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Evaluating service quality and performance of higher education institutions: A systematic review and a post COVID-19 outlook


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Purpose This study aims to present a systematic review on service quality in higher education. It discusses about the latest opportunities and challenges facing higher educational institutions (HEIs) following the outbreak of the coronavirus (COVID-19) pandemic. Design/methodology/approach The study relied on the grounded theory’s inductive reasoning to capture, analyze and synthesize the findings from academic and non-academic sources. The methodology involved a systematic review from Scopus-indexed journals, from intergovernmental and non-governmental policy documents, as well as from university ranking sites and league tables. Findings The comprehensive review suggests that HEIs can use different performance indicators and metrics to evaluate their service quality in terms of their resources, student-centered education, high-impact research and stakeholder engagement. Moreover, this paper sheds light about the impact of an unprecedented COVID-19 on higher education services. Practical implications During the first wave of COVID-19, the delivery of higher educational services migrated from traditional and blended learning approaches to fully virtual and remote course delivery. In the second wave, policy makers imposed a number of preventative measures, including social distancing and hygienic practices, among others, on HEIs. Originality/value This timely contribution has synthesized the findings on service quality and performance management in the higher education context. Furthermore, it investigated the effect of COVID-19 on higher education services. It deliberates on the challenges and responses in the short/medium term and provides a discussion on the way forward. In conclusion, it implies that HEI leaders ought to embrace online teaching models and virtual systems, as they are here to stay in a post-COVID-19 era.
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Evaluating service quality and performance of higher education
institutions: A systematic review and a post COVID-19 outlook
By Mark Anthony Camilleri, University of Malta, Malta and University of Edinburgh, Scotland, UK.
Suggested citation: Camilleri, M.A. (2021). Evaluating service quality and performance of
higher education institutions: A systematic review and a post COVID-19 outlook. International
Journal of Quality and Service Sciences. DOI: 10.1108/IJQSS-03-2020-0034
This is a pre-publication version
Purpose: This contribution presents a systematic review on service quality in higher education.
It discusses about the latest opportunities and challenges facing higher educational institutions
(HEIs) following the outbreak of the Coronavirus (COVID-19) pandemic.
Design / methodology: The research relied on the grounded theory’s inductive reasoning to
capture, analyze and synthesize the findings from academic and non-academic sources. The
methodology involved a systematic review from Scopus-indexed journals, from
intergovernmental and non-governmental policy documents as well as from university ranking
sites and league tables.
Findings: The comprehensive review suggests that HEIs can use different performance
indicators and metrics to evaluate their service quality in terms of their resources, student-
centered education, high impact research and stakeholder engagement. Moreover, this paper
sheds light about the impact of an unprecedented COVID-19 on higher education services.
Practical implications: During the first wave of COVID-19, the delivery of higher educational
services migrated from traditional and blended learning approaches to fully virtual and remote
course delivery. In the second wave, policy makers imposed a number of preventative
measures, including social distancing and hygienic practices, among others, on HEIs.
Originality / value: This timely contribution has synthesized the findings on service quality
and performance management in the higher education context. Furthermore, it investigated the
effect of COVID-19 on higher education services. It implies that HEI leaders ought to embrace
online teaching models and virtual systems, as they are here to stay in a post-COVID-19 era.
In conclusion, it deliberates on the challenges and responses in the short/medium term and
provides a discussion on the way forward.
Keywords: Service quality, higher education, higher education service quality, higher
education performance, COVID-19, universities, education technology.
1. Introduction
Students are continuously evaluating the service quality of their higher education
institution (HEI). They assess the HEIs in terms of their tuition fees; educational services that
they offer; their physical aspects, including the technical and functional quality of their
infrastructure; interactions with academic and administrative employees, as well as their
corporate image and reputation, among other issues (Ozkan and Koseler, 2009; Clemes, Gan
and Kao, 2008; Hill, 1995). Parasuraman, Zeithaml and Berry (1988) contended that consumers
evaluate service providers in terms of their reliability or capability to deliver the service; ability
to inspire confidence; empathy (i.e. sensibility towards the consumers’ feelings);
responsiveness (i.e. prompt positive reactions); and tangibles (i.e. the appearance of the
physical facilities, personnel and communication materials). The consumers are continuously
comparing their expectations with the service providers’ actual performance (Cronin and
Taylor, 1992), as service quality comprises both the process as well as the outcome of the
service delivery
(Clemes et al., 2008; Tan and Kek, 2004; Parasuraman et al., 1988). The
evaluation of service quality is based upon the customer–employee interaction (i.e., the process
aspect), the service environment, and the service outcomes (Quinn, Lemay, Larsen and
Johnson, 2009; Snipes, Oswald, LaTour and Armenakis, 2005; Brady and Cronin, 2001).
In the higher educational context, there are a number of stakeholders, including the
students, their employers as well as the government. These stakeholders are often considered
as the consumers of universities and colleges (Raaper, 2019; Lomas, 2007). They demand high-
quality educational service from HEIs in terms of the provision of education, high impact
research and outreach that will ultimately benefit to their business, industry and society at large
(QS Ranking, 2019; THE, 2019). EU (2017) pointed out that HEIs ought to focus on (i)
improving the skills of their students, (ii) addressing the social dimensions, (iii) fostering
innovation and regional engagement, and (iv) reviewing performance management systems to
incentivize and reward good practice. Tertiary education service providers, including
universities and colleges have to address any skill gaps and mismatches in different labor
markets (Camilleri and Camilleri, 2016). There are higher education students, who for different
reasons, are leaving their educational institutions with poor skill sets and capabilities (HBR,
2019). HEIs are expected to deliver quality and inclusive higher education services to the most
vulnerable individuals in society (EU, 2017). They can collaborate with other institutions on
research and learning projects to address shared challenges relating to innovative,
interdisciplinary ecosystems (EUA, 2019). This way, they will build their corporate image,
reputation and branding.
Those HEIs that are not delivering appropriate service quality to their stakeholders will
usually receive negative reviews and ratings. Over time, this may result in a devastating effect
on their international rankings and league tables. HEI leaders ought to recognize the tangible
and intangible attributes of their higher education services. Hence, there is scope for them to
regularly evaluate their performance in terms of their resources, education, research and
1.1 Research question
This contribution presents a systematic review on the service quality of HEIs, including
universities and colleges. It captures, analyzes and synthesizes the findings from high-impact
theoretical underpinnings and empirical studies on ‘higher education’ and ‘service quality’. It
examines the relevant literature that is focused on the higher education students, on their
learning experience, and on the delivery and performance of their service provider. Afterwards,
it deliberates on the impact of COVID-19’s preventative measures on the provision of higher
education. It discusses on the challenges and responses in the short/medium term and on the
way forward in a post COVID era. It elaborates on the implications to policy makers in
education and outlines future research avenues to academia.
2. Data capture, analysis and reporting
This research relied on the grounded theory’s inductive approach to capture and
interpret the findings (Eisenhardt, Graebner and Sonenshein, 2016). This systematic
methodology involved a methodical collection and syntheses of qualitative data from journal
articles that were indexed in Scopus. “Higher education” and “service quality” were the typed
keywords in the search criteria. The researcher delved through the articles’ research
question(s), methodology sections, findings and implications. The search has yielded 640
items. 515 of them were journal articles. There were 82 conference proceedings, 21 reviews
and 15 book chapters that were focused on the search topic. The most common keywords
included higher education (283), service quality (273), students (88), student satisfaction (75),
quality of service (70). Table 1. features twenty of the most cited publications and the keywords
that were used to describe their content (the keywords were identified by the researcher, where
they were not included by the publisher).
Table 1. A non-exhaustive list of contributions on higher education and service quality
Authors Year keywords
Ozkan, S., Koseler, R. 2009 e-Learning information systems;
Learning management systems;
e-Learning evaluation;
e-Learning evaluation survey;
Statistical analysis;
Students’ satisfaction.
Hill, F.M. 1995 Service quality; expectations; perceived quality
experience; perceived service performance;
students’ expectations.
Oldfield, B.M., Baron, S. 2000 Service quality; higher education; consumer
O’Neill, M.A., Palmer, A. 2004 Performance management; education; quality.
