Determinants of graduate economics student preparation in an online environment

Abstract This paper analyses the determinants or factors that best explain student research skills and success in the honours research report module during the COVID-19 pandemic in 2021. The study reported in this paper employed the mixed methods approach comprising a quantitative and qualitative analysis. The quantitative and econometric analysis of the dependent variable, namely, the final marks for the research report and the independent variables that explain it. The results show significance in terms of the assignments and existing knowledge marks in terms of their bachelor’s average mark. We extend the analysis to a qualitative and quantitative survey, which indicated that the mean statistical feedback was above average and therefore strongly agreed/agreed except for library use by the student. Students, therefore, need more guidance in terms of library use and the open questions showed a need for a research methods course in future. Furthermore, supervision tends to be a significant determinant in all cases. It is also here where supervisors can use social media instruments such as WhatsApp and Facebook to inform students further. This study contributes as the first to investigate the preparation and research skills of students for masters and doctoral studies during the COVID-19 pandemic in an online environment.


Introduction
The Bachelor's Honours Degree is a graduate specialisation qualification on South Africa's National Qualification Framework (NQF). It is awarded at level 8 NQF. In some countries, this qualification is offered as an undergraduate degree to prepare students for graduate study. In South African universities. This degree is meant to prepare students for research-based graduate study. University of South Africa (Unisa) is one of the universities offering an honours degree at a graduate level. Examples of honours degrees at this university include Bachelor of Commerce Honours, Bachelor of Social Science Honours, Bachelor of Arts Honours, and Bachelor of Science Honours. This degree prepares students for masters and doctoral studies.
Unisa is celebrating its 150th birthday in 2023. It is regarded as the first of its kind in the world, namely, a single-mode distance education institution (Peters, 2010 p. 57). As a mega university, it is also Africa's leading open distance learning (ODL) university. Unisa's vision and mission statements, as well as the motto "Define tomorrow", relate to its African but also futuristic character. The open nature of the university means that it also serves the underprivileged. Therefore, the academic staff at Unisa need to deal with a range of unemployed, young students who are digital learners chatting online in groups (Letseka & Pitsoe, 2014). The vision and mission statements of Unisa relate to the African character of the university, with open learning catering for quality life-long learning. A further key point in the mission statement refers to addressing the needs of a diverse learner profile by offering relevant learner support, facilitated by appropriate information and communications technology (ICT) (Unisa 2030 Strategy). Online or technology-enhanced learning can assist South Africa and the African continent's young population to stay relevant, vibrant and progressive within the fast-paced modern society. The African continent has become more connected, with interconnectivity at the doorstep of most learners (Unisa 2030 Strategy).
In the corporate world, more emphasis is on skills and abilities than on academic knowledge (Royal Bank of Canada, 2018). Therefore, universities need to produce research and graduates that are relevant to industry or employment to optimise their contribution to the workplace. As such, graduateness usually covers the following key aspects (Coetzee et al., 2012): • A suite of attributes that graduates acquire during their university study; • The relationship between graduateness and employability, including employer needs and expectations; and • Student attitudes and orientation towards the labour market.
Therefore, this paper is the first attempt of investigating the determinants of the graduate Economics student preparation for master's and doctoral studies, and ultimately belonging within an online environment. Herein lies the research gap which needs to be filled with specific emphasis on the preparation of graduate students for master's and doctoral studies. Therefore, the evaluation of the Economics honours degree offering through student progress and a value accretive initiative of the College of Economics and Management Sciences (CEMS) (Unisa) transformation agenda has become essential. It will foster and create a world-class, though still uniquely African offering.
The objective of the study is therefore to find the factors that best explain the student preparation and performance in the Honours Economics Research report. Challenges faced and issues arising may include pedagogic interventions but also assisting with a more efficient, effective and economic online environment.
This study is divided into five sections. The first section describes the background and introduction. The second section is a literature review. The third section describes the research methodology. The fourth section entails a summary of the results, and the last section concludes the study.

