EXPERIENTIAL LEARNING THEORIES OF WORKPLACE LEARNING

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CHAPTER 3: RESEARCH METHODOLOGY

INTRODUCTION

Chapter 1 outlined the general orientation to this study. The rationale for this study and its aims and objectives as well as the research questions guiding the investigation were also presented. A review of the literature in Chapter 2 highlighted the gap between the formal learning (theory) and the informal workplace learning (application of the theory) of statisticians, which served to confirm the need to integrate statisticians’ formal learning with their workplace learning. Should this integration not take place, it would be very difficult to close or at least narrow the skills gap experienced in certain statistical areas. In the literature that was reviewed it was stressed that integrating the formal learning of statisticians with their workplace learning was not a mere need but a necessity due to the important role that statisticians fulfil at all levels of society. To this end, this research assessed the effectiveness of an internship programme as a method for integrating the formal learning of statisticians with their workplace learning.
The main research question for this study, as indicated earlier, (see paragraph 1.4) was: How can the formal learning of statisticians be integrated with their informal workplace learning to ensure that statistical graduates are equipped to fill areas where statistical shortages are experienced? This study was a convergent, parallel constructivist, mixed-method case study, the purpose of which was to collect data to answer the following research questions about internship programmes for statisticians:

• What are the respondents’ (intern statisticians) and participants’ (mentors) views and experiences about the role of institutions of higher learning in South Africa in the work readiness of statisticians?
• What are the respondents’ views and experiences regarding integration between their formal and informal workplace learning?
• How is the informal learning of statisticians supported in the workplace?
• What suggestions can be made to Stats SA and institutions of higher learning to ensure integration between the formal and informal workplace learning of statisticians?

INQUIRY STRATEGY AND BROAD RESEARCH DESIGN

Research paradigm

Cohen et al (2011:5) define a research paradigm as “a way of pursuing knowledge” based on principles that guide the researcher as to what phenomena or problems are worth researching and what the best research method would be. Bryman (2012:30) and Cohen et al (2011:5) refer to two views of research in the social sciences, the first of which is the positivist or “established traditional” view according to which research is “essentially the same as the natural sciences” and is “concerned with discovering the natural and universal laws regulating and determining individual and social behaviour”. The second view is the interpretive view that “emphasises how people differ from inanimate natural phenomena, and indeed, from each other” (Cohen et al 2011:5). In order to best explain the view that is appropriate for this study, it is necessary to first investigate the epistemological and ontological assumptions on which these two views are based (Cohen et al 2011:5).
The epistemological position of any study indicates the understanding of the nature of knowledge and how it can be acquired. Cohen et al (2011:5) and Nieuwenhuis (2007:81) see ontology as assumptions which concern the very nature or essence of the social phenomena being investigated.
Epistemology is defined as “the nature of knowledge – its nature and forms, how it can be acquired and how [it can be] communicated to other human beings” (Cohen et al 2011:6). The epistemological position of this study – its understanding of the nature of knowledge and how it can be acquired, is an interpretivist one. The main focus of this paradigm is to understand man’s activity and behaviour, or, as Cohen et al (2011:17) put it, to “understand the subjective world of human experience”.

The interpretivist paradigm

In an interpretivist paradigm the focus is on people’s subjective experiences of the world, and this paradigm is based on the ontological belief that reality is socially constructed (Bryman 2012:28). I identified the interpretivist paradigm as the most suitable mode of enquiry since the intention of this study was to understand, describe and interpret the experiences and views of intern statisticians and their mentors of the integration between formal and informal workplace learning rather than to explain this phenomenon (Cohen et al 2011:17). Since the underlying assumption of this study was that statisticians learnt through experience and while interacting with others (as explained in Chapter 2), the interpretivist approach was deemed to be the most suitable approach for this study. The nature of inquiry based on this paradigm is interpretive and the purpose is to understand a particular phenomenon and not to generalise it to a population (Farzanfar 2005).
The logic of reasoning in this study was inductive since the aim was to understand how both Stats SA and institutions of higher learning approached the formal and informal workplace learning of statisticians with a view to closing the perceived statistical skills gap currently experienced in South Africa.

