The Doctoral Schools of PADA are held twice a year during the inter-semester break - in January and June/July. Each school offers one- or two-week intensive modules on a number of specialized topics. Modules usually run from Monday to Friday, from 8:30 to 5:00 pm.
You may register for the Doctoral Schools here.
Conducting original and innovative research and having enough numbers to justify sound statistical conclusions are important, but are not the only considerations in scholarly research; equally crucial is the communicating findings to the broader research community. This course will help doctoral students master scholarly writing in order to engage more confidently in conversations in their disciplines.
Students will participate in interactive sessions on scholarly argumentation, writing style and language, punctuation and mechanics, editing, summarizing and paraphrasing, tense and voice, as well as proper citation formats. Samples of scholarly writings will provide students practice in identifying the elements of an effective argument which they can apply in their writing. A range of writing activities' including invention, planning, drafting, revision, and editing will be conducted to prepare students for various stages of their academic writing.
The essence and end result of scientific research is to disseminate information for the use of other scientists and society in general. In the absence of exchange of information, there is no science. However, for the information to be useful to its intended target, it must be communicated clearly and effectively.Scientific writing and communication normally occur between the scientist and
- other scientists within the same discipline.
- other scientists in related or unrelated disciplines.
- non-scientific academics.
- the general public.
The course will examine each of these forms of communication has its stylistic requirements and specific skills needed for competence.
The last two decades has seen a paradigm shift in scientific research with systematic review emerging as core methods for generating the best possible evidence needed in support of decisions and policies about what works and what does not work. Usually evidence is contained in a number of individual studies within an ocean of literature and there is a danger in attempting to use findings from a single study to inform policy decisions, especially if individual studies are reach conflicting conclusions. Systematic reviews pool data from all the available studies to provide an overall best (reliable) estimate. The growing application of evidence synthesis in all forms of decision making underscores the need for scientists and decision makers, particularly contemporary PhD students, to have basic knowledge in this research method.
This course focuses on how to build a competitive advantage with emerging technologies through a culture of innovation based on creativity and problem-solving, critical thinking, communication, collaboration and computational thinking (the 5Cs). As students explore the value of innovative thinking at all levels of meaningful learning, they will evaluate the habits of innovative thinkers and engage in assignments that put their new knowledge, skills and creative mindset to the test to tackle a critical challenge facing their scholarly pursuits.
The class will meet physically and also use on-line technology to deliver course materials through the course website hosted at the University of Ghana's SAKAI Learning Management System.
The university in Africa faces pressures from a global knowledge economy which emphasizes innovation and invention. Early and emerging scholars are the drivers of knowledge production in this new context, where career advancement is tied to local innovation and transnational competitiveness and the idea of the scholar as leader, marketer and innovator.
This course introduces early and mid-career scholars to the changing profile of the emerging African scholar. It will explore global and African landscapes of 21st century knowledge production in order to help students understand changes taking place in the role and function of the scholar, and appreciate the new challenges and responsibilities the next generation of African scholars are expected to meet.
The process of obtaining a doctoral degree can be a difficult, long and lonely journey. It requires persistence and a plan to deal with resources, time and people. Having these skills will make your journey to a PhD less stressful and will guarantee that you will finish your thesis in good time.
The course is designed as a practical guide; it is conducted in a seminar style, with emphasis on experiential and peer learning. The course incorporates exercises and assignments that encourage students to individually reflect on and put into immediate practice what they learn.
- The nature of the PhD process
- Institutional environment and your obligations
- Managing your time
- Managing your supervisors
- Managing your thesis writing
- Managing life during the PhD (school-life balance; managing your studies as a female or part-time student; dealing with stress, frustration, etc.)
- Guide to grants, conferences and publishing in graduate school
- Managing your literature review (including using bibliographic managers e.g. Endnote, Mendeley)
The principles underlying the delivery of effective presentations apply to scientific talks as much as they do to other public speaking engagements. The course will explore important verbal and nonverbal skills, proven presentation structures, and innovative delivery techniques that are the hallmarks of impactful presentations. By the end of the course, students will have a good understanding of the essence of a presentation, the major dos and don'ts in oral and poster presentations and how to build verbal and non-verbal communication skills. Further, though individual exercises and small group activities, students will improve their ability to speak with poise, clarity, and conviction.
Qualitative methodology is not a discrete set of techniques or methods but an approach that shapes the entire process of research from choice of research strategy, through data collection and analysis, to write up. We assume at least an introductory knowledge of qualitative methodology from previous graduate level courses. This course will therefore focus on building practical skills and the confidence to undertake qualitative research. The course will be intensive and interactive, with hands-on individual and group activities.
This course introduces students to basic quantitative techniques for social science research; it examines the theory and application of standard quantitative techniques, from descriptive statistics through inferential statistics to multivariate techniques. A broad approach is taken to give students ample opportunity to critically assess the rationale, theories, and concepts behind the various statistical techniques. The ultimate aim is to equip students with the necessary statistical tools for social science and humanities research.
The course places emphasis on the how-to as against the what-is aspects of quantitative application in social science research and, thus, students will learn how to design a structured quantitative questionnaire and code and analyze the resulting data using SPSS.
The course is conducted in a computer environment with the aid of the Statistical Package for the Social Sciences (SPSS) on Windows.
The module provides PhD students in the Social and Life (Biological) Sciences knowledge of commonly used statistical methods and other advanced methods for analyzing data. The course will develop each student’s ability to use this knowledge to become more effective as researchers. It will present an overview of the important concepts of statistical methods; inferential statistical methods; univariate and bivariate statistical techniques; non-parametric inferential techniques; statistical modelling; and sampling techniques.
R is an open-source, flexible and powerful statistical analytic software used by researchers worldwide. It is a preferred environment for data manipulation, visualization of publication-quality graphs and charts, and data analysis. The course helps students to understand the diverse applications in statistics and data analysis. It also introduces students to basic programming in R. The main goal of the course is to train students in the use of R software package for data management, manipulation, graphics and analysis.
The course is aimed at helping students gain practical skills in managing their data with NVivo. The course will cover creating projects, importing data, editing, changing page view, creating nodes and sub-nodes, collapsing and expanding nodes, coding, uncoding, creating models and exporting nodes and models. Students will also learn to run queries, create matrices and explore data. The course will be useful for participants who have collected data and have transcripts to analyze. However, those without data will be given sample data for practical sessions.