ARTICLES

 

Creating an environment that nurtures deep learning: How does the National University of Lesotho fare?

 

 

Tebello Tlali

National University of Lesotho, Kingdom of Lesotho

 

 

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ABSTRACT

The paper sought to explore the lecturers' experiences concerning their teaching strategies and students' learning approaches at the National University of Lesotho (NUL). Thus, the paper analysed these practices mainly from the lecturers' perspectives. The growing media negative views about the quality of the teaching and learning practices at NUL necessitated research on the matter. Departing from an interpretive paradigm, the study adopted a qualitative design. Date were gathered through semi-structured interviews with lecturers across the seven faculties of NUL. The population consisted of 300 lecturers. However, participants were purposively selected, and 14 (two from each of the seven faculties) participated in this study. The assessment papers provided by the interviewed lecturers were analysed. The findings indicate that lecturers are frustrated by the lack of a clear teaching and assessment policy. This situation is exacerbated by inadequate training in teaching and assessment. In addition, the findings suggest that there is a high prevalence of memorisation, reproduction of class notes and plagiarism among the students. The paper proposes that the institution addresses these shortcomings through clear teaching, learning and assessment policies as well as the establishment of comprehensive staff development and student support programmes.

Keywords: deep learning, quality teaching, quality assessment, student motivation, academic integrity, institutional factors

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INTRODUCTION

The National University of Lesotho (NUL) has operated as the sole university in Lesotho ever since its establishment in 1975 (Ntimo-Makara, 2009). The Lesotho higher education landscape changed in 2008, when a Malaysian, Limkokwing University satellite campus was opened in Lesotho. Later in 2016, Botho University (originating in Botswana) also branched into Lesotho. Other Lesotho higher education institutions worth mentioning include: the Lesotho College of Education (LCE) and the Lerotholi Polytechnic (LP). Despite the presence of these other institutions, NUL is still the largest public academic higher education provider, and it continues to cater for over 50% of the students in this sub-sector.

Currently, NUL has a student population of more than 9000 and about 300 lecturers of which approximately 31% hold PhDs (NUL - CHE Report, 2018). However, the majority of the latter group of lecturers (with a few exceptions) have no training in teaching and assessment matters. Thus, most of the lecturers were employed on the basis of their expertise in other disciplines, such as Law, Economics, Financial Management, Sociology, Physics, Chemistry, Linguistics, to mention a few examples. When most of these lecturers were initially employed, a credential in pedagogical issues was not a requirement. However, the Lesotho Council on Higher Education (CHE) has stipulated that all higher education teachers must improve their profiles by acquiring a teaching credential (CHE, 2010). The aim is to improve the quality of higher education in the country.

 

PROBLEM STATEMENT

The necessity for creating an environment that nurtures quality teaching and learning is captured in the NUL strategic goal which aims to turn this institution into 'a university of choice providing high quality educational experience' (NUL Strategic Plan, 2015: 19). Conversely, the achievement of this strategic goal seems questionable and compromised. For example, the media has been critical of both the lecturers' teaching methods and students' learning approaches. Lloyd (2012: 1) harshly writes: 'lecturers read notes to students instead of engaging them and do not allow students to ask questions in class; ...students consider studies a secondary reason for their being at university'.

The view that further casts doubt on NUL's ability to achieve its strategic goal is expressed by the Ministry of Education and Training (MOET, 2005) and the Lesotho Council on Higher Education (CHE, 2010) who concede that quality teaching and learning is a critical challenge confronting Lesotho higher education. This, in a nutshell, is what drove my curiosity to get to the core of this matter. My intention was to find information on the basis of which I could recommend measures to improve the situation. This paper, therefore, is guided by the following main research question: Does the NUL environment encourage or discourage deep learning?

 

RESEARCH AIM AND OBJECTIVES

This study sought to analyse the NUL teaching and learning context with the aim to establish whether or not the environment nurtures deep learning. Drawing on this aim, the study had two objectives, namely:

• to explore the views and experiences of the NUL lecturers with regard to their teaching strategies and the students' learning approaches

• to suggest mechanisms for enhancing deep learning at the institution.

