needs of students (course participants) or a crisis. It is an evolutionary improvement of study programs and adaptation of them to new market requirements (student needs). Thus, the scope of distance learning in this approach concerns numerous elements (educational service, internet solutions, the process of managing study programs, incremental improvement), which should follow from the values adopted at the university and the quality standards of distance learning.

Perceived value

The concept of customer perceived value in higher education has not gained sufficient attention in scholarly literature so far, even though it offers great theoretical and practical potential (for example, see Stach & Bąk, 2009). The concept was introduced to management studies by Peter Drucker in 1954. He pointed out that price is not an indicator of the value of a product or a service, but it is merely one of the multiple factors that the customer considers when assessing a marketing offer (Drucker, 1998). Zeithaml's research suggests four ways to understand value: value as low price, value as what one expects from a product, value as what one gets in return for what one pays, and what one receives in return for what one provides (Zeithaml, 1988). The key role of the concept of value has been fully appreciated in marketing. Kotler and Armstrong (2008) propose that the purpose of marketing is to create value for customers and to capture this value from customers in return. To Grönroos (2006), marketing refers to a customer focus that permeates organizational functions and processes and is geared towards making promises through value propositions enabling the fulfillment of individual expectations.

Expanding further our understanding of the value concept, it is useful to account for both the perspectives of the value-creator and value-receiver.

Thus from the HEI perspective, value may be perceived in at least two ways:

  • as a basis for marketing orientation, i.e. a perspective that helps to understand the market and students' needs and to create an educational offer in such a way that it can become the potential source of competitive advantage,
  • as a general experience of a student-consumer, who partly co-creates and affects their satisfaction and perception of the HEI.

Likewise, from the perspective of a student-consumer, value can be understood in many ways, including a sufficiently low price, quality obtained at the price paid, a benefit-cost ratio, or the sum of all customer expectations (see Tab. 1).

Table 1
Selected ways in which value may be understood and defined

Understanding of value Example of a definition
Value understood as a quality obtained at the price paid Value is defined as a quality-price ratio (Lichtenstein et al., 1990).
Value understood as an attractive price Value is the ratio of the hypothetical price of a supplier's offer that allows the customer to cross the break-even point - to the best alternative available to the customer for the realisation of the same set of functions (Oliva, 2000).
Value understood as the total of all customer expectations Value refers to the total benefits a customer believes they will obtain if they accept the market price (Hunt & Morgan, 1995).
Value understood as a benefit-cost ratio Value constitutes a comprehensive assessment of a product and its acquisition and usage, which is performed by a customer by comparing the received benefits and the incurred costs (Näslund et al., 2006).

Source: Współtworzenie wartości w marketingu. Przykład szkolnictwa wyższego (pp. 22-26). K. Dziewanowska, 2018, Wydawnictwo C. H. Beck.

The benefit-cost ratio-based operationalization of customer value can be useful from the managerial viewpoint and has been successfully employed in Osterwalder's Value Proposition Canvas (Osterwalder et al., 2014) because it focuses the value providers' attention on identifying those features of the item offered which are perceived by their customer as either value-enhancing or value-diminishing. This realization becomes an opportunity to actively improve the item offered to highlight the first type and alleviate the second. Inspired by the benefit-cost ratio approach to value, one can come up with a list of value enhancers (or benefits) and value diminishers (or costs) for the HEI (see Tab. 2).

Table 2
A list of common value enhancers and diminishers in education products offered by a HEI

Potential value enhancers Practical effects
  • Acquisition of knowledge, practical skills, understanding of market and business
Social effects
  • Making social connections, contacts, learning about diverse cultures
Strategic effects
  • Education/diploma/master's or bachelor's degree
Potential value diminishers Material costs of studying
  • Study fees, textbook costs, equipment costs (laptop), accommodation expenses, travel expenses
Psychological costs of studying
  • Stress related to classes and examinations, missing family, students' and their families' expectations
Sacrificed benefits
  • Free time, time spent with family, comfort, mobility (flexibility), traveling, entertainment.

Source: authors' work based on "Making sense of higher education: students as a consumer and the value of the university experience", T. Woodall, A. Hiller, & S. Resnick, 2014, Studies in Higher Education, 39(1), 48-67 (https://doi.org/10.1...).