Cheong Cheng, Y., Ming
Tam, W.
1997 Higher education; quality assurance; quality
management; schools; service quality.
Voss, R., Gruber, T., Szmigin,
2007 Service quality; higher education; means-end;
Ford, J.B., Joseph, M.,
Joseph, B.
1999 Customer satisfaction; higher education;
performance management; service quality;
services marketing.
Hemsley-Brown, J., Lowrie,
A., Gruber, T., Fuß, S., Voss,
R., Gläser
Zikuda, M.
2010 Customer services quality; students; higher
education; Germany; customer satisfaction.
Abdullah, F. 2006 Service quality assurance; higher education;
measuring instruments.
Abdullah, F. 2006 Service quality; measuring instrument; higher
education, unidimensionality;
Service quality; measuring instrument; higher
education; unidimensionality.
Tsinidou, M., Gerogiannis,
V., Fitsilis, P.
2010 Higher education; service quality assurance;
Owlia, M.S., Aspinwall, E.M. 1996 Factor analysis; higher education; quality.
Lagrosen, S., Seyyed-
Hashemi, R., Leitner, M.
2004 Quality management; education; universities;
service quality assurance.
Brochado, A. 2009 Service quality assurance; higher education;
Ng, I.C.L., Forbes, J. 2009 University; service; value co-creation;
Tan, K.C., Kek, S.W. 2004 SERVQUAL; student satisfaction; student
perceptions; student expectations.
Snipes, R.L., Oswald, S.L.,
LaTour, M., Armenakis, A.A.
2005 Employee job satisfaction:
Employee empowerment:
Customer satisfaction;
Service quality;
Job facet satisfaction;
Services management.
Angell, R.J., Heffernan, T.W.,
Megicks, P.
2008 Customer services quality; service quality
assurance; postgraduates; higher education;
Clemes, M.D., Gan, C., Kao,
2008 Higher Education; Hierarchal Model; Student
Satisfaction; Service Quality; Service Quality
Dimensions; Behavioral Intentions.
Quinn, A., Lemay, G., Larsen,
P., Johnson, D.M.
2009 Service quality; higher education; quality
techniques; quality measurement; continuous
(Note: Sorted by highest number of citations)
This research was grounded on relevant theoretical underpinnings and empirical studies
(on higher education service quality). Moreover, it also involved a review of intergovernmental
and non-governmental organizations’ policy documents as well as from university ranking sites
and league tables relating to performance management and COVID-19.
3. The service quality of HEIs
HEIs are expected to adapt to ongoing developments in their macro and micro-
environments as they are usually operating with budget constraints (Camilleri, 2019).
Therefore, they compete for funding and for student numbers in a global marketplace (OECD,
2019; Hägg and Schölin, 2018; Tian and Martin, 2014). Very often, they are using the corporate
language as they formulate marketing plans, set objectives to control their resources, and are
becoming customer-driven (Lynch, 2015; Sojkin, Bartkowiak and Skuza, 2012; Naidoo,
Shankar and Veer, 2011; Ng and Forbes, 2009). The logic behind these managerial reforms is
to improve the HEIs’ service quality and performance (Rutter, Roper and Lettice, 2016;
Mourad, Ennew and Kortam, 2011; Abdullah. 2006a).
The challenge for HEI leaders is to identify their students’ and other stakeholders’
expectations on service quality. The consumers’ perceived service quality is defined as the
degree and direction of discrepancy between their perceptions and expectations (Quinn et al.,
2009; Parasuraman et al., 1988). Quality is distinguished from satisfaction, in that, the latter is
assumed to involve specific transactions. As part of the conceptualization, expectations are
viewed as desires or wants of consumers (Zeithaml, Berry and Parasuraman, 1993).
Parasuraman et al. (1988) measured the individuals’ perceptions and expectations about service
quality. Their SERVQUAL scales assessed service quality in terms of tangibility, reliability,
responsiveness, assurance and empathy services (Brochado, 2009; Tan and Kek, 2004). In a
similar vein, other authors noted that service quality comprises three significant dimensions;
service processes, interpersonal factors, and physical evidence (Tsinidou, Gerogiannis
and Fitsilis, 2010; Angell, Heffernan and Megicks, 2008;
Oldfield and Baron, 2000).
Notwithstanding, the HEIs’ physical evidence (that is associated with their tangible aspect) can
also influence the students’ satisfaction levels (Wilkins and Balakrishnan, 2013; Ford, Joseph
and Joseph, 1999).
3.1 The students’ learning experience
The students are considered as the primary customers of tertiary education institutions
(Quinn et al., 2009; Lomas, 2007; Snipes et al., 2005). Their expectations on the HEIs’ service
performance plays a key role on their quality perceptions (Raaper, 2009; Brochado, 2009;
Abdullah, 2006b; Hill, 1995). Students spend a considerable amount of time on campus, in
lecture rooms, libraries, IT labs, canteens, sport grounds, et cetera (Hill, 1995). They will
probably use the HEIs’ service facilities, technologies and equipment. Ozkan and Kozeler
(2009) maintained that the learners’ perceived satisfaction with higher education technologies
is dependent on the quality of the instructors, the quality of the systems, information (content)
quality and supportive issues. Hence, HEI leaders have to ensure that the tangible aspects of
their higher educational services ought to be in good working order for the benefit of their
3.2 The service delivery
The provision of higher education services involves “persontoperson” interactions
(Clemes et al., 2008; Solomon et al., 1985). The frontline employees (like faculty employees)
can influence the degree of their consumers’ (or students’) satisfaction and experiences
(Raaper, 2019;
Ng and Forbes, 2009; Ford et al., 1999; Bitner et al., 1990). Both academic and
administrative employees’ ability and willingness to deliver appropriate service quality will
determine the students’ overall satisfaction with their higher education services (Tsinidou et
al., 2010). Oldfield and Baron (2000) contended that students rely on the nonacademic
employees, including administrators and support staff, over whom the course management
teams have no direct control. They pointed out that the students may not be interested in the
HEIs’ organizational hierarchies, as they expect their employees to work in tandem. Therefore,
the administrative employees should also communicate and liaise with the academic members
of staff, to ensure that the students receive an appropriate quality of service. The course
instructors should be evaluated in terms of their technical and interpersonal skills, consistency
of performance and appearance (Camilleri, 2021; Angell et al., 2008). The students want their
lecturers to be knowledgeable, enthusiastic, approachable, and friendly (Voss, Gruber and
Szmigin, 2007).
The HEI leaders should be aware that their employees’ interactions with their students
will have an effect on their satisfaction during their learning journey (Quinn et al., 2009). The
members of staff represent their employer whenever they engage with students and other
stakeholders (Voss et al., 2007). Therefore, HEI leaders ought to foster an organizational
culture that represents the institutions’ shared values, beliefs, assumptions, attitudes and norms
of behavior that bind employees to deliver appropriate service quality and the desired
performance outcomes (Kollenscher, Popper and Ronen, 2018; Pedro, Mendes and Lourenço,
2018; Trivellas and Dargenidou, 2009; O’Neill and Palmer, 2004).
4. Measuring the service performance of HEIs
The employees’ performance is usually evaluated against their HEIs’ priorities,
commitments, and aims; by using relevant international benchmarks and targets (OECD, 2019;
Brochado, 2009; Lo, 2009 O’Neill and Palmer, 2004). Generally, the academics are usually
appraised on their research impact, teaching activities and outreach (Camilleri, 2021; QS
Ranking, 2019; THE, 2019). Their academic services, including their teaching, administrative
support as well as the research and development (R&D) duties, all serve as performance
indicators that can contribute to build the reputation and standing of their employer (Geuna and
Martin, 2003). The university leaders should keep a track record about the age and distribution
of their faculty members; diversity of students and staff, in terms of gender, ethnicity, race, et
cetera. In addition, their faculties could examine discipline-specific rankings; and determine
the expenditures per academic member of staff, among other responsibilities (Camilleri, 2019).
