Postgraduate Student Satisfaction of Program Experience on Tertiary Education Institutional Planning in the Covid-19 Higher Education Competitive Environment

6. 8. 2021
Štítky

Competition in tertiary education is challenging and even more so in the current- and post-Covid-19 era. This has created a demand for greater efficiency in higher education institutions, particularly in post-graduate programs for MBA and DBA studies, which includes assessing customer (student) satisfaction that leads to retention rates. The inherent effects of such satisfaction considerations focus around the learning experience in direct relation to the career aspirations of new entered workforce participants, or inexperienced professionals, and their perception of the institution’s ability to provide the necessary knowledge and abilities in meeting those career goals and objectives. This study examines those perceptual issues for establishing a baseline of recommendations for revision efforts in tertiary educational institutions.

1. Introduction

Competition for tertiary education in the present- and post-Covid-19 environment is significant and requires a thorough comprehension of student expectations for their professional goals post-graduation. The role of tertiary adult education / higher education institutions such as the City University of Macau (CityU) serving an international student population that, nevertheless, hails predominately from mainland China as opposed to Macau natives, is to provide an educational experience that ensures their future success, as all likewise institutions do, but without the recognition as some of the more reputable competing institutions possess.  Such competitive forces indicate a strong sense of targeted consumer perceptions, i.e. the student population, and what degree program study focuses should be expected that ultimately fulfills their satisfaction, keeps them enrolled, and promotes the tertiary institution via word-of-mouth advertising. It is this gap in knowledge awareness of the learning institution that limits their ability to effectively plan and budget for the future competitiveness of tertiary education, and therefore calls for research to provide guidance and awareness in navigating this new level of competition.

The aim of this study is to provide a baseline of observances and inherent recommendations that fulfill consumer (student) goals that result in attracting and retaining adequate student enrollment numbers in the face of such significant competition, specifically for the Faculty of Business (FOB) at CityU. More specifically, the aim will utilize this baselines recommendation set providing insight for CityU in the face of the changing business environments and their demands on new graduates with the Covid-19 pandemic altering the business landscape forever.  The Master of Business Administration (MBA) students and Doctor of Business Administration (DBA) students were the primary data population for this study to examine what experiences align with post-graduate expectations of personal career development that CityU is anticipated to help achieve their goals. Through this data analysis, a better comprehension is obtained of what MBA and DBA students’ expectations are compared with their satisfaction level post-graduation in the current- and post-Covid-19 world.  The anticipated outcomes provide the recommendations for how best to revise and update the curriculum, teaching quality, and overall learning environment that grant those consumer expectancies, consequently obtaining of a greater competitive reputation from larger numbers of future satisfied graduates. The benefit to CityU and likeminded institutions, especially in the Greater Bay Area of Hong Kong, Macau, and the Guangdong province, is the establishing of revision and development guidelines post-Covid-19 that builds an attractive brand image of the institution to enhance enrollment, with subsequent benefits in long-term strategic planning efficiency.

1.1 Research Problem

The state of competition for tertiary learning institutions such as CityU takes on new levels of concern as key competitors increase their activities and tactics to capture ‘customers’ (students) in the adult education / higher education market.  Competition among tertiary learning institutions is nothing new to the market (Ishak, 2016; Khan, Zia-ur-Rehman, & Khan, 2016; Migin, Falahat, Yajid, & Khatibi, 2015; Pucciarelli, & Kaplan, 2016), but the influence of technology allowing for greater volumes of information to be obtained by those potential customers affords them the opportunity to compare and contrast higher learning opportunities and make the best choice possible for their personal career expectancies (Collins, & Lewis, 2016; Manzuma-Ndaaba, Harada, Nordin, Abdullateef, & Rahim, 2018; Shahijan, Rezaei, & Guptan, 2018; Wong, Ng, Mak, & Chan, 2016).  While this state of technological development might very well be viewed as a benefit to the student, the results of such tech-savvy ‘customers’ see an increase in competitiveness amongst adult education / higher education institutions that are only in recent times becoming understood and incorporated into institutional marketing strategies (Endo, de Farias, & Coelho, 2019; Hossler, 2015; Parahoo, Santally, Rajabalee, & Harvey, 2016; Pucciarelli, & Kaplan, 2016).  The inherent results of such sourcing opportunities increases the marketing effort and innovativeness of the institution that, ultimately, reduces the spending budget and time needed for such activities and resources for the details outlined in the learning environment and teaching methodology section prior.  The concern is how to progress and grow amidst such stiff competition.

The increased competitive environment demands innovative approaches to marketing the institution to potential customers – students (Badwan, Al Shobaki, Naser, & Amuna, 2017; Kettunen, 2015; Raaper, 2016; Sunder, 2016).  Budget cuts, high staff/faculty turnover, stalled teaching innovativeness, overly saturated market competitors, and an ever-evolving job market leaves such institutions making drastic or radical decisions to try an become more productive and profitable for increased longevity (Bingham, & Solverson, 2016; Bowman, & Culver, 2018; Falcone, 2019; Rizkallah, & Seitz, 2017; Wong, Ng, Mak, & Chan, 2016).  The issues that are of primary concern to the institution include the determination of student satisfaction factors to post-graduation as per expectations, the varying amounts of engagement time necessary, the mode of the study experience, the knowledge acquired, and whether the students’ perspectives are altered between first beginning their program of study against post-completion (Bingham, & Solverson, 2016; Wong, Ng, Mak, & Chan, 2016).

The critical consideration prompting this study is the impact of the current- and post-Covid-19 pandemic is the influence on technology utilization in the learning environment, which inherently impacts the student perception of the brand quality of the tertiary institution and the question or whether said institution can fulfill their career expectations (Code, Ralph, & Forde, 2020; Yan et al., 2021). The pandemic has positively impacted technology usage in the learning environment, but whether or not the tertiary institution can meet customer, student, expectations for their career goals in this technologically-driven market environment draws the need for the study.

