Samenvatting
Summary Talent Identification and Development
Summary of the lectures + notes and mandatory literature
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Voorbeeld 4 van de 80 pagina's
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Voorbeeld van de inhoud
Talent identification and DevelopmentLecture 1 – Introduction
➢ Students are able to summarize and examine the implications of adopting a multi-disciplinary
research perspective for the comprehensive study of talent development and identification,
and identify and elaborate upon the limitations of existing research on talent identification
and development (expert performance).
➢ Students are able to make recommendations for future research on understanding talent
development and for implementing talent developmental programs
Part 1
1. Why it is difficult to do TID
2. Why it is difficult to predict TD
3. What are the different path ways of TD
4. Concept of Talent = View of Talent
Short term prediction: easier than long term (10 years), because sports change quickly (and
therefore we don’t know what the talent must be like over then (requires different skills))
- Problem: also sports change on short term
What is a talent → “Degree of individual potential”
➢ Successful athletes seem to improve more within the same or even less time when compared
to their less successful counterparts.
• Preservation is a characteristic for talent
• Game insight
• Multidimensional concept
• Many scientific disciplines explain what talent is, each within their own paradigm
• Definitions originate from specific paradigms
Traditional model: selection every year
➢ In every level you go through the cycle of Williams and Reilly
,Model (Williams): doesn’t necessarily imply that the best athletes are selected (injuries, team
composition, long-term goals, etc…)
- Looks like a linear path, but this is not the case! (Gulbin et al, 2013)
Gulbin et al., 2013: assumes a linear path, but this is not the case (see Figure 2)
- Looked back on the path of Olympians/World champions which path they followed
, Results
o Linear path only followed by 16%
o Mixed ascent followed by 26% (non-linear path, but always moving forward)
o Mixed descent followed by 57% (non-linear path, sometimes drop-out/descent)
Conclusion
o Talent development is in most cases not linear (80%)
o Talent development systems are based on linear development
Talent identification
- Looking for similarities within a group of talents
- Commonalities (gemeenschappelijke kenmerken) used for identification
- Question: What could be the problem with this line of thought?
o Correlation vs. causality
▪ You may find a correlation, but that doesn’t mean it causes the talent
▪ All talents may have similar characteristics, but all these characteristics may
also be shared by many other persons (e.g., self-regulation)
Gold mine effect (Rasmus ankersen)
Separate performance from potential
Whispering talent: not discovered in the first years
Shouting talent: obvious talents → linear talents
1. Great talent is not necessarily right talent
2. What you see is not necessarily what you get
a. “A raw 10.6 sec might be better than a trained 10.2 sec sprint”
3. Never overrate certificates & never underrate character
, Part 2: What are the models of TD (part 2)
Pathways of talent development
• Early specialization
• Late specialization
• Diversification
• Early engagement
Talent development models
1. 10K Ericsson- early specialization
2. 3 stage model of Cote (Bloom)
3. Bayli: Long Term Athletic Development
4. FTEM: Australia
5. Athletic Skill Model- early engagement
Ericsson
- 10.000 hour rule (origins from musicians)
- Deakin & Cobley, 2003: relative comparison with sports
- Deliberate practice: “Deliberate practice effective learning occurs through involvement in a
highly structure activity”
o Requires effort
o Generates no immediate rewards
o Motivated by the goal of improving performance (rather than inherent joy)
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