The quantitative metrics concerning the students’ performance may include their
enrolment ratios, graduate rates, student drop-out rates, the students’ continuation of studies at
the next academic level, and the employability index of graduates, among others (QS Ranking,
2019; THE, 2019). Moreover, qualitative indicators can also provide insightful data to HEIs on
the students’ opinions and perceptions about their learning environment. HEIs could evaluate
the students’ satisfaction with teaching; satisfaction with research opportunities and training;
perceptions of international and public engagement opportunities; ease of taking courses across
boundaries; and may also determine whether there are administrative and/or bureaucratic
barriers for them (Kivisto, Pekkola and Lyytinen, 2017). HEIs should regularly analyze their
service quality and performance through financial and non-financial indicators (Camilleri,
2021; Lagrosen, Seyyed-Hashemi and Leitner, 2004).
A relevant review of the literature suggests that the institutions ought to be evaluated
on their organization; corporate governance, autonomy; accountability; system structures;
resourcing and funding; consultation processes; digitalization; admission processes; student-
centered education, internationalization; regional development; continuing education; lifelong
learning qualifications; research, innovation and technology transfer; high impact publications,
stakeholder engagement with business and industry; labour market relevance; collaborations
with other HEIs and researcher centers; and quality assurance among other issues (OECD,
2019; EU, 2017; Lagrosen et al., 2004; O’Neill and Palmer, 2004; Cheng and Tam, 1997;
Owlia and Aspinwall, 1996). The Organization for Economic Cooperation and Development
(OECD) regularly reviews the current state of higher education systems in its member
countries. Its benchmarking exercises are intended to scrutinize the performance of universities
and colleges. OECD (2019) has used 24 domains to evaluate different aspects of the HEIs’
organizational performance. Table 2 features a list of 45 performance indicators that can assess
the HEIs’ resources and their key functions.
Table 2. OECD’s HEIs’ performance indicators
Resources Expenditure on higher education, as a percentage of Gross Domestic
Product (
Total public expenditure on higher education, as a percentage of public
Annual expenditure per student by higher education institutions
expenditure per student for all services
Higher education expenditure on R&D, as a percentage of GDP
Proportion of higher education institutions expenditure on R&D
Household expenditure on higher education institutions per student
Share of non
household private expenditure on higher education institutions
Expenditure per student on grants and scholarships
Share of academic staff younger than 35
Share of academic staff 60 or older
Share of women among academic staff
Proportion of current expenditure spent on staff
Ratio of academic staff to student in higher education institution
academic staff per 100 academic staff
Education First-time entry rates to bachelor's or equivalent programs, excluding
international students
Proportion of students in master's and doctoral
Access rate gaps
parents without tertiary education
Proportion of new entrants 25 or older, bachelor's
Proportion of part
time students, bachelor's
Proportion of international or foreign students, master's
Proportion of new entrants who graduate on time or within three years from
the expected time
34 year
olds with higher education qualification
Percentage of graduates reaching at least literacy proficiency level 3, 16-34
Employment rates of master’s graduates, 25
34 year
Employment premium for higher education graduates, 25
34 year
Percentage of graduates employed or in education, 15
29 year
Earnings of bachelor's graduates, relative to other workers, 25
34 year
Relative level of self-reported health for higher education graduates, 16-34
Relative level of self-reported interpersonal trust for higher education
graduates, 16
34 year
time equivalent researchers per 1
000 people, 25
64 year
Proportion of researchers working in higher education
Proportion of women researchers in higher education
Share of doctorate holders in the population
Proportion of foreign
citizen doctorate holders
Share of higher education research and development that is funded by the
business enterprise sector
Higher education
business collaboration in
research and development
Share of small and medium sized enterprises collaborating on innovation
with higher education or research institutions
Share of PCT published applications by the higher education secto
Proportion of Higher education R&D on basic researc
Number of publicatio
ns per 1000 population, 25
64 year
Percentage of publications among the 10% most cited
Share of research documents based on interna
onal scientific collaboration
Difference between annual fractional inflows and outflows per 100 full-time
Share of scientific documents with open access
(adapted from OECD, 2019)
There are different methodologies and key performance indicators that can be used to
evaluate the service quality in higher education. The above metrics are used to compare the
OECD countries’ HEI performance in terms of allocated resources, the provision of student-
centered education, research and engagement. However, this scorecard and the quality of its
outputs ought to be validated in different contexts. There are other performance variables,
including the pedagogical knowledge and experience of the course instructors, the HEIs’
working conditions, teaching methodologies and practices, the usage of education
technologies, engagement with business and industry, et cetera, that were not featured in this
scorecard. Perhaps, in reality it may prove difficult to measure qualitative issues. For instance,
while HEIs may be willing to demonstrate their engagement with different stakeholders,
currently, there are no mechanisms in place to monitor, report and assess their outreach
The HEIs’ responsibility is to address the skill gaps and mismatches in their labor
market (OECD, 2019; EU, 2017). The governments’ policy makers together with the HEI
leaders need to address sector-specific skill shortages. Specifically, EU (2017) proposed that
HEIs ought to: (i) better understand what skills are required by the prospective employers (ii)
communicate to society, practitioners and policy-makers about what they are already doing to
prepare graduates for the labor market; (iii) prepare students and influence their choice of
study; and (iv) implement effective learning programs that rely on blended learning
methodologies including traditional and digital learning approach
5. The impact of COVID-19 on higher education services
5.1 Social Distancing
During the first wave of the pandemic, several universities and colleges have closed
their doors to contain the spread of COVID-19 (Ren et al., 2020; Archila et al., 2020). They
had to adapt to an unprecedented situation that disrupted their higher education services (Obaid
AI-Youbi et al., 2020; Ana, 2020). The outbreak of COVID-19 has resulted in both challenges
and opportunities for them. They had to take radical measures, including social distancing, to
slow the contagion. The educational institutions, including HEIs have embraced the dynamics
of the digital technologies to provide their educational services (Burns, 2020; Watermeyer et
al., 2020; OECD, 2020; EUA, 2020). Most of them have articulated emergency plans as they
disseminated information about the virus, trained their employees to work remotely, and
organized virtual sessions with their students and/or other stakeholders (Hashim et al., 2020;
Jowsey et al., 2020). In many cases, the preventative measures have led to the closure of the
educational establishments (EUA, 2020). Hence, HEIs were expected to utilize education
technologies (Longhurst et al., 2020; Romero-Rodriguez et al., 2020; Johnson et al., 2020).
5.2 Remote learning through virtual technologies
Several tertiary education institutions were in a position to migrate from traditional and
blended learning approaches to fully virtual and remote course delivery to respond to COVID-
19 (Worldbank, 2020; Jowsey et al., 2020). Very often, this contingent situation has resulted
in different problems to teachers and their students (Obaid AI-Youbi et al., 2020; Longhurst et
al., 2020;). Both parties necessitated training, facilitation or orientation sessions to acquaint
themselves with electronic learning (elearning) resources (Baloran, 2020). They also required
appropriate internet connectivity (at their homes) to use their HEIs’ learning management
systems (LMS) like Moodle, Blackboard and Canvas, among others. Alternatively, they
interacted with their students through virtual meetings, in real time (Budi et al., 2020; Arora
and Srinivasan, 2020). The educators could have used Massive Open Online Courses (MOOCs)
platforms like Coursera and EdX or video-conferencing platforms including Zoom, D2L,
Webex, Adobe Connect, Skype for Business, Big Blue Button and EduMeet, among others
(Worldbank, 2020). The market for these solutions is supported by cloud-providers such as
Amazon Web Services, Microsoft, Google as well as national research education networks
Hence during COVID-19, most HEIs relied on LMSs for asynchronous learning
through text, video lectures, et cetera. At times, they engaged in synchronous, interactive
communications with their students (as they used video conferencing) to improve their
students’ learning experiences (Salman et al., 2020). COVID-19 has pushed HEIs to embrace
elearning and mobile learning (m-learning). HEI leaders and their course instructors were
expected to develop a new modus operandi to deliver their higher education services (Johnson
et al., 2020; Rastogi and Priya, 2020). The course instructors were pressed (by their HEI
leaders) to provide remote teaching to their students through virtual classroom services (EUA,
2020). As a result, instructors designed formative questions, tests, or exercises that were made
available through the digital and mobile technologies. Very often, they engaged and interacted
with their students in real time. However, the shift to online, synchronous classes did not come
naturally. Technically speaking, it could have proved difficult for some educators to connect
with a large number of students (or course participants) at the same time. In fact, many HEIs
relied on responsive helpdesks to support them in case of disruptions and/or to solve technical
5.3 Possible challenges and responses in the short and medium term
Arguably, the educators in higher education and other levels, can never replace their
traditional, face-to-face lectures and discussions with online teaching. However, the pandemic
and its social distancing implications has resulted in school closures. Consequentially, the
students’ isolation could have had the potential to unsettle them (Araújo et al., 2020) or could
have contributed to their lack in self-discipline (Bao, 2020). The educators’ responsibility is to
continuously monitor their students’ emotional health (Zhai and Du, 2020) and psychosocial
challenges (Longhurst et al., 2020). They can do so by organizing regular virtual interactions
with them to address their sense of loneliness or helplessness, encourage them to share
their experience, and discuss about coping strategies (Baloran, 2020).
