Research Skills Part A, B and C
Run by School of Human and Behavioural Sciences
20.000 Credits or 10.000 ECTS Credits
Organiser: Dr Jamie Macdonald
Overall aims and purpose
This is a fabulous hands-on opportunity to learn about research design and data analysis, skills that are critical to reading and writing research material, during your degree and beyond. It is delivered in a lively, professional, and very friendly manner by world-renowned researchers. They will help you develop the necessary skills to run your own programme of research, and to evaluate that of others. These skills are not only important for research, but are also important to enable you to think critically to select the best interventions to apply in real world vocational practice. Despite possible preconceived ideas about research design and analysis, students end up loving this module!
The aims: To provide critical understanding of research design and data analysis.
To prepare students to complete their Research Project Proposal or Dissertation Proposal module, and their Research Project or Dissertation module.
Part A of this module covers quantitative research design. Using an experiential and flipped teaching format, students will read a series of scientific papers to develop their critical understanding of research design, including formulating a question, generating a hypothesis, study designs, sampling methods, ensuring validity and reliability, and good dissemination practices. Both original investigations and review studies will be included.
Part B of this module covers material relevant to the analysis of group differences and regression analyses using quantitative methods. Specific content includes: Single factor analysis of variance with and without repeated measures; Two factor analysis of variance with and without repeated measures; Single factor and two factor multivariate analysis of variance (with and without repeated measures); Doubly repeated measures analysis of variance; Analysis of covariance; Follow-up procedures for all of the above; Assumptions underpinning all of the above and available options for dealing with violations to these assumptions. Regression based analyses: simple and multiple linear regression; curvilinear regression; mediation and indirect effects; moderated hierarchical regression; moderated mediation.
Part C of this module covers qualitative research methods and analysis.
The qualitative part of the module will address the different philosophical positions underpinning quantitative and qualitative research; qualitative research data collection methods, including interviews, focus groups and observational methods; and qualitative data analysis, including thematic content analysis, grounded theory and discourse analysis.
Module failure that prevents you passing the year will require resit assessment and attendance at Supplementary Assessment Week (exact date TBC but expected to be second week of July 2022).
Parts A & C: Demonstrates a good understanding of qualitative and quantitative research design. Is able to recognise research designs, validity and reliability threats. Few inaccuracies or misconceptions.
Part B: Students will demonstrate a solid understanding of most of the analyses. These analyses will typically include one of the more complex analyses (e.g., MANOVA, ANCOVA, MANCOVA, mixed-model ANOVA) and the more straightforward analyses (e.g., two-factor fully randomized ANOVA) will be covered in a largely comprehensive manner. The student’s explanations will be fairly concise and precise, demonstrating a reasonably good working knowledge of the analyses and most of their intricacies (e.g., assumptions, follow-up analysis considerations, decisions with regard to unequal group sizes, etc.) with some errors, inconsistencies, or a degree of superficiality. The student will be somewhat reliant on the portfolio and will answer questions in a largely precise but sometimes rather superficial manner. The verbal communication style will be fairly clear with some redundancy.
Parts A & C: A thorough understanding of qualitative and quantitative research design. Demonstrates a consistent ability to recognise research designs, validity and reliability threats. Be able to propose solutions to threats to research design.
Parts B: Students will demonstrate an in-depth understanding of each of the analyses. These analyses will typically include at least one of the more complex analyses e.g., MANOVA, ANCOVA, MANCOVA) with the more straightforward analyses (e.g., one-way repeated measures ANOVA) covered in a comprehensive manner. The student’s explanations will be concise and precise, demonstrating an integrated knowledge of the different analyses and their various intricacies (e.g., assumptions, follow-up analysis considerations, decisions with regard to unequal group sizes, etc.). The student will use the portfolio only to the extent that it supports his/her well-integrated understanding. The student will answer questions in a concise and accurate fashion. The verbal communication style will be clear and concise.
Parts A & C: Basic understanding of qualitative and quantitative research design. Some ability to recognise research designs, validity and reliability threats. Inaccuracies and misconceptions evident.
Students will demonstrate an acceptable understanding of the analyses although this understanding may be marginal at times. The analyses that are covered will typically include the more basic analyses (e.g., single-factor
randomized and repeated measures ANOVA, two-factor fully randomized ANOVA, basic hierarchical regression)
with perhaps an attempt at explaining one of the more complex analyses (e.g., fixed-model ANOVA). The explanation of the more straightforward analyses will be
good to fair while any coverage of more complex analyses will be largely descriptive. The student will demonstrate
a largely acceptable working knowledge of the main analyses albeit with some (possibly quite large) gaps in the underlying intricacies (e.g., assumptions,
follow-up analysis considerations, decisions with regard to unequal group sizes, etc.). The explanations will be
somewhat confused at times with some errors and superficiality, most of which will be remedied with some prompting. The student will be rather reliant on the
portfolio. The student will answer questions in a somewhat superficial manner at times and the verbal communication style will sometimes be somewhat unclear and unnecessarily verbose.
On successful completion of Part C of this module, students will:
Be able to critically evaluate the qualitative designs and associated analytical procedures that are used in sport science
On successful completion of Part B of this module, students will:
Be able to explain the statistical procedures and the assumptions that underpin the statistical procedures associated with experimental and quasi-experimental designs as well as explain the options available to deal with violations of these assumptions.
On successful completion of Part A of this module, students will:
Be able to criticize and defend the experimental and quasi-experimental research designs that are often utilized in sport and exercise and performance psychology studies.
On successful completion of Part B of this module, students will:
Be able to use SPSS for Windows and understand, and be able to explain, the statistical outputs produced by SPSS.
