Feedback Interventions

Just completed a research proposal on the 'Impact of Feedback Interventions on kicking accuracy in Football (Soccer)', what do you think?

Overview of the problem

The proposed research study will look at the impact of positive, negative and neutral feedback (feedback interventions) has on individuals kicking accuracy. The study will also indirectly access at their effect on overall performance. By looking at the effects of feedback interventions on accuracy, it is hoped the research will aid in the better understanding of how the application of feedback affects individuals. Currently there are large inconsistences within the literature regarding the effect that feedback interventions have on performance, of which much of this is controversial and highly debated. 

At the conclusion of the study it is hopped that there will be a clearer and more in depth understanding of the most effective feedback interventions to used. This data will assist in implementing the optimal feedback intervention to an individual to improve accuracy and thus performance. Therefore, the key question that this study will try to answer is ‘Does feedback interventions effect kicking accuracy, and if so which is the most effective intervention?’

Aims/Objectives

To find out if feedback interventions effect kicking accuracy over a 6 month period, which intern will help identify the optimal feedback process to elicit a positively affect an athletes performance.

Key Terms and Definitions

Feedback interventions; actions taken by an external agent to provide information regarding aspects of one’s task performance.

Positive and Negative Feedback: knowledge of a result and/or performance that has the potential to influence behaviour or modify further performance in an three ways, adversely, beneficial or have no effect.

Neutral feedback:  Similar to positive and negative however no information is given regarding knowledge of result and/or performance.

Historical Context and justification

Since the early 1900’s research has been conducted around the area of feedback interventions in psychology, however their has been very little if any consensus regarding the affects feedback has on individuals and more specifically on kicking accuracy in sport. However there are three theories that have appeared in feedback intervention literature. They are; Goal Setting Theory, Control Theory and Feedback Intervention Theory.

Goal Setting Theory (Locke and Lathem 1990) and Control Theory (Carver and Sheier 1981) both look at feedback as a theoretical component of psychology. Approaching feedback interventions in this way limits these theories ability to be applied to different areas within feedback (e.g. can only look at cognitive process effects), therefore researchers are only able to analyse a single dimension of overall effects.

            Feedback Intervention Theory (Kluger and Denis 1996) takes elements of Control, Goal Setting, and Action Identification Theory as well as small components of several other theories in order to develop a holistic approach in understanding effects of feedback. Research into this approach by Klugar and Denis have found that it poorly details overall effects of feedback interventions as well as lacking specificity in predicting feedback responses.

As a result of the lack of sufficient theory and poor understanding within the area of feedback interventions there has been a growing hypotheses being derived from Behaviouristic Law of Effect (Thorndik 1927). However they have been disproven due to inconsistences within data collection methods by Annett (1969). Further to this, research conducted by Levi (1965), Patkai (1971) and Frankenhaeuser (1975) shows that positive feedback can produce physical arousal/stimulation, just as research by Suls and Mullen (1981) highlight how negative feedback is able to elicit the same outcomes as positive feedback, as well as force changes to an individuals behaviour. Finally, studies by Burick and Burnes (1958) and Gomly (1971 and 1974) show that information ‘in opposition to one’s self opinion elicits physiological arousal’.

As highlighted above there is currently very limited and unclear evidence to conclusively outline the effect(s) of feedback on performance and more specifically accuracy. Due to this, it is of great importance that there is a study that looks into the impact feedback interventions has on kicking accuracy, in order to determine the effects on performance.

Hypotheses

Drawing from what has been discovered and presented in published literature this proposal hypothesises that:

H₁: Both positive and negative feedback will have and equal beneficial effect on kicking accuracy over a short period of time, but will then have a progressively greater impact over a long period of time.

H₀: Feedback interventions will have no impact on kicking accuracy over either a short or a long period.

Method

Participants

Participants will be selected from students between the ages of 18 – 40. The participants will be an equal mix of males and females, whom study a Bachelor of Sport Coaching and Exercise Science at the University of Canberra, and have had previous experience in playing soccer. Individuals will be chosen using these criteria in order to maximise the likelihood of them being able to competently complete assigned tasks. The range of ages and an equal number of male and females will help identify if feedback effects differ with age and gender. A pre exercise-screening questionnaire will be conducted prior to the start of the experiment and analysed by an accredited sports scientist to make sure there are no health concerns.