In many cases, the educators could have defined the duration of live streaming sessions,
according to their students’ self-regulation and metacognitive abilities Their interactive
lectures could have been supplemented with non-digital learning activities. HEIs had to ensure
that their distance learning programs were accessed by all students, including those with
disabilities or from low-income backgrounds (EU, 2017). UNESCO (2020) proposed that the
governments can assist these vulnerable individuals by providing them with learning
technologies (like laptops or tablets, if necessary) and support them with internet connectivity
and other issues. Notwithstanding, HEIs were expected to protect the privacy and security of
their instructors and students, as they had to upload educational resources through the Internet
(Murphy, 2020; Sulisworo et al., 2020). The online resources, platforms and applications (apps)
that are used for elearning purposes should not violate their users’ data privacy (EUA, 2020).
5.4 The way forward in a post COVID-19 era
Those HEIs that have opened their doors to students and lecturers are encouraging them
to wear masks, to keep social distancing, and to limit their gatherings in all public spaces,
including outdoors. Their requirements may include daily screenings for symptoms before
entering their campuses; strict hygienic measures like wearing a face mask in public spaces;
maintaining two meters of distance from others; and the compliance with the signages in
hallways, elevators, and stairwells (Chronicle, 2020).
At the time of writing this paper, everyone is expected to abide by their local health and
safety policies. The students may be reminded about the nearest hand sanitizing station and to
ease congestion at building entrances and exits (Archila et al., 2020). While most traditional-
age students aren’t at serious risk of developing complications if they contract the infection,
many HEI employees are. As a result, several HEIs have updated their rules and regulations
with COVID-19 procedures. In some cases, they have clarified the consequences for violations.
6 Conclusions
COVID-19 has had an impact on the delivery of service quality of HEIs. The pandemic
has disrupted the education of millions of students in different contexts. However, on a positive
note, it has opened a window of opportunity for higher education stakeholders. COVID-19 has
triggered many educators to start using new teaching methodologies including synchronous,
interactive communications to continue delivering their curricula and educational programs.
Their sudden and unprecedented closure has led them to experiment with virtual education
technologies and to engage with their students in real time, through video conferencing
software. There were (and still are) a number of challenging issues and implications for the
successful transition from traditional and blended learning approaches to fully virtual and
remote course delivery (some of these issues were duly pointed out in this contribution).
COVID-19 urged HEI leaders to embrace virtual technologies to continue delivering student-
centered education, to disseminate high impact research as well as for stakeholder engagement
and outreach.
6.1 Recommendations and future research avenues
Arguably, the integration of education technologies in higher education will be
accelerated in the foreseeable future. The use of interactive technologies shall become the
norm, in a post COVID-19 era. Therefore, HEIs ought to invest in online learning
infrastructures, resources and facilitating conditions, for the benefit of their students and faculty
employees. This way, they will be in a position to improve their legitimacy with societal
stakeholders, to attract prospective students, lure prolific faculty members and/or researchers,
whilst raising the quality and standards of their higher education services.
Indeed, there is scope for further research that investigates the impact of remote
teaching through digital and mobile learning technologies on the students’ learning journey.
Prospective research can use different methodologies, sampling frames and analytical
techniques to shed more light about the implementation and effectiveness of remote learning.
Future studies can explore the students’ perceptions about the service quality and performance
of higher education services that rely on distance learning approaches. They may also examine
the effects of having fully virtual and remote course delivery on the students’ experience and
their learning outcomes.
Abdullah, F. (2006a), "Measuring service quality in higher education: HEdPERF versus
SERVPERF", Marketing Intelligence & Planning, Vol. 24 No. 1, pp. 31-47.
Abdullah, F. (2006b), “Measuring service quality in higher education: three instruments
compared”, International Journal of Research & Method in Education, Vol. 29, No. 1, pp. 71-
AI-Youbi, A. O., Al-Hayani, A., Bardesi, H. J., Basheri, M., Lytras, M. D. and Aljohani, N. R.
(2020), “The King Abdulaziz University (KAU) pandemic framework: a methodological
approach to leverage social media for the sustainable management of higher education in
crisis”, Sustainability, Vol. 12, No. 11, pp. 4367-4388.
Ana, A. (2020), “Trends in expert system development: A practicum content analysis in
vocational education for over grow pandemic learning problems”, Indonesian Journal of
Science and Technology, Vol. 5, No. 2, pp. 71-85.
Angell, R.J., Heffernan, T.W. and Megicks, P. (2008), "Service quality in postgraduate
education", Quality Assurance in Education, Vol. 16 No. 3, pp. 236-254.
Araújo, F. J.,D.O., de Lima, L. S. A., Cidade, P. I. M., Nobre, C. B. and Neto, M. L. R. (2020),
“Impact of Sars-Cov-2 And its reverberation in global higher education and mental
health”, Psychiatry Research, In Press.
Archila, P.A., Molina, J. and de Mejía, A.M.T. (2020), “Using Historical Scientific
Controversies to Promote Undergraduates’ Argumentation”, Science and Education, In Press.
Arora, A.K. and Srinivasan, R. (2020), “Impact of Pandemic COVID-19 on the Teaching–
Learning Process: A Study of Higher Education Teachers”, Prabandhan: Indian Journal of
Management, Vol. 13, No. 4, pp. 43-56.
Camilleri, M.A. & Camilleri A. (2016). Education and Social Cohesion for Economic
Growth. International Journal of Leadership in Education. 19 (5), 617-631.
Camilleri, M.A. (2019). Higher Education Marketing: Opportunities and Challenges in the
Digital Era. Academia, 0(16-17), 4-28.
Camilleri, M.A. (2021). Using the balanced scorecard as a performance management tool in
higher education. Management in Education. 35(1), 10-21. 10.1177/0892020620921412
Baloran, E. T. (2020), “Knowledge, Attitudes, Anxiety, and Coping Strategies of Students
during COVID-19 Pandemic”, Journal of Loss and Trauma, In Press,
Bao, W. (2020), “COVID19 and online teaching in higher education: A case study of Peking
University”, Human Behavior and Emerging Technologies, Vol. 2, No. 2, pp. 113-115.
Brady, M.K. and Cronin Jr, J.J. (2001), “Some new thoughts on conceptualizing perceived
service quality: a hierarchical approach”, Journal of Marketing, Vol. 65, No. 3, pp. 34-49.
Brochado, A. (2009), "Comparing alternative instruments to measure service quality in higher
education", Quality Assurance in Education, Vol. 17 No. 2, pp. 174-190.
Burns, R. (2020), “A COVID-19 panacea in digital technologies? Challenges for democracy
and higher education” Dialogues in Human Geography, In Press,
Budi, H.S., Ludjen, J.S.M., Aula, A.C., Prathama, F.A., Maulana, R., Siswoyo, L.A.H. and
Prihantono, A.S. (2020), “Distance learning (DL) strategies to fight coronavirus (COVID-19)
pandemic at higher education in Indonesia”, International Journal of Psychosocial
Rehabilitation, Vol. 24, No. 7, pp. 8777-8782.
