Workshop Information - ADA Summer School

ADA Summer School 2018 Workshop Information 

We list the detailed information about the course, your textbooks and the prices below. The preparatory course, Creating a successful dissertation takes place from 4 - 6 January and the one day courses on Saturday 13 January. Courses 2 to 9 will be offered in week 1 (8 - 12 Jan) and courses 12 - 18 will be offered in week 2 (15 - 19 January). 

The week long courses take place from Monday to Thursday 8am - 4pm and Friday 9am to 1 pm.

Register here after referring to the Workshop Information as below, and the "Which course is right for me?" page.

Please note there is overlap between "Creating a successful dissertation'' and "Preparing for the PhD." Please only select "Creating a successful dissertation' 

Course 1: Creating a successful dissertation (4 - 6 Jan)

Presenters

Bookings Closed: long waiting list.  

Dr Layla Cassim - Layla Cassim ERS Consultants

Cost

Flat rate of R3 500 + R350 for prescribed Toolkit. 

Prescribed Material: Postgraduate Toolkit, a roadmap for your postgraduate studies - by Dr Layla Cassim. 
Capacity

25 Delegates

Format  This preparatory course overlaps to a large extent with the course Preparing for the PhD, co-presented by Dr Cassim and Dr Herman in the first week of the Summer School, and can be seen as a condensed version of this valuable workshop. We have decided to offer this course before the Doctoral School formally starts, so delegates that want to attend Research Design Courses in the first week can also do so.
Target audience

Delegates planning to start their PhDs imminently or are in the early phase of their PhD and want to understand the background and context of the doctoral process. Delegates who are preparing for a research degree or project. If you think that you would benefit from further lectures in managing the supervisor relationship, building resilience and publishing from the PhD, please consider Preparing for the PhD in week 1. 

What to bring

The course will include lectures, exercises and group work. Participants are encouraged to bring their own writing to the workshop but it is not compulsory. Each participant and his/her writing will be treated confidentially and with respect.

Course description:

This three-day workshop covers the entire research process, and each day builds on what was covered the previous day.  The three-day format below allows us to cover a considerable amount of content as well as giving us sufficient time for group work, feedback and individual interactions.  Participants also receive a copy of the Postgraduate Toolkit – the Toolkit and the workshop reinforce each other, and participants can refer to the Toolkit chapters and voice recordings to revisit what was covered in the workshop.  

Course description:

Day 1: The research proposal
On day 1, we cover the fundamentals of research – what research is, ethical considerations in research, the importance of narrowing down the scope of the research project, defining key terminology (such as the research question, problem statement, aims and objectives) and the importance of a well-conceptualised research proposal.  We look at the structure of a comprehensive research proposal, with each component covered in detail.  In the afternoon, there is a group exercise, in which participants are asked to formulate key components of a research proposal, present this and are given feedback.

Day 2: Research design and methodology
Now that we have the basics in place, on day 2 we spend the whole day looking at research design and methodology.  We define what this is, look at the importance of effective record keeping, as well as different types of data and commonly used research methods.  It is emphasised that participants need to be able to rationalise why they have selected certain methods.  We also cover key concepts that examiners are likely to raise, such as sampling, error, bias, reliability, validity and pilot testing.  We also take a quick look at data analysis, both quantitative and qualitative.  We go through an example of a comprehensive research design and methodology chapter, so that participants have a framework within which to structure and plan for their research design and methodology.  Project management principles in research are also covered.  In the afternoon, participants go back into their groups from the previous day, make changes in the light of the feedback that has been received and then take the exercise further and develop a detailed research design and methodology.  It is interesting to note how the group projects evolve over the two days of the workshop.

Day 3: Thesis writing
We start the day by looking at important initial considerations, such as when to start writing, institutional requirements regarding the thesis, the process of editing, writer’s block and other problems that students may have, which may act as stumbling blocks to the completion of the thesis.  Then we look at different structures of a thesis, what goes where and how to write the different chapters or sections.  Special emphasis is placed on writing a high quality literature review.  We then cover university requirements relating to thesis submission, and examiners’ expectations.  We go through a typical examiner’s form, so that participants can ensure that they have covered these aspects in their theses.  We also look at common mistakes in academic writing that students make when writing their theses.  This list is based on what I have noticed when editing more than 250 theses, papers and reports across different disciplines.  There is a detailed consideration of the thesis examination process, what can go wrong in this and how to address examiners’ feedback.

 

Course 2: Preparing for the PhD - a road map for your dissertation (Week 1)

Presenters

Dr Layla Cassim - Layla Cassim ERS Consultants

Dr Nicoline HermanDeputy Director of the Centre for Teaching and Learning, SU

Cost

Early Bird Rate: R6 800 + R350 for prescribed Toolkit. 

SU staff and students paying by OE code/student account, retain this price until bookings close.

Standard Rate: R7 600 + R350  for prescribed Toolkit

Prescribed Material: Postgraduate Toolkit, a roadmap for your postgraduate studies - by Dr Layla Cassim. 
Capacity

25 Delegates

Target audience

Delegates planning to start their PhDs imminently or are in the early phase of their PhD and want to understand the background and context of the doctoral process. Delegates who are preparing for a research degree or project.

The course also places a focus on creating resilience for PhD candidates, developing and identiy key to doctoral studies, as well as planning to publish from the PhD. Another important aspect covered in this course is supervisory roles and maintaining good a good relationship with your supervisor - one of the most important a postgraduate student will have in their lives.

What to bring

The course will include lectures, exercises and group work. Participants are encouraged to bring their own writing to the workshop but it is not compulsory. Each participant and his/her writing will be treated confidentially and with respect.

