Annals of Educational Research and Reviews

Research Article - (2022) Volume 10, Issue 1

Where is the Malawian higher education heading? A call to the former glory and a more visible and internationalized higher education system
Lazarus Obed Livingstone Banda1*, Jane Thokozani Banda2, George N. Chidimba Munthali3, Colleen Mbughi4, Helex Kayembe5, Peter Ngulube6 and Rabson Madi7
1Department of Education, Beijing Institute of Technology, Kanengo, Lilongwe, Malawi
2Department of Education, Directorate of Higher Education, Lilongwe, Malawi
3Department of Finance, University of Chidimbah Research Centre, Luwinga Mzuzu, Malawi
4Departments of Geography and Earth Sciences, University of Yangtze, Zomba, Malawi
5Department of Finance, University of Mzuzu, Luwinga Mzuzu, Malawi
6Department of Biological Sciences and Immunology, University of Malawi Science and Technology, Ndata Estate, Thyolo, Malawi
7Department of Education, Directorate of Basic Education, Capitol Hill, Lilongwe, Malawi
*Correspondence: Lazarus Obed Livingstone Banda, Department of Education, Beijing Institute of Technology, Kanengo, Lilongwe, Malawi,

Received: 16-Mar-2022, Manuscript No. AERR-22-57546; Editor assigned: 21-Mar-2022, Pre QC No. AERR-22-57546 (PQ); Reviewed: 04-Apr-2022, QC No. AERR-22-57546; Revised: 11-Apr-2022, Manuscript No. AERR-22-57546 (R); Published: 21-Apr-2022, DOI: 10.51268/ 2736-1888- 22.10.133


Aim: This study investigated the intentions, opportunities, and barriers to engaging in a meaningful internationalization of higher education in Malawi, once a global player, to reposition itself on the global stage.

Methods: This cross-sectional research was done between June and October 2021. Using a stratified sampling technique, we recruited 202 respondents from various higher education institutions in Malawi. Multi linear regression analysis was used to analyse the factors with the P-value set at 0.05 level of statistical significance.

Results: The results indicated that most respondents were males (63.7%) who fell into 30 years age bracket. Further, the results from the multi linear regression analysis indicate that Institutional collaboration (ß=0.326, p=0.000, CI=0.27- 0.383), clear Policy on Mobility (ß=0.146, p=0.0.004, CI=0.047-0.246), experience (ß=0.083, p=0.117, CI=-0.021-0.186), academic rank (ß=0.114, p=0.000, CI=0.069-0.159) were positively statistically significant variables, whereas on the other hand, Occupation (ß=-0.131, p=0.002, CI=-0.213-0.49), academic qualification (ß=-0.106, p=0.013, CI=-0.19-0.023 and mobility Importance (ß=- 0.116, p=0.022, CI=-0.215-0.017) were negatively significant variables respectively.

Conclusion and Recommendations: institutions need to invest in international and inter-institutional collaboration, clarify policy direction regarding academic mobility, keep track and linkages with mobile faculty, create a conducive social and formal institutional culture that attracts back mobile faculty, and reduce staff turnover. The study awakes African higher education systems to their former glory to align themselves with Sustainable Development Goals (2030) alongside Agenda 2063.


Academic mobility, Higher education, Malawi education system, Academic inbreeding, Teaching incest.


The number of mobile students has been increasing drastically. Increasingly more students want to study outside their home countries at universities that rank highly (Robert Morse and Juan Vega-Rodriguez, 2020). Therefore, making institutions visible across the region and beyond is imperative. Higher education is undergoing tremendous changes in response to the national global dynamism (Hazelkorn E et al., 2014). The way institutions carry out and comprehend, interpret, and respond to ranking differs with differing institutions (Hazelkorn E et al., 2014). While some universities rank higher each time, and others get introduced to the ladder, others are ousted.