Cheong Cheng, Y. and Ming Tam, W. (1997), "Multimodels of quality in education", Quality
Assurance in Education, Vol. 5 No. 1, pp. 22-31.
Chronicle (2020). Universities and colleges say they can reopen safely. But will students follow
the rules?
Clemes, M. D., Gan, C. E. and Kao, T. H. (2008), “University student satisfaction: An
empirical analysis”, Journal of Marketing for Higher Education, Vol. 17, No. 2, pp. 292-325.
Cronin Jr, J.J. and Taylor, S.A. (1992), “Measuring service quality: a reexamination and
extension”, Journal of Marketing, Vol. 56, No. 3, pp. 55-68.
Eisenhardt, K. M., Graebner, M. E. and Sonenshein, S. (2016), “Grand challenges and
inductive methods: Rigor without rigor mortis”, Academy of Management Journal, Vol. 59,
No. 4, pp. 1113-1139.
EU (2017), “Communication from the Commission to the European Parliament, the Council,
the European Economic and Social Committee and the Committee of the Regions: A renewed
EU agenda for higher education {COM(2017) 247 final}”, European Commission, Brussels,
EUA (2019), “The role of universities in regional eco systems innovative”, European
University Association, Brussels, Belgium.
EUA (2020), “Covid-19 and Universities”, European University Association, Brussels,
Ford, J.B., Joseph, M. and Joseph, B. (1999), "Importanceperformance analysis as a strategic
tool for service marketers: the case of service quality perceptions of business students in New
Zealand and the USA", Journal of Services Marketing, Vol. 13 No. 2, pp. 171-186.
Geuna, A. and Martin, B.R. (2003), “University research evaluation and funding: An
international comparison”, Minerva, Vol. 41, No. 4, pp. 277-304.
Hägg, G. and Schölin, T. (2018), “The policy influence on the development of entrepreneurship
in higher education”, Education + Training, Vol. 60, Nos. 7/8, pp. 656-673.
Hashim, S., Masek, A., Abdullah, N. S., Paimin, A. N. and Muda, W.H.N.W. (2020),
“Students’ intention to share information via social media: A case study of COVID-19
pandemic”, Indonesian Journal of Science and Technology, Vol. 5, No. 2, pp. 61-70
HBR (2019), “6 Reasons Why Higher Education Needs to Be Disrupted”, Harvard Business
Review, Cambridge, MA, USA.
HemsleyBrown, J., Lowrie, A., Gruber, T., Fuß, S., Voss, R. and GläserZikuda, M. (2010),
“Examining student satisfaction with higher education services”, International Journal of
Public Sector Management, Vol. 23, No. 2, pp 105-123.
Hill, F.M. (1995), "Managing service quality in higher education: the role of the student as
primary consumer", Quality Assurance in Education, Vol. 3 No. 3, pp. 10-21.
Johnson, N., Veletsianos, G. and Seaman, J. (2020), “U.S. Faculty and Administrators’
Experiences and Approaches in the Early Weeks of the COVID-19 Pandemic”, Online
Learning Journal, Vol. 24, No. 2, pp. 6-21.
Jowsey, T., Foster, G., Cooper-Ioelu, P. and Jacobs, S. (2020), “Blended learning via distance
in pre-registration nursing education: A scoping review”, Nurse Education in Practice, In
Press, 10.1016/j.nepr.2020.102775
Kivisto, J, Pekkola E and Lyytinen A (2017), “The influence of performance-based
management on teaching and research performance of Finnish senior academics”, Tertiary
Education and Management, Vol. 23, No. 3, pp. 260–275.
Lagrosen, S., SeyyedHashemi, R. and Leitner, M. (2004), "Examination of the dimensions of
quality in higher education", Quality Assurance in Education, Vol. 12 No. 2, pp. 61-69.
Lomas, L. (2007), “Are students customers? Perceptions of academic staff”, Quality in Higher
Education, Vol. 13, No. 1, pp. 31-44.
Longhurst, G. J., Stone, D. M., Dulohery, K., Scully, D., Campbell, T. and Smith, C. F. (2020),
“Strength, Weakness, Opportunity, Threat (SWOT) Analysis of the Adaptations to Anatomical
Education in the United Kingdom and Republic of Ireland in Response to the Covid19
Pandemic”, Anatomical Sciences Education, Vol. 13, No. 3, pp. 301-311.
Lynch, K. (2015), “Control by numbers: New managerialism and ranking in higher
education”, Critical Studies in Education, Vol. 56, No. 2, pp. 190-207.
Mourad, M., Ennew, C. and Kortam, W. (2011), “Brand equity in higher education”, Marketing
Intelligence & Planning, Vol. 29, No. 4, pp. 403- 420.
Murphy, M. P. (2020), “COVID-19 and emergency eLearning: Consequences of the
securitization of higher education for post-pandemic pedagogy”, Contemporary Security
Policy, Vol. 41, No. 3, pp. 492-505.
Naidoo, R., Shankar, A. and Veer, E. (2011), “The consumerist turn in higher education: Policy
aspirations and outcomes”, Journal of Marketing Management, Vol. 27, Nos. 11-12, pp. 1142-
OECD (2019), “Benchmarking Higher Education System Performance”, Organization for
Economic Cooperation and Development, Paris, France.
OECD (2020), “OECD Policy Response to CoronaVirus: Education responses to COVID-19:
Embracing digital learning and online collaboration”, Organization for Economic Cooperation
and Development, Paris, France.
Oldfield, B.M. and Baron, S. (2000), "Student perceptions of service quality in a UK
university business and management faculty", Quality Assurance in Education, Vol. 8 No. 2,
pp. 85-95.
O’Neill, M.A. and Palmer, A. (2004), "Importanceperformance analysis: a useful tool for
directing continuous quality improvement in higher education", Quality Assurance in
Education, Vol. 12 No. 1, pp. 39-52.
Owlia, M.S. and Aspinwall, E.M. (1996), "A framework for the dimensions of quality in higher
education", Quality Assurance in Education, Vol. 4 No. 2, pp. 12-20.
Ozkan, S. and Koseler, R. (2009), “Multi-dimensional students’ evaluation of e-learning
systems in the higher education context: An empirical investigation”, Computers &
Education, Vol. 53, No. 4, pp. 1285-1296.
Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1988), “Servqual: A multiple-item scale for
measuring consumer perceptions, Journal of Retailing, Vol. 64, No. 1, pp. 12-40.
Quinn, A., Lemay, G., Larsen, P. and Johnson, D.M. (2009), “Service quality in higher
education”, Total Quality Management, Vol. 20, No. 2, pp. 139-152.
Raaper, R. (2019), “Students as consumers? A counter perspective from student assessment as
a disciplinary technology”, Teaching in Higher Education, Vol. 24, No. 1, pp. 1-16.
Rastogi, R. and Priya, A. (2020), “Recent trends in Indian higher education system”,
International Journal of Advanced Science and Technology, Vol. 29, No. 8, pp. 2216-2222
Ren, T., Lyu, J., Yu, C.Q. and Li, L.M. (2020), “Rethinking public health education and public
health workforce development in China”, Chinese Journal of Preventive Medicine, Vol. 54,
No. 5, pp. 457-464.
J. Romero-Rodríguez, I. Aznar-Díaz, F. Hinojo-Lucena and Gómez-García, G. (2020),
"Mobile Learning in Higher Education: Structural Equation Model for Good Teaching
Practices", IEEE Access, Vol. 8, pp. 91761-91769.
Rutter, R., Roper, S. and Lettice, F. (2016), “Social media interaction, the university brand and
recruitment performance”, Journal of Business Research, Vol. 69, No. 8, pp. 3096-3104.
Salman, M., Mustafa, Z.U., Asif, N., Zaidi, H.A., Hussain, K., Shehzadi, N., Khan, T.M. and
Saleem, Z. (2020), “Knowledge, attitude and preventive practices related to COVID-19: a
cross-sectional study in two Pakistani university populations”, Drugs & Therapy Perspectives,
In Press,
Sojkin, B., Bartkowiak, P. and Skuza, A. (2012), “Determinants of higher education choices
and student satisfaction: the case of Poland”, Higher Education, Vol. 63, No. 5, pp. 565-581.