 

This workshop is co-presented by our seasoned lecturers in postgraduate student success and has two distinct sessions.

Dr Layla Cassim

This part of the workshop will be an intensive session on the practicalities of getting started with your degree. This three-day workshop covers the research process, and each day builds on what was covered the previous day.  The three-day format below allows us to cover a considerable amount of content as well as giving us sufficient time for group work, feedback and individual interactions.  Participants also receive a copy of the Postgraduate Toolkit – the Toolkit and the workshop reinforce each other, and participants can refer to the Toolkit chapters and voice recordings to revisit what was covered in the workshop.  

The research proposal

During this part of the workshop, we cover the fundamentals of research – what research is, ethical considerations in research, the importance of narrowing down the scope of the research project, defining key terminology (such as the research question, problem statement, aims and objectives) and the importance of a well-conceptualised research proposal.  We look at the structure of a comprehensive research proposal, with each component covered in detail.  In the afternoon, there is a group exercise, in which participants are asked to formulate key components of a research proposal, present this and are given feedback.

Research design and methodology

Now that we have the basics in place, on the second day we spend the whole day looking at research design and methodology.  We define what this is, look at the importance of effective record keeping, as well as different types of data and commonly used research methods.  It is emphasised that participants need to be able to rationalise why they have selected certain methods.  We also cover key concepts that examiners are likely to raise, such as sampling, error, bias, reliability, validity and pilot testing.  We also take a quick look at data analysis, both quantitative and qualitative.  We go through an example of a comprehensive research design and methodology chapter, so that participants have a framework within which to structure and plan for their research design and methodology.  Project management principles in research are also covered.  In the afternoon, participants go back into their groups from the previous day, make changes in the light of the feedback that has been received and then take the exercise further and develop a detailed research design and methodology.  It is interesting to note how the group projects evolve over the two days of the workshop.

Thesis writing

We start the day by looking at important initial considerations, such as when to start writing, institutional requirements regarding the thesis, the process of editing, writer’s block and other problems that students may have, which may act as stumbling blocks to the completion of the thesis.  Then we look at different structures of a thesis, what goes where and how to write the different chapters or sections.  Special emphasis is placed on writing a high quality literature review.  We then cover university requirements relating to thesis submission, and examiners’ expectations.  We go through a typical examiner’s form, so that participants can ensure that they have covered these aspects in their theses.  We also look at common mistakes in academic writing that students make when writing their theses.  This list is based on what I have noticed when editing more than 100 theses across different disciplines.  There is a detailed consideration of the thesis examination process, what can go wrong in this and how to address examiners’ feedback.

In the second part of the workshop, Dr Herman who is the facilitator of a monthly PhD discussion group for support staff at SU undertaking PhD studies with an educational research focus, will deal with the following concepts:

Resilience and Academic writing

  • Introduction to doctoral studies
  • Identity development as key to doctoral studies
  • Dealing with the PhD
  • Introduction to academic writing
  • Publishing from the PhD - structuring your research for publication from the start.

This part of the workshop focusses on roles and relationships, and closes with some thoughts about staying the course during your doctoral studies.

  • Supervisory roles and relationships
  • How to select a supervisor 
  • Resilience in your studies

The course will include lectures, exercises and group work. The Toolkit and class notes will be distributed during the classes.

Course 3: Introduction to quantitative research design (Week 1)

 

Presenters

Prof Timothy C Guetterman, PhD, - University of Michigan, Ann Arbour, USA

Cost

Early Bird Rate: R6 800

SU staff and students paying by OE code/student account, retain this price until bookings close.

Standard Rate: R7 600 

Capacity

30 Delegates

Requirements  Participants should have a basic understanding of the process of research. It is critical to come with an idea for a research project and topic. We will refine and work on it throughout the course.
Target audience

This course will benefit delegates who want to learn more about quantitative research design and methods. It is idea for students who are at the early phases of their PhD, who can actively develop their proposal through the course. Delegates planning a quantitative research study will benefit. The course is highly interdisciplinary, as is the instructor, and will use examples from the education, social, and health sciences conducted across locations

What to bring

 

Introduction to Quantitative Research Design is an introductory course to develop foundational quantitative research design knowledge and skills. Quantitative research may be broadly defined as an inquiry approach useful for describing trends and explaining the relationship among variables generally through collecting and analysing numeric, closed-ended data.

The primary expectation is that delegates will work on their project and exit with the building blocks of a quantitative research design. As a group, we will actively work on the major aspects of quantitative research designs, including the statement of the problem; purpose statements, research questions, or hypotheses; a specific quantitative design; data collection and analysis plans; and limitations. 

At the completion of the course, students will have skills to:

  • Understand the process of conducting research using a quantitative approach
  • Plan a research design
  • Specify a quantitative purpose, research question, or hypothesis
  • Understand the types of quantitative research designs including
    • Survey design
    • Correlational design
    • Causal comparative design
    • Quasi-experimental/ Experimental designs
  • Know how to select a research design
  • Plan quantitative data collection procedures
  • Understand threats to validity in quantitative research

Class notes and readings will be provided.

 

Course 4: Introduction to qualitative research design and methodology (Week 1)

 

Presenter

Prof Wayne A Babchuk, University of Nebraska-Lincoln, USA

Cost

Waiting list starting to form (pending payments).

Early Bird Rate: R6 800 + R450 for Textbook. 

SU staff and students paying by OE code/student account, retain this price until bookings close.