 RESEARCH APPROACH

A research approach, which can be classified into three major categories, namely, quantitative, qualitative and mixed method (McMillan & Schumacher 2006:22), outlines how a study is conducted. These three research approaches are discussed next.

Quantitative approach

When the aim of the research is to describe a situation exactly as it is, a quantitative approach is usually be employed (Leedy & Ormrod 2005:179). This study employed a self-administered online survey to collect quantitative data from participants.

Qualitative approach

Qualitative research is usually employed when one wants to understand the meaning that people assign to a particular problem (Creswell 2014:3).If the intention of a study is to obtain information regarding attitudes, views, opinions or previous experiences of a group or groups of people, then a qualitative research approach would normally be employed (Leedy & Ormrod 2005:183).

Mixed-method research approach

Initially there were only two approaches to data collection, namely, quantitative and qualitative. The mixed-method approach (a combination of both quantitative and qualitative approaches) emerged around the late 1980s and early 1990s when researchers discovered that it might be an excellent approach to answering research questions (Creswell 2014:81; McMillan & Schumacher 2006:401). Creswell (2014:217) is of the opinion that mixing data from both approaches leads to a better understanding of the problem under investigation.
I employed a mixed-method approach for this study. However, the qualitative approach carried more weight than the quantitative approach: interviews were conducted with the mentors in order to obtain rich data since they were the ones who had more experience and could provide more insight into what was needed to inform the framework. Surveys were conducted in order to compare the views of the interns and the mentors in order to obtain rich data to assist in answering the main research question: How can the formal learning of statisticians be integrated with their informal workplace learning to ensure that statistical graduates are equipped to fill areas where statistical shortages are experienced?
I collected both quantitative and qualitative data concurrently to provide a more comprehensive understanding of the research problem (Creswell 2014:217), thus a mixed-method research approach was followed. By combining both quantitative and qualitative approaches, I hoped to gain better insight into the problem under investigation. Creswell (2014:217) is of the opinion that by analysing the data obtained from both quantitative and qualitative sources in the form of responses to research questions, a better understanding of the research problem can be gained.
The different types of mixed-method approaches as illustrated by McMillan and Schumacher (2006:404) are presented in Figure 6 below.
According to the above-mentioned approach, quantitative and qualitative data is gathered simultaneously whereafter both quantitative and qualitative data analysis methods are used to merge the two data sets and then interpreted together. Even though one can follow the other, equal emphasis is give to each method. Both methods can also conducted simultaneously (McMillan and Schumacher 2006:404).
After collecting the quantitative and qualitative data simultaneously as already mentioned, I also interpreted the results concurrently to obtain a better understanding of the phenomenon being investigated, namely, Stats SA’s internship programme and its role in terms of the integration between the formal and informal learning of statisticians (McMillan & Schumacher 2006:404). The concurrent collection of both quantitative and qualitative data is referred to by Creswell (2014:220) as the “convergent parallel mixed method approach”, which is illustrated in Figure 7.
The mixed-method approach allowed me to collect data by means of self-administered questionnaires that were mailed to the respondents (interns) (phase 1). I could continue with conducting interviews with the participants (mentors) in person (phase 2) while awaiting responses requested during the quantitative phase.
McMillan and Schumacher (2006:404) refer to a mixed-method study whereby both quantitative and qualitative data are gathered simultaneously as the triangulation mixed-method approach. In this approach, a researcher merges the data gathered by making use of both quantitative and qualitative data analysis methods and then “interprets the results together” in order to better understand the phenomenon that is being investigated. This process is illustrated in Figure 8.