Spurlock, D. (2020), “Scholarship During a Pandemic: Secondary Data Analysis”, Journal of
Nursing Education, Vol. 59, No. 5, pp. 245-247.
Sulisworo, D., Astuti, A.Y. and Fatimah, N. (2020), “Online learning implementation during
COVID-19 mitigation in Indonesia: Measuring the lecturers’ technology readiness”,
International Journal of Advanced Science and Technology, Vol. 29, No. 7, pp. 2252-2263
Tan, K.C. and Kek, S.W. (2004), “Service quality in higher education using an enhanced
SERVQUAL approach”, Quality in Higher Education, Vol. 10, No. 1, pp. 17-24.
Tian, X. and Martin, B. (2014), “Business models for higher education: an Australian
perspective”, Journal of Management Development, Vol. 33, No. 10, pp. 932-948.
Trivellas, P. and Dargenidou, D. (2009), “Organisational culture, job satisfaction and higher
education service quality: The case of Technological Educational Institute of Larissa”, The
TQM Journal, Vol. 21, No. 4, pp. 382-399.
Tsinidou, M., Gerogiannis, V. and Fitsilis, P. (2010), "Evaluation of the factors that
determine quality in higher education: an empirical study", Quality Assurance in Education,
Vol. 18, No. 3, pp. 227-244.
UNESCO (2020), “COVID-19: 10 Recommendations to plan distance learning solutions”,
United Nations Educational, Scientific and Cultural Organization, Paris, France.
Voss, R., Gruber, T. and Szmigin, I. (2007), “Service quality in higher education: The role of
student expectations”, Journal of Business Research, Vol. 60, No. 9, pp. 949-959.
Watermeyer, R., Crick, T., Knight, C. and Goodall, J. (2020), “COVID-19 and digital
disruption in UK universities: afflictions and affordances of emergency online
migration”, Higher Education, In Press,
Wilkins, S. (2020), “The positioning and competitive strategies of higher education institutions
in the United Arab Emirates”, International Journal of Educational Management, Vol. 34, No.
1, pp. 139-153.
Worldbank (2020), “The COVID-19 Crisis Response: Supporting tertiary education for
continuity, adaptation, and innovation”, Worldbank Group Education, Washington, USA.
Zeithaml, V.A., Berry, L.L. and Parasuraman, A. (1993), “The nature and determinants of
customer expectations of service”, Journal of the Academy of Marketing Science, Vol. 21, No.
1, pp. 1-12.
Zhai, Y. and Du, X. (2020). Addressing collegiate mental health amid COVID-19
pandemic. Psychiatry Research, Vol. 288, No. 113003.
... There is a vast theoretical foundation for analysing the use of educational technology in general and of social networks in particular. Davis (1986) based his work on the Theory of Reasoned Action (TRA) by Fishbein and Ajzen (1975) and formulated the technology acceptance model (TAM; Althunibat, 2015;Camilleri & Camilleri, 2021;Park et al., 2007). However, the flaws in this TAM were identified by its own creator, who discovered that it lacked the variables to answer questions such as perceived usefulness or ease of use. ...
... Consequently, in order to find a more contextual explanation, he supplemented his model with the approach of the uses and gratification theory (UGT) (Katz et al., 1974), which established a valid theoretical model to understand the reason behind the choice (Saini & Abraham, 2019). This model consists of five items: perceived ease of use, perceived usefulness, attitudes towards technology, the intention to use it and real behaviours (Al-Rahmi, 2021;Camilleri & Camilleri, 2021;Davis, 1989). ...
... In fact, as a result of many of the changes that took place, the possibility of including real-time interactive communication emerged. In this way, both teachers and students would be able to continue the teaching process (Camilleri, 2021). The facilitating conditions of both teachers and institutions were key to achieving this (Camilleri & Camilleri, 2022). ...
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Social networking sites form part of everyday life in classrooms at all educational levels. Within these, general social networking sites (GSNSs) offer pre-service teachers flexibility, versatility and the possibility of forming educational communities by connecting formal, non-formal and informal settings. This research analyses the nature, intensity, and type of pre-service teachers’ use of such for educational purposes in their initial training in order to detect the most important aspects for improvement. Possible factors shaping behaviour were gender, whether individuals belonged to universities operating online or in person, differences in the types of studies they were undertaking, and the time at which the questionnaire was administered, before or after the COVID-19 health crisis. To this end, we studied how much and with what aims these students use the most widely used GSNSs for educational purposes. To do so, we administered a questionnaire to a total of 812 students from 6 Spanish universities. The results show a preference for WhatsApp, YouTube, and Instagram. In addition, it was found that undergraduate students used them more intensively than postgraduate students. In the case of online universities, there was a greater need to cover affective and emotional aspects than in in-person universities. As in almost all areas, the situation caused by COVID-19 changed the way social networks were used. The findings also show that pre-service teachers consumed more information on social media than what they produced, which leads to a failure to fully exploit social capital and potential job or academic opportunities that could be generated through their own creations.
... Los estudios científicos han demostrado cómo intervienen estas en el estado psicológico de los estudiantes universitarios (rodríguez-Hidalgo et al., 2020). Se trata también de un nuevo escenario que ha obligado a las universidades a (Camilleri, 2021). Aun así, los datos de este trabajo apuntan a que los estudiantes de los Grados de Educación Infantil y Primaria siguen mostrando un alto engagement académico y una buena valoración sobre la formación en inclusión, obteniéndose cifras similares a las encontradas en otros periodos, por lo que parece que las medidas adoptadas por las universidades han mantenido la calidad docente. ...
... Aun así, los datos de este trabajo apuntan a que los estudiantes de los Grados de Educación Infantil y Primaria siguen mostrando un alto engagement académico y una buena valoración sobre la formación en inclusión, obteniéndose cifras similares a las encontradas en otros periodos, por lo que parece que las medidas adoptadas por las universidades han mantenido la calidad docente. Así, algunos trabajos señalan que estas deberán adoptar un modelo bimodal u online en la era post-CoVID (Camilleri, 2021). Por su parte, los estudiantes, pese a la situación sanitaria producida por el CoVID-19, han seguido motivados, entusiasmados y comprometidos con su carrera universitaria (Baber, 2020), si bien existen trabajos en los que han hallado resultados opuestos (Fyllos et al., 2021) por lo que es necesario continuar la investigación sobre la repercusión que ha tenido la pandemia en los universitarios. ...
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RESUMEN Poner en práctica una educación inclusiva, de calidad y sostenible requiere docentes comprometidos, entusiasmados y constantes que tengan actitudes favorables hacia la inclusión y, especialmente, hacia el alumnado con Necesidades Educativas Especiales-NEE-cuya presencia es cada vez mayor en las aulas. Los estudios han probado cómo la formación en inclusión se relaciona con unas actitudes más favorables. Sin embargo, no se ha examinado el efecto que puede tener el engagement o compromiso académico de los estudiantes universitarios en sus actitudes hacia la inclusión y el efecto mediador de este tipo de formación sobre dicha relación. El propósito del presente trabajo es probar si el engagement académico de los estudiantes universitarios influye en la valoración que hacen de la formación en inclusión y si una mejor valoración hace que aumenten las 10
... Individuals will probably use technologies to enhance the quality of their work or job performance (Camilleri, 2020a;Camilleri, 2021a;Cheon, Lee, Crooks & Song, 2012;Davis, 1989;Garcia & Silva, 2017). They may perceive that some technologies are useful for them, particularly if they help them increase their productivity. ...
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This contribution investigates higher education students' perceptions about mobile learning (m-learning) applications, as well as the effects of social influences and of appropriate facilitating conditions, on their intentions to continue using them. A structured survey questionnaire integrated valid measures from the Technology Acceptance Model (TAM) and from the Unified Theory of Acceptance and Use of Technology (UTAUT) to better explain their acceptance and use of m-learning software. The findings reported that facilitating conditions including the provision of resources, ongoing training opportunities and technical support, were affecting the respondents' engagement with m-learning programs. The respondents indicated that they were not influenced by others, to use mobile technologies for educational purposes. The results also suggest that they were well acquainted (and habituated) with the use of mobile devices and their applications. Evidently, they helped them improve their learning journeys.