Theoretical and empirical literature review
We provide a summary of the theoretical models considered in terms of retention. Most of these models describe the potential factors that can affect dropout and retention. Spady (1970): Sociological model Tinto (1975): An integration model Student success/throughput "is one of the most widely studied issues in higher education over the past twenty-five years". Although this research resulted in "an ever more sophisticated understanding of the complex web of events that shape student leaving and persistence . . ., most institutions have not yet been able to translate what we know about student retention into forms of action that have led to substantial gains in student persistence and graduation" (Tinto, 1975). The most compatible model adjusted to our analysis in this article is probably Bean's causal path model (Bean, 1980); (Bean, 1982). The background variables are performance, socioeconomic status, state residence, distance from home, and hometown size. The organisational determinants are routinisation, development, practical value, institutional quality, integration, university GPA [grade point average], goal commitment, communication, requirements (rules), distributive justice, centralisation, advisor, staff/faculty relationship, campus job, major (area), major (certainty), housing, campus organizations, opportunity, transfer (job) (home). Conversely, the intervening variables are satisfaction and institutional commitment. Kember (1989): A distance education model The idea is to get the best-suited theoretical model adjusted with empirical literature for the current online environment of Unisa. This has also assisted with relevant questions in the survey done at a later stage. The focus will fall on more recent studies in the South African education environment (curriculum research also) and not just within an ODeL environment. Keeve et al., 2012:121) find that for three-year-curriculum students, academic factors such as Grade 12 performance and language proficiency provide a significant explanation. Nevertheless, this does not apply to four-year-curriculum students where psychosocial factors such as parent's education level play a role. Following a study by Davis and Venter (2011), the contributing factors of graduate honours business management, and student success pertain to formative assessment, student enjoyment of the course, lecturer involvement and attendance of course workshops. In terms of international graduate students, key factors of academic success relate to good supervision mechanisms, student adjustment programmes offered for students to adjust within the country of learning, workshops and financial services, library services and individual characteristics of international students (Kaur & Singh, 2018). Rashied and Inglesi-Lotz (2017) reveal that the student-to-supervisor ratio has no significant impact on the research proficiency of an Economics Honours student. This shows that various other factors influence the research proficiency of these students. Financial difficulties, personal challenges and fewer opportunities for students to get study leave from employers can also impact throughput (Botha, 2018). Various articles refer to the importance of supervisory skills and relationships in academic success, notably Roongtawanreongsri and Awour (2018).

Research design and methodology
The research methodology is a mixed-methods analysis with sequential and exploratory design as can be seen from the diagram 1:

Diagram 1
The approach followed is that of the first described in the diagram 1, namely the sequential, explanatory design. A quantitative approach was enlightened by a description of empirical literature building to the quantitative analysis of data, using EViews for the statistical analysis of the study, which is a computer-based statistical analysis. In this study, both descriptive and inferential statistics were used in analysing quantitative data. This is because descriptive statistics are used in research to describe and summarise the data and inform what the data set looks like. Conversely, the inferential statistic allows the researcher to make predication and generalised the population. These statistics convert and condense a collection of data into an organised, visual representation or picture, in a variety of ways for the data to be meaningful. The descriptive statistics in this study include frequency distributions with minimum and maximum values, mean percentages, and standard deviation. In the case of the survey, questions are both closed and quantitative, and open and qualitative.
The purpose of the Honours research report module is to guide students in putting together a research paper that demonstrates their ability to conduct guided research in the local context. This is a 36-credit module and is presented online. Students can only choose a research topic in one of the two elective modules they were registered for or are currently registered for. Their choice of research method can be either qualitative (or descriptive-analytical) or quantitative (or empirical-econometric). Each student will be allocated a supervisor. The module delivery format is fully online. The purpose of the module is to equip students with the competencies required to plan, execute and write an acceptable academic research paper in Economics. Students will be able to reason, debate in a written format a specific economic topic, recognise existing international and national research on the topic, and integrate appropriate research methodologies in Economics. The data for the empirical analysis drew on the year 2021. This sample comprised approximately 220 students, with 152 students retained for analysis.

Empirical methodology and model specifics
To assist the student, we needed to understand the determining factors in terms of student performance. The model was designed according to previous literature as discussed earlier but additional variables have also been chosen to support the discussion behind the success rate and belonging of honours Economics students at the fourth-year level, namely: The dependent variable is effectively the final mark reached or student success, while using a dummy variable to indicate pass or failure.   Tables 1 and 3, the dependent variable is the Finalmark_Hon_Ecn which is the final mark obtained for the Economic honours research report. A further dependent variable is the Dum_Final which is the dummy used for the final mark either passed or failed. The coefficients, or explanatory variables, consist of the following: Age is the age of the student, dummy time variable ("Dum_fulltime", with a value of 1 for full-time study, else 0), dummy language variable ("Dum_HL", with a value of 1 for study in the home language, else 0), dummy gender variable ("Dum_male", with a value of 1 if for male, else 0 if female); Final_mark_B Com_Average is the average final mark reached undergraduate or in their B Com degree.