While developed countries compete to develop as many world-class universities and those in developing countries build research-intensive institutions, it is not clear whether Malawian universities as a system among the newly developing economies feel that ranking matters (Dembereldorj Z, 2018). It has not made it into either the top 1000 global QS World University Rankings (2021) or Africa’s top 53 non-academic universities ranking by universities rank (2020) for the past five years. There is a general outcry as to whether it is worth funding institutions whose academic products cannot address the desires of their society. Other criteria for registering such visibility are institutional research and publication productivity, institutional linkages, quality and quantity of publications, and citation rate (Times Higher Education, 2021; The world University Rankings, 2022). Academic mobility enhances publication productivity. Researchers like Fernandez et al. found that academic mobility enhances social capital (Alipova O et al., 2018). It is a vehicle for knowledge circulation (Baker A, 2015). Internationalization through academic mobility is another effective strategy. It provides an opportunity for broadening faculty perspective, better networking, and research collaboration which may impact publishing productivity (Alipova O et al., 2018; Fernandez-Zubieta A et al., 2015). Institutional collaboration enhances quality, and publication productivity (Horta H et al., 2016; Rogers M et al., 2014; Lathabai HH et al., 2021).

On a non-academic UniRank league, the University of Malawi is ranked the 171st (Top 200 Universities in Africa | 2021 African University Ranking ( out of the top 200 African universities in 2021. UniRank produces a rank of top 200 universities in Africa based on “valid, unbiased and noninfluence able web metrics provided by independent web intelligence sources rather than data submitted by the Universities themselves” (Top 200 Universities in Africa | 2021 African University Ranking (

Regardless of the stages of development to improve their higher education systems, there is a need to increase the institutions’ internationalization. Strategies for this include academic mobility, employment of international teachers, and internationalizing curricula while achieving quality learning experiences are some of the critical priorities of Higher Education Institutions (HEI’s) (Huang F et al., 2019; O'Brien B et al., 2019). Investing in quantitative and qualitative development of higher education includes investing in knowledge, skills, and abilities necessary to create greater productivity and highly add value, and of which the human capital is the crucial factor (Sekuloska JD, 2014). Many HEIs invest in academic mobility to increase competitive advantage in the higher education system (Sekuloska JD, 2014; Tanhueco-Nepomuceno L, 2019; Sekuloska JD, 2014). There is an increase in the global mobility of students attending higher education (Hepple E et al., 2017). Academic mobility may take the form of long-term or short-term mobility programs, which, among others, benefit the participants on cultural exchange and professional development (Hepple E et al., 2017).

Various HEIs develop academic mobility programs to improve their systems in different forms (O'Brien B et al., 2019; Tanhueco- Nepomuceno L, 2019; Hepple E et al., 2017; Arunasalam ND et al., 2018). For example, domestic students have mixed with international students in a classroom setting, where among others, they reported that they benefited in developing awareness, connecting, and sharing cultural knowledge (O'Brien B et al., 2019). In other institutions, academic mobility involves having faculty from abroad to teach students in their home country, which has both positive and negative impacts on both students and faculty (Huang F et al., 2019; Arunasalam ND et al., 2018). Some institutions embrace international exchange programs for students and faculty. This involves students from different countries coming to one institution. Also, students from the host institution can go to other institutions for a short period of study, which influences their literature and functional value in terms of having a contextual value of studying abroad (Gallarza MG et al., 2017). Furthermore, faculties are sent to other countries for short-term teaching programs to promote cultural self-awareness and professional development (Hepple E et al., 2017).

Despite the global competition on achieving quality higher education, the higher education sector in lower-income countries, such as Malawi, is still struggling to achieve quality (Sharipov F, 2020). Many talented students in these countries are pulled by higher-income countries to acquire higher quality education abroad, thereby maintaining the brain drain from the low-income countries (Campbell 2017). There is an outcry about delayed completion of programs and persistent dropout rates. Therefore, it is necessary to consider academic mobility to improve higher education (Arunasalam ND et al., 2018). However, as noted by other institutions, this approach has positive and negative impacts on mobile individuals and the host and home institutions (Hepple E et al., 2017; Gallarza MG et al., 2017). Hence, we are raising these questions:

a) If Malawian Higher Education System is to improve quality by considering students and faculty mobility, what could be the opportunities and the setbacks?

b) Are there significant relationship independent factors with the Quality of Higher Education in Malawi?

