Perspectives of Management Accounting Education Online

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CHAPTER THREE: METHODOLOGY

INTRODUCTION

In the previous chapter, the literature review established some theoretical and contextual foundations on which this research is based. The current chapter outlines the methodology used in this study as well as the rationale in choosing a mixed-methods approach, the design of an online quantitative survey and the unstructured interview questions.
The purpose of this research is to explore and investigate ways of how e-learning can be deployed to enhance the learning and teaching of Management Accounting at Unisa. The study relied on the mixed methods research design because this enables the researcher to study complex phenomena within their context. In this study, the researcher seeks to develop a detailed understanding of the processes of how students and instructors experience and evaluate online learning in Management Accounting using the myUnisa e-learning platform. The detailed understanding of the phenomena is hoped to provide useful information that can further inform researchers and educational practitioners.
The layout of the chapter is as follows: Section 3.2 introduces the Research Onion. Section 3.3 discusses the philosophical stances while Section 3.4 portrays the approaches. Section 3.5 discusses the strategies, whereas Section 3.6 explores the choices that the researcher has. Section 3.7 gives the time horizon of the research while Section 3.8 discusses the techniques and the procedures of the research. Section 3.9 discusses the population of the study. Section 3.10 introduces sampling and sample sizes while Section 3.11 discusses random samples. Section 3.12 discusses judgemental sampling and Section 3.13 sample size table. Section 3.14 discusses technological glitches. Data collection and analysis is covered in Section 3.15. Section 3.16 discusses the validity of the study and Section 3.17 covers the reliability of the study. Section 3.18 is about ethical considerations. Section 3.19 gives a summary of the chapter.
The next section introduces the research onion, which is used to guide the discussion of the methods employed in this research. Figure 3.1 illustrates the research onion.

THE RESEARCH ONION

The suggested research onion has six layers, with each layer having one or more further items that the researcher would be required to choose from. The layers are indicated in order from the outside as: the philosophical orientation of the researcher; the research approaches adopted; appropriate research strategies; the research time lines under consideration; and the data collection and analysis techniques employed by the researcher (Saunders, Lewis & Thornhill 2012).

PHILOSOPHICAL STANCES

Layer one of the research onion contains the philosophical stances associated with the philosophies. Each choice at this level requires careful thought since they provide structure and guidance, and possible limitations to subsequent decisions and ultimately how the researcher can collect and analyse data to create valid findings (Sapford 2007). The researcher adopted the constructivism philosophical stance at this level. The other philosophies like interpretivism, pragmatism or positivism may be used whenever applicable.
Objectivism recognises that social phenomenon and their meanings exist separately to social actors. Constructivism argues the opposite to objectivism. It believes that social phenomena are actually by social actors. Constructivism is one of the theories discussed at length in the framework. It is also the ontological worldview of choice on the philosophical stances. Creswell (2014) discusses constructivism extensively, and how it might contribute towards knowledge construction in general. The two main reasons for this choice are, firstly, constructivism is the preferred theoretical approach when it comes to new areas of study like e-learning. Moreover, when using the qualitative approach, constructivism is better suited as a theoretical approach (Creswell 2014). This research uses qualitative analysis for the unstructured interviews held with lecturers.
Positivism generates hypotheses or research questions that can be tested. Any explanation can be measured against knowledge of the worldviews. Emphasis is on quantitative results that lend themselves to statistical analysis (Neuman 2011; Babbie 2013). Realism is similar to positivism in its processes and belief that social reality and the researcher are independent of each other. Interpretivism refers to approaches emphasising the meaningful nature of people’s participation in social and cultural life (Mouton 2001; Neuman 2011). Researchers analyse the meanings people confer upon their own and others actions and hope to understand the changes and meanings attached by these people. Pragmatism argues that both constructivism and objectivism are valid ways to approach research. Pragmatism allows the researcher to view the topic from either or both points of view, which creates a practical approach to research. Therefore, there are times when there are interactions of these philosophies.