It is, however, important to stress that in some instances, value diminishers may become value-enhancing if a different meaning is attached to them. An obvious example may be the tuition fee, where in some cases the higher the tuition students are expected to pay for a given program, the higher the perceived value, because the tuition cost may be strongly associated with selectivity, and exceptional quality. Yet again, the list of potential costs and benefits will change over time due to advances in technology and social trends, and is strongly context-related. It can be argued that the transition to remote teaching caused by the COVID-19 pandemic has modified the sets of costs and benefits because there has been a profound change in experience and expectations. The unpublished research conducted in the authors' institution provides an insight into what students might nowadays perceive as value enhancers or cost (i.e., value diminishers) (see Tab. 3).

Table 3
Post-pandemic changes in perceived benefits and costs related to the transition to remote teaching

Value-adding components
  • More free time (it is not necessary to leave home, travel to the college).
  • Saving money (no rent or travel expenses)2.
  • Higher mobility (the possibility to participate in classes from any location).
  • Comfort.
  • Higher quality of lectures (silence, better concentration).
  • Reduced amount of stress during examinations, classes, and presentation of thesis.
Cost-related components
  • Lower quality of classes due to technical issues (lack of equipment, poor-quality equipment, slow Internet connection or no connection at all).
  • Weaker social interactions with other students. Difficulties in developing new contacts.
  • A lack or a limited possibility to enjoy the sports, cultural and social events offered by the city.
  • Weaker ties in project teams.
  • Lower quality of some practical classes.

Source: students' satisfaction after transferring to remote study (2021).

Virtual university concept

Indeed, the recent experience, literature review, and research results have led the authors to conceptualize a framework that might be referred to as a Virtual University Concept (VUC) of the new normal. To begin, the authors listed five fundamental areas of focus that need to be addressed before attempting to model the VUC (see Fig.1).

Figure 1
The Virtual University system model - proposal

Source: authors' own work.

They include the technical and technological capacity of a HEI, faculty development, cost management, innovation, and students' and employers' value perceptions. Thus the institution of higher education needs to have adequate technical and technological capacity and competent faculty and administrators digitally literate and able and willing to innovate. All this must be done with the goal of providing value to key stakeholders at a reasonable cost.

Digitization and virtualization of learning and teaching need to be fully compatible with the mission and vision of a HEI. Once the strategic decisions are made, the focus needs to be on delivering new products (study programs, courses, etc.), improving processes, and delivering new business models (Trias de Bes & Kotler, 2011). Reducing the uncertainty of the process of digitization through its long-term evaluation is vital for the learning process in an organization (Hubbard, 2014). The control system confirms that all conditions (i.e. the necessary resources, process, and values proposition) are effectively applied in practice. These perspectives, taken together in the context of active capabilities, provide the conceptual parameters for the VUC which can be depicted using the business logic triangle proposed by Osterwalder and Pigneur (2002) (see Fig. 2).

Figure 2
Conceptual settings - dynamic capabilities perspective

Source: authors' own work based on an eBusiness model ontology for modeling eBusiness. 15th Bled Electronic Commerce Conference eReality: Constructing the eEconomy (pp. 75-91), A, Osterwalder, & Y. Pigneur, 2002, http://citeseerx.ist...; "Business models and dynamic capabilities", D. J. Teece, Long Range Planning, 51(1), 40-49 (https://doi.org/10.1...); "Digitalization and its influence on business model innovation", M. Rachinger, R. Rauter, C. Müller, W. Vorraber, & E. Schirgi, 2019, Journal of Manufacturing Technology Management, 30(8), 1143-1160 (https://doi.org/10.1...).

The dynamic capabilities perspective offers an exploratory view of the concept of the VUC and allows the authors to argue that the operationalization of the VUC depends on an HEI's capabilities (Teece, 2018).

The digitalization process underlies the value creation capabilities of an HEI and is strongly influenced by the digitalization of an HEI's environment. That is why it is crucial to adjust an HEI's processes and structures to support value creation (Rachinger et al., 2019). Summed up, this is the use of digital technologies to change an education model and provide new value opportunities; it is the process of switching to a digital mode of education. This paper provides such a framework, organized around key priorities that will be useful for any university's executive team. These areas are remote access; engaging students; accelerating agility and efficiency; reducing operational costs.

Methodology

Academic literature recognizes the multidimensional nature of value, as well as challenges with the operationalization of the concept (Stach, 2009). One way to measure the perceived value in higher education is to use various single or multidimensional scales to examine functional, perceived, emotional or social value as well as different combinations of value types (Dziewanowska, 2018).