Standard Rate: R7 600 + R450 for Textbook

Textbook Merriam, S., & Tisdell, E.J. (2016). Qualitative research: A guide to design and implementation (4th ed.). San Francisco: John Wiley and Sons. 
Capacity

30 delegates

Requirements

Participants are expected to have a general broad-based knowledge of the process of research whether that be a qualitative, quantitative, or mixed or multi-methods orientation. 

Target Audience

This course will benefit participants who want to learn more about and fine-tune their skills in qualitative design and implementation. The course will have a strong holistic and interdisciplinary focus and draw upon examples from the social and health sciences and education over time and across cultures.

Course description:

Introduction to Qualitative Research Design and Methodology is an introductory course presented in two parts.

Part 1 provides fundamental knowledge of three interlocking aspects of the research enterprise:

  1. the history of qualitative research across disciplines,
  2. the ethics and responsible conduct of research, and
  3. the epistemological or philosophical assumptions underlying qualitative designs.

We then systematically compare key attributes and procedures of widely utilized qualitative approaches including basic qualitative research, narrative, phenomenology, grounded theory, ethnography, grounded ethnography, case study, and participatory action research.

Part 2 extends our understanding of these approaches as participants learn more about the practice of qualitative research. As an engaged community of learners, we will focus on core processes of qualitative design and implementation: writing problem statements, purpose statements, and research questions, sampling strategies, interviewing and participant observation, and data analysis. We will also discuss assessment, validation, and writing reports for diverse audiences. This course will draw upon examples from participants’ own research interests that we will hone through collaborative problem-solving and instructional techniques. Upon completion of this course, participants will gain a deeper understanding of qualitative research and will have refined and practiced the skills needed to design and conduct their own studies.

Course Outcomes: 

After completion of the course, the participants will have insight into

  • Important themes and scholars that define the history of qualitative research over time and across disciplines
  • Ethics and the responsible conduct of research
  • Philosophical or epistemological assumptions undergirding qualitative research
  • Principles and practices of contemporary approaches to qualitative research (i.e., basic qualitative research, narrative, phenomenology, grounded theory, ethnography, grounded ethnography, case study, and participatory action research)
  • Designing qualitative research studies (purpose, sample, research questions)
  • Qualitative interviewing skills, participant observation, and other data collection techniques
  • Strategies of qualitative data analysis
  • Evaluating, writing, and publishing qualitative research 

Course material will consist of notes distirbuted during the class, a 'reader' hosted online and further texts.

Course 5: Essential tools for "R" - an introduction (Week 1)

 

Presenter

Prof An Carbonez, Leuven Statistics Research Centre, KU Leuven, Belgium.

Cost

Early Bird Rate: R6 800. 

SU staff and students paying by OE code/student account, retain this price until bookings close.

Standard Rate: R7 600

Capacity

25 delegates

Requirements

Knowledge of some basic statistical concepts is required (descriptive statistics, hypothesis testing,…) 

Target Audience

Everybody who is interested in using the R programming language for writing R scripts, managing your own scripts and using R for data analysis.

Course description:

This course gives an introduction to the use of the statistical software language R. This course presents the basics of R’s syntax and grammar and shows how to use Rstudio for data handling, visualization and basic statistics. This is a hands-on course with exercises.

Following topics are considered:

  • An introduction to the software package R
  • Different data structures in R
  • Importing data in R
  • Writing R functions
  • Making basic graphs in R
  • Performing some basic descriptive analysis in R
  • Performing some basic inference tests in R (i.e., testing independence, proportions, t-tests, regression analysis)
  • Using loops in R 

Course Outcomes:

At the end of the course, the student is able to:

  • Write an R script
  • Work with data structures
  • Create an R function
  • Create R graph
  • Use R function to produce basic statistical results
  • Install R packages and work with R help

Format:

The course will include formal lectures in the computer lab every morning and informal computer lab components every afternoon for participants to complete the programme exercises.
 

Course 6: Advanced qualitative data analysis with ATLAS.ti (Week 1)

Presenter

Dr Susanne Friese, Max Planck Institute for the Study of Religious and Ethnic Diversity. Göttingen, Germany.

Cost

Early Bird Rate: R6 800.

 SU staff and students paying by OE code/student account, retain this price until bookings close.

Standard Rate: R7 600

Capacity 20 delegates
Requirements

Delegates who are preparing for a research degree and researchers who are already working on a project. You should already be familiar with the basic concepts of social research and be computer literate and competent in order to register for this course. It is required that users have a a strong working understanding of ATLAS.ti already to benefit from the course.

Please send a short (1 – 3 pages) description of your research project to the instructor by December 15th, 2017 with focus on your analysis method. If you have started analysing your data in ATLAS.ti already, please also describe the current state of your ATLAS.ti project. Email: adainfo@sun.ac.za

Target Audience

This course is interesting for all those who want to learn about a tool that can support them during their literature review stage in their research and for those who plan to work with qualitative data like interview or focus group transcripts, field nodes, reports, images or videos. ATLAS.ti is a tool that supports the process of analysing such data.

Software

This course will feature version 8 of ATLAS.ti, which was released in December 2016. The classes are presented in a fully equipped computer laboratory (classroom) and personal laptops cannot be accommodated. Please note that the course fee does not include the software. However, if you are a student, you can purchase the software at a discounted price via the ATLAS.ti website

Course description:

The aim of this course, is to teach you how the technical aspects of ATLAS.ti liaison with the methodological aspects of computer-assisted analysis. Based on the chosen methodological approach, different functions of the software come into play. Before one “jumps” into analysis, slips can already occur when setting up a project. These will later be a potential barrier for further analysis. In the course, you will learn how to set up a project based on different data types (e.g. interview data, ethnographic data, focus groups, or surveys); how to build an efficient coding system and based on it, how to best use the advanced analysis tools. You will learn how to approach analysis in an inductive manner, e.g. using a Grounded Theory approach, and how to approach it in a mixed inductive-deductive, or deductive manner, e.g. using a thematic analysis approach. 