1.2 Significance of Research

For CityU, determining the factors of satisfaction of study at the post-graduate level in a Covid-19 radicalized world would align goals of marketing and curriculum development, and especially classroom environment design / revision and teaching methodology improvement, in order to provide a more effective learning medium and graduate gratification outcomes.  The inherent benefit to CityU would then have the consequential outcome of gradually improving the regional reputation of the institution that attracts new customers to the MBA and DBA programs, possibly even the BBA program.  The inevitable further outcome would then be a greater number of retained students as satisfied customers that enables CityU to further revise and develop the FOB degree programs, which serves the ultimate aim to continuously achieve greater customer satisfaction and repeat business (i.e. re-enrollment and word-of-mouth advertising).

Institutions external to CityU will benefit from the study with an increase in the similar impact of benefits for achieving comparable goals and objectives.  As stated already, the increased competitiveness amongst the adult education / higher education institutions demands greater innovation in planning and budgeting in the new Covid-19 world, and this is not only true for CityU, but it is taken to be true for competing institutions based on notions of mutual competitive markets in higher education conducted in other studies (Badwan, Al Shobaki, Naser, & Amuna, 2017; Kettunen, 2015; Raaper, 2016; Sunder, 2016).  While CityU is indeed in competition with such institutions, unlike commercial or industrial competitiveness where industry competitiveness seldom sees cooperative efforts (Chen, Wang, & Chan, 2017; Kamp, & Parry, 2017; Lichtenthaler, 2017; Lii, & Kuo, 2016; Pisano, 2017; Sarturi, Vargas, Boaventura, & Santos, 2016; Vendrell-Herrero, & Wilson, 2017), the educational market is more cooperative since the goals are ultimately related to the overall improvement of the society in question (Becker et al., 2017; Carpenter, 2015; Fitzgerald, Bruns, Sonka, Furco, & Swanson, 2016; Geiger, 2017).  This study provides key and usable data that can be beneficial to many institutions in helping to conduct studies or planning and budgeting efforts that ultimately help the community at large.

2. Review

Factors that influence the satisfaction level of postgraduate students study experience include the following sections on secondary data.

2.1 Student Engagement Time and User Experience Satisfaction

Of significant consideration for curriculum development in any program is the engaging of student / learner participation.  As noted by Buchanan et al. (2016), the results of studies observed in their research indicate a strong relationship between the engagement level inclusive during their education and the required tests and examinations required to obtain higher scoring when completing a particular subject.  Buchanan et al. (2016) concluded that, “The overwhelmingly positive findings on student engagement and academic achievement in the implementation of IBL (i.e. Inquiry Based Learning) models demonstrate its worth as an effective modern day learning model” (pp.25-26).

Barkley (2017) defines student engagement thusly, “Student engagement is a process and a product that is experienced on a continuum and results from the synergistic interaction between motivation and active learning” (p.40).  This concept can be more pointedly refined as the design of a learning environment that promotes self-reliance in critical thinking exercises, with the intended reaction being to give the learner a greater sense of confidence in their own ability to cognitively utilize the information presented to craft a response or solution that has never before been presented in book or lecture, yet effectively resolves the challenge or circumstance.  It is the need to appeal to the adult learner ego that dictates the students’ own efforts in engaging in the classroom that must understood in this definition to comprehend the significance engagement has on the effectiveness of the learning environment that produces qualified graduates (Boucouvalas, 2016; Boydell, 2016; Foote, 2015; Karina, Cecilia, & Sánchez, 2017; Reinerman-Jones, Lameier, Biddle, & Boyce, 2017; Treff, & Earnest, 2016).  As noted by Kim and Baker (2015), the need to develop a fully integrated learning environment for the effect of successful graduates, not just the successful completion of the course, is tied directly to the learners’ self-esteem as they progress through their higher learning experience and gauge the success, career-wise, with their expectations before entering said learning environment.  This is an outcome of having designed the learning environment that addresses the adult learner ego expectations with realistic experiences in the classroom that adequately prepares them for the realities of the business world post-graduation.

A significant consideration is the evaluation by the adult learner into whether or not the learning environment has a value worthiness compared with the expectancies they have with the results of their learning experiences as a reflection on their futures, specifically with their career potential.  In essence, does the degree they have obtained deliver a successful career?  From a traditional teaching perception, this question might appear as a degradation of the college or university learning medium and its intent on producing graduates with self-motivating factors to be successful through their own initiative, for the perception of teaching in the past was to present lectures and examinations as a part of the responsibility of the instructor, with the responsibility of learning being held to the student (Barkley, 2017).  Learner expectancies are driven by the previous learning experiences, the self-confidence gained in success of those previous experiences (or not), and the perception of the challenge that the learning environment has in direct contrast to what is believed to be the chosen career path’s job demands (Barkley, 2017; Boydell, 2016; Reinerman-Jones et al., 2017).  The importance of understanding motivation in comparison with expectancies is vital to the future learning program because it accounts for how the student perceives the learning environment in reflection to their own inadequacies and self-reliance.  As noted by Barkley (2017), “Even a student who has low confidence in his or her ability to learn math, for example, might become more confident with a teacher whose approach to teaching math is supportive and  more in line with his style of learning” (p.44).  The effect of nurturing the learning environment to be more considerate of the adult learner ego has a direct reflection on their ability to achieve scores and grades competitive with the job market post-graduation, determining the satisfaction of the student in obtaining a career that they expected, and the inevitable consequence on the reputation of the learning institution in direct comparison with the satisfaction of that student’s outcomes (Barkley, 2017; Boucouvalas, 2016; Foote, 2015; Kim, & Baker, 2015).