Materials and Methods

Study setting and design

The authors conducted this study in Malawi, a country located in the southern part of Africa bordering Tanzania, Mozambique, and Zambia (Millington A et al., 2008; Munthali GN et al., 2020). Malawi is one of the developing countries in Africa where the majority of its citizen depend on agriculture and education to enhance a better life within a society (Munthali GN et al., 2020). Education has been at the heart of the policymakers with help from other local and international organizations (Munthali GN et al., 2020). After the National Council for Higher Education (NCHE) accreditation, public and private learning institutions operate in Malawi. This overall body accredits and supervises the higher education quality, which has helped promote the quality of education in Malawi. This study focused on institutions of higher learning education in Malawi as shown in Figure 1.


Figure 1. Showing the study area of Malawi.

Study design

The study design for this study was a crosssectional survey conducted using a populationbased representative sample. Variables are collected for several sample units at the same points in time (one time shoot), just the data Collected from the respondents directly at Particular time.

Sampling and population

This research used stratified sampling techniques to collect data. Ministry officials and human resources from various higher learning education institutions. Stratification aimed at data collection triangulation to get a richer understanding of the study targets. The population was stratified as students, faculty, and academic leadership. The students’ strata were undergraduates, masters, and PhDs. Faculty comprised two strata: Deans and heads.

The population was calculated using the sampling calculators (Government of the Republic of Malawi, 2013; Taherdoost H, 2016). The respondents comprised academic staff, students (Bachelors, Masters, and Ph.D.), academic institution leadership (Deans and head of departments).

Development of an instrument

The instrument had two parts. The first part captured the social demographic characteristics of the respondents, whereas the second part captured the measurement of assessed variables.

Source of data

We used primary data by designing a questionnaire form. Primary data refers to the data when the researcher collects data directly from his observations and experience (Sample Size Calculator, 2020).

Validation and pretesting

The researchers pre-tested the instrument through a pilot study with 15 Masters and 15 Ph.D. students in Malawi. They further sent the instrument to five experts to verify whether the instrument passed the Alpha Cohn bran for internal instrument consistency.

Study variables

The variables considered in this study were based on earlier studies at the global and national levels. As discussed in the literature review, socio-economic, demographic, and related characteristics are essential for our work (Table 1).

Table 1. Variables definitions.

S.No. Variable name Variable definition
1 Gender 1=Male, 0 Female
2 Age-Group 1=Below 30, 2=31-40,3=Above 41
3 Nature 1=Student,2=Officer,3=Lecturer, 4=Alumni
4 Qualification 1=Studying towards first Degree (If undergraduate 1), 2=BD,3=MD,4=PhD
5 Academic rank 1=Student, 2=high school teacher, 3=Lecturer,4=Senior Lecturer 5=others (Ass.Prof,Prof,Direct,etc)
6 Experience 1=Not Yet Employed, 2=Less than 5 years, 3=Above 5 years
7 Experience No 1=Less than 5, 2=Above 5 less 10, 3=above 10
8 Likert Scale 1=SD,2=D,3=N,4=A,5=SA

Response variable/Dependable variable

The dependent variable for this study was the Quality of Higher Education (QOH). QOH is a complex concept, relative and contextual, which must be understood within the interplay among culture, politics, and economics (Elman C et al., 2016; Haseena VA et al., 2015). It embodies national and global relevance of curricula and the related academic and administrative processes, staff development strategies, qualification of faculty, and the processes leading to the training of the same, the physical, social and academic environment, and abilities, skills, attitudes, and knowledge the students can demonstrate on successfully going through an academic program (Gayef A et al., 2014; Kercher J, 2018). Quality of education has various indicators, including levels of flexibility and ability to embrace change in light of scientific research, the composition of faculty, students, time of graduation, retention rates, quality of student support systems, external examiners’ reports, infrastructure, extra-curricular activities, graduate employability, quality and quantity of publication, indexing, and citation rates, and ranking (Elman C et al., 2016).

Data analysis

Data were analyzed using SPSS version 26; descriptive data were presented; after that, we ran a multi linear regression model with a statistical P-value at 0.5 level of statistical significance.

Statistical model

Multiple linear regressions required that the dependent variable be continuous and the independent variable be discrete, continuous, and categorical.