Please send a short (1 – 3 pages) description of your research project to the instructor by December 15th, 2017 with focus on your analysis method. If you have started analysing your data in ATLAS.ti already, please also describe the current state of your ATLAS.ti project. Email: s.friese@quarc.de

Course Outcomes: 

The main learning outcomes of the course are: You know how to best make use of ATLAS.ti to achieve your research goals, rather than to allow ATLAS.ti to drive your analysis.

Delegates will be provided with PDF notes and readings online. 

Course 7: Introduction to SPSS (Week 1)

Presenter

Dr Cindy Lee Steenekamp - Director Graduate School of Arts and Social Sciences; Centre for International and Comparative Politics, SU

Cost

Early Bird Rate: R6 800. 

SU staff and students paying by OE code/student account, retain this price until bookings close.

Standard Rate: R7 600

Capacity

25 delegates

Requirements 

Delegates must be computer literate and competent to register for this course.

Software

The SPSS classroom is equipped with computers which provide delegates with the latest version of SPSS. A license for the SPSS package for private use is not included in the price of the workshop and must either be purchased or provided by delegates or their institution if they wish to make use of the software. Please note that we cannot accommodate private laptops in the class.

Target Audience

Postgraduate students, supervisors and researchers interested in acquiring quantitative research skills and techniques. This course is especially useful for participants who make use of surveys or want to conduct secondary data analysis based on survey research.

Course description

During this course, participants will be introduced to the Statistical Package for the Social Sciences (SPSS) – one of the most widely used social statistical packages in the world. It needs to be emphasized that this is an introductory course, ideally suited for first time users or participants with limited experience with the software program. Participants should be computer literate and competent as this is a computer-based course with an emphasis on skills transfer. This short course focuses specifically on the knowledge and skills required for quantitative data analysis. The broad objectives of this course are to provide participants with an understanding of the logic of quantitative data analysis and to give participants the opportunity to develop the practical computer skills required for data analysis.

Course Outcomes:

When delegates have completed this course they should:

  • Be familiar with the layout and basic functioning of SPSS
  • Be able to create and maintain a database
  • Be able to do a summary analysis of a data set - produce frequencies, descriptive statistics, cross-tabulations and comparison of means
  • Be able to manipulate data - recode, treat missing values and construct a variable
  • Be able to graphically illustrate data using a variety of chart options
  • Be able to interpret and present the ensuing results
  • The following aspects are covered:

o    Levels of measurement, creating and editing a data file, transporting a file from Excel

o    Univariate and bivariate analyses

o    Frequencies, descriptive statistics, cross-tabulations

o    Inspecting variables

o    Recoding variables, missing values, computing variables, selecting cases and splitting files

o    Graphs

Course material: Class slides; homework exercises and homework memo. No prescribed textbook.

The course will include formal lectures in the computer lab every morning and informal computer lab components every afternoon for participants to complete the course exercises.

Course 8: Writing and publishing an article during the final phases of the PhD (Week 1)

Presenters

Dr Ruth Albertyn and Dr Christel Troskie-De Bruin

Centre for Higher and Adult Education, SU

Cost

Bookings Closed: long waiting list.

Early Bird Rate: R6 800. 

SU staff and students paying by OE code/student account, retain this price until bookings close.

Standard Rate: R7 600

Capacity

16 (8 per facilitator). The size of the class is kept purposefully small, so delegates have optimal time with their facilitator. 

Target audience

This course is aimed at doctoral candidates who have already begun their doctoral research project and are at a stage where they have completed a section of their work and have some publishable material. It is essential that the data has already been analysed or the literature already collected. The focus of this workshop is on actual writing of the article during the workshop (hands-on).

Novice writers in the life sciences could also consider taking Course 14, Scientific article writing for novices in the life sciences in week 2.

Requirement

Participants must have the following in place before the course commences:

  • The first rough draft of an article based on completed research (for example completed data analysis or completed section of the literature review)
  • Identified a journal where you would like to submit an article
  • The guidelines for authors of this journal
  • A laptop to use during the workshop (not only a tablet or iPad)
  • Power cables and adaptor for laptop.

Course description:

During this hands-on course, participants plan and write an article for publication in a scholarly journal. Participants work on material from their doctoral studies and it is essential for this workshop to have a draft manuscript to work on during your time with the ADA. Input is provided by the facilitator and participants then craft their article with one-on-one discussion and feedback from facilitators during the writing process.

Course Outcomes

After completion of the course, the participant will have a completed article which can be submitted for consideration by the intended journal. Throughout the week:

  • Input is provided on each section of the article
  • Participants write the relevant section
  • Facilitator reads work and provides feedback
  • Participants redraft before writing the next section of the article

Course material: A reading consisting of key readings that will be distributed during the class.

Course 9: Doctoral supervision: A theory-based and practical course for new and experienced PhD Supervisors (Week 1)

 

Presenter

Prof Jan Botha - The Centre for Research on Evaluation, Science and Technology (CREST), SU

Cost

Early Bird Rate: R6 800 + R400 Textbook. 

SU staff and students paying by OE code/student account, retain this price until bookings close.

