HEL617 Technology in sport: Making decisions in a time of data overload
- ECTS Credits:
- 5
- Responsible department:
- Faculty of Health and Sport Sciences
- Course Leader:
- Matthew Ronald Spencer
- Lecture Semester:
- Spring, Autumn
- Teaching language:
- English, if any English as mother tounge participants.are enrolled.
- Duration:
- 1 term
The course is connected to the following study programs
Teaching language
English, if any English as mother tounge participants.are enrolled.Prerequisites
Adimtted to a PhD-program
Recommended prerequisites
-
EX-605 Philosophy of Science in Health and Sport Sciences
-
ME-617 Systematic Reviews and Evidence Synthesis or equivalent
-
ME-626 General Quantitative Research Methods or equivalent
Course contents
-
General to sport-specific: Progression from laboratory to field-based assessments
-
Testing and monitoring athletes in endurance, strength/power and team sports settings
-
Using day-to-day data to optimize individual training load: Stress/Recovery balance
-
Opportunities and limitations of using Artificial Intelligence in sport
-
Development and opportunities with distributed/crowdsourcing data methods
-
Effective interpretation and presentation of data for coaches and athletes
-
The evolution of sport and the future of e-sport
Learning outcomes
On successful completion of the course, the candidate will have acquired:
Advanced knowledge about:
- Current technologies and data collection methods employed in high-level sports (endurance, strength/power and team sports)
- Relevance and interpretation of laboratory versus field-based assessments
- Training data analytics applied to performance monitoring and development
- Distributed data collection approaches
- Validity and reliability of commonly used metrics in high-level sport
- Integrating and interpreting physiological and psychological metrics
- Artificial Intelligence/machine learning in sport science
Skills
- Can critically evaluate, disseminate results within data analysis and interpretation in high-level sport
- Can critically evaluate assessment methods used for physiological and psychological data metrics in high-level sports
- Can formulate relevant research questions and plan the implementation of data analysis and interpretation in high-level sport research and interventions
General competence
- Can communicate relevant knowledge through scientific and popular scientific channels
Examination requirements
Participation in compulsory lectures, group work, practical workshops, discussions and presentations as stated in the course description
Teaching methods
Over five days, teaching and learning methods will consists of a combination of lectures, group work, practical workshops, discussions, and presentations based on course topics and the candidates own research experiences and work.
Admission for external candidates
No
Offered as Single Standing Module
No
Assessment methods and criteria
Individual two-weeks home examination will be assessed as pass/fail.
Other information
Contact persons: Matthew Spencer (matthew.spencer@uia.no) and Stephen Seiler (stephen.seiler@uia.no)