Multiple Linear regression model (LR)



Y is response variable

β0 is constant parameter

β1,…βk, are unknown parameters. I=1, 2…k x1, x2……xk, were explanatory variables

ε is the error term

Assumption of multiple linear regression models

a) Multiple regression models should be linear.The parameter should enter the model in linear form (Linearity).

b) Errors have a normal distribution with mean vector zero (Normality).

c) The variance of the errors at each fixed value of the independent variables is constant that is δ2 (Homoscedasticity).

d) There is no correlation between successive error terms. That is corr (εi, εj=0) (nonautocorrelation). Autocorrelation occurs when the residuals are not independent of each other.

There must not be significant relation between the independent variables. In other words, x is an n × k matrix of full rank (no Multicolinerity). It occurs when several independent variables correlate at high levels with each other. Participants were informed in advance that the study participation was voluntary, that they could withdraw at any time without any problem, and that their confidentiality would be kept. In Malawi, this study was approved by the Ministry of Education with reference number EDU/HE/21/95 dated 11 May 2021. The study followed all the procedures; laid down under the Helsinki Declaration of conducting a study involving human beings.


Social-demographic characteristics

The study assesses the demographic characteristics of respondents is the demographic makeup on improving higher education through faculty mobility opportunities and challenges. Data were collected on gender, age group, occupation, academic qualification, academic rank, and the number of expatriates. A total number of 222 participated in the survey representing.

Presents the respondents’ social-demographic characteristics (Table 2). The study results show that most respondents were males, representing 63.7% (n=135) while the females were 36.3% (n=77). The majority fell within the age bracket of 30 years, representing 42.5% (n=90), followed by those within 31-40 years, representing 33% (n=70), while those above 40 years old, representing 24.5% (n=52). Furthermore, on the occupation, the results reveal that the majority were students, representing 48.6% (n=103), followed by officers, representing 25.5% (n=54), lecturers representing 24.5% (n=52) and alumni representing 1.4% (n=3). On academic qualification, the results reveal that the majority of the respondents had been studying towards BA, representing 37.3% (n=79), followed by MD representing 35.8% (n=76), BD representing 17.9% (n=38), and those with Ph.D. representing 9% (n=19). On academic rank, the results demonstrated that the majority were lecturers representing 35.8% (n=76), followed by students representing 34.4% (n=73), Dir. Prof. Mg. etc representing 20.8% (n=44), high school teachers representing 8% (n=17) and senior lecturer representing 0.9% (n=2). In terms of experience, the results reveal that the majority of the respondents were not yet employed, representing 39.6% (n=84), followed by five years plus representing 37.3% (n=79) and those less than five years representing 23.1% (n=49). Lastly, on the number of expatriates, the result reveals that the majority of respondents were less than five, representing 45.8% (n=97), followed by those above five representing 39.2% (n=83), and those above ten representing 15.1% (n=32).

Table 2. Descriptive characteristics of the respondents (N=212).

Variable Category F %
Gender Female 77 36.3
Male 135 63.7
Age-Group Below 30 90 42.5
  31-40 70 33
  41+ 52 24.5
Occupation Student 103 48.6
  Officer 54 25.5
  Lecturer 52 24.5
  Alumni 3 1.4
Academic qualification Studying towards BA 79 37.3
  BD 38 17.9
  MD 76 35.8
  PhD 19 9
Academic rank Student 73 34.4
  High School teacher 17 8
  Lecturer 76 35.8
  S. Lecturer 2 0.9
  Other (Dir. Prof.Mg etc.) 44 20.8
Experience Not yet employed 84 39.6
  Less than 5 49 23.1
  5+ 79 37.3
Expatriates-No Less than 5 97 45.8
  Above 5 below 10 83 39.2
  10+ 32 15.1

The absence of Multicollinearity can be checked by VIF (Variance Inflation Factor) in regression analysis (Table 3). When the value VIF for each predictor variable is less than 10, we can conclude the absence of Multicollinearity. Therefore, upon looking at our study, we meet the condition of the Multicollinearity test, which enabled us to conduct the regression analysis.

F-test also revealed that this proportion of variance is statistically significant. The overall model is statistically significant for the data. All the assumption of regression analysis was satisfied. Due to formal tests and diagnostic plots, normality, constant variance, absence of Multicollinearity, linearity, and absence of autocorrelation were satisfied.