In their study, the authors focused on a selected number of core measures implemented in their institution in response to COVID-19 that are associated with e-learning and remote study. The package of remote study solutions that addressed the students' immediate needs included web-based classes, online consultations, extracurricular webinars and training sessions, and online assessments and examinations. The students were offered online services of the Dean's Office, which dealt with all issues concerning the academic progression toward graduation. To support the learning and studying effort, an online platform (Office 365 and Moodle.org) was made compulsory for all classes which migrated online. Online library services were publicized, although they had been partially in place before. The authors decided to add a "limited presence on campus" measure, although this is a consequence of the safety measures introduced due to the pandemic. Nevertheless, it can be perceived as a total offering component of the educational package and would potentially be valued by students on some occasions. The recent COVID-19 experience and the literature review have led the authors to hypothesize as follows:

  • The selected core measures implemented in response to COVID-19 are perceived by students as adding value to their educational experience with the HEI.
  • Part-time students perceive the core measures as adding value more often than full-time students.
  • Working students perceive the core measures as adding value more often than students who did not have a job.
  • First-year students perceive core measures as adding value less often than more senior students.
  • The core measures are positively correlated with students' expectations toward the HEI.

To test the listed hypotheses, the authors conducted in June and July 2021 a census-type study by sending an online survey to all undergraduate students currently enrolled in the College of Economics and Computer Science (WSEI) in Cracow, Poland. 957 students returned completed questionnaires, which were checked for errors and inconsistencies and entered into a statistical analysis package (open source PSPP software).

An ordinal level scale was designed to measure the perceived value of the virtual university components as well as students' expectations.

Students' perceived value was measured using a seven-point fully labeled and balanced ordinal scale (used originally in Polish): how was the value of studying at WSEI affected by the following (list of items)? (1) significantly reduced value; (2) reduced value; (3) somewhat reduced value; (4) had no impact; (5) somewhat added value; (6) added value; (7) significantly added value.

Students' expectations were measured using an unbalanced fully labeled six-point ordinal scale: to what extent your expectations were met: (1) not met at all; (2) met to a small extent; (3) met at 50%; (4) mostly met; (5) met completely; (6) were exceeded.

The data analysis was conducted using parametric tests following the common practice among researchers, supported by empirical findings that confirm their robustness for ordinal scales (Norman, 2010; Sullivan & Artino, 2013; de Winter & Dodou, 2010).

Findings and discussion

Sample

The obtained sample covered 71% of male students, with 82.3% of the students between the ages of 19 and 25. 68.7% of students majored in Computer Science. 58% of the sample were first-year students. Almost half of the surveyed students currently live in Cracow, the city where the college is located. The surveyed students follow one of the available modes of study. There were 35.2% of full-time (traditional, campus-based) students and 64.8% part-time students (attend classes on campus on weekends) among the respondents. 31.8% of full-time students and 89.4% of part-time students had a job when taking part in the survey (Tab. 4).

Table 4
Characteristics of the obtained sample

Overall academic program
Year of study Year 1 = 58.2% Year 2 = 26.6% Year 3 or 4 = 15.2%
Academic program Computer Science and Econometrics = 68.7% Business Administration = 19.0% Finance and Accounting = 12.3%
Sample characteristics
Gender Female = 28.7% Male = 71.3%
Age 19-25 = 82.3% 26-35 = 15.5% 36-45 = 1.7% >45 = 0.5%
Place of residence Cracow = 47.9% Other city > 100,000 = 5.3% City < 100,000 = 16.2% Rural area = 30.6%
Study mode & jobs Full-time = 35.2% Part-time = 64.8%
with a job = 31.8% no job = 68.2% with a job = 89.4% no job = 10.6%

Source: authors' analysis using the open-source statistical analysis package PSPP GNU pspp 1.2.0-g0fb4db.

The perceived value of the core measures

Based on the literature review and the authors' first-hand observations in the last academic year, they hypothesize that the core measures implemented by WSEI are perceived by students as adding value to their educational experience.

The average scores for all the questionnaire items referring to the core measures were between 4.6 and 6.07 on a seven-point scale, suggesting that on average the respondents found all the items on the value-adding side of the measurement scale. The surveyed students found all but one evaluated measure as adding value to their college experience. It is interesting to note that three measures were considered especially value-adding. They include the Dean's Office online services, online assessments and examinations, and the online platform. These were found by respondents to enhance their value experience (86.7%, 85.8%, and 87.1% respectively). Also, online classes and a limited campus presence are among those least valued measures. They also display a much more distributed opinion range, with a significant percentage of respondents finding them to be value-diminishing. 20% of respondents perceived online classes and 26.3% of respondents perceived limited campus presence to be value-diminishing.

The only measure in the core measures package perceived as not adding value was online library services. 65% of respondents stated that the library services did not change the value experience from them. The presented empirical observations seem to support the hypothesis with the somewhat unclear exception of the online library component (for more see Tab. 5).