Standard Rate: R7 600 + R400 Textbook

Capacity

30 delegates 

Textbook

Mouton, J. 2001. How to succeed in your master's and doctoral studies: A South African guide and resource book. Pretoria: Van Schaik Publishers. (R400, subsidised by the ADA).

Requirement

Delegates must already have a PhD (or be graduating in the next few months) in order to participate in the workshop.

 
Course description: 
 
The Doctoral Supervision course is an accredited short course at the University of Stellenbosch. The University will issue a Certificate of Competence to delegates who complete and submit all the assignments and meet the assessment criteria.

The focus of the course is on the PhD as knowledge production accompanied by the appropriate pedagogical principles and practices. Insights based on up-to-date research on doctoral education underpin the course. Theoretical and practical dimensions of doctoral supervision are blended in the presentations and activities.  Delegates will have the opportunity to do hands-on exercises, participate in group work, and work on projects related to the supervision of their own PhD students.  Delegates will also have opportunities to interact with experienced supervisors in different disciplines.

The course will cover topics such as:

  • The context of doctoral supervision in Africa
  • The nature of the PhD-qualification
  • Roles and responsibilities of supervisors
  • Models and styles of supervision
  • Joint or co-supervision
  • Research integrity
  • The process of supervision (guidance, feedback and assessment)
  • Supervising the development of the research proposal
  • The literature review
  • The examination of PhD theses

A reader with key readings and class notes will be provided online and/or printed and distributed during the classes.

Course 10: Grant writing fundamentals (Saturday 13 Jan)

Date Bookings Closed: long waiting list.  One day course, presented on Saturday 13 January 2018
Presenter

Ms Riana Coetsee - Division of Research Development, SU

Cost

Flat rate of R950

Capacity

20 delegates

Requirements

Participants should be busy with research, be it at postgraduate or postdoctoral level or in full-time academic staff capacity.

Target Audience

Researchers (including postgraduate students and postdocs) who need to generate research funds.

Course description:

Although funding organisations and their application requirements differ, there are important elements expected from all funding agencies, whether it relates to small or to large grants.  The following elements will be thus be discussed and practised in the workshop:

  • Basic structure of grant proposal
  • Why grant proposals fail
  • The core components of a grant proposal
  • Why writing style matters
  • The budget
  • Where to look for funding
  • Explaining peer review panels

Course Outcomes: 

Participants will understand the following:

  • What basic and core components an application should have to make it competitive
  • What pitfalls should be avoided when writing grant proposals
  • What elements should be included in the budget
  • Where to start looking for funding

Course material:

Notes on what will be presented in the workshop, as well as additional reading material

Course 11: Project management principles: Planning and Execution for your PhD (Saturday 13 Jan)

Date Bookings Closed: long waiting list. One day course on Saturday 13 January 2018.
Presenter

Mr Joubert van Eeden, Department of Industrial Engineering, SU

Cost Flat rate of R950
Capacity

30 delegates

Target Audience

Researchers who are preparing for or have recently started with an individual research projects (PhD, Masters or other).

Course description:

The course will provide participants insight into the following aspects of project management: project management theory; scope management; stakeholder engagement; quality management; time management;  risk management; project control and progress monitoring.

The course has a specific focus on individual research projects for participants that are involved in research towards a degree.

Course Outcomes: 

  • Understand how the basic principles of project management relates to individual research projects
  • Argue the importance of time management within research project delivery and describe the cost and quality interdependency
  • Plan a research project at a high level and provide a clear scope statement and project plan
  • Be able to apply the basic risk management process to rank and mitigate risk on research projects
  • Have the ability to compile a (brief) report on project progress against defined key milestones

Course material:

Notes will be provided.

Course 12: Mixed methods research design (Week 2)

Presenter

Prof Timothy C. Guetterman, applied research methodologist at the University of Michigan (Ann Arbor), USA

Cost

Early Bird Rate: R6 800. 

SU staff and students paying by OE code/student account, retain this price until bookings close.

Standard Rate: R7 600

Capacity

25 Participants

Target Audience

Delegates from the Social Sciences, or those that area about to design a mixed methods research study.

Requirement

Familiarity with the basics of either qualitative or quantitative methods; preparatory reading on mixed methods research design is highly recommended. Selecting to do the Qualitative or Quantitative Research Design and Methodology course in Week 1 would be highly recommended if it is of benefit to your research.

Course description

Mixed methods research studies, sometimes also called methodological triangulation, is an innovative and increasingly important way to conduct research in the social sciences. This research design combines qualitative and quantitative components in a single research study and overcomes many of the inherent limitations of mono-method research. As a research and design strategy, it often yields results which go beyond the "sum" of a qualitative and quantitative component within a single research project.

This introductory course will teach participants when, how and why to integrate a qualitative and a quantitative research components into a single research project. It connects to and builds on the course "interviewing and qualitative data analysis" which was previously offered at the ADA's Summer School by Prof Max Bergman.

This workshop will have four distinct sessions:

In the first session, definitions and characterisations of qualitative and quantitative research methods will be explored. The limitations and opportunities of these approaches with regards to combining both techniques in a mixed methods framework is discussed. Various research designs and the different possibilities of integrating qualitative and quantitative techniques are examined, as well as the justification for mixed methods research, their implications and potential problems.

The second and third sessions are divided into qualitative and quantitative aspects of mixed methods design respectively. Research projects are used to illustrate different approaches to mixed methods research. Theoretical implications, the research question, characteristics of data collection, data analysis and design issues with a specific focus on the integration of qualitative and quantitative techniques will be discussed. Central themes include sampling, research process and project planning.