APPROACHES

A pilot study had been carried out during the design of the interview questions and the online questionnaire. The questions were pilot-tested on Unisa students and tutors doing Management Accounting (MAC2601) at a Unisa satellite campus. The researcher incorporated the suggestions and recommendations of the students and tutors before taking his draft questions to the supervisors for further scrutiny. The supervisors gave their input and suggestions both for the interview questions and the questionnaire. The online questionnaire was further taken to a statistician who also gave his professional views. Once in final format, the supervisors gave the researcher permission to carry out the interviews and administer the online survey.
In layer two, the researcher used both the deductive and the inductive approaches when there was a need. A survey strategy is associated with a deductive approach. Survey research is the collection of data obtained by asking questions in person, on paper, by phone or online. The researcher sent an online questionnaire in order to collect data from the respondents. Conducting the survey is one form of primary research that is obtaining data from source. When the same data is accessed by other interested parties later, it will be a form of secondary research. Common types of survey include interviews and questionnaires usually comprised of multiple choice questionnaires, opinion or pols. Questionnaires were to be distributed through mail surveys while interviews would be held in person or over the phone. A survey offers the researcher an economical way of collecting large amounts of data which can address the what, who, whom, where, when and how of any given topic (Sapford 2007). Deduction goes in the opposite direction to that of induction. A deductive method is an approach where conclusions are drawn from general laws, theories or hypotheses in quantitative analysis. Induction, on the other hand, is a method by which one attempts to arrive at a theory or general knowledge by summarising observations of occasional incidents or phenomena (Creswell, 2014) as in qualitative analysis. Onwuegbuzie, Bustamante and Nelson (2010) state that mixed methods research includes the use of induction, which refers to the discovery of patterns, deduction, which involves testing theories and hypotheses, and abduction, which refers to uncovering and relying on the best set of explanations for understanding the results. Therefore, the researcher used the inductive approach to analyse the interviews and the deductive approach to analyse the survey instrument.

STRATEGIES

Case study design involves one or more individuals or cases in the real context. The number of cases need to be restricted in order to draw clear conclusions about the cases. The data to be collected may include interviews with participants or watching aspects of their behaviour.
The online survey used a questionnaire with thirty-seven (37) Likert type statements. A questionnaire is a form containing a set of questions, especially addressed to a statistically significant number of subjects and is a way of gathering information for a survey. The Oxford living dictionary (2018) defines a questionnaire as a written or printed list of questions to be answered by a number of people, especially in a particular survey. This instrument was emailed to all the participants in the sample and later to all the participants in the population. Repeat e-mails were also done (twice) reminding participants of the invitation.