 

LITERATURE REVIEW

Quality teaching and learning constitutes the cornerstone of any world-class institution of higher learning. As a research theme, this area deals with teaching and learning approaches (deep and surface) and factors which influence them (Tlali, 2014; Tlali & Jacobs, 2015). In the quest to stay relevant and to gain better global ranking, higher education institutions need to reposition themselves by repackaging their product (Le Grange, 2006; Singh, 2011). The achievement of quality higher education also requires utilisation of more student-centred (constructivist) approaches. This trend has made constructivism a dominant theoretical perspective adopted in nurturing deep/quality learning at the various levels of education (Vanderstraeten, 2002). Hence the literature review has been framed within constructivism as the overarching theoretical perspective. The literature defines deep learning by also contrasting it with its antonym, surface learning. In addition, ways of inculcating deep learning are discussed.

Constructivism advocates

Constructivism advocates the teaching activities that shift focus from the educator to the students (Biggs & Tang, 2011). Constructivism is based on the conviction that the students use their own activities to construct knowledge (Biggs & Tang, 2011). This theoretical perspective is associated with theorists or philosophers such as John Dewey (1859-1952) and Lev Vygotsky (1896-1934), (Sutinen, 2008; Vanderstraeten, 2002; Kivinen & Ristela, 2003). Dewey's ideas are construed as the most relevant for this paper. In Dewey's view, constructivism postulates that knowing is an active creation or building process, rather than a passive registration of the outside world (Sutinen, 2008; Vanderstraeten, 2002). Unlike theoretical perspectives such as positivism which perceive the learner as a passive recipient of external stimulation, constructivism emphasises the centrality of action as well as the active nature of learning. This view is captured in Dewey's famous principle of 'learning by doing'. As far as this principle is concerned, experience, learning and knowing result from doing or active involvement of the learner.

The reason for aligning this paper with Dewey's ideas, is that he puts a great emphasis on 'active involvement', 'active creation' and 'learning by doing'. These are the very tenets which make his ideas most comprehensive and relevant in fostering deep learning (Biggs & Tang, 2011). As part of the constructivist theoretical perspective, it is deemed vital to unpack the notion of 'deep learning' and to contrast it with 'surface learning', in order to highlight features of the two concepts.

Deep versus surface approach

Tight (2012) identified eight main research themes in Higher Education Studies, namely: teaching and learning, course design, the student experience, quality assurance, systems policy, institutional management, academic work, and knowledge. Against this backdrop, quality teaching and learning can be seen as a key issue in higher education. As a research theme, teaching and learning deals with teaching and learning approaches (deep and surface), including factors which influence them (Tight, 2012).

Deep learning and its antonym, surface learning, are two distinctive learning approaches, initially conceptualised by Marton and Saljo in their 1976 study (Biggs & Tang, 2011). Deep learning involves the learner's ability to go beyond the surface and thereby grasp the core of the learning material. It also implies the ability to figure out how the individual pieces of learning material constitute the whole (Baeten et al., 2010; Biggs & Tang, 2011). Deep learning originates from the learner's aspiration to use high cognitive skills with the aim of accomplishing the task accurately and meaningfully. Students who adopt a deep approach to learning are able to formulate knowledge which is highly structured and coherent. This results in the development of relational responses to tasks, long-term retention, ability to apply knowledge to novel situations, as well as the ability to generate new meanings.

On the contrary, students who adopt the surface approach tend to browse the learning material superficially, thereby reducing learning to a reproduction activity. A surface approach only engages lower cognitive levels, thus resulting in a limited understanding of concepts. It also results in the students' inability to distinguish principles from examples, difficulties in developing a logical argument in identifying the key ideas. Unconnected facts are passively accepted and memorised for reproducing when required (Fisher, 2003). The symptoms of surface learning include listing points without constructing an argument and presenting a verbatim recollection of information whilst failing to interpret or demonstrate a critical reflection thereof. In addition, it becomes difficult for the student to even apply the information in novel situations (Baeten et al., 2010).

Strategies for nurturing deep learning

The adoption of a particular learning approach (deep or surface) is not innate. Each learning approach can to a great extent, be influenced by factors that originate from a particular teaching and learning environment (Biggs & Tang, 2011; Smith & Colby, 2007). As part of the context, the educator's approach is key in determining a particular learning approach (deep or surface) which the learners adopt. The next section highlights the educator's role in nurturing deep learning.