The fourth session explores practical problems and solutions to mixed methods research with a special focus on issues raised during the workshop or connected to the delegates' research projects. Finally, future directions and new opportunities of mixed methods research will be discussed.

At the end of this workshop, delegates will understand the principles of mixed methods research, identify the possibilities and limitations of mixed methods research and outline the basics of a mixed methods design appropriate for any specific purpose.

Format: Throughout the week, daily exercises on how to collect and analyse data for mixed methods research will accompany the lectures. The participants are invited to work on their own data during the course. The 'reader' will be loaded online, and class notes and exercises distributed during the workshop.

Course 13: The productive PhD - Creating structure, gaining clarity & overcoming blocks (Week 2)

Presenter

Dr Sebastian Kernbach, University of St Gallen, Switzerland.

Cost

Bookings Closed: long waiting list. 

Early Bird Rate: R6 800.  

SU staff and students paying by OE code/student account, retain this price until bookings close.

Standard Rate: R7 600

Capacity

16 delegates

Requirements

No particular prerequisites are required, especially not in terms of being creative or being good at drawing. All you need is a mindset of curiosity, openness and experimentation.

About design thinking

Simply put, design thinking is a method for problem solving, popularized in the early 1990s by applying it to product design. Since that time, a variety of design thinking approaches have been applied to an ever-increasing range of challenges including research challenges. Think of it as a constellation of iterative steps and best practices for tackling complexity rather than a specific process.

Target Audience

This workshop relies heavily on the concept of  'design thinking' but is designed for participants without previous experience in design thinking (especially those who may have very little idea what design thinking even means!).

Course description:

In this hands-on one-week workshop, participants will have the opportunity to apply visual thinking and design thinking tools and methods to their own research projects. They will apply simple and easy to learn visual tools to structure their ideas, literature, academic discourses, and potential contributions, among others. Through the process of prototyping and iterating they will gain clarity in their PhDs and for their future research careers. In addition, interventions from the field of positive psychology and positive leadership will help participants to overcome blocks and flourish in their PhD.

Based on the design thinking framework and mindset established at the d.school at Stanford University, participants will gain creative confidence in their research process and when facing challenges, get problem-solving abilities to better deal with ambiguity using analytical skills and creative intelligence and improve their emotional well-being by being proactive about their emotional needs which ultimately leads to improved productivity.

The goal of this workshop is to recognize the creative, playful mindset that underlies successful innovation in scholarship and explore how design thinking can improve the research process to make us more innovative scholars or scientists. And with this, to increase the ability of researchers to create quality research and a systematic application of creativity in their own research development. Especially because emerging scholars and interdisciplinary researchers need tools, techniques, support, and inspiration to approach their research in an innovative and playful spirit of design.

Participants will explore a variety of design skills and mindsets, but focus especially on how being mindful of your own research process, work styles, emotional state, and sometimes-hidden assumptions can help you get “unstuck” when facing research bumps in the road. The instructor seeks to help participants to explore potential solutions to problems in their research efforts.

Participants will be given short input sessions from the instructor and will have time to apply design thinking to their own project(s), giving and getting feedback and improving their research project.

Course Outcomes: 

During this workshop, participants will gain…

  • Creative confidence
    • with tools, techniques and inspiration for an innovative mindset
    • to improve their research process
    • to make themselves more innovative scholars
    • to become “unstuck” in times of research blocks
  • Problem-solving abilities
    • reflecting, iterating and tolerating ambiguity
    • refining questions, processes, and methods, viewing setbacks as opportunities for further learning
    • highlighting the creative process of scholarly research
    • combining analytical skills and creative intelligence
  • Emotional well-being
    • being proactive about emotional needs (as it leads to greater productivity)
    • creating a social-support network (academic, non-academic)
    • creative a supportive, non-judgmental environment
    • work in tandems and experience peer-coaching

Participants will present their prototypes and iterative developments from throughout the week and will present their research story in new presentation and storytelling formats such as Visual Storytelling. The Visual Storytelling Canvas will help participants to shape a story of the current research.

The workshop is characterized by a positive, intimate and encouraging atmosphere in which exchanging successful practices and failures (also known as “learning opportunities”) is central to the learning success of all participants. Therefore, the number of participants is kept small to enable meaningful exchanges.

About design thinking:

Simply put, design thinking is a method for problem solving, popularized in the early 1990s by applying it to product design. Since that time, a variety of design thinking approaches have been applied to an ever-increasing range of challenges including research challenges. Think of it as a constellation of iterative steps and best practices for tackling complexity rather than a specific process.

About the d.school at Stanford University:

The d.school at Stanford University has been among the first to teach design thinking to participants from areas such as engineering, medicine, business, law, the humanities, sciences, and education. They define themselves as the hub for innovators at Stanford and are recognized around the world. They were also the first to apply design thinking methods and tools to the research process and I had the pleasure to work with them in Stanford. This workshop is an extension of the Stanford workshop.

Course 14: Scientific article writing for novice writers in the life sciences (Week 2)

Presenter

Dr Maarten GhequireCentre of Microbial and Plant Genetics, KU Leuven, Belgium

Cost

Early Bird Rate: R6 800. 

SU staff and students paying by OE code/student account, retain this price until bookings close.

Standard Rate: R7 600

Capacity

10 delegates. A smaller class size facilitates a good interaction with the presenter.

Requirements

Participants are asked to bring the following elements:

  • A (partial/complete) rough draft of a manuscript containing results from their own research.
  • Participants that have already prepared figures and tables are encouraged to bring these with them.
  • A journal to which the participant wants to submit his/her research + author guidelines for the journal
  • A laptop to use during the workshop (no tablet) as well as their charger and a lead
Target Audience

This course aims to attract early phase PhD doctoral candidates who are in the early stages of their PhD and would like to start publishing from either their Master’s degree or from initial data or from early dissertation work. Participants must have obtained (publishable) research data and the focus will be on delegates from the life sciences and possible engineering.

