Postgraduate Proposal and Thesis Development Mentorship Course
Details
Introduction
Post graduate students taking either a Master’s degree or a Doctor of Philosophy degree are mostly faced with challenges in developing an academic proposal and thesis/dissertation. Some of the challenges are experienced on choosing the topic of the study, literature review, coming up with problem statement, data analysis method and the appropriate software for quantitative and qualitative data. This research mentorship course aim at improving research knowledge and skills, proposal and thesis/dissertation quality as well as quantity and quality of journal articles publishable in refereed journals emerging from postgraduate student’s research work.
Duration
10 days
Who should attend?
o Post graduate students who have just finished course work and are working on their project and thesis proposals
o Post graduate students who have are about to collect data
o Postgraduate students who have collected data and are in the process of analyzing it
o Postgraduate students who want to publish their research work
Course objective
The objective of this course is to guide participant on a step by step process of developing an academic proposal, thesis or dissertation or a scientific paper for publishing in a referred journal. At the end of the training, the participants will be able to;
o Learn how to choose a research topic,
o Know how to do literature review without plagiarism
o Understand useful tips on how to write a problem statement
o Know how to develop specific, measurable, achievable and realistic research objectives
o Understand both quantitative, qualitative and mixed methods research designs
o Learn different sampling techniques and sample size determination
o Learn different data collection methods
o Learn data analysis methods (Descriptive statistics and inferential statics)
o Identify fundamental style for developing a journal article for publication in a refereed journal
Modules to be covered
Module 1: Introduction to research methods
o Understanding the academic research process
o Developing an academic research idea
o Identification and writing a problem statement
o Formulation of good research questions and hypothesis
Module 2: Literature Review
o Identifying different sources of literature to review
o Theoretical versus empirical literature
o Purpose of literature review
o Ingredients of a good literature review
o Assessing value of literature and critical review of literature
o Citation of literature review (why, what, when)
o Avoiding plagiarism
o How to document literature review
Module 3: Data and Methodology
Cross-sectional data
o Conceptual, analytical and theoretical frameworks
o Difference between qualitative and quantitative research designs
o Empirical framework and econometric model specification
o Data types and sources
o Qualitative and quantitative data
o Primary versus secondary data and sources
o Sampling techniques (probability and non-probability sampling) and sample size determination
o Variable description, selection and definition
o Data management (database design, data entry, data cleaning, data processing)
o Data collection methods (qualitative and quantitative data)
Module 4: Data and Methodology (continued)
Time Series
o Conceptual, analytical and theoretical frameworks
o Research design
o Empirical framework and econometric model specification
o Data types and sources
o Qualitative and quantitative data
o Primary vs. Secondary data and sources
o Sampling and sample size determination
o Data management (database design, data entry, data cleaning, data processing)
o Variable creation, selection and definition
Module 5: Data and Methodology (continued)
Panel data
o Conceptual, analytical and theoretical frameworks
o Research design
o Empirical framework and econometric model specification
o Data types and sources
o Qualitative and quantitative data
o Primary vs. Secondary data and sources
o Sampling and sample size determination
o Data management (database design, data entry, data cleaning, data processing)
o Variable creation, selection and definition
Module 6: Introduction to Software skills and practical applications
o General overview of statistical software (SPSS, Stata, R studio, Eviews, Stata, SPSS, Nvivo, Atlas ti)
Module 7: Model Estimation Techniques, Interpretation and Discussion of Results
Cross section
Basic software skills and practice
Module 8: Time series
Basic software skills and practice
Module 9: Panel data
Basic software skills and practice
Module 10: writing the research output thesis or journal article
LINK:
https://upskilldevelopment.com/postgraduate-proposal-and-thesis-development-mentorship-course
Upskill Development Institute is a leading provider of training, research and consultancy services to international organizations. We assist our clients to improve their skills and confident by offering the best possible solutions to enable them fulfill their objectives for a sustainable result. We strive to improve the quality and accessibility of the training by creating an environment that ensures successful learning from start to finish. Choosing an institution that supports your needs and understands your goals can be a challenge. We aim to eliminate this overwhelming process by providing you with high-quality solutions and courses that fully encompass the shifting tides of the different fields.
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