The educator's role

As indicated earlier, constructivism advocates the teaching activities that shift focus from the educator to the students (Biggs & Tang, 2011). This implies that educators should always ensure student-centred teaching regardless of the class size. If a lecture method has to be used, it has at least to be interactive, only then can the achievement of deep learning be enhanced (Biggs & Tang, 2011). In a quest to promote deep learning, a good educator does not simply display information for the learners to absorb. Rather, he or she motivates the learners to take responsibility for their own learning (Cooner, 2010). His or her focus is primarily on what the learners do. Such an educator is also aware that how he or she assesses students' performance has a bearing on how the students learn. In essence, learners tend to focus their learning on what they think they will be assessed (Reid, Duvall & Evans, 2007; Van Tonder, Wilkinson & Van Schoor, 2005). It can therefore be inferred that when assessment focuses on high order tasks, the result will be promotion of deep learning.

In order to nurture deep learning the educator needs to create a teaching and learning environment where trial and error is accommodated and learners are at ease to make mistakes and learn from them (Biggs & Tang, 2011). In addition, the educator must find out learners' prior knowledge and build on that, while at the same time identifying learner misconceptions and eradicating them. Furthermore, teaching must also seek to bring out an active response from the learner (Biggs & Tang, 2011). Thus, teaching should not merely focus on expanding information. Rather the educator must employ problem-based activities and questioning techniques to involve the learner actively (Tek-Yew, 2011). Emphasis must be placed on depth (quality) not the width (quantity) of learning.

Moreover, teaching and assessment must be applied in a manner that is directly linked to the intended learning outcomes (Biggs & Tang, 2011; Tek-Yew 2011). This can be achieved by making use of learning taxonomies such as the Revised Bloom's taxonomy and the Structure of Observed Learning Outcome (SOLO) taxonomy (Biggs & Tang, 2011; Smith & Colby, 2007). The learning taxonomies are regarded as some useful teaching and assessment tools because they help educators to articulate the desired behaviours that must be elicited from the students. The use of learning taxonomies enables educators to determine what knowledge and skills are to be acquired, as well as the cognitive processes that are to be employed (Biggs & Tang, 2011; Smith & Colby, 2007).

In addition, educators can nurture deep learning by utilising constructive alignment. This is a teaching and learning design which helps to foreground the intended learning outcomes. When constructive alignment is used with a view to promote deep learning, the different components of the teaching and learning environment have to be aligned in a manner that promotes this goal (Biggs & Tang, 2011; Reid, Duvall & Evans, 2007). Such components include: learning outcomes, learning content, learning activities and assessment tasks.

Educator factors which hinder deep learning include: lack of reflection and lack of professional training, lack of resources and lack of time to engage in practices that can contribute to deep learning (Frick & Kapp, 2009; Green, 2006). Hence it can be agreed with Smith and Colby (2007) that it is important for educators to undergo academic professional development which is focused on teaching and learning as a disciplinary field. Such training must promote appreciation of what deep learning means and how it can be nurtured. This necessitates a clear institutional academic staff development plan that focuses on the achievement of deep/quality teaching and learning (Frick & Kapp, 2009).

 

RESEARCH DESIGN AND METHODOLOGY

The study was framed within an interpretivist paradigm and a qualitative design was adopted (Cohen, Manion & Morrison, 2011; Merriam, 2009). I commenced by conducting a literature review to inform the subsequent empirical work (Fouche & Delport, 2011). I then conducted semi-structured interviews with lecturers. I gave the participants a choice to be either interviewed in the comfort of their own offices or to come to mine. The interviews were audio-recorded and transcribed verbatim after which data were analysed.

NUL has about 300 lecturers who constituted the population for this study. However, I only interviewed a group that was purposively selected (Greeff, 2011) to ensure representation of the different faculties. Ultimately, I interviewed two lecturers from each of the seven faculties at NUL (namely: the Faculties of Agriculture, Education, Health Sciences, Humanities, Law, Science and Technology, and Social Science). This group was made up of eight females and six males with varying experience in teaching and learning. Their teaching experience varied from two to 18 years.

I also purposively selected lecturers who have a teaching qualification and those who do not. This was meant to highlight the importance of professionalisation of higher education teaching. For example, two lecturers had formal teacher training and subsequently acquired a Master of Education (MEd) and a Master of Science Education (MSc Ed) respectively. As highlighted in the introduction, the other lecturers in the group did not have a teaching qualification. Instead, they held qualifications (Masters' degrees and PhDs) in various specialisations, such as Law, Economics, Financial Management, Sociology, Mathematics, Physics, Chemistry and Linguistics. When most of these lecturers were initially employed, NUL did not emphasise a need for them to acquire a teaching qualification. Their areas of specialisation were regarded as adequate for teaching at this level. However as noted earlier, the Lesotho-CHE has since stipulated that a teaching qualification is a requirement for higher education teachers (CHE, 2010).