... One may argue that the m-learning paradigm is associated with constructivist approaches [8], including with discovery-based learning. Key theoretical underpinnings suggest that the use of ubiquitous technologies including smart phones and tablets, can improve the delivery of quality, student-centered education [21,33]. ...
Conference Paper
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Students are increasingly utilizing mobile learning applications (m-learning apps) in various contexts. They can access their content from anywhere, anytime. This research explores the students' perceptions about learning technologies in a higher educational context. It integrates the Technology Acceptance Model's (TAM) constructs with "perceived enjoyment" to better understand their dispositions to engage with educational apps. The data was gathered through an online survey questionnaire among 317 research participants who were following full time university courses in a Southern European country. The findings suggest that the students were motivated to use learning apps. Their perceived usefulness, ease-of-use and enjoyment were having a significant effect on their intentions to continue using them in the future. This contribution implies that "perceived enjoyment" construct can be combined with TAM to shed more light on the users' intrinsic motivations to use mobile apps for educational purposes.
... Marco-Laraja et al. (2021) reiterated that this model is considered an essential tool for evaluating customer satisfaction. During the COVID-19 pandemic, the SERVQUAL model had been widely utilized to evaluate service quality in several different, fields such as e-learning (Swani et al., 2021;Shahzad et al., 2020;Camilleri, 2021), health and healthcare (Babroudi et al., 2021), and even marketing (Yang et al., 2020;Ö zden and Celik, 2021;Ong et al., 2021a;Nilashi et al., 2021;Rumiyati and Syafarudin, 2021). Since the core of SERVQUAL is to evaluate the quality of service by businesses to enhance customer satisfaction (Balinado et al., 2021), the need to consider the new normal living condition should be explored to create a baseline on how businesses should be run during the COVID-19 pandemic. ...
The implementation of lockdown due to the COVID-19 pandemic has affected most businesses worldwide. The transportation business, specifically in the Philippines, has been heavily affected since only the healthcare and essential workers were allowed to leave their homes during the early stage of the pandemic. This paper aimed to explore the service quality of Public Utility Vehicles (PUV) in the Philippines during the COVID-19 pandemic utilizing the SERVQUAL dimensions. A total of 564 participants answered an online questionnaire using the convenience sampling approach, consisting of 58 questions. Structural equation modelling (SEM) was applied to derive the causal relationships between SERVQUAL dimensions, COVID-19 safety protocol, and customer satisfaction simultaneously. Out of the six dimensions, the SEM indicated that COVID-19 protocols, tangibility, and latent assurance variables were found to significant affect PUV service quality and thus customer satisfaction. This study is one of the first complete studies that analyzed the PUV service quality during the COVID-19 pandemic. The findings could provide the government with an evaluation of the compliance of PUVs to the imposed COVID-19 protocols. Furthermore, the framework of this study could also be applied and extended in evaluating PUV worldwide.
... COVID-19 and the Sustainability of Agricultural Extension Models. International Journal of Applied Chemical and Biological Sciences, 3(1), [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] The following sections offer a brief historical and overview of each of the core models in use. In order to replicate, generalize, and scale novel extension models or improve current ones, researchers and policymakers may use the lessons identified against each model. ...
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Agricultural extension and advisory services in information and technology dissemination and delivery are critical in a developing country's food security and sustainability. Without extension service provision, the productivity and production smallholder farmers are experiencing would have been much lower, and current global hunger and malnutrition worse. This paper assesses the effects of COVID-19 on the sustainability of agricultural extension models/approaches for smallholder farmers in developing countries. Over 60 papers were reviewed covering 2019-2021, commencing with the disease outbreak in China. Based on characteristics and usage, the findings indicate most reviewed extension models were disrupted. No single model was entirely disbanded as the impact of COVID-19 was being felt. However, each model incorporated a digital means of communication to keep farmers and service providers in touch. There is considerable criticism around the inadequacy of these extension techniques in advancing the agenda for smallholder farming's long-term viability that needs to be addressed.
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This study aims to identify the psychological components related to student success in a blended learning environment. The research method is applied , and data collection was conducted using a qualitative approach through a systematic review method. To achieve the goal of the study, a systematic and comprehensive review of the research background was conducted based on Sandlowski and Barroso's (2006) seven-step model. For this purpose, resources from databases (Elsevier, Scopus, ProQuest, Eric, Emerald, Springer) and related keywords were searched. After reviewing 480 papers from theoretical and scientific sources related to the research topic based on specific criteria and removing unrelated papers, a full review of the remaining 58 studies was performed. The systematic review of the research background resulted in the identification of 5 components, 9 concepts, and 75 codes. The results of the meta-synthesis indicate that the psychological components of students who want to succeed in the blended learning environment at the university include the following: emotional strategies and components (positive emotions and motivational beliefs), communication (connection resources, communication skills), cognitive (high-level thinking and academic engagement), metacognitive (self-management in learning and self-perception of learning), and personality.Among these, the role of emotional and metacognitive strategies and components is more important than others. Therefore, they have a greater impact on the success of blended learning.
The most crucial determinant of success in any service environment is the perception of the customers about the service quality or the product quality as it derives satisfaction and loyalty. Considering this imperative, the present review focuses on the service quality of online teaching, which has become a new normal during the pandemic. The pandemic has resulted in a paradigm shift of imparting education from brick to click classrooms. Hence, this article reviews the literature on the factors influencing service quality of click classrooms and mentions the parameters that lead to learners’ satisfaction. The systematic review helps in understanding how the research in this field has progressed. It is evident from this review that creating an interactive learning environment, giving prompt feedbacks, providing rich digital resources and course content, competent and skilled faculty members and continuous student support play a crucial role in enhancing the service quality of click classrooms leveraging learners’ satisfaction. The findings of this study support the educational institutions towards developing a sound and sustainable online learning environment by comprehending the students’ expectations about the service quality of an online learning environment. The study aims to propel future research works towards improving the service quality of click classrooms and enriching learners’ experience to impart quality education for all the stakeholders.
A pandemic crushes assumptions and inherited narratives of higher education. This chapter explores how COVID-19 tested the parameters of teaching and learning and how universities failed this test. Through the panic of shutdowns, lockdowns, economic restructures, social distancing, and closures, the speed of change and decision making was profound and under public scrutiny. Online learning has been a panacea for economic and social problems for 20 years. To manage a crisis the scale of COVID-19, online learning would be the obvious solution. However, the pandemic showed the flaws in this strategy and the toxic reality of quick fixes to higher education. Students were short changed and academics pushed to exhaustion. After COVID-19, higher education is in shreds. The visions and futures of universities are blurred. Using the theories of Paul Virilio, particularly his University of Disaster, this chapter probes how higher education unravels and dissociates teaching and research. When time is short and risks are high, what mode of leadership will survive in the post-pandemic university?
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The impact of the COVID-19 has emerged as a varied issue, ranging from the economy, society's social order, and edu­cation, especially when social and physical distancing have been introduced in various areas of community activities as one of the prevention. It has also affected the tertiary edu­cation institution where learning activities should be con­ducted from and at home, forcing the higher education communities to shift learning from conventional learning to online learning. Needless to say, learning that does not re­quire practicum is easier compared to learning that needs it. Consequently, it is a new task for lecturers to ensure the meaningful practicum learning implementation is con­ducted as it should be. Therefore, the creation of expert systems for practicum learning in vocational education is urgently required in online learning. The aim of this litera­ture review was to examine the development of an expert system used at practicum learning in tertiary institutions and how the design of learning systems could be integrated into vocational education in facing the COVID-19 pandemic. The method used was the literature study, through research stages starting from the finding and selection of articles and journals with relevant topics, and then analysing the data. The findings of this study was to identify the development of an expert program in an attempt to promote practicum learning using e-learning in the midst of the COVID-19 pan­demic outbreak.