CHOICES

Mixed-method is when the researcher uses qualitative and quantitative methods in the process of the study, data collection and data analysis. This is the method the researcher used and it has clear benefits as highlighted by Bergman (2008). Mixed method research evolved in response to the observed limitations of both quantitative and qualitative designs and is a more complex approach (Caruth 2013). Mixed methods research offers richer insights into the phenomenon being studied and allows for the capture of information that might be missed by using only one research design. It also enhances the body of knowledge and more questions of interest for future research. It can furthermore handle a wider range of research questions as it is not limited to one research design (Onwuegbuzie & Leech 2010).
Quantitative researchers have often claimed that qualitative research is hard to generalise, interpret, and duplicate. Meanwhile, qualitative researchers have claimed that quantitative researchers utilised immaterial hypotheses and shallow descriptions (Caruth 2013). The goal of quantitative research is to propose a hypothesis to be either accepted or rejected, while the goal of qualitative research is to produce a hypothesis (Caruth 2013). Therefore, the mixed method approach has certain strengths and weaknesses as explained in the next sections.
This research adopted a mixed-method approach. Onwuegbuzie and Leech (2010) define mixed method as a method that includes both qualitative and quantitative data collection and analysis in parallel. It is a type of research in which a researcher uses the qualitative research paradigm for one phase of the study and a quantitative research paradigm for another phase. Onwuegbuzie and Leech (2010) claim that mixed-method is a natural complement to using either the qualitative or quantitative research methods in isolation. Therefore, mixed method is a type of research where the researcher mixes qualitative and quantitative research techniques, methods, approaches, concepts or languages in a single study.
Onwuegbuzie et al (2010) state that mixed method includes the use of induction, which refers to the discovery of patterns, deduction which involves testing theories and hypotheses, and abduction which refers to uncovering and relying on the best set of explanations for understanding the result. Onwuegbuzie and Leech (2010) identified the following rationales for mixing qualitative and quantitative approaches: participant enrichment, instrument fidelity, treatment of integrity and significance enhancement. Participant enrichment entailed that the number of participants were increased from 1,176 to 5,884 by the researcher, because Onwuegbuzie and Leech (2010) argue that the larger the sample, the more reliable and valid the research findings will be. The researcher had to increase the sample size to obtain more responses. If the researcher had obtained a satisfactory response rate, he would not have increased the sample size.
According to van der Merwe (1996), quantitative research uses methods from the natural sciences that are designed to ensure objectivity, generalisability and reliability. Denzin and Lincoln (2012) define qualitative research as a situated activity, which locates the observer in the world. It involves an interpretive, naturalistic approach to the worldview. Denzin and Lincoln (2012) argue that human learning is best researched by using qualitative data. The central phenomenon in this study is about how students experience and evaluate online learning. One question, which may have to be answered is: Which research methodology might satisfactorily address how to investigate the way in which distance students experience and evaluate online learning? Guba (1990) suggests selecting a research methodology that supports the paradigm whose assumptions are best met by the phenomena being investigated.
This study is about e-learning, and seeks to understand how distance students experience and evaluate this mode of learning. The qualitative approach will be suitable for part of this exploration. Qualitative approaches are becoming more widely used as methods improve and researchers look for better ways of gathering data about a problem (Denzin & Lincoln, 2012). The qualitative approach will be used to analyse the interview questions and other open-ended questions on the online survey, while the online survey will be analysed quantitatively using statistical techniques.
The basic sets of beliefs that guide an action are sometimes called paradigms, epistemologies or ontologies or broadly conceived research methodologies (Babbie 2013; Neuman 2011; Creswell 2014). Denzin and Lincoln (2012) suggest that a paradigm consists of ontology, epistemology, methodology, and, methods. The highest level of complexity in research is referred to as the methodological paradigm. This includes qualitative and quantitative paradigms (Mouton 2001; Neuman 2011). Qualitative research is described as a paradigm that allows the research to obtain an insider perspective on social action (Babbie 2013). Qualitative data is usually rich and informative. A qualitative approach is more likely to uncover the subjective experiences of participants, discover their perceptions, and is more likely to focus on the meanings that individuals attribute to their experiences (Denzin & Lincoln 2012). Each paradigm makes its own assumptions about the nature of reality (Babbie 2013). Issues of research methods are secondary to questions of paradigm in that the paradigm which is the world view, guides the investigator in the choice of methods (Creswell 2014). These are some of the reasons the researcher included the interviews in combination with the online survey.
In quantitative research, the researcher decides what to study and asks specific questions; collects quantifiable data from participants; analyses the numbers using statistics, and conducts the inquiry in an unbiased objective manner (Creswell 2014). On the other hand, in qualitative research, the researcher relies on the views of participants; asks broad, open-ended and general questions; collects data consisting mostly of words and statements from participants (or shows them pictures or diagrams); describes and analyses these words for themes; and conducts the inquiry in a subjective, biased manner (Creswell 2014). Quantitative research is “Explaining phenomena by collecting numerical data that are analysed using mathematically based methods” (Denzin & Lincoln 2012:21). In research, the objective is always to explain something, usually phenomena.
Quantitative research methods are used when a research question is demanding a quantitative answer. Generally, quantitative research methods can cover breadth but usually not depth. Research is deemed good if it provides rich evidence and offers credible and justifiable accounts, if it can be utilised by someone in another situation, and if the research process and findings can be replicated (Cohen, Manion, & Morrison 2007). However, quantitative studies appear to lack the sensitivity to aid understanding of the nature, quality or processes engaged within an experience (Denzin & Lincoln 2012). These limitations led to the choice of a mixed method research design in this thesis.
Figure 3.2 aims to capture the interrelationship of the philosophical stances, methodologies and design approaches of research problems.

TIME HORIZON

Cross-sectional designs can use quantitative and qualitative research as they measure an aspect or behaviour of the many groups or individuals at a single point in time. The time-horizon for the study was cross-sectional. Longitudinal design can use qualitative and quantitative research, but they study events and behaviours using concentrated samples over a longer period (Field 2009). This research was limited to the original timeframe and any slippages in terms of time-horizons were coincidental and not intended. While this study was cross-sectional in nature, the researcher believes that a longitudinal research could be useful to establish how students experience and evaluate online learning over a number of years, say from first year to third year, as suggested by Schneider and Stern (2010).