The results in Table 3 revealed that the model is adequate (good fitted the data), implies that 49% of the variability in the Quality of Higher Education are explained by the variability of the independent variables in the estimated regression and while 51% explained by other non-explained factors out of our determined independent variable in the study. Durbin Watson test revealed the absence of autocorrelation for the assumption of multiple linear regressions. Errors must be uncorrelated.

Table 3. Multicollinearity test.

Variables Model 1 Model 2
  Tolerance VIF Tolerance VIF
Gender of the respondent 0.972 1.029 0.912 1.097
Age-Group 0.33 3.033 0.325 3.075
 Occupation 0.56 1.786 0.549 1.823
Academic qualification 0.381 2.622 0.368 2.719
Academic rank 0.626 1.598 0.619 1.615
Experience 0.334 2.99 - -
Expatriate - - 0.334 2.995
Clear Policy on Mobility - - 0.426 2.345
mobility Importance - - 0.431 2.318
Institutional Collaboration - - 0.889 1.125

Furthermore, the results from the multi linear regression analysis indicates that Institutional collaboration (ß=0.326, p=0.000, CI=0.27— 0.383), clear Policy on Mobility (ß=0.146, p=0.0.004, CI=0.047-0.246), experience (ß=0.083, p=0.117, CI=-0.021-0.186), academic rank (ß=0.114, p=0.000, CI=0.069- 0.159) were positively statistically significant variables, whereas on the other hand, Occupation (ß=-0.131, p=0.002, CI=-0.213- 0.49), academic qualification (ß=-0.106, p=0.013, CI=-0.19-0.023 and mobility Importance (ß=-0.116, p=0.022, CI=-0.215- 0.017) were negatively significant variables respectively (Tables 4 and 5).

Table 4.Factors determining/affecting the quality of higher education in Malawi using a Multi linear regression analysis.

Variables Model 1   Model 2    
  B P-Values B P-Values 95.0% CI
(Constant) 6.497 0 - - [6.298-6.696]
Gender of the respondent 0.137 0.056* - - [-0.003-0.278]
Age-Group -0.073 0.32 - - [-0.219-0.072]
 Occupation -0.12 0.023** - - [-0.223-0.017]
Academic qualification -0.118 0.027** - - [-0.223-0.014]
Academic rank 0.14 0.000*** - - [0.083-0.197]
Experience 0.07 0.296 - - [-0.062-0.201]
(Constant) 5.205 0.000*** - - [4.853-5.557]
Gender - - 0.014 0.803 [-0.1-0.128]
Age-Group - - -0.047 0.423 [-0.162-0.068]
 Occupation - - -0.131 0.002*** [-0.213-0.049
Academic qualification - - -0.106 0.013** [-0.19-0.023]
Academic rank - - 0.114 0.000*** [0.069-0.159]
Experience - - 0.083 0.117* [-0.021-0.186]
Clear Policy on Mobility - - 0.146 0.004*** [0.047-0.246]
Mobility Importance - - -0.116 0.022** [-0.215-0.017]
Institutional Collaboration - - 0.326 0.000*** [0.27-0.383]
Number of Observation -   212   -
R-Squared - - 0.168 49.4 -
 F-Value - - 6.898*** 43.288*** -
DF - - [6,205] [3,202] -
Durbin Watson - - 1.683   -

Table 5. Statement of hypothesis results.

Variables Results Accept/Reject
Gender of the respondent N/A Reject
Age-Group N/A Reject
Occupation - Accept
Academic qualification - Accept
Academic rank + Accept
Experience N/A Reject
ClearPolicyonMobility + Accept
MobilityImportance - Accept
InstitutionalCollaboration + Accept


The current study investigated the intentions, opportunities, and barriers to engaging in a meaningful internationalization of higher education in Malawi, which included study, institutional collaboration, international visibility through ranking, abroad experiences, enrolment in foreign universities, student and faculty exchange programs, and the enrichment of curriculum with foreign languages and subject matter through international and area studies programs. Many of these actions, of course, continue and have accelerated. Several new methods and techniques have also emerged (Benson RE, 1997). These include increasing student and teacher mobility, international curriculum content integration, growth of interinstitutional collaborations and partnerships, and trans-border educational services such as the construction of branch campuses and distance and online learning (Lathabai HH et al., 2021; Maringe F et al., 2012; Pandey D et al., 2021).

