Technology in sport: Making decisions in a time of data overload
HEL617-1
Included in Study
PhD Programme in Health and Sport Sciences
Language of instruction
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
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
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
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.
Examination requirements
Participation in compulsory lectures, group work, practical workshops, discussions and presentations as stated in the course description
Assessment methods and criteria
Individual two-weeks home examination will be assessed as pass/fail.
Offered as Single Standing Module
No
Admission for external candidates
No
Other information
Contact persons: Matthew Spencer (matthew.spencer@uia.no) and Stephen Seiler (stephen.seiler@uia.no)