Table 5
Perceived value of core measures introduced in response to COVID-19

No. Items N Mean (Std. Deviation) Decreases perceived value (%) Changes perceived value (%) Increases perceived value (%)
1. Online classes 957 5.36 (1.923) 20.0 9.4 70.6
2. Online Dean's Office / Registrar 957 6.14 (1.266) 3.4 9.8 86.7
3. Online consultations 957 5.71 (1.454) 4.1 24.2 71.7
4. Online training & webinars 957 5.66 (1.385) 4.1 22.2 73.8
5. Online assessments & examinations 957 6.07 (1.406) 7.1 7.1 85.8
6. Limited presence on campus 957 4.93 (2.142) 26.3 16.2 57.5
7. Online platform 957 6.01 (1.286) 4.5 8.4 87.1
8. Online library 957 4.62 (1.304) 4.2 65.0 30.8

Source: The authors' analysis using the open-source statistical analysis package PSPP GNU pspp 1.2.0-g0fb4db.

Part-time students and students with jobs

Unlike traditional, campus-based full-time students, part-time students attend classes on weekends (usually every second weekend). They tend to be older than the traditional college age, with careers and families. However, not only part-time students have jobs. With financial pressures and job market opportunities, many full-time students find jobs very early in their college life.

The remote mode of study seems especially convenient to those students who have jobs and need to find a balance between study and work obligations. By studying remotely, they are not expected to show up on campus and they can attend classes online and submit their assignments and take examinations via distance learning platforms. By eliminating the need to travel, in many cases, they can save a substantial amount of time and gain a degree of flexibility in planning their work, college, and home activities. Therefore, the authors have hypothesized that both part-time students and those currently having jobs will perceive virtual university components as adding value to their college experience more often than full-time students and students who do not have jobs.

Again, the hypothesis can be supported by the obtained empirical data. Part-time students and those students with jobs consistently rate higher the value-adding property of each of the core measures. All the mean differences for the measured items are statistically significant (see Tab. 6 and 7).

Table 6
Mean differences in perceived value enrichment potential of selected virtual university tools between full-time and part-time students

No. Items N = FT/PT Mean (std. Deviation) Levene's Test for Equality of Variances (p-value) Independent Samples t-test for Equality of Means (p-values) Equal variances (assumed / not assumed) Statistically significant
FT PT
1. Online classes 337/620 4.59 (2.014) 5.78 (1.734) .000 assumed .000
not assumed .000
2. Online Dean's Office / Registrar 337/620 5.85 (1.414) 6.30 (1.148) .000 assumed .000
not assumed .000
3. Online consultations 337/620 5.27 (1.493) 5.94 (1.377) .001 assumed .000
not assumed .000
4. Online training & webinars 337/620 5.44 (1.328) 5.78 (1.401) .017 assumed .000
not assumed .000
5. Online assessments & examinations 337/620 5.71 (1.552) 6.27 (1.278) .000 assumed .000
not assumed .000
6. Limited presence on campus 337/620 4.10 (2.180) 5.38 (1.984) .089 assumed .000
not assumed .000
7. Online platform 337/620 5.82 (1.282) 6.12 (1.277) .402 assumed .000
not assumed .000
8. Online library 337/620 4.41 (1.197) 4.74 (1.345) .000 assumed .000
not assumed .000

Note. FT - full-time; PT = part-time.
Source: authors' analysis using the open-source statistical analysis package PSPP GNU pspp 1.2.0-g0fb4db.

Table 7
Mean differences in perceived value enrichment potential of selected virtual university tools between full-time and part-time students

No. Items N = J/NJ Mean (std. Deviation) Levene's Test for Equality of Variances (p-value) Independent Samples t-test for Equality of Means (p-values) Equal variances (assumed / not assumed) Statistically significant
J NJ
1. Online classes 661/296 5.59 (1.860) 4.86 (1.970) .036 assumed .000
not assumed .000
2. Online Dean's Office / Registrar 661/296 6.20 (1.254) 6.00 (1.285) .616 assumed .019
not assumed .020
3. Online consultations 661/296 5.85 (1.429) 5.39 (1.462) .131 assumed .000
not assumed .000
4. Online training & webinars 661/296 5.72 (1.412) 5.53 (1.317) .065 assumed .056
not assumed .050
5. Online assessments & examinations 661/296 6.21 (1.327) 5.78 (1.529) .000 assumed .000
not assumed .000
6. Limited presence on campus 661/296 5.20 (2.091) 4.32 (2.135) .849 assumed .000
not assumed .000
7. Online platform 661/296 6.05 (1.278) 5.92 (1.302) .644 assumed .141
not assumed .144
8. Online library 661/296 4.71 (1.318) 4.44 (1.255) .000 assumed .003
not assumed .002

Note. J = has a job; NJ = does not have a job.
Source: authors' analysis using the open-source statistical analysis package PSPP GNU pspp 1.2.0-g0fb4db.