Precisely, respondents’ demographic characteristics, intentions, and sociodemographic variables on improving higher education through faculty mobility, opportunities, and challenges were measured. Our population characteristics indicate that most of the participants were students (48.6%) with more males (63.7%) studying towards their first degree (37.3%); hence their work experience characteristics showed that most of these students (39.3%) were not yet employee. This characteristic has a significant bearing on the data.

We can confidently postulate that students as the main clients in education could make good evaluators of the goods and services offered by education. Therefore, their opinions in this study were of paramount importance. There were more males among the participants (63.7%), indicating that there are still imbalances in the education system despite affirmative action policies regulating admission. We attributed the disparities to the fact that it is a long way from primary education to higher education for girls with social vulnerabilities. Nonetheless, the disparity seems to be narrowing.

The findings suggest academic qualification is significantly correlated with improving the quality of higher education in Malawi. Most respondents (35.8%) were studying towards a first degree on this variable. They wished that only well-qualified faculty should take them through their coursework. Students feel confident if they know that some authority is responsible for their academics. They will, therefore, prefer to be handled by a highly qualified member of faculty because they believe that such individuals have the expertise in their discipline to take them through research guidance (Kreber C, 2009). Scholars postulate that many students will not perform well when their teachers or professors do not possess adequate expertise, knowledge, skills, and attitudes (Kreber C, 2009; Khozaei F et al., 2015). This qualification encompasses formal certification and credentials and all psychosocial and linguistic aspects that enhance effectiveness and efficiency since student success is a result of the quality of the process of teaching and learning (Singh JK, 2020; Sidhu GK et al., 2014; Gobel P et al., 2013). Scholars such as cite inadequate language proficiency, inadequate student-faculty interface on campus, and snags in sociocultural adjustment as impediments to quality education. Research posits that a feeling of relatedness with the faculty makes students develop healthy study habits coordinators, which ultimately positively impacts academic achievement (Lamas HA, 2015; Wen W et al., 2018).

The study found that academic rank (p=0.000) significantly impacts the quality of education in Malawi. Most respondents on this variable were faculty members (35.8%), followed by students (34.4%). All factors held equal, faculty and students are better placed to comment on the importance of higher education institution’s ranking. Students think that an institution ranking high is more credible than those off the rank. Such institutions give them a sense of assurance for future academic and career prospects.

Similarly, faculty associated with high-ranking institutions are more likely to engage in interinstitutional collaboration and international scientific joint projects. Institutions with high academic rankings will attract more international students (Dembereldorj Z, 2018). Such institutions are likely to realize more revenue for funding academic programs and research. Such investments bolster the quality of curriculum innovation, implementation, and delivery of quality services. Our result agrees with what is in extant literature. Much as it is complicated to define how institutional rankings affect higher education, institutional ranking impacts the quality of higher education in various ways (Hazelkorn E et al., 2014; Dembereldorj Z, 2018). Scholars found that academic ranking serves as a reliable source of information for decision making both by prospective students and institutional management for marketing purposes, benchmarking, decision making, choice of host international institution, and filling relevant operations gaps (Hazelkorn E et al., 2014; Dembereldorj Z, 2018).

Cross-border comparisons and competition is inevitable and will only keep intensifying. Such that opting out of the race is only anti-global and not in line with the expected internationalization of higher education (Hazelkorn E et al., 2014; Dembereldorj Z, 2018). As such, institutional sustainability will be possible through joining the healthy competition and improving institutional research capacity in today’s knowledge-driven economy (Dembereldorj Z, 2018). Although there are lots of criticisms against the criteria used in national, regional, and global rankings, the process remains an indispensable tool for maintaining standards in higher education holding institutions accountable to society, and helping institutions judiciously, guardedly and tactically underpin institutional development (Dembereldorj Z, 2018; Hazelkorn E et al., 2014; Haahr JH et al., 2005).