As indicated in
The assignment weight contribution is covered in the following Table 2: The assignment marks count little in the beginning and then build up to the third, fourth and final assignment mark contribution. Assignment 4 counts the most and serves also as the examination.

Profile of students
The group comprised mainly females with a mean age of approximately 32, and where students mostly did not study in their home language. The home language is included in the analysis as a reliable indicator of student success. Students need to submit four assignments during the year with the last assignment serving also as an examination. For this study, the handing in and passing of the four assignments were taken as showing effort and commitment on the part of the student.

Results and discussion
Secondary data was given through an ethical clearance from Unisa ethics committee. The results on EViews of this data suggest that the final marks of the first-, second, third and fourth assignment marks have a significant impact on the final mark (Table 3). This was obvious and to be expected looking at the weight contribution of these assignments. The better the student performs in the assignments, the better the final mark of the student. However, home language does not turn up as a contributor because these students can be regarded as more senior and more mature students in their studies. Indeed, many of the students can be considered as studying part-time, and they may be active in an environment where English is the main language of communication.
Further, within age and the status of the student, full-time or part-time, the results tend to show insignificant outcomes (see , Table 3). Existing knowledge from the B Com average mark shows significant results and confirm that pre-existing knowledge matter (Athey et al., 2007). The results       are also confirmed by the literature review in this paper. Our binary logit results turned out to be insignificant.

Survey results
This study adopted a mixed methods approach with a quantitative approach from secondary data. We went further and confirmed results by collecting primary data from 39 registered Economics Honours Unisa students of 2021 through a survey designed on Qualtrics. The quantitative and research questions developed from demographic factors and subject knowledge including assignments to supervisor influence and other factors in terms of experience or belonging that play a role (see anonymous link at https://unisa.qualtrics.com/jfe/form/SV_9GFV9IKZuIk881U). This has also expanded the study to include the dropout and retention factors. In terms of the demographic information, half of the cohort was female, most between ages 25-29 and 35-39, of which most resided in urban areas, and most were employed. Half of the cohort has parents with a qualification, and most have access to the internet at home. We have sent out a satisfaction survey to honour students to gain more insight.
We found that in terms of the descriptive statistics of the questions asked (see Table 4), the overall feedback was positive with the mean statistic above average, strongly agreed/agreed, except for the use of the library. This might mean that we need to include more information about the library for student use as a pedagogic improvement. The correlation shows the interrelationships of the questions, closed and open-ended, with the overall experience of the module significantly related to all the questions which is a sign that the questions make good sense and can be used in future with all honours groups. The supervision questions' correlation or dependence were significant and confirms the importance of supervision. This confirms De Vogel (2022) in saying that "A learning environment that is characterized by supervision security, high expectations to participate in scientific discourse, and strong support in network integration" leads to academic achievement. It is also here where supervisors used social media such as WhatsApp and Facebook besides the learning management system-MyUnisa for information sharing. In terms of the open and qualitative questions, it is positive that some students wanted a research methods course, and we are busy developing such a course for the third years economics students from 2024. The feedback is especially significant for all higher education institutions in terms of graduate preparation and research skills of students and the possibility to switch to an online environment also post COVID-19 pandemic.

Conclusion
The purpose of the Economics Honours research report module at Unisa is to guide students in compiling a research paper that demonstrates their ability to conduct guided research in the local context. It also serves as preparation measure for master's and doctoral studies. This paper analyses the determinants or factors that best explain student preparation and success for masters and doctoral studies during the Covid-19 pandemic in 2021. This study is divided into five sections. The first section describes the background and introduction. The second section is a literature review. The third section describes the research methodology. The fourth section entails a summary of the results, and the last section concludes the study. The study employed a mixed methods approach with a quantitative methodology with an econometric analysis of the dependent variable, namely, the final marks for the research report and the independent variables that explained it. The results show significance in terms of the assignments and existing knowledge marks in terms of their Bachelor average mark. However, demographic factors showed up insignificant, showing that other factors such as the supervision and the holistic experience (including belonging) become more important for graduate students. These other factors were investigated as part of a survey (including quantitative and qualitative components), confirming importance also post COVID-19 pandemic in an online e-learning environment. As an immediate pedagogic intervention, three post-graduate assistants will be appointed in the Department of Economics, Unisa, to assist all supervisors providing feedback on assignments to students. Future studies include further investigation of the supervision influence, also using social media such as WhatsApp and Facebook, and how to address the immediate needs of the Economics honours research report student, which includes preparation for masters and doctoral studies.