First-year students

The first-year students are students that came to college during the COVID-19 pandemic, which started in the last semester of their high school education. At some point in the spring semester of 2020, their schools switched to an online mode of instruction. Their experience with distance learning had largely been improvised and was often far from optimal. This unfortunately may have reinforced a rather negative social attitude toward the value of online studies. Moreover, freshmen usually look forward to campus life and, since the higher education experience is something new and foreign for them, they will probably feel safer in the in-person setting, where they have more traditional contact with professors and college administrators. Thus, the authors have hypothesized that first-year students will perceive the core measures introduced in response to COVID-19 as diminishing the value of their college experience.

However, the authors found that the obtained data did not support the hypothesis. The first-year students all rate the items referring to the core measures in the value-adding region of the scale. Moreover, they seem to perceive five out of eight components as value-adding more often than more senior students. They seem to value more online consultations with the faculty, online training and webinars, online examinations and assessments, and the online platform more than their more senior counterparts (Tab. 8).

Table 8
Mean differences in perceived value enrichment potential of selected virtual university tools between first-year students and more senior students

No. Items N = FY/SY Mean (std. Deviation) Levene's Test for Equality of Variances (p-value) Independent Samples t-test for Equality of Means (p-values) Equal variances (assumed / not assumed) Statistically significant
FY SY
1. Online classes 557/400 5.46 (1.869) 5.23 (1.991) .071 assumed .074
not assumed .077
2. Online Dean's Office / Registrar 557/400 6.3 (1.049) 5.87 (1.477) .000 assumed .000
not assumed .000
3. Online consultations 557/400 5.80 (1.370) 5.58 (1.556) .001 assumed .018
not assumed .020
4. Online training & webinars 557/400 5.78 (1.327) 5.50 (1.449) .015 assumed .003
not assumed .003
5. Online assessments & examinations 557/400 6.20 (1.290) 5.90 (1.538) .000 assumed .001
not assumed .002
6. Limited presence on campus 557/400 4.95 (2.107) 4.89 (2.193) .192 assumed .674
not assumed .676
7. Online platform 557/400 6.22 (1.051) 5.72 (1.510) .000 assumed .000
not assumed .000
8. Online library 557/400 4.69 (1.259) 4.53 (1.361) .966 assumed .063
not assumed .067

Note. FY = first-year students; SY = senior students, incl. 2nd, 3rd, and 4th years.
Source: authors' analysis using the open-source statistical analysis package PSPP GNU pspp 1.2.0-g0fb4db.

The core measures and the students' expectations

Contemporary students are often called digital natives (Prensky, 2001; Stolzer, 2007) because they grew up with access to computers, mobile devices, and the Internet. Even though the use of digital tools, multimedia, and digital student grade books are common within the K12 education in Poland, the pre-university school experience is still rather traditional. Online socializing outside school and extracurricular education are far more common. Teenagers nowadays also have extensive and successful experience with online shopping and are very quick to adopt all web-based innovations. Given the broad experience of contemporary teenagers and their Internet and computer literacy, the authors have hypothesized that by the time they enter college or university, the core measures introduced in response to COVID-19 and associated with online learning/studying will positively correlate with students' perception of their expectations toward college/university being met. This hypothesis also seems to be supported by empirical evidence. All questionnaire items referring to the core measures are positively, yet only slightly correlated with the students' expectations scale. All (Pearson's) correlations are statistically significant (at p < 0.01) (see Tab. 9). The multiple regression model suggests that all the core measures together account for 15% of the overall students' expectations met.

Table 9
The correlation of the core measures and students' expectations

Core measures To what extent your expectations were met
Online classes 0.282
Online Dean's Office / Registrar 0.252
Online consultations 0.284
Online training & webinars 0.250
Online assessments & examinations 0.190
Limited presence on campus 0.207
Online platform 0.310
Online library 0.258

Source: authors' analysis using open-source statistical analysis package PSPP GNU pspp 1.2.0-g0fb4db.