Besides, the study revealed that a clear policy on mobility has a significant positive impact (p=0.004) on university education quality. A clear policy on academic mobility would significantly impact the quality of higher education in Malawi. The institutional operational policy sets a general blueprint and framework that directs employees towards desired outcomes and rational decision-making as it enables planning in advance and related resource mobilization for quality service delivery (Elman C et al., 2016). Organizational management theories advocate timely and relevant communication for the organization's success. Leadership and management should formally communicate the goals of the organization. This is the shared view about the direction the institution is supposed to take. Therefore, the explicit policy provides this direction as enshrined in the institutional strategic plan, stipulating the intended goals. Shared policy formulation and dissemination facilitate implementation by faculty to attain the institutional goals with excellence (Hazelkorn E, 2013; Peter Sn et al., 2020; Huo X et al., 2018). Written policies save much institutional prime time, preventing legal confusion, role conflict, and other chaotic operations because they indicate universities’ best practices and enable institutional process reuse (Bao L et al., 2020). Besides impacting ethical conduct, the policy ensures guidance, consistency, accountability, clarify, and efficiency. This finding is consistent with the extant research of Spencer et al. (Altbach PG et al., 2007). The irrefutable evidence of the positive impact of a clear academic mobility policy is manifest in the outcomes of the Bologna Process (Spencer- Oatey H et al., 2019).

Institutional collaboration was reported to impact higher education quality (p=0.000) significantly. This is because institutional collaboration enhances synergies in pedagogy, curriculum, scientific research, and policy development among the collaborators. This explains why institutions with strong ties with others have higher academic output and quality programs than those excluded from the network fabric (Maynard DC et al., 2013). Our findings correspond well with international practices such as those between Mexico and the United States of America signed during President Obama’s time to enhance the quality of education between the two countries while enhancing stronger bilateral political ties (Betru T et al., 1997). Our results are consistent with volumes of literature on expected outcomes of institutional collaboration (Vassar D et al., 2014). Nonetheless, some literature also reveals a critical negative impact of institutional collaboration due to implementation flaws in the program (Deng J et al., 2019).

Academic mobility significantly negatively impacted the quality of education. The more students and teachers get involved in international mobility, the more they are involved in permanent migration resulting in brain drain. As a developing country, Malawi loses many of its brains to the developed countries, where pull factors for highly skilled and highly qualified human resources are prevalent (Mihut G et al., 2016; Mazzarol T et al., 2002). Such creates inconsistency between the production of rare talents and profitability. There is an incredible mismatch between the demands for such skilled and highly qualified rare talents needed to improve university education and their availability for improving university education standards. These findings concur with preceding studies which reveal adverse effects of permanent human resource migration from developing to developed countries (Yu S et al., 2021; Muthanna A et al., 2018; Odhiambo G, 2012; Docquier F, 2014; Canibano C et al., 2015; Hussain SM, 2015). Similar studies indicate that if academia migrates permanently and does not remit anything to their country, the practice adversely impacts their families and the nation’s education system (Artuc E et al., 2015). Temporary migration enormously positively impacts home institutions (Djajic S et al., 2015).

A competing branch of the literature reveals that permanent migration per se does not impact the home institutions negatively unless the home institutions do not maintain linkages and collaboration with the mobile academia. When the migrant academia joins faculty in their destination, it can present an excellent opportunity for research collaboration. This is in line with extant literature (Bertoli S et al., 2015). If home institutions and the host institutions engage in institutional linkages and enhance collaboration, this migration would significantly benefit the donating institution (Yan G et al., 2015). Besides, if the migrant faculty remits to the home country, such funds may bolster research activities in the donor institution (Choi WS et al., 2016).

On the other hand, the study’s findings revealed that occupation (p=0.023) and academic qualification (p=0.027) present significant setbacks on faculty mobility in HEIs. The higher the qualification, the lower the impact they have on the students’ learning. This result agrees with the expectations from the extant plethora of literature. For instance, some scholars report that overqualified faculty performs better at managerial positions than at handling coursework. Inopportunely, since formal and bureaucratic organizational structure follows the pyramidical shape, the university setup will not accommodate all highly qualified faculty in leadership positions.

Consequently, perceived over qualified faculty feel less satisfied with their job (Licuanan V et al., 2015). Those overqualified feel frustrated when they perceive that what they get is lower than what they deserve, be it in monetary rewards or responsibilities entrusted to them. Therefore, the institutions need to constantly assure the highly qualified faculty that they value them greatly. Any befitting incentives should be given to them, following institutional incentivization policy (Erdogan B et al., 2015).