Active learning is the key here. Barkley (2017) states, “to truly learn, we need to take an idea or a concept or a problem solution and make it our own by working it into our personal knowledge and experience” (p.46).  This seems to agree with the editorial work produced by Buchanan, Harlan, Bruce, and Edwards (2016) that examined multiple studies on inquiry based learning models, information literacy, and student engagement.  As an adult learner ego values a challenge that is perceived within their realm of abilities, yet reinforced by empathetic instructors providing support for the self-perceived inadequate abilities, the notion of active learning builds on these perceptions by integrating activities of direct learning objectives of the particular course in question with self-directed research opportunities, collaborative / team-oriented exercises, problem-solving learning practice, and customer-centric service learning for various industries, not only the typical customer-service jobs as with hospitality and tourism (Arnold, 2017; Barkley, 2017; Cranston, & Kusanovich, 2016; Omori, Okon, & Obun, 2019).  The idea is to give the adult learning more varied opportunities at discovery of the prescribed information in a self-driven manner that grants increasing levels of self-actualization and confidence in not only the subject presented, but also in the overall learning institution (Khalil, & Elkhider, 2016; Lee, & Hannafin, 2016; Sogunro, 2015).  Multiple techniques have been in use by colleges and universities around the world for decades (Kokotsaki, Menzies, & Wiggins, 2016; Waldrop, 2015), and include such activities as mitten discussion, opinion line-up, sticky note clustering, dotmocracy, fishbowl, cumulative brainstorming, crowdsourcing, structured debates, one-minute reflections, etc. (Chang, Hung, & Lin, 2015; Freeman et al., 2014; Hung, 2015; Jensen, Kummer, & Godoy, 2015; Lumpkin, Achen, & Dodd, 2015; Wanner, & Palmer, 2015).

2.2 Study Mode of the Postgraduate Program in Macau

The lack of studies conducted on education and study behavior in the Greater Bay Region of Hong Kong, Macau, and the Guangdong province region demonstrates a strategic undervaluation in the perceived importance of curriculum revision and teaching development. Of the available studies in the region, Wei (2019) notates that there does not seem to be a standard that all institutions follow.  The reliance on programs, books, and systems outside of the area, indeed outside of China altogether, draws a critical evaluation of the standards employed in the education in the region for validity and success assessment compared to student expectations (Hao, 2016; Wei, 2019; Yu, 2019; Yu, Zhang, Zheng, Yuan, & Zhang, 2019).  The overall effect is noted as being more passive learning that is devoid of genuine learner engagement at the adult ego level (Boydell, 2016; Karina, Cecilia, & Sánchez, 2017; Hung, 2015); Kim, & Baker, 2015; Omori, Okon, & Obun, 2019; Waldrop, 2015).

2.3 Knowledge Acquisition Motive and User Experience Satisfaction

 A study conducted for the Hong Kong area by Law, Hills, and Hau (2017) notes that the level of commitment by the institution is critical to the motivation of the adult learner, and thereby the satisfaction outcome of said learner.  The study suggests that once learners are exposed to varying factors of integrability of the gained knowledge into realistic career potential scenarios, the learner showed more interest and more participation in the learning activities.  Bauer, Orvis, Ely, and Surface (2016) note that an adult learner that is given the opportunity to test themselves against real-world scenarios where the applicability of the knowledge being exercised is a key to maintaining the relationship between personal motivation for the learning experience.  Studies by Al-Rahmi, Othman, and Yusuf (2015), Carriger (2015), Kuo, Belland, and Kuo (2017), Kurkul, and Corriveau (2018), and Schmalhofer (2019) confirm it is an opportunity for the learner to not only evaluate their skills and abilities into their chosen career path from a pragmatic perspective, but to also gain a greater sense of pride and accomplishment that ultimately leads to increased self-reliance and confidence levels with their future ability to cope with the perceived demands of the chosen career.

2.4 Legitimate Peripheral Participation (LPP)

Legitimate Peripheral Participation (LPP) is a research technique designed to give researchers a social comparative model between participant quantitative and qualitative responses, while removing as many bias obstacles as possible in the assessment of the relationship those two opposite sides of responsiveness might have in cross-comparison (Consalvo, Schallert, & Elias, 2015; Woo, 2015; Viteritti, 2015).  From the perspective of using LPP in assessing student engagement time and knowledge acquisition motive from a satisfaction perspective, the studies are unanimously in favor of such a model for adult learner motivations and expectancies.  Lave and Wenger’s (1991) seminal work on the LPP model is the standard to which the methodology is based by numerous studies of a similar assessment of learner motivation and satisfaction analyses (Bunting, 2019; Consalvo, Schallert, & Elias, 2015; Eberle, Stegmann, & Fischer, 2015; Rådesjö, 2018; Park, 2015; Viteritti, 2015; Woo, 2015; Yim, & youn Ahn, 2018).  Most of the reviewed studies indicated LPP was ideal in the original format presented by Lave and Wenger (Bunting, 2019; Yim, & youn Ahn, 2018; Woo, 2015; Viteritti, 2015).  Some studies like Park (2015) suggest revisions to LPP are necessary to encompass larger numbers of activities in the learning environment that are not contained in the original LPP concept.  Other studies suggest revisions are necessary to accommodate the variations in culture regarding learning habits and assessments, as well as cultural differences in career expectancies (Evans, 2019; Pavlik, 2015; Young, Hoffman, & Frakes, 2019).

2.5 The Covid-19 Factor

The impact on tertiary education from the Covid-19 pandemic, especially in regards to the technological demands and revisions inherent to teaching methodologies, is a direct effect on student engagement in the learning environment, the students’ sense of satisfaction of learning mediums, and the ultimate assessment of students’ goals on the career aspirations (Code, Ralph, & Forde, 2020; Dwivedi et al., 2020; Yang, & Huang, 2021). Technology demands both in hardware and software has placed new transitioning strategies on tertiary education institutions from less face-to-face lesson planning to more digital presentations, and therefore impact the cost efficiency planning and qualified instructors in utilizing these new technological learning environments (Han, Zhou, Shi, & Yang, 2021; Rasiah, Kaur, & Guptan, 2020; Yan, 2021). Such factors do not have existing literature in great abundance, though it is gathering at the moment, in guiding tertiary institutions into navigating this competitive environment where technologically-savvy consumers and existing hardware/software are coming into direct conflict in traditional learning mediums.