In addition, I conducted a content analysis of assessment papers provided by the lecturers I interviewed, with the view to scrutinise their style and coverage (Nieuwenhuis, 2007; Strydom & Delport, 2011). In conducting this study, pertinent ethical issues such as obtaining the required permission, issuing informed consent, protecting the dignity of the participants and ensuring confidentiality (Cohen, Manion & Morrison, 2011) were observed. No coercion took place and participants were advised of their right to withdraw from the research whenever they wished to do so (Cohen et al., 2011). I employed direct quotes from the qualitative data in the presentation of the findings in order to increase credibility of the research study (Merriam, 2009).

 

THE FINDINGS

In an attempt to establish whether or not deep learning is nurtured at NUL, I compared the empirical findings with literature on best practices in teaching for deep learning. The discussion in this section is based on the main constructs which emerged from the findings. These include: institutional factors, teaching practices, assessment practices, students' motivation, students' studying practices and academic integrity.

Institutional factors

According to the interview findings a number of institutional factors seem to hinder quality teaching and learning at NUL. These include the lack of a clear policy, lack of training and a well-coordinated orientation programme, lack of monitoring mechanisms and inadequate teaching facilities. In order to support this position, one participant explained:

...because of a disjointed way of doing things at NUL, somehow students' learning gets affected; this is due to lack of a clear policy on teaching.

Assessment and class attendance were cited as impediments. One participant emphasised:

...regulations are a mess and they have some loopholes which students sometimes take advantage of. If we could align regulations which cover all the areas of teaching and learning, this would be a perfect place to work in.

Lack of a compulsory orientation and professional development programme was mentioned as another limitation. Thus, a participant noted:

...there is a need for a more efficient and well-coordinated orientation or professional training.

Another participant concurred:

...we could use some education courses...we need to have some short courses, workshops on education so that we are at the same level with other universities.

Participants also mentioned the absence of monitoring and evaluation mechanisms as one of the factors which make them feel unsupported. For instance, one participant highlighted:

...there is no one to check. I have never seen anyone come to my class. It's up to me what I do in there. So I don't feel any support. There was no orientation, I went straight to class. I didn't even know where the class was.

In addition, participants cited lack of facilities as one of the challenges. For example, a participant stated:

...lack or shortage of facilities such as library books, laboratory resources as well as teaching and learning technology also have a negative impact.

Moreover, participants unanimously cited large classes and staff shortages as some of the demoralising factors. For instance, one participant stressed:

...the issue of large classes is a big concern, and it is mostly a concern with marking of assignments, because with assignments you would have given a five paged work to mark for every student. I wish we could hire more lecturers.

From the above findings, it seems participants are frustrated by the absence of supporting policies, teaching facilities, monitoring mechanisms, as well as lack of education training on their part. These factors could make it difficult to uphold quality teaching strategies.

Teaching practices

The study found that some of the teaching methods that are used include problem solving, case-based learning, collaborative/group learning and class presentation. One participant indicated:

.. I consciously avoid situations where students would just sit and absorb whatever I tell them and later reproduce it. Rather I allow them to do research on their own on assigned topics and then they share the information through class presentations.

...I usually assign them group work...it makes my job very easy because they are able to explain to each other and learn from their peers...

However, the majority of the participants reported use of the traditional lecture method due to large classes. This can be typified as a teacher-centred method that does not encourage any activity from the student. As one participant highlighted:

You have to stand in front of a huge group and there are no projectors, no system to assist you to do it in a way that you feel comfortable that you have covered everything to the depth that you wanted. Sometimes it becomes a pain to teach large classes without such facilities.

Participants unanimously acknowledged that, due to the big numbers of students, they are unable to give their best. One participant explained:

...due to big numbers, one is not able to give them as many assessment tasks as desired, and as such even the feedback that they get is not a true reflection of what they are capable of.

Another participant elaborated:

...the objectives are simply written in the course outline. I must confess that I tend to forget that at the end of the topic or at the end of the lesson I should still go back to my objectives to determine whether they have actually been achieved.