Conclusions and implications

Even though online programs have been widely available for many years, there appears to be disagreement regarding their value in formal higher education, even among students themselves. With the COVID-19 pandemic, many HEIs were forced to implement distance learning methods and virtual university measures on a massive scale, regardless of their attitudes towards virtualization of the education process and prior experience with online education services. This led to the exposure of enormous numbers of students to the experience of online learning and virtual university, with all its advantages and drawbacks. Just as the remote work experience has already changed the working environment and employees' expectations, it is commonly believed that the online education experience of the COVID-19 crisis will change the practices and expectations of the higher education sector, and the value equation perceptions among current and future students.

The authors took advantage of the opportunity presented by COVID-19 and the remote learning/studying measures implemented at the authors' institution to measure the students' perceived value of online studying. The authors assessed the extent to which the remote study/learning measures correlate with students' expectations towards their college. The hypotheses have largely been supported by the data. In general, the online studying/learning measures have been found to be value-adding, and even more so by part-time students and students with jobs. Contrary to the authors' expectations, the first-year students were not less enthusiastic toward online studying, in fact, they found the online studying/learning measures even more value-adding than their senior peers. As expected, all implemented remote study measures correlate positively, although only slightly, with students' expectations with their college.

It is important to remember that the empirical findings need to be judged considering the study limitations. The sample structure does not seem to be significantly different from a sample one may obtain from other HEIs in Poland, yet there is no way to assess its representativeness for the student population in general. The authors have studied only a small subset of online studying/learning measures that are being or can be introduced at a HEI willing to embark on a virtual university project. Despite the limitations, the research findings provide a platform on which future research and conceptual work can be continued.

The COVID-19 pandemic turned the traditional system of education upside down for institutions at all levels, making the unbelievable normal. The return to business as usual may prove to be impossible. The post-pandemic education industry is likely to undergo a complex process of adjusting to the reality of the newly obtained experience, novel expectations, and freshly acquired capabilities. The challenge is to find a value proposition with sufficient appeal to all stakeholders to lead the transformation of HEI into the new normal.

It can be argued that many of the online studying measures introduced during COVID-19 will be retained to some extent, probably to be expanded or redesigned when the key stakeholders of HEIs are ready. COVID-19 sped up the digital transformation of many industries around the world, including higher education. Digital transformation is a change driver in the world of science because it offers new technologies based on the Internet with profound implications for society (Unruh & Kiron, 2017). Even traditional universities, which until now have not looked at digitization and virtualization as a key process, began considering these trends in their new development strategies, because they have proven their value, and they possess enormous potential to redesign higher education to meet the needs and expectations of the new normal - the post-covid world.

To put the presented framework in the context of the authors' research findings, one needs to understand how students' value perceptions fit into the VU concept outlined above. The value offered by the HEI is dependent on the how (technology), who (faculty, administrators), what (innovative programs), at what cost (tuition, sacrifices, pains), and to what end (how it enables achievement of one's goals). Technology, faculty, and administrators are value enablers that are as good as the value creation, preparation, and capture processes allow them to be. It is, however, the digitization process that underlies the value chain that is the game-changer. It can effectively address the issue of the "what" and "at what cost", to allow "the who" to offer the "to what end".