The factors needing attention for effective Covid-19 impact planning include an assessment of the tertiary institutions present technological provisions, the current faculty’s technical capabilities, and the access to obtaining the necessary hardware and software for fulfilling student expectations (Dwivedi et al., 2020; Rasiah, Kaur, & Guptan, 2020). This says nothing about whether the technological infrastructure of the physical location can even support such demands, where in mainland China where the majority of CityU students hail from, have significant I.T. infrastructure support issues to sufficiently provide a reliable educational experience when distance learning was required in 2020 (Han, Zhou, Shi, & Yang, 2021; Yang, & Huang, 2021).

While the Greater Bay Area of Hong Kong, Macau, and the Guangdong province performed well during the 2020 lockdown period (Yang, & Cao, 2021), the problem was in establishing reliable connections via distance learning with the student base located in various parts of the mainland, whose server access and internet connectivity was questionable a greater majority of the time. These harsh realities are some of the more significant contributing factors to student graduate satisfaction and the impact on their perception of the institution to adequately prepare them for their future careers.

3. Research Questions

The first question takes an analysis of the student’s perception on the general experience in the program. The resulting question formatted for this correlation measurement is as follows:

R1: Study Mode and Program Experience Satisfaction: Has the mode of study (i.e. MBA day classes, MBA night classes, and DBA programs) experience impacted the students’ satisfaction level and their retention motivation?

H10: There is no significant difference in the mode of study and the students’ satisfaction level and their retention motivation.

H1a: There is a significant difference in the mode of study and the students’ satisfaction level and their retention motivation.

As per the LPP framework, the second research question was a measurement of the students’ perceptions compared against the query in R1:

R2: Career Plan and Program Experience Satisfaction: Has the mode of study (i.e. MBA day classes, MBA night classes, and DBA programs) experience impacted the students’ satisfaction level in achieving personal career development goals and objectives?

H20: There is no significant difference the mode of study and the students’ satisfaction level in achieving personal career development goals and objectives.

H2a: There is a significant difference the mode of study and the students’ satisfaction level in achieving personal career development goals and objectives.

To be thorough, the assessment of the role that gender plays on the perception of the participants was called for and evaluated against the responses for determining if a particular gender had greater or lesser levels of satisfaction.  This called for a third question to be developed:

R3: Role of Gender on Satisfaction: Does the identification of gender have an impact on the perceptions of students for satisfaction and career development?

H30: There is no significant impact from gender on the perceptions of students for satisfaction and career development.

H3a: There is a significant impact from gender on the perceptions of students for satisfaction and career development.

            The final question assessed focused another query on one of the more significant and impactful aspects the LPP framework, that of the variances in customer perceptions over specific periods of time in relevant work experience relational to their chosen degree program(s) of study.  The survey presented to all participants included the designation of the status of the student, being either considerable amount of work experience compared with participants with less work experience.  The question generated is as follows:

R4: Prior Work Experience: Does the difference between participants with a considerable amount of work experience compared with participants with less work experience have a significant impact on student perspectives of satisfaction leading to retention motivation?

H40: There is no significant difference between participants with a considerable amount of work experience compared with participants with less work experience have a significant impact on student perspectives of satisfaction leading to retention motivation.

H4a: There is a significant difference between participants with a considerable amount of work experience compared with participants with less work experience have a significant impact on student perspectives of satisfaction leading to retention motivation.

4. Research Methodology

The study is a quantitative correlational examination of consumer response factors for satisfaction on learning experiences in connection to career objectives. The objective of this study is to learn about student experiences and expectations for studying an MBA / DBA at a private university, specifically the City University of Macau. The Student Satisfaction and Perceptions of Efficacy (Vamosi, Pierce, & Slotkin, 2004) 5-point Likert scale, with 1 = low and 5 = high, was utilized to gauge student’s satisfaction level to the experience in the program in direct correlation to the expectancies of their career aspirations.

Thirteen aspects were measured: study plan of the program, coverage of recent trends in your field, quality of learning materials, study workload expected by professors, quality of faculty professors, access to faculty professors, engagement and interactions in the class, knowledge and skills learned, opportunities for networking with industry, administration service support, class schedule, adequacy of space, facilities and equipment, and dissertation guidance and supervision. Demographic questions were used including gender, career plan, the program they are studying, program commencement year, and years of prior work experience simply to determine participant eligibility. Analysis of collected data utilized Cronbach’s α for reliability of measurements between programs of study and participant demographics against the perceived satisfaction rating, as well as ANOVA for validity confirmation between measured data sets.

5. Data Sources

5.1 Participant Rights and Protection

The survey was completed anonymously, and all participant personal and response data is kept confidential.  Selected participate candidates were informed of their anonymity, as well as being informed of their full liberty to choose to not respond if such is their wish, and none of the data collected will be used for any other purpose than the purposes of this study.

5.2 Demographics

The study utilized an online questionnaire distributed via social media to 394 postgraduate students in CityU’s FOB. Of the total number of surveys distributed, 315 returns were collected: 83.2% from the full-time MBA program, 5.4% from the part-time MBA program, and 11.4% from the DBA program, with a total representation of a 79.9% response rate.  Of those responses, 63.5% of had appropriate work experience before taking the post-graduate program (see Table 1).

Demographics

6. Findings & Discussion

            Multiple testing was used via SPSS 21.0 for both reliability and validity of analyses outcomes. Reliability tests were conducted using a Cronbach’s α value for program satisfaction, and resulting with a 0.962 value, which is well above the 0.70 baseline (see Table 2). This implies that all items in the scale possessed a strong internal reliability.

Table 2

Cronbach’s α Test for Reliability.

Cronbach’s α

Based on standardized Cronbach’s α projections

Items

0.962

0.963

13

 

The specific 13-item statistics were also gauged for discriminate validity (see Table 3).

Table 3

Table 4 shows the mean scores and standard deviations for each group of participants; full-time MBA, part-time MBA, and full-time DBA.