TECHNIQUES AND PROCEDURES

The last (innermost) layer of the research onion moves the research design into the practicalities of data collection and analysis. The researcher is best suited to decide on the methods to employ in order to answer the research questions. The layer includes decisions on the sample groups, questionnaire content, and questions to be asked in interviews. The decisions and tools employed at this final stage must comply with the philosophies, philosophical stances, strategies, choices and time-horizons already stipulated if results are to be created (Brace 2008). Questionnaires, mostly about the myUnisa platform, were used as research instruments of this study. The literature review was used to construct questionnaires for the online survey. More detail about how data was collected including some challenges is covered in Section 3.14 – Technological Glitches.
Research design is a plan for collecting and analysing evidence that will make it possible for the researcher to answer questions that may be posed. The design of an investigation includes all aspects of the research, from data collection details to the selection of the techniques of data analysis (Neuman 2011; Babbie 2013; Creswell 2014). Qualitative and quantitative research differs in some ways and yet they can complement each other. Qualitative research relies on soft data such as impressions, words, sentences, symbols, diagrams, photos, etc. and, and it gathers rich data while quantitative research relies on specific data in the form of numbers. The two approaches use different research strategies. Qualitative data involves documenting real events, recording what people say, their words, gestures, tone, observing specific behaviours, studying written documents, or examining visual images (Mouton 2001; Neuman 2011).
The following is a description of the methodology that the researcher utilised in order to collect the relevant data. The researcher designed twenty-four unstructured interview questions; these were directed at the lecturers and were processed qualitatively. The researcher also designed a quantitative instrument mostly around the myUnisa platform and was processed quantitatively. These two appear in Appendix A and B respectively. The methodology, therefore, became a mixed method approach. The mixed method approach is superior to a mono method that is either a quantitative or a qualitative method, because it combines both quantitative and qualitative perspectives.
The researcher, supervisors and the Unisa statistician met on several occasions in order to agree on the structure and strategies to be followed when implementing the online survey. The recommendations by the statistician and supervisors were followed; these included the structure of the instruments, the total number of items and their possible effects to validity and reliability.
For the purpose of this study, the questionnaire (Appendix A) formed the primary data collection method, and its content was guided by the literature reviewed and recommendations from the statistician. The advice from the statistician was helpful with regard to obtaining validity and reliability of the items for statistical purposes. The statistician recommended thirty-seven items in the instrument based on the anticipated sample size. The questionnaire was administered initially to 1,176 participants, and later increased to the total population of 5,884 because of a poor response rate.

POPULATION OF THE STUDY

In order to define a population, the researcher specifies the unit being sampled, the geographical location, and the temporal boundaries of the population (Mouton 2001; Neuman 2011). Any characteristic of a population is called a population parameter. A population can be in two categories namely: the target and the accessible populations. The target population is the actual population that the researcher would ideally like to generalise. However, this population is rarely available. Therefore, the population that the researcher is able to generalise is the accessible population. In other words, a population is the theoretical specified aggregation of the elements in a study (Babbie 2013). This population refers to the complete set of elements and their characteristics about which a conclusion is to be drawn, based on a sample. This population includes all individuals whom the researcher is interested in obtaining information from, and making inferences. In this study, the population studied included all second year Management Accounting students registered at Unisa in 2015. This amounted to 5,884 students.

SAMPLING AND SAMPLE SIZE

While it is not necessary to collect data from every individual in the population in order to get valid findings, it would naturally enhance the reliability of the study. In qualitative and quantitative research, only a sample of a population is selected for any given study. A sample is a smaller set of cases that a researcher selects from a larger pool (population), and may generalise results to the whole population (Babbie 2013; Neuman 2011). A researcher needs to choose a sample because this would be more affordable in terms of time and costs. A good sample needs to be representative and it needs to deepen an understanding about the population at large. Representative samples are based on theories of probability from mathematics. The ratio of the size of the sample to the size of the target population is the sampling ratio. Generally, a representative sample can give more accurate predictions about a specific sample.
There are two ways of choosing a sample, namely:
Probability (random) sampling which ensures that the probability of each case being selected from the population is known and is usually equal for all cases (Babbie 2013).
Non-probability (non-random) sampling is a sampling technique where the samples are gathered in a process that does not give all the individuals in the population equal chances of being selected (Babbie 2013).
The major difference between the two methods is that probability sampling allows the reliability of the sample results in approximately the population statistics under study. In non-random sampling, this assessment of reliability is not possible regardless of how careful the researcher is in selecting elements of the sample. Naturally, in non-random sampling, there is no guarantee that the samples represent the populations being studied (Leedy 2010). The researcher should, however, strive to ensure the sample is representative of the population under study, and that the outcome of the research can be relied upon.