Design

The study will be a randomised continuum test that will be conduct in a lab setting to minimise any effects of the external environment. The independent variable is feedback given, while the dependant variable is kicking accuracy. By looking at these variables the effects of feedback interventions on kicking accuracy can effectively be measured. Written consent will be required by all participants and an a detailed explanation of the different ways feedback may given regarding knowledge of result and/or performance so that everyone is confortable and prepared

Equipment Require

1. A soccer ball
2. A movable mini soccer goal post (0.5 x 1m) and
3. A cone marker

Analysis

Procedure

Prior to testing, participants will be divided into three groups with equal age and gender distributions (Group 1 – No Feedback, Group 2  - Negative Feedback and Group 3 – Positive Feedback) with only the experimenter knowing their assigned groups. Group members will be tested one at a time in a randomised order, with the test involving them to kick a soccer ball into a goal (set at a distance of 15m) five times. They will be given specific feedback according to their allocated group and retested. Tests will be conducted once a month, continuously for six months to analyse the effects of feedback over a long-term period.

Analysis

In order to analyse data collected a Three – Way ANOVA was used to show the effects that experiment variables have on kicking outcome while removing implications that random results have on data sets. While, kurtosis and skewness test will be conducted to ensure data collected is clean. Results will be presented in both tabular and graph form with changes in kicking accuracy due to feedback given being of key importance (shows feedback interventions affect kicking accuracy).

Talent Identification Models

Sorry for such a long break from writing, have been trying to stay on top of some university assessments. The following is a presentation I submitted for one of of my units, hope you find it helpful.

Talent identification in the process or processes of recognising & identifying individuals with a natural talent and ability through the use of systematic, subjective and objective measures that have the greatest perceived potential to produce the greatest return on resource investment.

Most TID programs are currently aimed at pre adolescent athletes that are perceived to have the current ability to succeed at an elite level in the future.

Once identified athletes are institutionalised & taken in by sporting clubs or governing bodies such as the Australian Institute of Sport. There they are given specialised coaching and training aimed at accelerating development & increase chances of elite success.

The concept of TID has been around for as long as team selection in sport has been however, the formalised process was introduced in the 1950’s and 60’s by Eastern bloc countries such as the soviet union, Germany, Bulgaria and Romania who used what is now know as the Traditional Model for TID.

The Traditional model relies on performing systematic measures on physical and performance characteristic of athletes, in particular young athletes aged between 6 – 16. As well as using the haphazard system which involves looking purely at an athletes performance from an aesthetic point of view in order to try to identify athletes that are talented and would benefit from institutionalisation.

Strengths

1. Indicates an athletes current physical attributes and ability
2. Allows for early allocation of resources 
3. Easy to understand model that can be reproduced as well as being cost effective

Weaknesses

1. Poor accuracy in predicting long term potential for success in young athletes
2. No research backing up claim that early sport specialisation will lead to greater likelihood of success 
3. Haphazard system leads talent being miss judged both positively and negatively 

Over the past 20 – 30 years the area of TID has  finally been taken seriously throughout the rest of the world and has led to the development of specialised programs such as ‘The Australian Talent Search Program’ and the ‘UK High Performance Program’.

Currently countries and sporting organisations are trying to develop models that are able to more accurately & efficiently identify athletes in order to make better use of invested resources. However, due to the lack of consensus on the best ways to define talent there is no uniform framework to guide current or potential research & methods.

This had led to many varying models to identify talent both for young and mature, with all models looking at varying amounts and types of individual characteristics to try and judge talent & future elite success in a specific sport. 

Some of these methods include but are not limited to: -

Differentiated Model of Gifted and Talented (DMGT)

Designed by Francois Gagne this model places great emphasis on nature & nurture approaches, both play a key role in identification of talent as well as being able to take into consideration dynamic and multidimensional characteristics of an athlete over time.

DMGT also allows for the distinction between potential and current ability by taking into account unique features of success such as maturity both physical and mental, previous experience and capacity to learn

Strengths

1. Uses a holistic approach to TID
2. Takes into consideration current ability, this has the potential to lead to more accurate predictions in elite success
3. Focuses on individuals strengths not weaknesses
4. More efficient use of current resources in terms of long term development and success

Weaknesses 

1. Complex model that requires large amounts of data to be collected in order to make talent assessments
2. High short term costs that may not lead to the identification of any appropriate athletes
3. No sufficient evidence/evaluations on efficiency or accuracy

Evidence Based Model

Model was first developed in a study by Abbott & co in 2002 places an emphasis on predicting and athletes capacity to develop in the future by using current mental performance measures.