Publishing a scientific article is a milestone for many researchers and often an end point after several years of research. In this practical course a broad range of topics that are linked to the manuscript preparation and publication process will be discussed. Participants will work on their own manuscript draft and be able to receive feedback from the presenter at regular time points.

This course is aimed at early phase PhD candidates that are busy planning articles from their research in the life sciences.

Topics covered in the course:

  • When and why should I publish?
  • How does the publication process look like? What is peer-reviewing? How do I select the right journal to publish my data in
  • What is data deposition?
  • Ethics in publishing 
  • What are the different sections of a manuscript, and what appears/does not appear in each of these (scholarly expectations)? How do I structure each of these sections?
  •  How do I start writing; is there a certain order in which to write the different parts? What about the author order?
  •  Writing a convincing and attractive abstract. The importance of the main title and other (sub)titles in the manuscript.
  • Assembling good figures and graphs (do’s and don’ts).
  • What is a cover letter and what information should I mention?
  • Final things to verify before submitting the manuscript. Common reasons why manuscripts are rejected by the editor and reviewers.
  • What to do after publication?
  • Other article types.

Course Outcomes

  • The class is kept purposefully small so that delegates will have optimal time with the facilitator
  • Participants receive feedback on form/format of (certain sections of) their manuscript/figures/tables
  • Participants receive tips and ideas on writing different manuscript sections; understand the scholarly expectations of each of these
  • Participants have a general understanding of the writing/publication/reviewing process
  • The class is kept purposefully small so that delegates will have optimal time with the facilitator
  • Participant redraft parts of their manuscript in accordance to the information received

Course material: Readings will be distributed during the class.

Course 15: Effective scientific communication: Presenting a poster, writing an article, and giving an oral presentation (Week 2)

Presenter

Prof John Creemers, Director of the Doctoral School of Biomedical Sciences,  KU Leuven, Belgium

Ms Vicky Davis, SU

Cost

Early Bird Rate: R6 800. 

SU staff and students paying by OE code/student account, retain this price until bookings close.

Standard Rate: R7 600

Capacity

20 participants

Target Audience

PhD researchers in the broad field of Life Sciences who are going to present a poster or give an oral presentation at a scientific meeting, or need to write a manuscript for publication.

Requirement

The participants need to be able to read and understand a scientific publication. 

Course description:

This course will explain the principles of effective communication, how to make and present a poster at a scientific meeting, how to analyse and write a scientific article, and how to give an oral presentation with slideshow. Finally, we will discuss how to answer questions and how to deal with nerves.

Exercises will be selected on an individual basis in the specific field of research of the participant.

Course Outcomes:

After completion of the course, the participants will have insight into:

  • The principles of effective communication
  • How to have an impact with a poster
  • The principle of an elevator pitch
  • The peer-review process in publishing
  • The composition of an IMRAD-based manuscript
  • How to write an IMRAD-based manuscript
  • How to make an effective slideshow
  • How to give an oral presentation with slideshow
  • How to answer questions after a presentation
  • How to deal with nerves

Course material:  The course material are slides, which will be made available as handouts. Personalised homework assignments will be given, based on the participants specific research field.

 

Course 16: The Digital Scholar: Using emerging and multimedia technologies to further your research and teaching projects (Week 2)

Presenter

Prof Wim Van Petegem, Faculty of Engineering Technology, KU Leuven, Belgium

Cost

Early Bird Rate: R6 800. 

SU staff and students paying by OE code/student account, retain this price until bookings close.

Standard Rate: R7 600

Capacity 15 delegates
Target Audience 

The course is designed for the Digital Scholar of the future, i.e. PhD students and graduates from all disciplines, starting lecturers, or more senior academics, with a keen interest in digital technologies. Participants want to further develop their skills on how to drive project websites, how to use social media, how to set up a personal blog on their academic activities, how to visualize research outcomes or learning analytics, how to cope with fast moving new trends in multimedia technology for research and teaching, how to develop multimedia learning materials, etc.

Requirement

Participants should have a genuine interest in modern multimedia technologies and their application in research and education. Some basic experience with the use and/or production of multimedia materials or affinity with social media might be helpful in the practical sessions.

It is strongly recommended for the participants to bring their own devices (laptop, smartphone,…) to make use of them during the course.

Course description:

The course is based around the following framework: 


The whole course will be immersed in the idea of cumulative knowledge building and representation through multimedia communication.

The course will concentrate around the following themes: 

1) understanding the digital scholar concept,

2) making your research felt on the web, 

3) creating interactive multimedia materials, 

4) coping with new multimedia technology in research and teaching.The whole course will be immersed in the idea of cumulative knowledge building and representation through multimedia communication. 

The course will include presentations of theoretical evidence-based concepts, models and frameworks, good practices, inspiring examples, practical illustrations, and interesting (open) resources, combined with some hands-on exercises. Together with the instructors participants will engage in a co-creation process and will start to build their own digital scholarly presence on the web during the course.

Furthermore, guest lectures by local experts will be provided on certain aspects of the course, either face-to-face or online.