References

  • Długosz, P. & Foryś, G. (2020). Zdalne nauczanie na Uniwersytecie Pedagogicznym im. Komisji Edukacji Narodowej w Krakowie z perspektywy studentów i wykładowców. Wydawnictwo Naukowe Uniwersytetu Pedagogicznego. https://rep.up.krako...
  • Drucker, P. (1998). Praktyka zarządzania. Wydawnictwo Czytelnik.
  • Dziewanowska, K. (2018). Współtworzenie wartości w marketingu. Przykład szkolnictwa wyższego. Wydawnictwo C. H. Beck.
  • Fatani, T. H. (2020). Student satisfaction with videoconferencing teaching quality during the COVID-19 pandemic. BMC Medical Education, 20(396). https://doi.org/10.1...
  • Gaebel, M., Kupriyanova, V., Morais, R., & Colucci, E. (2014, November 17). E-learning in European Higher Education Institutions. Report. European University Association. https://eua.eu/resou...
  • Goliński, M. (2011). Społeczeństwo informacyjne - geneza koncepcji i problematyka pomiaru. Oficyna Wydawnicza SGH.
  • Grönroos, Ch. (2006). On defining marketing: finding a new roadmap for marketing. Marketing Theory, 6(4), 395-417. https://doi.org/10.1...
  • Hubbard, D. W. (2014). How to measure anything: finding the value of in business. Wiley.
  • Hunt, S. D., & Morgan, R. M. (1995). The comparative advantage theory of competition. Journal of Marketing, 59(2), 1-15. https://doi.org/10.1...
  • Kotler, P., & Armstrong, G. (2008). Principles of marketing (12th ed.). Pearson Prentice Hall.
  • Lichtenstein, D. R., Netemeyer, R. G., & Burton, S. (1990). Distinguishing coupon proneness from value consciousness: An acquisition-transaction utility theory perspective. Journal of Marketing, 54(3), 54-67. https://doi.org/10.2...
  • Mazurek, G. (2019). Transformacja cyfrowa - perspektywa instytucji szkolnictwa wyższego. In J. Woźnicki (Ed.), Transformacja Akademickiego Szkolnictwa Wyższego w Polsce w okresie 30-lecia 1989-2019 (pp. 313-332). KRASP.
  • Näslund, D., Olsson, A., & Karlsson, S. (2006). Operationalizing the concept of value - an action research-based model. Learning Organization, 13(3), 300-332. https://doi.org/10.1...
  • Norman, G. (2010). Likert scales, levels of measurement and the "laws" of statistics. Advances in Health Sciences Education, 15, 625-632. https://doi.org/10.1...
  • Oliva, R. A. (2000). Brainstorm your e-business. Marketing Management, 9(1), 55-57.
  • Osterwalder, A., & Pigneur, Y. (2002). An eBusiness model ontology for modeling eBusiness. 15th Bled Electronic Commerce Conference eReality: Constructing the eEconomy (pp. 75-91). http://citeseerx.ist...
  • Osterwalder, A., Pigneur, Y., Bernarda, G., & Smith, A. (2014). Value proposition design: how to create products and services customers want. John Wiley & Sons.
  • Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5), 1-6. https://doi.org/10.1...
  • Rachinger, M., Rauter, R., Müller, C., Vorraber, W., & Schirgi, E. (2019). Digitalization and its influence on business model innovation. Journal of Manufacturing Technology Management, 30(8), 1143-1160. https://doi.org/10.1...
  • Sandkuhl, K. & Lehmann, H. (2017). Digital transformation in higher education - the role of enterprise architectures and portals. In A. Rossmann, & A. Zimmermann (Eds.), Digital Enterprise Computing (pp. 49-60). Gesellschaft für Informatik e.V. https://dl.gi.de/bit...
  • Seres, L., Pavlicevic, V., & Tumbas, P. (2018). Digital transformation of higher education: competing on analytics. In Proceedings of INTED2018 Conference (pp. 9491-9497). https://doi.org/10.2...
  • Sharma, K., Deo, G., Timalsina, S., Joshi, A., Shrestha, N., & Neupane, H. C. (2020). Online learning in the face of COVID-19 pandemic: Assessment of students' satisfaction at Chitwan Medical College of Nepal. Kathmandu University Medical Journal, 18(2), 40-47. https://doi.org/10.3...
  • Stach, P. (2009). Problemy konceptualizacji i operacjonalizacji wartości dla klienta. Przegląd Organizacji, 6, 43-45. https://przegladorga...
  • Stach P., & Bąk, J. (2009). Na ścieżkach zadowolenia i lojalności-poszukiwanie modelu w kontekście uczelni. Marketing i Rynek, 6, 20-25.
  • Stolzer, J. M. (2007). The ADHD epidemic in America. Ethical Human Psychology and Psychiatry, 9(2), 109-116. https://doi.org/10.1...
  • Students' satisfaction after transferring to remote studying. (2021). Survey report. College of Economics and Computer Science (WSEI) (unpublished).
  • Sullivan, G. M., Artino, A. R. Jr. (2013). Analyzing and interpreting data from Likert-type scales. Journal of Graduate Medical Education, 5(4), 541-542. https://doi.org/10.4...
  • Surahman, E., & Sulthoni. (2020). Student satisfaction toward quality of online learning in Indonesian Higher Education during the COVID-19 pandemic. 6th International Conference on Education and Technology (ICET) (pp.120-125). IEEE. https://doi.org/10.1...
  • Teece, D. J. (2018). Business models and dynamic capabilities. Long Range Planning, 51(1), 40-49. https://doi.org/10.1...
  • Trias de Bes, F., & Kotler P. (2011). Winning at innovation: The A-to-F model. Palgrave Macmillan.
  • UNESCO. (n.d.). COVID-19 impact on education. Retrieved August 9, 2021 from https://en.unesco.or...
  • Unruh, G., & Kiron, D. (2017, November 6). Digital transformation on purpose. MIT Sloan Management Review. https://sloanreview....
  • Winter, J. C. F., de, & Dodou, D. (2010). Five-Point Likert Items: t-test versus Mann-Whitney-Wilcoxon. Practical Assessment, Research and Evaluation, 15(11). https://doi.org/10.7...
  • Woodall, T., Hiller, A., & Resnick, S. (2014) Making sense of higher education: students as a consumer and the value of the university experience. Studies in Higher Education, 39(1), 48-67. https://doi.org/10.1...
  • World Health Organization. (2020, March 11). WHO Director-General's opening remarks at the media briefing on COVID-19. https://bit.ly/3xM0L...
  • Zbarachewicz, B. (2020). Uczelnie w czasie koronawirusa - problemy transformacji cyfrowej i postulaty na przyszłość. Wiedza Obronna, 272(3), 75-99. https://doi.org/10.3...
  • Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. Journal of Marketing, 52(3), 2-22. https://doi.org/10.2...
  • Zeng, X., & Wang, T. (2021). College student satisfaction with online learning during COVID-19: A review and implications. International Journal of Multidisciplinary Perspectives in Higher Education, 6(1), 182-195.