In order to achieve this EBM looks mainly at the psycho behaviour of an individual and how this will potentially develop over time – this steams from Behaviourism theory of learning that is based upon the idea that all behaviours are acquired through conditioning

Also in this model the process of TID & TDE are combined to give an athlete the greatest possible opportunity to develop areas needed for success – before an athlete is selected or removed from a program their progress in development is monitored extensively

Strengths

1. Emphasis on long term capacity in TID
2. Holistic approach with a focus on psycho behaviour
3. Combines ID &DE in a combined long term process
4. Constant monitoring before selection or de-selection – more informed and accurate selection process

Weaknesses

1. High ongoing cost of monitoring of athletes
2. Complex process of identifying athlete psychological behaviours
3. No real evaluation or research regarding the efficiency or accuracy of the model

Talent Crossover Model

Study by Ward in 2004 looking into alternative strategies in identifying & promoting talented individuals found that diversified training in early stages of development could improve likelihood of reaching elite level in sport in the future

This research in conjunction with other research has brought about an alternative thought regarding early athlete specialisation, which is talent recycling and mature talent identification. Essentially the assessments are similar to that of the Traditional Model but done at a later age/maturity level

            Talent recycling; involves athletes moving from different sports with similar or complementary skill requirements once their unique skill set is know longer suited or required by their current sport. Main aim of this approach is to prolonging athletes sporting career and maintaining talent with the talent pool. 

            Mature Talent Identification; athletes move from sport to sport developing different sport specific skills in order to have a more holistic understanding of sports movements and Athlete selects a specific sport once fully matured. Aim is to prevent athlete burnout from early specialisation as well as building a diverse sport experience profile. 

Strengths

1. Potential to more accurately and efficiently predict athletes chances of elite success
2. Allows athletes to re-use previously attained skills, extend careers and increases and size of talent pool
3. Saves on valuable resources which allows for better long term allocation
4. Decreases time needed to develop athlete due to past experiences

Weaknesses

1. Decreases opportunities for younger athlete
2. Athletes learn bad habits from other sports, making learning difficult
3. Requires strong communication & sharing of resources between different sporting bodies.

As the area of sport has grown, so has the demand on clubs, in particular their sporting departments to identify and select the very best talent available in order to win.

These demands however, have revealed major floors in the methodology behind TID models, the main one being a models ability to accurately predict if a young talent has what it takes to become successful at an elite level.

This is due to the unknown impact hormonal changed during adolescents with have on an individual. In order to try an overcome such issues some researches/sport scientists have tried developing ID talent, as mentioned above. However, most sports persist with out dated methods despite research stating that they should move forward. 

Methods based on age, physical attributes and performance are not able to predict variations in maturity status (hormonal changes) at a given age and therefore become problematic due to the links between performance and maturity status 

Until sporting federations decide to move to more innovative and accurate identification methods they will continue to miss allocate resources and allow talented athletes to slip through the cracks

• As well as those mentioned previously, TID regardless of the accuracy predicting elite success provides an opportunity to an athlete to have high levels of exposure to the best possible resources in order to try an reach their potential

• Talent Model that can accurately predict future elite success will lead to a greater competitive edge on rival clubs and sporting codes as quality of competition and players will be significantly increased and thus attracting sponsorship and larger crowd numbers

Further Research Areas

• Key areas that need to be further researched in order to gain a much better understanding of TID models: -
• Efficiency and accuracy of current models in predicting potential for athletes to reaching elite level
• In particular the use of talent crossover model and DMGT Effects of institutionalised programs on development of athletes
• Main characteristics that indicate potential elite success
• More realistic testing protocols to improve predictive measures and assessments

TID models vary in their ability to predict an athletes future potential. In order improve resources allocations, success of clubs and prolong an athletes career, more accurate and reliable selection methods need to be promoted by sporting federations and clubs as well as vastly improving communication pathways between similarly skilled sports of athlete selection. 

http://prezi.com/dnehzztx8y5a/present/?auth_key=pfu7bfb&follow=hjugnphujtee&kw=present-dnehzztx8y5a&rc=ref-31528857