CHAPTER 1: GENERAL ORIENTATION
1.1 INTRODUCTION
1.2 PROBLEM FORMULATION
1.3 PURPOSE STATEMENT
1.4 RESEARCH QUESTIONS
1.5 AIM AND OBJECTIVES OF THE STUDY
1.6 RESEARCH DESIGN
1.7 RESEARCH POPULATION, SAMPLE AND SAMPLING METHOD
1.8 VALIDITY
1.9 SIGNIFICANCE OF THE STUDY
1.10 DELIMITATIONS AND ASSUMPTIONS OF THE STUDY
1.11 OUTLINE OF CHAPTERS
1.12 CHAPTER SUMMARY
CHAPTER 2: INTEGRATING THE FORMAL LEARNING OF STATISTICIANS WITH THEIR INFORMAL WORKPLACE LEARNING
2.1 INTRODUCTION
2.2 THE IMPORTANCE OF STATISTICS FOR NATIONAL DEVELOPMENT AND THE NEED FOR DEVELOPING STATISTICIANS
2.3 FORMAL LEARNING THEORIES
2.4 FORMAL LEARNING
2.5 EXPERIENTIAL LEARNING THEORIES OF WORKPLACE LEARNING
2.6 WORKPLACE LEARNING
2.7 INTEGRATING THE FORMAL LEARNING OF STATISTICIANS WITH THEIR WORKPLACE LEARNING
2.8 INTERNSHIP AS A VEHICLE TO FACILITATE THE PROCESS
2.9 CONCEPTUAL FRAMEWORK FOR INTEGRATING FORMAL LEARNING WITH WORKPLACE LEARNING .
2.10 CONCLUSION
CHAPTER 3: RESEARCH METHODOLOGY
3.1 INTRODUCTION
3.2 INQUIRY STRATEGY AND BROAD RESEARCH DESIGN
3.3 RESEARCH APPROACH
3.4 RESEARCH DESIGN
3.5 DATA COLLECTION
3.6 DATA ANALYSIS METHODS
3.7 STEPS TAKEN TO ENSURE THE QUALITY AND RIGOUR OF THE RESEARCH
3.8 ETHICAL CONSIDERATIONS
3.9 CONCLUSION
CHAPTER 4: PRESENTATION AND ANALYSIS OF THE FINDINGS
4.1 INTRODUCTION
4.2 QUANTITATIVE RESULTS (ONLINE SURVEY)
4.3 QUALITATIVE FINDINGS (SEMI-STRUCTURED INTERVIEWS WITH MENTORS)
4.4 DOCUMENT ANALYSIS
4.5 CONCLUSION
CHAPTER 5: DISCUSSION OF FINDINGS
5.1 INTRODUCTION
5.2 WORK READINESS
5.3 UTILISATION OF SKILLS
5.4 SUPPORT FOR INFORMAL LEARNING IN THE WORKPLACE
5.5 DEVELOPMENTAL PRACTICES
5.6 BENEFITS OF INTEGRATING THE FORMAL LEARNING OF STATISTICIANS WITH THEIR INFORMAL WORKPLACE LEARNING
5.7 CONCLUSION
CHAPTER 6: EVALUATION OF RESEARCH, CONCLUSION, LIMITATIONS AND RECOMMENDATIONS
6.1 INTRODUCTION
6.2 EVALUATION OF THE RESEARCH
6.3 CONCLUSION OF THE RESEARCH
6.4 FRAMEWORK TO INTEGRATE THE FORMAL LEARNING OF STATISTICIANS WITH THEIR INFORMAL WORKPLACE LEARNING
6.5 LIMITATIONS OF THE RESEARCH
6.6 UNIQUE CONTRIBUTION OF THE RESEARCH
6.7 AREAS FOR FUTURE RESEARCH
6.8 CONCLUSION
REFERENCES
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A framework to integrate the formal learning with the informal workplace learning of statisticians in a Developmental state