HEL617 Technology in sport: Making decisions in a time of data overload (Høst 2023)
- Studiepoeng:
- 5
- Ansvarlig avdeling:
- Fakultet for helse- og idrettsvitenskap
- Emneansvarlig:
- Matthew Ronald Spencer
- Undervisningssemester:
- Høst og Vår
- Undervisningsspråk:
- English, if any English as mother tounge participants.are enrolled
- Varighet:
- ½ år
Innholdsfortegnelse
Emnet er tilknyttet følgende studieprogram
Undervisningsspråk
English, if any English as mother tounge participants.are enrolled
Forkunnskapskrav
Adimtted to a PhD-program
Anbefalte forkunnskaper
- EX-605 Philosophy of Science in Health and Sport Science
- ME-617 Systematic Reviews and Evidence Synthesis or equivalent
- ME-626 General Quantitative Research Methods or equivalent
Læringsutbytte
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
Innhold
- 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
Undervisnings- og læringsformer
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.
Vilkår for å gå opp til eksamen
Participation in compulsory lectures, group work, practical workshops, discussions and presentations as stated in the course description
Eksamen
Individual two-weeks home examination will be assessed as pass/fail.
Tilbys som enkeltemne
No
Tilgang for privatister
No
Annen informasjon
Contact persons: Matthew Spencer (matthew.spencer@uia.no) and Stephen Seiler (stephen.seiler@uia.no)
Sist hentet fra FS (Felles studentsystem)
15. okt. 2026 14:07:03