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NATURE OF THE STUDY
This study was exploratory by nature and, therefore, this research was mostly interpretive. According to Cohen, Manion and Morrison (2007), interpretivist research begins with individuals and how they understand and make sense of the world around them. In this study, the researcher interpreted the realities of the veterinary students as they worked and studied in a blended learning environment. How the research participants constructed their own meaning of the use of mobile technology in the blended learning environment, was therefore, the focus of the study. The way in which the participants used and experienced technology was studied in their authentic learning environment and in the everyday situations in which they found themselves during their studies. In addition, the participants in this study constructed their own meaning (Hammersley, 2007) from what they experienced (Mackenzie & Knipe, 2006) while functioning in different realities such as the activities and events that take place inside the classroom, as well as their individual experiences away from the classroom and laboratories, such as studying in private and preparing for classes.
After studying the work of authors like Myers (1997), Creswell (2012) and White (2005), the researcher realised that this study would be mostly qualitative by nature, supported by limited quantities of quantitative data in the form of descriptive statistics. Creswell (2012) states that qualitative research is best suited for exploring a particular phenomenon, as was the case in this study. Myers (1997) and White (2005) confirm that the focus in qualitative research is on understanding the social events or experiences from the participants’ point of view, while quantitative research is engaged in establishing the existence of statistically meaningful relationships between variables, by making use of data in its numerical format (White, 2005).
This research was conducted in the natural learning environment of students where the views of the participants were central (Creswell, 2007). The assumption was that because of the omnipresence of mobile devices, students were already using them in their natural learning environment. Although the use of mobile devices in class was not encouraged by all the lecturers, the researcher believes that when students are given the opportunity, they explore and find ways to use mobile devices in their learning environment to their advantage without any external prompting. Therefore, in this study, students were invited to use their mobile devices for educational activities in a natural learning environment and to then reflect on their experiences. These reflections constituted a large proportion of the data that was analysed for this study.
The reflections and feedback were analysed in patterns, themes were identified, and suggestions were made on how mobile devices could be used. This is in line with the Creswell’s (2007) definition of qualitative research as well as the characteristics he derived from the work of other researchers. He mentions that qualitative research is done in the natural setting where the researcher plays a key role in the collection of multiple forms of data. Inductive data analysis is done where the meanings of the participants are the focus, and the research emerges and changes so that the focus stays on the participants’ views. The inquiry is fundamentally interpretive and, therefore, a holistic view of the phenomenon emerged.
When describing qualitative research methods, authors such as Myers (1997), Creswell (2012) and Collins, Joseph and Bielaczyc (2004) list various methods like action research, case study research, ethnographic research, narratives, grounded theory, and design research. While each of these methods has a role to play in qualitative research, the overarching research strategy for this study fits the qualities of a case study. In this case students’ and clinicians’ views and experiences, while they worked in their natural learning environment, were the focal points of the research.
The focus of this research was also on how mobile devices can be used in a blended learning environment in higher education, this case study was exploratory in nature. Yin (2009) states that when “how” questions are asked, the research probably leads to the use of case studies. In order to explore the possibilities of using mobile devices and applications in both pre-clinical and clinical environments, a series of case-studies was done. This followed the train of thought of Yin (2009), Creswell (2007), Olivier (2009) and Stake (1995), who reason that in a case study the researcher is interested in either one event, or a series of related events, and therefore, case study research includes both single and multiple case studies (Yin, 2009). As it was important to record the experiences of the students in their various places of study, they were asked to give feedback on how they used the mobile devices while attending lectures and when doing practical work in a clinical learning environment. This is confirmed by Yin’s (2009) statement that a case study explores an event in the real-life context. Although the data included in case study research can be qualitative, quantitative or both (Eisenhardt, 1989), the aim of this research was to collect valuable insights in the experiences of the participants in the pre-clinical and clinical environments, and therefore mostly qualitative data was collected.
In this study, various data collection methods such as questionnaires, interviews, group interviews and observations were used. This is in line with an observation by White (2005), namely that case study research offers opportunities to use a variety of data collection methods. Oliver (2009) also confirms that, in his opinion, interviews and direct observations are two of the popular data collection methods in case study research.