Literature posits that employees who feel overqualified for their job or doing a job that even less qualified colleagues are also doing feel less satisfied with their job, have less organizational commitment levels, and tend to be associated highly with job turnover (Deardorff DK, 2006). Much as discipline experts are advantageous to students as they can easily guide the students through a milliard of relevant research literature instrumental for successful completion of a program, wellqualified faculty renowned academicians are more involved in research and international consultancy work, making them less available for the student’s research supervision and coursework than the lower qualified faculty (Culbertson SS et al., 2011; Gube JC et al., 2017). Many studies justify this finding (Kreber C, 2009; Gao Y, 2019). This makes facultystudent contact less effective. This is also evident in the delayed completion of students pursuing graduate and postgraduate programs conspicuously evident in the Malawian higher education system. Literature attests that 45- 50% of graduate students complete their course work yet fail to graduate due to supervision-related challenges (Gube JC et al., 2017). This is consistent with the previous research that emphasizes a time-based conflict when employees over-prioritize one role over another (Deardorff DK, 2006). Notwithstanding this, under qualified faculty may also be deleterious to student progress as they lack the skills and competence to correctly direct their students to appropriate literature that can help the students comfortably handle their research (Khozaei F et al., 2015; Gube JC et al., 2017).

Furthermore, highly skilled human resources and rare talents quickly drain their home institutions for greener pastures. This makes the home institution lose out through brain migration. Such mobility negatively impacts the continuity of learning (Kramer WM, 2020; Banda LO et al., 2012).


This study explores and establishes some of the critical determinants that bolster and encumber the quality of higher education in Malawi. Regarding our data analysis, there is strong proof to propose that the qualities of higher education in Malawi are statistically significant and positively influenced by clear policy mobility (such as the institutional operation policy), institutional collaboration, and academic rank. Besides that, our study has revealed that academic qualification is significantly related to enhancing higher education quality in Malawi. On the other hand, the study results have established that the quality of higher education in Malawi is statistically significant and negatively impacted by Occupation, academic qualification, and mobility importance.

Our study recommends that in Malawi, higher education institutions need to regain the lost glory and bounce to the regional, continental, and global university rankings. Cognizant of the strategies to achieve the Sustainable Development Goals and the Agenda 2063, the educational systems need to revamp themselves to avoid delaying sustainable development. All the actors in higher education in the country need to realize that they have one common goal: to contribute to meaningful regional and global development through intra-national collaboration, regional, continental, and global partnership. The monitoring organs need to intensify quality assurance and meaningful regulation of the public and private higher education actors and agents for a vibrant system. The national competition will be necessary only if it aims at benchmarking and not at outdoing each other. Since each institution has unique discipline-based strengths, the entire national higher education system needs to upgrade collaborative efforts in the related research activities.

The universities and colleges need to develop a clear academic mobility policy and disseminate it among faculty to guide and inform institutional decision-making. Faculty need to balance attention to their mandates such as research, teaching, training, and outreach not to compromise student academic performance. They need to make their vision clear and strategies set to register their availability and presence on the regional scene. Secondly, they need to prioritize institutional linkages and collaboration, capacity building, skills, and professionalism within the country and the region to improve research output and quality.

The government should consider policy development that enhances collaboration between home institutions and the migrant faculty. Besides, the government and the academic institutions need to synergize in making the mobile faculty too long to return home.

The renowned countrywide institutions should gear up to help the relatively higher education institutions play a commendable role in improving education. Due to high staff turnover, Institutions should fix a transparent staff financial incentive scheme policy and promote a salary increment policy. Besides that, we believe that good planning and an influential, supportive culture will help to improve the quality of higher education in Malawi. Institutions should work on peer coaching. Using peer coaching with international students can reduce cross-cultural communication issues and solve the problem of loneliness in the work environment.

Declaration of Interest

We declare that this work is original and is not a copy of any other intellectual property.


The authors sincerely thank the Ministry of Education for granting permission to collect data from higher education institutions in Malawi. Much more, the role played by relevant institutional leadership in facilitating timely and coordinated data collection cannot be ignored.


This study did not receive funding from any institutions.

Credit Authors Contribution

All authors made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data, drafted the article or revised it critically for important intellectual content; agreed to submit to the current journal, and gave final approval of the version to be published.


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