Undergraduate Course: Research and Statistics in Sport Science 3 (SPRT10003)
Course Outline
| School | Moray House School of Education and Sport |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 10 (Year 3 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This half-course will build on Sport Science 2D research methods, and will introduce the student to inferential statistical techniques. Computers will be used (along with appropriate software) to enable students to understand the theory and practice of empirical data analysis. The reporting of scientific research data will also be covered in detail as a preparation for the Sport Science 3 Project and the Sports Science 4 Dissertation |
| Course description |
This teaching and learning is research-led. Members of academic staff the Institute for Sport, Physical Education and Health Science (ISPEHS) who contribute to this course are all members of one or more of the following research groups hosted by ISPEHS: (1) Physical Activity for Health Research Centre (PAHRC), (2) Edinburgh Sports Research, (3) Human Performance and Aquatics and (4) Physical Education Research Forum (PERF).
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
Students MUST have passed:
Sport Science 2D (SPRT08007)
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | Visiting students must have previously completed at least 3 Sport Science courses at grade B or above (or be predicted to obtain this) and receive permission from the Moray House School of Education to enrol. We will only consider University/College level courses. |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2022/23, Available to all students (SV1)
|
Quota: 0 |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 11,
Supervised Practical/Workshop/Studio Hours 20,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
165 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
0 %,
Practical Exam
100 %
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| Additional Information (Assessment) |
1 x 2 hour examination. A computer based exam. |
| Feedback |
Informal Feedback - This takes place during teaching, seminars and practicals throughout the semester. Your tutors will comment on your understanding of the ideas covered in the course, and may give you specific advice regarding your progress. Such feedback is intended to help you understand what your strengths and development points are, and to enable you to take informed responsibility for your learning and progression.
Discussion forum - Throughout the course as a whole the students are encouraged to use a discussion forum in LEARN. Any questions posted by students about teaching, learning and assessment are be responded to by the course tutors for everyone to see.
Cohort feedforward - Detailed cohort feed-forward from previous cohorts of students is provided for all assessments on this course.
Formative Feedback - There will be a mock examination in the final week of the course. Feedback will be provided directly after this mock examination as to correct and incorrect procedures and answers.
Summative Feedback- A detailed cohort feedback document discussing the examination and some common problems and successes will be available. The exam feedback given to last year's students will be available too.
All students are able to request one to one meetings with course tutors to review their exam
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| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S1 (December) | | 2:00 | | | Resit Exam Diet (April/May Sem 1 resits only) | | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- Understand the principles underlying the use of inferential statistics
- Critically evaluate the use of different paradigms and techniques in published research papers
- Apply knowledge to choose and carry out statistical tests for a range of empirical data
- Use ICT resources (e.g. SPSS/Excel) for the advanced analysis of data
- Demonstrate the ability to analyze statistically data collected in the student¿s own research projects
|
Reading List
| Field, A. (2009) Discovering Statistics using SPSS (3rd Ed.) Sage, London |
Additional Information
| Course URL |
http://www.education.ed.ac.uk/courses/ug/sport-sci.html |
| Graduate Attributes and Skills |
This course addresses 13 of the 21 graduate attributes developed on the BSc Applied Sport Science degree
RESEARCH AND ENQUIRY
(1) Understand the philosophy of scientific methods of enquiry in order to critically evaluate evidence and analyse research literature.
(2) Search for, access, critically analyse, evaluate and synthesize information from literature in order to answer research questions in sport and exercise sciences.
(3) Plan and execute research projects, involving data collection and analysis, which answer research questions in sport and exercise sciences.
(4) Interpret data collected or reported in sport, physical activity and exercise studies
(5) Synthesize knowledge from various disciplines so as to understand the multidisciplinary and interdisciplinary nature of sport and exercise sciences.
(6) Develop logical arguments surrounding issues within sport science, physical activity and exercise
PERSONAL AND INTELLECTUAL AUTONOMY
(7) Be independent learners who can take responsibility for their own learning
(8) Be able to respond to unfamiliar problems by extrapolating their existing knowledge and understanding
COMMUNICATION SKILLS
(9) Be able to communicate clearly using oral and written methods, including posters, presentations, essays, web pages, in order to critique, negotiate, create or communicate understanding
(10) Be able to use communication as a means for collaborating with and relating to others including staff, other students and research participants.
(11) Be able to engage in critical discussion demonstrating listening skills, effective use of evidence and their own experiences to articulate points and defend their own assertions
(12) Be able to initiate communication with non-university agencies connected to sport and exercise
PERSONAL EFFECTIVENESS
(13) Be able to plan and execute substantive research projects in sport and exercise sciences (including but not limited to the dissertation and mini-project)
(14) Have developed their organisational, time management and decision-making skills
(15) Be able to work effectively in a team; overcoming and discussing problems and recognising the diversity of contributions different individuals can make to collaborative work
(16) Be able to transfer knowledge and ideas between different contexts within sport, exercise and health
(17) Be able to engage effectively with outside agencies to foster or develop research, consultancy or support initiatives
TECHNICAL/PRACTICAL SKILLS
(18) Be able to use the test, measurement and analysis tools appropriate to sport, physical activity and exercise, including for example laboratory or field tests.
(19) Be able to design, deliver and analyse the effects of training interventions in sport, physical activity and exercise
(20) Be able to select and apply the appropriate statistical procedures to analyse empirical data
(21) Be able to present data and report research findings according to standard scientific conventions |
| Keywords | sport science research methods statistics |
Contacts
| Course organiser | Dr Shaun Phillips
Tel: (0131 6)51 4110
Email: |
Course secretary | Mr Pawel Horyszny
Tel: (0131 6)51 6571
Email: |
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