Course Outcomes: 

After completion of the course, the participants will:

  • Be able to represent and further their own, as well as research teams’ research projects on the web
  • Better understand cumulative knowledge building and representation as a framework to integrate research and teaching
  • Be aware of the huge potential of emerging and multimedia technologies for research and teaching
  • Be able to use multimedia and social media in research and teaching

Course Materials: 

The course material will comprise slide sets, readings and journal articles, on-line tutorials, manuals, video material, provided in the sessions, and partly co-created by the participants themselves.

Some on-line textbooks or references that partly cover the topic of this course are:

  1. Teaching in a Digital Age, by Tony Bates (http://www.tonybates.ca/teaching-in-a-digital-age/)
  2. Academics’ online presence. A four-step guide to taking control of your visibility, by Sarah Goodier and Laura Czerniewicz (http://open.uct.ac.za/handle/11427/2652)
  3. Digital Selves, Digital Scholars: Theorising Academic Identity In Online Spaces, Katia Hildebrandt and Alec Couros, http://socialtheoryapplied.com/journal/jast/article/view/16/10
  4. Lisa de Haardt & hans van de Water (2015). Research: how do you get it out there? Brussel: VLIR-UOS, Digital version available on http://www.vliruos.be/media/6365704/handbook_research_communication_vlir-uos.pdf

Format: The class is highly practical and interactive. The materials will be made available online during the classes.

Course 17: Introduction to qualitative data analysis with ATLAS.ti (Week 2)

Presenter

Dr Lauren Wildschut, The Centre for Research on Evaluation, Science and Technology (CREST), SU

Cost

Early Bird Rate: R6 800.

 SU staff and students paying by OE code/student account, retain this price until bookings close.

Standard Rate: R7 600

Capacity 30 delegates
Requirements

You should already be familiar with the basic concepts of social research and be computer literate and competent in order to register for this course.

Target Audience

This course is interesting for all those who want to learn about a tool that can support them during their literature review stage in their research and for those who plan to work with qualitative data like interview or focus group transcripts, field nodes, reports, images or videos. ATLAS.ti is a tool that supports the process of analysing such data.

This course will feature version 8 of ATLAS.ti, which was released in December 2016. Version 8 is not just a regular upgrade. It is re-programmed from scratch and has a whole new look and feel to it. For those familiar with ATLAS.ti, you will find elements that are familiar like the editor displaying your data on the left hand side and the codings on the right hand side in the margin area. The overall program handling however will be different as ribbons are introduced (instead of menus) – and of course there will be new tools like being able to import data from reference manages like Mendeley, Evernotes and Twitter. Thus, for those already familiar with an older version of ATLAS.ti might also find this course valuable.

Software

This course will feature version 8 of ATLAS.ti, which was released in December 2016. The classes are presented in a fully equipped computer laboratory (classroom) and personal laptops cannot be accommodated. Please note that the course fee does not include the software. However, if you are a student, you can purchase the software at a discounted price via the ATLAS.ti website

Course description:

This is an introductory course dealing with qualitative data analysis (QDA) using a software programme called ATLAS.ti. Participants will be introduced to the range of qualitative data analysis types. You will learn the technical side of handling and working with qualitative data in ATLAS.t. As a practical use case, you will be shown how this software programme can be utilised to assist with your literature review and how to analyse twitter data.

Specific course elements are the following:

  • Introduction to qualitative data analysis
  • Computer Assisted Qualitative Data Analysis Software (CAQDAS)

Interface

  • Finding your way around: Getting to know the ATLAS.ti User Interface

Project Management

  • How to set up a project / Working with various data types

Coding:                

  • Technical aspects of coding
  • Methodological aspects of coding: how to build an efficient coding schema

Use case:

  • Using ATLAS.ti for your literature review
  • Working with Endnote

While we are going through the use cases, you will be introduced to various other functions like writing comments and memos, simple analytic tools and the network view function.

Course OutcomesParticipating in the course will enable you to begin to work with the software and to utilise it for your own research project.

Course material: A reader with PowerPoint slides and readings will be supplied.

Course 18: Intermediary SPSS – Between a novice and an expert (Week 2)

Presenter  Dr Nelius Boshoff - The Centre for Research on Evaluation, Science and Technology (CREST), SU
Cost

Early Bird Rate: R6 800 + R600 Textbook

SU staff and students paying by OE code/student account, retain this price until bookings close.

Standard Rate: R7 600 + R600 Textbook 

Capacity

25 delegates

Textbook

Palant, Julie (2013). SPSS Survival Manual 5th edition. Open University Press. (R600, subsidised by the ADA).

Requirements and Recommendations

Delegates must already have a working understanding of the SPSS software package in order to participate in the workshop. Having already attended the introductory SPSS course offered by the ADA is preferred.

Course description:

This intermediary course builds on the introductory course in SPSS. At a minimum, interested Delegates should already be familiar with certain procedures in SPSS. These include the preparation of data files, the recoding of variables and how to perform basic descriptive analyses (e.g. frequencies and cross-tabulations). The workshop will then take the delegates’ knowledge and skill to a next level. They will be exposed to statistical significance testing in the context of bivariate analyses, focussing on both parametric and non-parametric techniques. Examples parametric techniques include the t-test, the one-way Anova and the chi-square test. Candidates will further be introduced to multivariate analyses, specifically multiple linear regression and factor analysis. Scale reliability (Cronbach’s alpha) will also be covered. The broad objectives of the course are to empower delegates to apply the mentioned procedures to their own data and to be able to summarise, visualise and write text to the data output.

Course outcomes

When delegates have completed this course they should:

  • Know when to apply the SPSS procedures covered
  • Know the limitations and value of the relevant procedures
  • Be able to perform the procedures
  • Be able to interpret the ensuing results
  • Be able to summarise and communicate the results

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