The remaining part of the nature of the study will be discussed in relation to the two sub-questions asked, as the data collection methods and research populations differed for the various themes.
To answer the first research sub-question, namely how blended learning tools can be used to promote success among South African undergraduate students, a literature review was done about the blended learning tools that can be used to address the key factors that influence student success. Searches were conducted in academic databases and the internet, using keywords such as “blended learning”, “blended learning tools”, “blended learning in higher education”, “motivation”, “critical thinking”, “under-preparedness”, “assessment” and “higher education”. The articles found were then grouped according to identified success factors, and analysed. To relate the research done with practical applications, blended learning tools were examined to determine whether they could assist in addressing the identified success rate factors either inside or outside the classroom. The result of this relationship between blended learning tools and success rate factors was tabled at the end of the discussion of each one of the success rate factors. Further particulars are provided in Chapter 2.
In an attempt to answer the second research sub-question on how mobile devices can be used in pre-clinical and clinical learning environments, a case study methodology was followed. Because the pre-clinical and clinical learning environments, and the way students in each of these environments use their mobile devices differ substantially, the groups were separated into two related, but separate case studies.
TECHNOLOGY ACCEPTANCE MODEL
There are many technology acceptance models, each with a variety of different sets of acceptance determinants. In one such study, Venkatesh, Morris, Davis and Davis (2003) compared eight acceptance models namely the Theory of reasoned action (Legris, Ingham & Collerette, 2003), the Technology acceptance model (Davis, 1989), the Motivational model (Davis, Bagozzi & Warshaw, 1992), the Theory of planned behaviour (Ajzen, 1991), the Combined technology acceptance model and the Theory of planned behaviour (Taylor & Todd, 1995), the Model of PC utilization (Thompson, Higgins & Howell, 1991), the Innovation diffusion theory (Moore & Benbasat, 1991) and the Social cognitive theory (Compeau & Higgins, 1995). These models were empirically tested to formulate a unified theory of acceptance and use of technology (UTAUT) (Venkatesh et al, 2003).
The UTAUT (Venktesh et al, 2003) describes four direct determinants that play a role in behaviour intention and usage, namely performance expectancy, effort expectancy, social influence and facilitation conditions. For the purpose of this study, the focus was mainly on performance and effort expectancy.
Therefore, this study was rather guided by the early version of the Technology Acceptance Model (TAM) as described by Davis (1989) and Davis, Bagozzi and Warshaw (1989). Researchers frequently apply this model when they try to explain users’ acceptance and usage of technology (Venkatesh & Davis, 2000). Davis (1989) adapted his theory from the Theory of Reasoned Action (Legris, Ingham & Collerette, 2003) and suggests that two elements are central to determine whether users will commit to using technology, or not.
Firstly, researchers claims that external variables such as age, gender and education, to name a few, have an indirect influence on beliefs and attitudes (Davis et al., 1989; Durodolu, 2016; Hubona & Whisenand, 1995). Then, Davis (1989) further describes the perceived usefulness of a technology intervention. Perceived usefulness refers to prospective users’ personal belief that using a specific application system will improve the job (Davis et al., 1989). Secondly, although users sometimes see the value of adopting a specific technology, they question the degree to which they expect the target system to be “free of effort” (Davis et al., 1989:320). In this case, the perceived usefulness (PU) is influenced by the perceived ease of use (PEU) (Davis, 1989). This corresponds to the opinion of Saade and Bahli (2005) that the amount of effort needed to use a system, will have an influence on the belief that the system makes users’ work better or not.
In Figure 2 below, the relationship between the different elements in the TAM is indicated, showing clearly that the perceived usefulness and perceived ease of use directly influence the attitude towards using the system. The attitude then has an influence on whether the users will consider using the system (behavioural intention to use), and will eventually determine whether, or not, they will actually use the system.
