Research Proposal: Research Design

In my previous post I discussed my research questions and objectives. This follow up post discusses my current thinking of the research design of my project.


I will follow a qualitative approach as this is an exploratory investigation that seeks to derive theory from data collected in a social setting (Babbie, 2010; Cresswell, 2009). In this context, the setting is Open and Distance Learning (ODL) universities. This investigation proposes the use of a Grounded Theory (GT) approach along with a Case Study approach as inductive theory building research paradigms. GT seeks to obtain multiple viewpoints using different observational techniques. This enables a triangulation of data and the comparison of several data sets to avoid any potential biases (Babbie, 2010). In this research, case studies of three or four different ODL universities will be used to provide a greater understanding of student learning behaviours at each university under examination, in detail and in context. A multiple-case approach provides the opportunity for a more robust and reliable study (Yin, 2009).


Three ODL universities in different countries have been proposed as cases, each one operating within different socio-economic conditions, with different histories, missions and student numbers. The proposed case studies are in Spain, United Kingdom and South Africa.

The population sample within each of these cases will consist of active undergraduate students in the academic years 2015/2016 and 2016/2017. To provide a university perspective, staff responsible for teaching and learning as well as IT support staff will also be sampled.

Data Collection

The data will be collected from through multiple methods:

  • Online Questionnaires: The questionnaire will obtain information from students about device usage, student motivations and learning tasks. An online survey tool such as GoogleForms will be used to administer the questionnaire.
  • Electronic Diaries: Electronic diaries will be used as reflective student “self-reports” to capture daily logs over a period of one week that will provide individual experiences of day-to-day learning habits in context.
  • Semi-structured Interviews: Interviews will be used to derive qualitative data around interpretations and insights of perceptions and habits by students and staff members.
  • Analytics: Tracking data from universities regarding access and use of Virtual Learning Environments (VLEs) will be obtained to compare with other data sets, to acquire learner behaviour patterns regarding device access to VLEs.

Data Analysis

The analysis will follow suggested procedures for GT and case study research designs (Corbin & Strauss, 2015; Yin, 2009). The analysis will begin with the organisation of the data obtained. Data from the questionnaires will be used to inform the gathering and analysis of the qualitative data to explain and interpret the relationships. The investigation will make use of a computer-assisted data analysis tool (Nvivo). An initial coding will take place that details data from the questionnaires. After this a more focussed coding will be done to select the most relevant or frequent codes from the interviews and diaries. An iterative process will be followed to generate conceptual categories. Finally, the specific properties of categories and how they relate will be analysed to emerge with theoretical patterns (Corbin & Strauss, 2015). Additionally cross-case analysis will be used to compare the different cases under study.


Babbie, E. (2010). The Practice of Social Research (12th ed.). Belmont, CA: Wadsworth Cengage Learning.

Corbin, J., & Strauss, A. (2015). Basics of qualitative research: techniques and procedures for developing grounded theory (4th ed.). Thousand Oaks, CA: Sage Publications.

Cresswell, J. W. (2009). Research Design: Qualitative, Quantitative and Mixed Methods Approaches (3rd ed.). Thousand Oaks, CA: Sage Publications.

Yin, R. K. (2009). Case Study Research: Design and Methods (4th ed.). Los Angeles, CA: Sage Publications.


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