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The COVID-19 pandemic has had a profound and rapid impact on higher education institutions across the world. In this study, we report the findings of a survey investigating the rapid transition to emergency remote teaching in the early weeks of the pandemic at public and private post-secondary institutions in the United States. Participants consisted of 897 faculty and administrators at 672 U.S. institutions. Findings reveal that with few exceptions nearly all reporting institutions transitioned to emergency teaching and learning approaches. Administrators reported that faculty with and without online teaching experience pivoted to online teaching, and nearly all administrators indicated that those who did not have online teaching experience were in the process of learning how to teach online. Regardless of whether faculty had previous experience teaching online or not, many faculty reported that they were using new teaching methods. A majority of faculty reported making changes to their assignments or exams as a result of transitioning to a new mode of delivery. Nearly half reported lowering the expected volume of work for students (including dropping assignments or exams) and/or shifting to a pass/fail model for this semester. The primary areas where faculty and administrators identified a need for assistance related to student support, greater access to online digital materials, and guidance for working from home. This study provides an early snapshot of efforts towards teaching and learning continuity at a large scale and provides some insights for future research and practice.
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The Covid-19 pandemic is the reason why humanity is paying more attention to the importance of regular and rigorous handwashing. Interestingly, in the nineteenth century, regular and rigorous handwashing was a key (and controversial) solution proposed by the Hungarian obstetrician Ignaz Philipp Semmelweis to cut drastically cases of puerperal fever. The purpose of this study was to provide evidence that the case of Semmelweis and puerperal fever—a crucial historical scientific controversy—can be used as a springboard to promote university student argumentation. Our study was inspired by the fact that the Organization for Economic and Cooperative Development (OECD) stressed that more efforts and resources should be invested in promoting argumentation as an essential component for scientifically literate citizens in twenty-first century societies. However, nowadays, argument and debate are virtually absent from university science education. The data was derived from 124 undergraduates’ (64 females and 60 males, 15–30 years old) written responses and audio and video recordings in a university biology course in Colombia. The findings show that the articulation of this historical controversy with decision-making, small-group debate, and whole-class debate activities can be useful for promoting undergraduates’ argumentation. This study contributes to the development of a research-based university science education that can inform the design of an argumentation curriculum for higher education.
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Agility of science and technology in communication has brought a new dimension of information dissemination, which may have influenced human perceptions, especially on the dissemination of news pertaining to this pandemic. This research aims to determine the students’ sources of information regarding the COVID-19 disease and investigate their intention to share the information pertaining to COVID-19. A survey study was designed using an online questionnaire involving 147 higher education students. The online questionnaire; measures three elements of the students’ intention, namely initiative, desire and resourcefulness. The findings; the sources of information regarding the COVID-19 pandemic are mainly the government authorities and local healthcare workers. The most preferred medium of information regarding the COVID-19 pandemic is social media, and the most trusted medium is the television broadcast. Also, finding suggests that the students take initiative to verify information and demonstrate a desire to share credible and right information with their family and friends through social media. As such, in an effort or attempt to disseminate credible information about any important matters to the general public, the government can count on students as agents for transmitting the information to third parties including their family and friends.
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The recent pandemic has raised significant challenges worldwide. In higher education, the necessity to adopt efficient strategies to sustain education during the crisis is mobilizing diverse, complementary, and integrative action in response. In this research article, we rise to the challenge of designing and implementing a transparent strategy for social media awareness at King Abdulaziz University (KAU). We introduce a framework for social media impact, termed the KAU Pandemic Framework. This includes the factors with the most important role in enhancing the deployment of social media in crisis in order to minimize the negative impact on education's sustainability. We used a mixed-methods approach, integrating quantitative statistical analyses of social media data and online surveys and qualitative interviews in such a way as to construct a comprehensive framework. The results show that a methodological framework can be justified and that Twitter contributes significantly to six areas: administrative resilience; education sustainability; community responsibility; positive sentiment; community bonds; and delivery of promised value. The components of our proposed methodological framework integrate five pillars of the strategic adoption of social media: social media governance; social media resilience; social media utilization; decision-making capability; and institutional strategy. Finally, we show that the KAU Pandemic Framework can be used as strategic decision-making tool for the analysis of the gaps and inefficiencies in any social media plan that is deployed and the management challenges arising from the pandemic.
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COVID-19 is a global concern affecting Higher Education Institutions (HEIs). This pandemic led to a strong reaction among students who experiences anxiety. This cross-sectional study aimed to examine students’ knowledge, attitudes, anxiety, and coping strategies during the COVID-19 pandemic. Results showed that students possessed sufficient knowledge and high-risk perceptions. Non-medical prevention measures were perceived as highly effective. Students were satisfied with the government’s actions to mitigate problems. However, an unwillingness with the online-blended learning approach was observed. Students utilized various ways to cope up with mental health challenges. It is necessary to address students’ mental health during this COVID-19 pandemic among HEIs.
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Mobile learning is a methodology that involves the use of mobile devices to carry out the teaching-learning process. In exceptional situations such as that experienced during the COVID-19 pandemic in Spain, virtual training methods take on great importance, being the main route for the education of students. The purposes of this paper were to analyse the degree of implementation of the mobile learning methodology in Spanish universities and to check the sociodemographic factors that influence the development of good teaching practices in mobile learning. Ten hypothetical relationships were established and contrasted using a structural equation model. The sample was made up of 1544 university professors from 59 Spanish universities who were asked to complete a questionnaire designed to evaluate mobile learning practices. The results indicated that the degree of implementation of mobile devices was almost 73% of the population surveyed. While the sociodemographic factors that significantly influenced the development of good teaching practices were: teacher status; type of institution; educational technology research; implementing pedagogical innovations on a regular basis; agree that mobile devices are appropriate; belief in the expansion of mobile learning. Finally, the main findings and practical implications derived from the data obtained were discussed.
The coronavirus disease, also known as COVID-19, is a new infectious virus (nCov) spread over 210 countries across the world. This virus is exacerbated in people with underlying systemic health conditions such as diabetes mellitus, hypertension, and cardiovascular disease. The COVID-19 pandemic has adversely impacted on all areas of life, including education, therefore, distance learning (DL) or e-learning is a supportive educational system under this condition. The purpose of this study is to describe the readiness of lecturers and students in the field of dentistry in using the distance learning (DL) system during this pandemic. The simple random sampling method, was used to obtain data from a total of 142 respondents using questionnaires. In the 2nd, 4th, 6th, 8th, and 10th semesters there were approximately 28, 21, 23, 69, and 1 respondent, respectively. From the 142 respondents, 90% stated that they already had personal computers or laptops, while 10% used those belonging to relatives, neighbors, or friends. In accordance with the availability of internet facilities at home, 84% stated that they already had access to the internet, while 16% had none. Related to the quota and stability of internet access, 51% of respondents stated that they were ready with fast internet and sufficient quota, while 49% reported that they were not ready due to limited quota, and unstable internet access. Furthermore, a total of 20 lecturers were given access to a licensed Zoom® account. Lecturers and students stated their readiness to conduct distance learning in a bid to fight COVID-19and support the work from home programs. © 2020, Hampstead Psychological Associates. All rights reserved.
Universities have transitioned to online education in order to slow the spread of COVID-19. This transition mobilizes the technological utopian imaginary that digital technologies can rescue populations from the disease. It also raises the risk of deepening neoliberal educational reforms and, by extension, poses a threat to democracy itself. This commentary explores this risk and suggests ways to resist the resulting neoliberalization of education that it could entail.
The COVID-19 pandemic has disrupted nearly every aspect of life in the United States and around the globe, including significant impacts to higher education, both in its teaching-learning and research missions. With the physical closure of so many college and university campuses, a looming challenge is how nurse researchers can continue to generate new knowledge during a temporary but extended period of social distancing where conducting research requiring physical interaction with participants is impossible. In this Methodology Corner installment, a brief overview of secondary data analysis is provided, and resources for locating potentially useful data are described. Although secondary data analysis will not replace the dominant approaches used in nursing education research, current circumstances require it to take a much more prominent place in the toolbox of nursing education researchers. [J Nurs Educ. 2020;59(5):245-247.].