RANDOM SAMPLES

Probability theory in applied mathematics relies on random processes (Mouton 2001; Neuman 2011). In a random process, each element has an equal probability of being selected. A simple random sample represents a sample design in which selections are drawn from a population in a way that gives every member and every combination of members an equal chance of being selected (Creswell 2014). Arguably the simplest way to select a simple random sample is to assign every member of the population a number and use a random number generator (captured as a table) to select the sample.
Simple random samples are important because randomness eliminates bias in research surveys. Moreover, many results in statistics are derived from probability theory. The use of probability assumes that random processes are at work. For statistical results to be valid, samples that can be treated as random variables should be chosen. However, some disadvantages are that, simple random samples can be very difficult to obtain in practice. Sometimes the mechanism for guaranteeing a truly random selection requires some ingenuity (Creswell 2014). Generally, human subjects make matters worse as they can simply refuse to participate in a statistical sample. The researcher experienced some of this resistance from prospective participants in this study as highlighted earlier.
Systematic sampling is simple random sampling which employs a shortcut for random selection. In systematic sampling, you choose every nth individual in the population until you reach your desired sample size (Creswell 2014). He further states that the researcher calculates a sampling interval by skipping elements in the frame before selecting one for the sample. This procedure is not as precise and rigorous as using the random numbers table, but it is convenient because individuals do not have to be numbered. In this study, the sample was initially chosen by selecting every fifth student number until 1,176 participants of the online survey were chosen.
Systematic sampling was employed in this study, since it has many advantages (Creswell 2014):
It is simple to implement.
It may be started without a complete listing frame.
It provides for a better random distribution than simple random sampling. The variance may be smaller than for simple random sampling.

TABLE OF CONTENTS
Abstract 
Acknowledgements 
List of Publications 
List of Figures 
List of Tables 
List of Abbreviations and Acronymns 
Chapter One: Introduction 
1.1 Introduction
1.2 background to the problem
1.3 Problem Statement
1.4 Research questions
1.5 Research objectives
1.6 Research Methodology
1.7 Literatrue Review
1.8 Definition of terms and concepts
1.9 Assumptions
1.10 Limitations
1.11 Delineations
1.12 The significance of the study
1.13 Ethical issues
1.14 Layout of the Thesis
1.15 Summary
Chapter Two: Literature Review 
2.1 Introduction
2.2 Distance Education
2.3 E-Learning
2.4 Online Learning
2.5 Perspectives of Management Accounting Education Online
2.6 Management Accounting
2.7 Challenges in Management Accounting
2.8 The Changing Focus of Educational Technology
2.9 The Models of Frameworks
2.10 Theories of Learning
2.11 Cognitivism
2.12 Cconstructivism
2.13 Scaffolding
2.14 Learning Communities
2.15 Cognitive Presence
2.16 Social Presence
2.17 Teaching Presence
2.18 Interaction
2.19 Summary
Chapter Three: Methodology 
3.1 Introduction
3.2 The Research Onion
3.3 Philosophical Stances
3.4 Approaches
3.5 Strategies
3.6 Choices
3.7 Time Horizon
3.8 Techniques and Procedures
3.9 Population of the Study
3.10 Sampling and Sample Size
3.11 Random samples
3.12 Judgemental sampling
3.13 Sample size Table
3.14 Technological Glitches
3.15 Data Collection and Analysis
3.16 Validity of the Study
3.17 Reliability of the Study
3.18 Ethical Considerations
3.19 Summary
Chapter Four: Preliminary E-Learning Framework 
4.1 Introduction
4.2 Open Distance Learning
4.3 Current Developments
4.4 Assumption
4.5 Constructivism
4.6 The Need For an E-Learning Framework
4.7 Suggestions synthesised from the analyses
4.8 Challenges emanating from Table 4.1
4.9 Contributions of the analyses
4.10 Observations
4.11 Analysis of the Framework
4.12 Further Value Added by the Framework
4.13 Summary
Chapter Five: Learning Management Systems 
5.1 Introduction
5.2 The Concept of Learning Management Systems
5.3 Learning Management Systems (LMSs) and Virtual Learning Environments(VLEs)
5.4 Philosophies Driving Some Learning Management Systems
5.5 Moodle
5.6 Sakai
5.7 Claroline
5.8 Comparison of the three LMSs – Moodle, Sakai and Claroline
5.9 Philosophies
5.10 Further metrics of comparison
5.10.1 Verdict
5.11 Sakai Learning Platform
5.12 Evaluating the Utility of the Framework for an LMS
5.13 Summary
Chapter Six: Conceptual Evaluation of the framework 
6.1 Introduction
6.2 Open Distance electronic Learning
6.3 Utility of the Framework
6.4 Knowledge Management Frameworks
6.5 Knowledge Acquisition and Construction
6.6 Understanding How Students Learn
6.7 Theories of Learning
6.8 Scaffolding
6.9 Online Learning
6.10 A Costing Scenario
6.11 Validating the Utility of the Framework
6.12 Summary
Chapter Seven: Qualitative and Quantitative Evaluation
7.1 Introduction
7.2 Analysis of the Interviews
7.3 Qualitative Findings
7.4 Limitations
7.5 Presentation of Results from Questionnaire
7.6 Summary
Chapter Eight: Conclusion, Recommendations and Future Work 
8.1 Introduction
8.2 Recommendations
8.3 Future Work
References
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