Table 4

Mean scores and standard deviations (SD)

Table 4

6.1 Findings for R1: Study Mode and Program Experience Satisfaction

A one-way ANOVA test was used to examine the students’ correlational differences on the effect of study mode on their program experience satisfaction level. The program the student studied in was assigned as the dependent variable, with all thirteen program experience items assigned as independent variables (see Table 5). Results show that students in a different study mode demonstrated a significant satisfaction difference in a few areas:

  • Access to faculty professors (F(df = SSB:2/SSW:312) = 5.124, p < 0.01)
  • Opportunities for networking with industry (F(df = SSB:2/SSW:312) = 3.707, p < 0.05)
  • Administration service support (F(df = SSB:2/SSW:312) = 6.275, p < 0.01)
  • Adequacy of space, facilities and equipment (F(df = SSB:2/SSW:312) = 5.563, p < 0.01)

Table 5

6.2 Findings for R2: Career Plan and Program Experience Satisfaction

The correlation for career plan and program experience satisfaction utilized the one-way ANOVA was used to examine the effect of students’ career plan on the satisfaction to each item of the program experience (see Table 6). The career plan was the dependent variable, all program experience items were independent variables. Results show that students with different career plans demonstrate a significant satisfaction difference in few areas:

  • Coverage of recent trends in your field (F(df = SSB:5/SSW:309) = 4.159, p < 0.01)
  • Study workload expected by professors (F(df = SSB:5/SSW:309) = 2.640, p < 0.05)
  • Quality of faculty professors (F(df = SSB:5/SSW:309) = 3.460, p < 0.01)
  • Access to faculty professors (F(df = SSB:5/SSW:309) = 2.505, p < 0.05)

Table 6

ANOVA for Career Plan and Program Experience Satisfaction

6.3 Findings for R3: Role of Gender on Satisfaction

Independent t-test sampling was used to examine the difference in program satisfaction between males and females (see Table 7). However, there was no evidence indicating that there was a significant difference between genders and is simply eliminated from further consideration.

Table 7

6.4 Findings for R4: Prior Work Experience

Independent t-test sampling also was used to examine the effect of work experience on the program experience satisfaction (see Table 8). The work experience was the dependent variable, and all program experience items were the independent variables. Results indicate that there is no real statistical difference in participant pre-work experience and their level of satisfaction, and therefore no real impact on the intention for re-enrolling in the institution as adherent to CityU’s determination of foreseeable retention rates.

Table 8

Satisfaction of program experience across postgraduate students with work experience

Table 8

7. Conclusions and Recommendations

The revelations of R1: Study Mode and Program Experience Satisfaction showed that, collectively, there was a slightly significant difference in the satisfaction of overall program experience between full-time MBA students and part-time MBA students (MFT = 3.99, MPT = 3.56, t = 3.769, p < 0.01). Yet, there was no significant satisfaction difference for full-time MBA and full-time DBA students (MMBA = 3.99, MDBA = 4.00, t = -.070, p > 0.05). Or, another way to view the results is as the sample sizes were quite different across groups (full-time MBA: 262, part-time MBA: 17, full-time DBA: 36), so a Hochberg’s GT2 test was used in SPSS post-hoc and confirmed the indication that there is still no significant difference between the satisfaction level of the overall program experience between each participant group (MFT = 3.99, MPT = 3.56, t = 3.769, p < 0.01).

7.1 R1 Baseline Recommendation

The inferred outcome of R1 on the impact of student satisfaction with their experience in their degree program can be that overall program was of sufficient experience for their post-graduate expectations, with only minor deviations in satisfaction in access to faculty professors, opportunities for networking with industry, administration service support, and adequacy of space, facilities and equipment. Inherently, the results confirm to accept the H1a and reject the H10 in that there is indeed a significant impact of the mode of study, namely a positive impact of the MBA day classes program and the DBA program as compared against the negative impact of the MBA night classes program, which ultimately affects student retention rates. The outcome therefore suggests the identified items of study mode should be improved specifically for the MBA night classes program more than any other.

It is with the R2: Career Plan and Program Experience Satisfaction results that showed a more noticeable significant difference between student’s career plan in the satisfaction of overall program experience (F(df = SSB:5/SSW:309) = 2.747, p < 0.05). Students who plan to proceed further study have higher satisfaction than the students who plan to work as a civil servant after graduation (MFUR = 4.18, MGOV = 3.65, p < 0.05). To further illuminate these satisfaction levels with the subsequent impact from occupational influence, a separate t-test was conducted to investigate the satisfaction to each aspect of program experience between these two groups of participants. Results show that there was a significant difference in eight of the thirteen item aspects of the program:

Table 9

7.2 R2 Baseline Recommendation

The implied recommendations for CityU’s future recruitment efforts for R2 focus on the improvement of the curriculum to be more reflective of industry needs, especially in the wake of the Covid-19 pandemic effects, and are evidentiary considering the negativity of the outcomes. Specifically, the study plan is indicative of being outmoded with current and future pandemic demands, as confirmed by the related coverage recent trends that was also divergent with satisfactory levels. Likewise, the study workload, the quality of faculty, the access to faculty professor, and the knowledge and skills imparted are deemed insufficient and are recommended for revision to provide more face-to-face interaction (or digital in pandemic considerations if applicable), but less self-study work that inherently promotes more interaction with students. Whether or not the individual faculty professors can find that much time to provide such customized services with the majority of students remains to be seen given the overloaded classroom size as-is. And, in the end, the students’ dissatisfaction with the arrangement of the class schedules and the adequacy of space, facilities, and equipment suggest more attention should be provided to procurement of greater facilities, such as additional classrooms to alleviate the class scheduling problem, and adequate funding to refurbish and enhance the physical learning environment to reflect the professionalism expected of a proper graduate studies program. The final conclusion is that the H1a must be accepted and the H10 must be rejected, in that all three modes of study (i.e. MBA day classes, MBA night classes, and the DBA programs) have a large significance on the impact of satisfaction levels that lead to student retention, and therefore constitute the bulk of revision efforts of CityU to improve the quality of learning experience to meet target consumer (student) career expectations.