Informacje o autorach

zobacz podgląd
Ryszard Ćwiertniak

The author holds a Ph.D. Social Sciences in the field of Management and Quality Sciences (Cracow University of Economics), an M.A. in Management Studies (Faculty of Management, University of Warsaw) and an engineering degree in Electronics. He is an Agile Design Methods and Design Thinking expert. He draws fully on design thinking in his training sessions for businesses, public administration, education, and the non-governmental sector. He has conducted several dozen workshops in the field of training planning, operational planning, and crisis response. He is involved in supporting organizations in their search for improvement. He currently conducts training courses for companies preparing teams to implement the Design Thinking methodology in the area of advanced production systems - Industry 4.0.

zobacz podgląd
https://orcid.org/0000-0001-9295-5549

zobacz podgląd
Przemysław Stach

The author holds a Ph.D. in Economics in the field of Management Science (Cracow University of Economics), and an M.A. in American Studies (American Studies Center, University of Warsaw). An academician with over twenty years of experience in teaching and scholarly research. He has worked for many institutions of higher education in Poland and abroad, and lectured in Germany, Denmark, and the UAE. His current teaching responsibilities include mainly Principles of Management, Strategic Planning in Digital Marketing, Marketing Research, Change Management, and Performance Management. Outside academia, he has been an active management consultant with Factor Consulting, where he specializes in change and performance management, sales and marketing organization, decision support, and market research. He has carried out projects in the IT, chemical, medical, pharmaceutical, HoReCa, R&D, and automotive industries.

zobacz podgląd
https://orcid.org/0000-0001-8393-0892

zobacz podgląd
Katarzyna Kowalska-Jarnot

The author holds a Ph.D. in Management and specializes in marketing. Her current teaching responsibilities include Marketing Research, Marketing, and Digital Marketing. Before starting her academic career, she worked for many organizations as a Training Specialist, Marketing Specialist, and PR Consultant. She was the Head of the Marketing Department for WSEI. She is active outside academia, consulting and conducting training courses for companies.

zobacz podgląd
https://orcid.org/0000-0003-2829-8841

zobacz podgląd
Karolina Worytkiewicz-Raś

The author holds a B.A and an M.A. in Economy, and specializes in management, especially family businesses. Her current teaching responsibilities include management and entrepreneurship. She is the Head of the Competence Development Center at WSEI, and also works in a family business as financial specialist.

zobacz podgląd
https://orcid.org/0000-0002-6169-7652

zobacz podgląd
Barbara Wachułka-Kościuszko

The author has a B.A. degree in English Philology and an M.A. in Human Resource Management and Practical Psychology of Management and Negotiations. She is a soft skill trainer, recruiter, and educator with fourteen years of experience. She has worked as a corporate training coordinator and recruiter for medium-sized and large enterprises. She has authored many training programs, and currently works as a freelance trainer with training companies and corporations. Her current teaching responsibilities include mainly Human Resources Management. At WSEI, she also serves as an HR Generalist and an international projects coordinator.

zobacz podgląd
https://orcid.org/0000-0003-3246-0418

Komentarze

Nie ma jeszcze komentarzy do tego artykułu.

dodaj komentarz dodaj komentarz

Przypisy

1 The discussion surrounding distance learning and e-learning covers many aspects. The subject of the analysis may be technology, technology sources and features, the way technology is adapted and used, and people implementing them at the HEI. There is also a problem with distinguishing between synchronous, asynchronous and hybrid rates.

2 Concerning students who live outside of Cracow.