From the above findings, some good practices such as assigning research to students and utilising group learning can be identified. However, it needs to be highlighted that the majority of the participants resorted to the traditional lecture method especially in big classes. In addition, most of the participants did not mention the constructive alignment of teaching and learning components. The literature maintains that deep learning can only be achieved when learning outcomes are aligned to teaching and assessment methods (Biggs & Tang, 2011; Cooner, 2010). When this alignment is not foregrounded, then it cannot be guaranteed whether or not the learning objectives are indeed achieved.

Assessment practices

I also requested the participants to provide samples of their test and examination question papers. Some complied. I received a total of 10 assessment papers (four test papers and six examination papers). Table 1 illustrates the analysis of assessment tools in terms of their coverage of high versus low order tasks.

From Table 1, it can be noted that only samples 1 and 2 have a greater percentage of high order questions (60% and 50%, respectively). The rest of the samples are dominated by low order questions. Sample 10 is on the extreme end with 100% low order questions, and 0% high order questions. When the participants were asked to define how they distribute the assessment tasks in relation to the different levels of the learning taxonomies, one participant indicated:

...my assessment papers carry more knowledge and less application tasks...something like 25% to application and 75% to knowledge.

Another participant also appeared to follows a similar trend. This participant divulged:

...my own assessment is dominated by more knowledge questions and remembrance.

Another participant added:

...in my assessment tasks I ask students one question that requires them to analyse and three questions that generally cover what was discussed in class.

From the above findings, it can be noted that if assessment practices mostly concentrate on lower order tasks, as appears to be the case, the achievement of deep learning can be jeopardised. However, one participant appeared to do things a lot differently from the rest, and it turned out this was one of the participants who held a teaching qualification. The participant explained:

...taking the Bloom's taxonomy of educational objectives, I try to ask questions which allow students to engage their mental faculties at a higher level. I ask evaluation questions where they analyse stuff, where they apply stuff. I do not ask simple recall questions.

This above quotation is exceptional in the sense that it epitomises an assessment approach that can help promote deep learning. Thus, students are made to engage higher levels of their cognitive domain. Otherwise, it appears to be a norm that the weighting of assessment tasks, focuses more on low order tasks.

Students' motivation and related personal factors

According to the lecturers' views, many students exhibit lack of motivation for their studies. One participant pointed out:

...some students regularly skip classes, they stay passive in class, and their lack of motivation is also illustrated by a high failure rate.

...it's even difficult to get them talking or to involve them in a discussion in class...as a junior lecturer I don't know what to do. I think they have this culture that even if they don't work as hard as they should, they would still pass...they don't aim high, they just say, 'if I get a fifty I will be ok.' So they settle for a fifty.

The above quotation not only illustrates how demotivated students are, but it also points to the fact that some of the lecturers have no classroom management skills. Lecturers like these feel helpless as they are not equipped with strategies to motivate the students. This confirms the need for continuous professional training for such lecturers. The participants also noted that students do not seem to care much about their studies. As put by one of the participants:

...the way some students write shows that they are careless. Even if you advise them to organise their points and improve how they write, they don't really take your advice.

Another participant pointed out:

...students are always on the internet and on social media during study time.

One participant commented:

...it seems students are more concerned with financial matters (the stipend) to the detriment of their studies. They are quick to go on strike if the sponsorship money is late.

One of the participants added:

...even when they get their book allowances, they do not buy books.

From these findings, the issue of student motivation remains questionable. According to the literature, motivation stems from students' determination to do well and the satisfaction that they get after completing a challenging task (Fisher, 2003). The literature adds that when students are motivated, they get their priorities in the correct order. For instance, they put their studies first and resist the temptation to do anything else that jeopardises their learning (Biggs & Tang, 2011). When students are demotivated, it may be difficult for them to attain deep learning.

Students' studying practices and academic integrity thereof

The participants indicated that students remain passive most of the time and expect to get all the information from the lecturers. In addition, they miss classes and refuse to go to the library to find information on their own. They also resort to dishonest practices such as plagiarism. In support of this position, a participant stated:

...there is a very small percentage of students who actually remember what was taught after they have written examinations. They just write to get a certificate.

One participant commented:

...there is a lot of cramming or memorisation that is actually going on. You find that you ask for a particular concept in a test. When students answer they present the class notes as they are, word for word.