Findings for R3: Role of Gender on Satisfaction and for R4: Prior Work Experience did not reveal any significant differences among any demographic groups. This essentially confirms the hypothesis that gender and prior work experience have no relevant impact on satisfaction levels for programs of study in graduate business programs. Consequently, there are no institutional recommendations that can be made for CityU in the improvement of their student recruitment efforts based on appealing to their career expectations.

8. Recommendations

The Covid-19 pandemic has made a significant impact on the current and future tertiary education industry that demands further research, but even without the pandemic effects the need for revising graduate programs of study is of paramount importance to any higher education institution. This study has confirmed that the study mode issues of study plan of the program, coverage of recent trends, study workload expected by professors, quality of faculty professors, access to faculty professors, knowledge and skills learned, class schedule, and the adequacy of space, facilities, and equipment are the key criteria for improvement. This is even more significant to a region as unique as the Greater Bay Area of Hong Kong, Macau, and the Guangdong province that combine international learning environments with traditional Chinese and Portuguese cultures. The inference, therefore, for future research studies is that attention should be paid particular interest in similar issues of study mode for institutions that are either within the same Greater Bay Area, or are in areas with similar cultural imperatives mixed with internationalized socio-cultural factors. For tertiary institutions not of similar background, it is recommended that future studies focus on similar attributes as the thirteen items for study mode utilized in this study, but adapted to whatever socio-cultural imperatives might influence target consumer (student) perceptions and their assessment of satisfactory indicators leading to student retention rates.

Author: Dr. Jason Lee Carter

Co-authors: Dr. Kin Yan Ho, Dr. Chia Wei Chu

Bibliography

9. References

Al-Rahmi, W. M., Alias, N., Othman, M. S., Marin, V. I., & Tur, G. (2018). A model of factors affecting learning performance through the use of social media in Malaysian higher education. Computers & Education, 121, 59-72.

Al-Rahmi, W. M., Othman, M. S., & Yusuf, L. M. (2015). Exploring the factors that affect student satisfaction through using e-learning in Malaysian higher education institutions. Mediterranean Journal of Social Sciences, 6(4), 299.

Arnold, R. (2017). Learning and Teaching in Adult Education. Researches in Adult Learning and Education: The European Dimension, 6, 43.

Badwan, J. J., Al Shobaki, M. J., Naser, S. S. A., & Amuna, Y. M. A. (2017). Adopting technology for customer relationship management in higher educational institutions. International Journal of Engineering and Information Systems, 1(1), 20-28.

Barkley, E. F. (2017). Terms of Engagement: Understanding and Promoting Student Engagement in Today’s College Classroom. Deep Active Learning, 35–57. DOI: 10.1007/978-981-10-5660-4_3

Bauer, K. N., Orvis, K. A., Ely, K., & Surface, E. A. (2016). Re-examination of motivation in learning contexts: Meta-analytically investigating the role type of motivation plays in the prediction of key training outcomes. Journal of Business and Psychology, 31(1), 33-50.

Becker, S. A., Cummins, M., Davis, A., Freeman, A., Hall, C. G., & Ananthanarayanan, V. (2017). NMC horizon report: 2017 higher education edition. pp. 1-60. The New Media Consortium. Retrieved from https://www.sconul.ac.uk/sites/default/files/documents/2017-nmc-horizon-report-he-EN.pdf

Bingham, M. A., & Solverson, N. W. (2016). Using enrollment data to predict retention rate. Journal of Student Affairs Research and Practice, 53(1), 51-64.

Boucouvalas, M. (2016). Toward transpersonal adult development. Adult Learning, 27(1), 30-37.

Bowman, N. A., & Culver, K. C. (2018). When do honors programs make the grade? Conditional effects on college satisfaction, achievement, retention, and graduation. Research in Higher Education, 59(3), 249-272.

Boydell, T. (2016). Facilitation of adult development. Adult Learning, 27(1), 7-15.

Buchanan, S., Harlan, M. A., Bruce, C. S., & Edwards, S. L. (2016). Inquiry based learning models, information literacy, and student engagement: A literature review. School Libraries Worldwide, 22(2), 23-39.

Bunting, B. D. (2019). Peer leaders as full participants in the academic work of the institution. Journal of Peer Learning, 12(1), 1-4.

Carpenter, D. (2015). School culture and leadership of professional learning communities. International Journal of Educational Management, 29(5), 682-694.

Carriger, M. S. (2015). Problem-based learning and management development–Empirical and theoretical considerations. The International Journal of Management Education, 13(3), 249-259.

Chang, R. I., Hung, Y. H., & Lin, C. F. (2015). Survey of learning experiences and influence of learning style preferences on user intentions regarding MOOCs. British Journal of Educational Technology, 46(3), 528-541.

Chen, X., Wang, X., & Chan, H. K. (2017). Manufacturer and retailer coordination for environmental and economic competitiveness: A power perspective. Transportation Research Part E: Logistics and Transportation Review, 97, 268-281.

Code, J., Ralph, R., & Forde, K. (2020). Pandemic designs for the future: Perspectives of technology education teachers during COVID-19. Information and Learning Sciences, 121(5/6), 419-431. https://doi.org/10.1108/ILS-04-2020-0112

Collins, F. L., & Lewis, N. (2016). New Zealand universities: the prospects and pitfalls of globalizing higher education. In The Palgrave Handbook of Asia Pacific Higher Education (pp. 597-613). New York, USA: Palgrave Macmillan.

Consalvo, A. L., Schallert, D. L., & Elias, E. M. (2015). An examination of the construct of legitimate peripheral participation as a theoretical framework in literacy research. Educational Research Review, 16, 1-18.

Cranston, J., & Kusanovich, K. (2016). Setting the Stage. In Ethnotheatre and Creative Methods for Teacher Leadership (pp. 7-16). New York, USA: Palgrave Macmillan.

Dwivedi, Y. K., Hughes, D. L., Coombs, C., Constantiou, I., Duan, Y., Edwards, J. S., ... & Upadhyay, N. (2020). Impact of COVID-19 pandemic on information management research and practice: Transforming education, work and life. International Journal of Information Management, 55, 102211. https://doi.org/10.1016/j.ijinfomgt.2020.102211

Eberle, J., Stegmann, K., & Fischer, F. (2015). Moving beyond case studies: applying social network analysis to study learning-as-participation. Learning: Research and Practice, 1(2), 100-112.