On successful completion of Part A of this module, students will:
Be able to demonstrate and apply the basic concepts of sample size estimation
|INDIVIDUAL PRESENTATION||Part A (Design) Presentation||
You will select one of three offered papers and critique this paper in terms of its research design. This assessment will allow you to practice delivering a powerpoint presentation but in the (relative) safety of a non-public setting. You will record a narration over your powerpoint slides and submit using the University's OneDrive. Thus you will also learn a transferable skill useful for recording instructional podcasts and youtube videos. Your mark will be reduced by one categorical grade (e.g. from A to A-) for every full minute you exceed the 10 minute time limit.
|VIVA||Part B (Statistics) Viva||
Throughout the module you will collect and print off SPSS computer statistical outputs from your practical workshops. Your understanding of these outputs will form the basis of this viva. You can have these outputs in front of you in your viva. But as everyone will print off identical outputs you will only be assessed on your ability to annotate them. The viva will be completed online via Skype. In this viva voce examination, you can bring with you whatever you want (e.g., outputs, books), apart from your best friend! You will be expected to answer questions set by the examiner on any of your outputs; the examiner will increase the difficulty of the questions if you answer the initial questions correctly. Your marks will be based on the verbal answers you give; the outputs will not be assessed only your annotation of them. Students tell us that this is a challenging and very rewarding experience.
|ESSAY||Part C (Qualitative): Essay||
With consideration of relevant literature, critique the rigor of the method the provided study has adopted, and offer potential recommendations for further research that are born from the strengths and limitations provided. Ensure to critique the mixed method design
|CLASS TEST||Sample size in class worksheet||
During a pre-recorded lecture you we will explore the concept of sample size estimation. To encourage your engagement, a worksheet will be completed. Those students who need further support to complete the worksheet may attend the shadow /enhancement class.
Teaching and Learning Strategy
Part C: 10 x 1 hr flipped lectures. For each lecture, students will first complete assigned reading. Then students will watch a one hour Panopto recording (a mixture of narrated lecture and screen capture recorded using Panopto and made available online via Blackboard) and complete a worksheet to apply the presented theoretical concepts.
|Practical classes and workshops||
Part B: 10 x 1 hour lectures (a mixture of narrated lectures and screen captures recorded using Panopto and made available online via Blackboard)
Part A: 3 x 1 hr shadow classes. Students will pose questions using Blackboard Discussions (an online message board). These will be answered in a shadow class delivered live using Blackboard Collaborate (an online virtual classroom). The shadow/enhancement class will also be recorded using Panopto to allow students to access the content offline.
Part C: 3 x 1 hr shadow classes, accessed via Blackboard online forum. Questions can also be asked beforehand via message board (and will be answered in the Panopto recording of the seminar)
Part A: 5 x 1 hr lectures. For each lecture, students will watch a one hour Panopto recording (a mixture of narrated lecture and screen capture recorded using Panopto and made available online via Blackboard) and complete questions to apply the presented theoretical concepts.
Part A: Reading associated with each Part A lecture (5 x 3 hours) = 15 hours; Preparing and completing Part A assignment = 32 hours.
Part C: Reading for each Part C workshop (3 x 3 hours) = 9 hours; Preparing and completing Part C assignment = 20.5 hours.
Part B: Reading (2 hours/lecture) = 20 hours; Developing portfolio (e.g., annotating papers and outputs; 3 hours/week) = 35 hours; Examination revision and examination = 23 hours.
- Literacy - Proficiency in reading and writing through a variety of media
- Numeracy - Proficiency in using numbers at appropriate levels of accuracy
- Computer Literacy - Proficiency in using a varied range of computer software
- Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
- Exploring - Able to investigate, research and consider alternatives
- Information retrieval - Able to access different and multiple sources of information
- Inter-personal - Able to question, actively listen, examine given answers and interact sensitevely with others
- Presentation - Able to clearly present information and explanations to an audience. Through the written or oral mode of communication accurately and concisely.
- Teamwork - Able to constructively cooperate with others on a common task, and/or be part of a day-to-day working team
- Argument - Able to put forward, debate and justify an opinion or a course of action, with an individual or in a wider group setting
Subject specific skills
- critically assess and evaluate data and evidence in the context of research methodologies and data sources
- describe, synthesise, interpret, analyse and evaluate information and data relevant to a professional or vocational context
- plan, design, execute and communicate a sustained piece of independent intellectual work, which provides evidence of critical engagement with, and interpretation of, appropriate data
- develop a sustained reasoned argument, perhaps challenging previously held assumptions
- demonstrate effective written and/or oral communication and presentation skills
- take and demonstrate responsibility for their own learning and continuing personal and professional development
- recognise and respond to moral, ethical, sustainability and safety issues that directly pertain to the context of study including relevant legislation and professional codes of conduct
- demonstrate an understanding of the philosophical basis of scientific paradigms
- demonstrate evidence of competence in the scientific methods of enquiry, and interpretation and analysis of relevant data and statistical outputs.
- develop transferable skills of relevance to careers outside of sport, health and exercise sciences.
- communicate succinctly at a level appropriate to different audiences.
- accurately interpret case study data
Resource implications for students
Ability to download GPower software
Talis Reading listhttp://readinglists.bangor.ac.uk/modules/jxh-4209.html
The Talis reading list includes all the reading associated with this module. Example texts include: Part A: How to design and report experiments. Book by Andy P. Field; Graham Hole, 2003; Part B: Applied multivariate statistics for the social sciences. Book by Keenan A. Pituch; James Stevens, 2016; Part C: Qualitative research & evaluation methods: integrating theory and practice. Book by Michael Quinn Patton, 2015.