...the assignments are a disaster...students simply copy and paste. They just take stuff from the internet as it is.

Another one reiterated:

...I have even avoided giving assignments because students copy and paste. .the situation is worse because the university has not installed computer programmes that can detect plagiarism.

From the above findings, a number of practices that are associated with students' surface learning can be identified. These include passiveness in class, as well as memorisation, cutting and pasting information without synthesising it. In addition, there seems to be a number of institutional factors which make the NUL environment inadequately equipped to promote deep learning. These include the lack of supporting policies, teaching facilities, monitoring mechanisms, as well as lack of pedagogic training on the lecturers' part. The majority of the lecturers admitted that they resort to the traditional lecture method due to big classes. They are also not able to assess students to the depth that they would desire. Against this backdrop, the depth of teaching and learning approaches at NUL remains questionable.

 

RECOMMENDATIONS

As indicated in the literature, constructivism advocates the teaching activities that shift focus from the educator to the students (Biggs & Tang, 2011). In addition, the teaching and learning activities must be guided by the learning taxonomies and be constructively aligned to the learning outcomes (Biggs & Tang, 2011; Smith & Colby, 2007). In light of this view, I recommend that NUL lecturers should make use of learning taxonomies and constructive alignment in their teaching. If a lecture method has to be used, it has to be interactive at least, and should strive to elicit action from the students. These strategies may help influence the depth of teaching and learning.

The literature also indicates that assessment plays an important role since it determines what students learn, and how they learn it. Thus, if assessment focuses on low order tasks, the result will be promotion of surface learning rather than deep learning (Baeten et al., 2010; Biggs & Tang, 2011; Tek-Yew, 2011). Against this background I recommend that assessment should be strategically positioned to encourage deep learning by focusing more on higher order tasks. This can be achieved by actually constructing an assessment blueprint to determine the coverage of assessment papers in terms of high order versus low order tasks (Van Tonder et al., 2005). A shift from lower order to higher order tasks is most likely to promote deep learning.

When students are motivated, they demonstrate interest in their studies (Biggs & Tang, 2011). The literature further reveals that some of the factors which contribute to students' lack of motivation may originate from the educator or the teaching and learning environment. For instance, some educators may generate unwarranted anxiety by telling students how difficult and unachievable the task is or they may openly express a dislike for teaching a particular topic thereby causing lack of interest on the part of the learners as well (Biggs & Tang, 2011; Smith & Colby, 2007; Tek-Yew, 2011). On the basis of this, I recommend that lecturers should strive to be positive and demonstrate passion in the subjects they teach. They should also try to nurture student confidence by giving them positive reinforcement and illustrating that tasks are attainable. These strategies could help to generate interest and enhance students' motivation (Cooner, 2010).

In the absence of formal pedagogic training, some lecturers may not be aware that their behaviour is negatively affecting students' learning. Hence, I recommend that NUL should ensure that lecturers obtain the relevant continuous professional development to enhance their teaching. In this way, they can be capacitated to become reflective practitioners who are better positioned to promote deep learning (Green, 2006). Moreover, NUL should strengthen student support services. In this regard, the literature emphasises the importance of student support in ensuring the achievement of the desired learning outcomes (Biggs & Tang, 2011). Most importantly, the institution has to strengthen monitoring strategies, while at the same time fast-tracking the dissemination of relevant policies with a view to create an environment that nurtures deep learning.

 

CONCLUSION

While the NUL strategic plan seeks to achieve quality education, the institution needs to be cognisant of the fact that quality higher education can only be achieved by ensuring a shift from surface to deep learning (Bings & Tang, 2010). Reflecting on the findings of this paper, I noted some good teaching practices at NUL, such as allowing students to do research on their own, as well as the promotion of collaborative learning by some lecturers. However, the majority of the practices that emerged from the findings cast doubt concerning the quality of teaching and learning practices at the institution. The recommendations made in this paper offer some guidelines on how deep learning can be enhanced. In the final analysis, it can be noted that unless NUL takes practical steps to scaffold and nurture deep learning, its strategic goal of becoming 'a university of choice providing high quality educational experience...' (NUL's Strategic Plan, 2015: 19) could remain fruitless.

 

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Date of submission 24 July 2018
Date of review outcome 23 October 2018
Date of acceptance 10 January 2019