Endo, A. C. B., de Farias, L. A., & Coelho, P. S. (2019). Service branding from the perspective of higher education administrators. Marketing Intelligence & Planning, 37(4), 401-416.

Evans, M. (2019). Doing it for real: A study of experiential and situated learning approaches in teaching journalism practice. Journalism Education, 8(1), 49-58.

Falcone, S. (2019). International student recruitment: Trends and challenges. Journal of International Students, 7(2), 246-256.

Fitzgerald, H. E., Bruns, K., Sonka, S. T., Furco, A., & Swanson, L. (2016). The centrality of engagement in higher education. Journal of Higher Education outreach and engagement, 20(1), 223-244.

Foote, L. S. (2015). Transformational learning: Reflections of an adult learning story. Adult Learning, 26(2), 84-86.

Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, 111(23), 8410-8415.

Geiger, R. L. (2017). To advance knowledge: The growth of American research universities, 1900-1940. pp. 110-115. London, UK: Routledge, Taylor and Francis Publishing Group.

Han, X., Zhou, Q., Shi, W., & Yang, S. (2021). Online Learning in Vocational Education of China during COVID-19: Achievements, Challenges, and Future Developments. Journal of Educational Technology Development and Exchange (JETDE), 13(2), 61-82. https://doi.org/10.18785/jetde.1302.06

Hao, Z. (2016). In search of a professional identity: higher education in Macau and the academic role of faculty. Higher Education, 72(1), 101-113.

Hossler, D. (2015). Origins of strategic enrollment management. Handbook of Strategic Enrollment Management, 3-17. New Jersey, USA: John Wiley & Sons.

Hung, H. T. (2015). Flipping the classroom for English language learners to foster active learning. Computer Assisted Language Learning, 28(1), 81-96.

Ishak, K. (2016). A factor analysis approach towards a study of the factors affecting students’ choice of higher education institution: A case study of a private institution (Twintech International University College of Technology). Journal of Social Economics Research, 3(2), 21-30.

Jensen, J. L., Kummer, T. A., & Godoy, P. D. D. M. (2015). Improvements from a flipped classroom may simply be the fruits of active learning. CBE—Life Sciences Education, 14(1), ar5.

Kamp, B., & Parry, G. (2017). Servitization and advanced business services as levers for competitiveness. Industrial Marketing Management, 60, 11-16.

Karina, L. C. R., Cecilia, M. H. R., & Sánchez, F. (2017, April). Comparative analysis of learner interactions in flipped and traditional classes using social network analysis. In 2017 Fourth International Conference on eDemocracy & eGovernment (ICEDEG) (pp. 234-239). IEEE.

Kettunen, J. (2015). Stakeholder relationships in higher education. Tertiary Education and Management, 21(1), 56-65.

Khalil, M. K., & Elkhider, I. A. (2016). Applying learning theories and instructional design models for effective instruction. Advances in Physiology Education, 40(2), 147-156.

Khan, M. M., Zia-ur-Rehman, C., & Khan, S. S. (2016). Factors influencing students’ choice of private college/university in Pakistan. New Horizons, 10(2), 69.

Kim, K. N., & Baker, R. M. (2015). The assumed benefits and hidden costs of adult learners’ college enrollment. Research in Higher Education, 56(5), 510-533.

Kokotsaki, D., Menzies, V., & Wiggins, A. (2016). Project-based learning: A review of the literature. Improving Schools, 19(3), 267-277.

Kuo, Y. C., Belland, B. R., & Kuo, Y. T. (2017). Learning through blogging: Students’ perspectives in collaborative blog-enhanced learning communities. Journal of Educational Technology & Society, 20(2), 37-50.

Kurkul, K. E., & Corriveau, K. H. (2018). Question, explanation, follow‐up: A mechanism for learning from others?. Child Development, 89(1), 280-294.

Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. pp. 31-32. Cambridge, England: Cambridge University Press.

Law, M. M. S., Hills, P., & Hau, B. C. H. (2017). Engaging employees in sustainable development–a case study of environmental education and awareness training in Hong Kong. Business Strategy and the Environment, 26(1), 84-97.

Lee, E., & Hannafin, M. J. (2016). A design framework for enhancing engagement in student-centered learning: Own it, learn it, and share it. Educational Technology Research and Development, 64(4), 707-734.

Lichtenthaler, U. (2017). Shared value innovation: linking competitiveness and societal goals in the context of digital transformation. International Journal of Innovation and Technology Management, 14(04), 175-180.

Lii, P., & Kuo, F. I. (2016). Innovation-oriented supply chain integration for combined competitiveness and firm performance. International Journal of Production Economics, 174, 142-155.

Lumpkin, A., Achen, R. M., & Dodd, R. K. (2015). Student perceptions of active learning. College Student Journal, 49(1), 121-133.

Manzuma-Ndaaba, N., Harada, Y., Nordin, N., Abdullateef, A., & Rahim, A. (2018). Application of social exchange theory on relationship marketing dynamism from higher education service destination loyalty perspective. Management Science Letters, 8(10), 1077-1096.

Migin, M. W., Falahat, M., Yajid, M. S. A., & Khatibi, A. (2015). Impacts of institutional characteristics on international students' choice of private higher education institutions in Malaysia. Higher Education Studies, 5(1), 31-42.

Omori, A., Okon, A., & Obun, M. (2019). Instructional Strategy and Teacher-student Relationships as Predisposing Variables of Adult Students’ Learning Interest in the Universities. International Journal of Innovation Education and Research, 7(5), 123-132.

Parahoo, S. K., Santally, M. I., Rajabalee, Y., & Harvey, H. L. (2016). Designing a predictive model of student satisfaction in online learning. Journal of Marketing for Higher Education, 26(1), 1-19.