CHAPTER 1: GENERAL ORIENTATION
-INTRODUCTION
-INTRODUCTION TO FIELD OF STUDY
-Affordances of mobile devices in higher education
-Blended learning
-Problem statement
-PURPOSE OF THE RESEARCH
-RESEARCH QUESTIONS
-NATURE OF THE STUDY
-TECHNOLOGY ACCEPTANCE MODEL
-DEFINITIONS
-ETHICAL CONSIDERATIONS
-SUMMARY
CHAPTER 2: BLENDED LEARNING
-Executive summary
-ABSTRACT
-Keywords
-INTRODUCTION
-METHODOLOGY
-BLENDED LEARNING AND BLENDED LEARNING TOOLS
-KEY FACTORS THAT INFLUENCE STUDENT SUCCESS
-BLENDED LEARNING TOOLS THAT CAN POSITIVELY INFLUENCE THE KEY SUCCESS -FACTORS
-Understanding the basic principles of the subjects
-Attitude and motivation of students towards teaching and learning
-Additional exposure to pre-testing and preparation for examinations
-Critical thinking skills (applying knowledge, problem-solving and logical reasoning skills)
-Applying theory and authentic work experience
-CONCLUSION AND FURTHER RECOMMENDATIONS
CHAPTER 3: NOTE-TAKING
-ABSTRACT
-INTRODUCTION
-LITERATURE REVIEW
-Note-taking
-Mobile devices in education
-RESEARCH QUESTIONS
-RESEARCH METHOD
-RESULTS
-Mobile device ownership and use
-Current note-taking practices
-Value of note-taking
-Devices and applications used
-DISCUSSION
-CONCLUSION
-ABSTRACT
-Keywords
-BACKGROUND
-LITERATURE REVIEW
-Note-taking
-Mobile devices in education
-Videos in education
-METHODOLOGY
-RESULTS
-Mobile devices students experimented with during video note-taking
-Action cameras (GoPro)
-Handheld video cameras
-Tablets
-Mobile phones
-Video as a note-taking tool during practical classes
-Benefits students experienced
-Suggestions when making videos
-RECOMMENDATIONS FOR FURTHER RESEARCH
-DISCUSSION AND CONCLUSION
-ABSTRACT
-Keywords
-INTRODUCTION
-METHODOLOGY
-RESULTS
-Why are the students recording video?
-Who are using the GoPro to make the recordings?
-What are the students recording?
-When are the students using the GoPro cameras?
-Where are they making the videos?
-DISCUSSION
-CONCLUSION
-ABSTRACT
-Keywords
-INTRODUCTION
-THE VALUE OF NOTE-TAKING AS A LEARNING ACTIVITY
-NOTE-TAKING WITH AN ELECTRONIC DEVICE
-THE AVAILABILITY OF MOBILE DEVICES
-RESEARCH DESIGN
-RESULTS AND DISCUSSION
-Open and edit existing notes
-Input mode
-Using the camera
-Accessibility of notes
-Organising and sharing notes
-NOTE-TAKING APPLICATION AFFORDANCES
-CONCLUSION
CHAPTER 4: VETERINARY EDUCATIONAL SOFTWARE
-ABSTRACT
-Keywords
-INTRODUCTION
-METHODOLOGY
-RESULTS
-Ease of use and Usefulness of Vetbox
-Motivation to use Vetbox
-Mobility and Accessibility
-Training
-DISCUSSION
-CONCLUSION
-ABSTRACT
-Keywords
-INTRODUCTION
-BACKGROUND AND CONTEXT
-LITERATURE REVIEW
-THE TECHNOLOGY ACCEPTANCE MODEL (TAM)
-METHODOLOGY
-RESULTS
-Booking system
-Logging system
-Assessment
-CONCLUSION
CHAPTER 5: CONCLUSION AND RECOMMENDATIONS
-INTRODUCTION
SUMMARY..
-Research questions
-Blended learning (Chapter 2)
-Note-taking (Chapter 3)
-Veterinary educational software (Chapter 4)
-METHODOLOGICAL REFLECTION
-SUBSTANTIVE REFLECTION
-SCIENTIFIC REFLECTION
-PERSONAL REFLECTION AND POSSIBILITIES FOR FUTURE RESEARCH
LIST OF REFERENCES