Park, J. Y. (2015). Student interactivity and teacher participation: An application of legitimate peripheral participation in higher education online learning environments. Technology, Pedagogy and Education, 24(3), 389-406.

Pavlik, J. V. (2015). Fueling a third paradigm of education: The pedagogical implications of digital, social and mobile media. Contemporary Educational Technology, 6(2), 113-125.

Pisano, G. P. (2017). Toward a prescriptive theory of dynamic capabilities: connecting strategic choice, learning, and competition. Industrial and Corporate Change, 26(5), 747-762.

Pucciarelli, F., & Kaplan, A. (2016). Competition and strategy in higher education: Managing complexity and uncertainty. Business Horizons, 59(3), 311-320.

Raaper, R. (2016). Academic perceptions of higher education assessment processes in neoliberal academia. Critical Studies in Education, 57(2), 175-190.

Rådesjö, M. (2018). Learning and growing from ‘communities of practice’: Autoethnographic narrative vignettes of an aspiring educational researcher’s experience. Reflective Practice, 19(1), 68-80.

Rasiah, R., Kaur, H., & Guptan, V. (2020). Business continuity plan in the higher education industry: University students’ perceptions of the effectiveness of academic continuity plans during COVID-19 pandemic. Applied System Innovation, 3(4), 51. https://doi.org/10.3390/asi3040051

Reinerman-Jones, L., Lameier, E., Biddle, E., & Boyce, M. W. (2017). Informing the long-term learner model: motivating the adult learner (Phase 1) (No. ARL-TR-8160). US Army Research Laboratory Aberdeen Proving Ground United States. Retrieved from https://www.arl.army.mil/arlreports/2017/technical-report.cfm?id=7991

Rizkallah, E. G., & Seitz, V. (2017). Understanding student motivation: A key to retention in higher education. Scientific Annals of Economics and Business, 64(1), 45-57.

Sarturi, G., Vargas, C. A. F., Boaventura, J. M. G., & Santos, S. A. D. (2016). Competitiveness of clusters: A comparative analysis between wine industries in Chile and Brazil. International Journal of Emerging Markets, 11(2), 190-213.

Schmalhofer, F. (2019). Constructive knowledge acquisition: A computational model and experimental evaluation. London, UK: Routledge, Taylor and Francis Publishing Group.

Shahijan, M. K., Rezaei, S., & Guptan, V. P. (2018). Marketing public and private higher education institutions: A total experiential model of international student’s satisfaction, performance and continues intention. International Review on Public and Nonprofit Marketing, 15(2), 205-234.

Sogunro, O. A. (2015). Motivating factors for adult learners in higher education. International Journal of Higher Education, 4(1), 22-37.

Sunder, M. V. (2016). Constructs of quality in higher education services. International Journal of Productivity and Performance Management, 65(8), 1091-1111.

Treff, M. E., & Earnest, S. E. (2016). Intentionally developmental teaching: Applying process tools for adult learner development. Adult Learning, 27(1), 16-22.

Vamosi, A. R., Pierce, B. G., & Slotkin, M. H. (2004). Distance learning in an accounting principles course: Student satisfaction and perceptions of efficacy. Journal of Education for Business, 79(6), 360-366. https://doi.org/10.3200/JOEB.79.6.360-366

Vendrell-Herrero, F., & Wilson, J. R. (2017). Servitization for territorial competitiveness: Taxonomy and research agenda. Competitiveness Review: An International Business Journal, 27(1), 2-11.

Viteritti, A. (2015). Practice-Based Learning of Novices in Higher Education: Legitimate Peripheral Participation (LPP) Revisited. In Practice-based Learning in Higher Education (pp. 127-140). Berlin, Germany: Springer, Dordrecht.

Waldrop, M. M. (2015). The science of teaching science. Nature, 523(7560), 272.

Wanner, T., & Palmer, E. (2015). Personalising learning: Exploring student and teacher perceptions about flexible learning and assessment in a flipped university course. Computers & Education, 88, 354-369.

Wei, B. (2019). Science teacher education in Macau: a critical review. Asia-Pacific Science Education, 5(1), 10.

Wong, P., Ng, P. M., Mak, C. K., & Chan, J. K. (2016). Students’ choice of sub-degree programmes in self-financing higher education institutions in Hong Kong. Higher Education, 71(4), 455-472.

Woo, D. (2015). Central practitioners’ developing legitimate peripheral participation in a community of practice for changing schools. Australasian Journal of Educational Technology, 31(2). DOI: https://doi.org/10.14742/ajet.314

Yan, L., Whitelock-Wainwright, A., Guan, Q., Wen, G., Gašević, D., & Chen, G. (2021). Students’ experience of online learning during the COVID-19 pandemic: A province-wide survey study. British Journal of Education Technology, 10(1), 1-20. https://doi.org/10.1111/bjet.13102

Yang, B., & Huang, C. (2021). Turn crisis into opportunity in response to COVID-19: experience from a Chinese University and future prospects. Studies in Higher Education, 46(1), 121-132. https://doi.org/10.1080/03075079.2020.1859687

Yang, Z., & Cao, Y. (2021). Development of International Education Industry in the Guangdong–Hong Kong–Macao Greater Bay Area. Journal of Contemporary Educational Research, 5(1), 92-98. https://doi.org/10.26689/jcer.v5i1.1811

Yim, S. Y., & youn Ahn, T. (2018). Teaching English in a foreign country: Legitimate peripheral participation of a native English-speaking teacher. System, 78, 213-223.

Young, D. G., Hoffman, D. E., & Frakes Reinhardt, S. (2019). An exploration of the connection between participation in academic peer leadership experiences and academic success. Journal of Peer Learning, 12(1), 45-60.

Yu, S. (2019). Learning from giving peer feedback on postgraduate theses: Voices from Master's students in the Macau EFL context. Assessing Writing, 40, 42-52.

Yu, S., Zhang, Y., Zheng, Y., Yuan, K., & Zhang, L. (2019). Understanding student engagement with peer feedback on master’s theses: A Macau study. Assessment & Evaluation in Higher Education, 44(1), 50-65.

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