Introduction to the Vision, Mission and History of the International Olympic Academy

**To Explore and Enhance the Contribution of Olympism to Humanity in the 21st Century**

“Defending and promoting the Olympic Ideal from both the sporting and the cultural point of view must be a task that we all share.” –Jacques Rogge, President of the IOC

### Vision

The International Olympic Academy functions as a multicultural interdisciplinary center that aims at studying, enriching and promoting Olympism. The foundation of such an institution was inspired by the ancient Gymnasium, which shaped the Olympic Ideal by harmoniously cultivating body, will and mind. On the eve of the 21st century, the centennial anniversary of the revival of the Olympic Games coincides with the global scale changes that are affecting every aspect of human thought and activity.

We, our cultures and our civilizations have already entered a greater transitional period in which the images of the world that we were used to taking for granted are being altered. The interrelated scientific, technological, economic, political and social developments that characterize the course of humanity towards the third millennium are influencing each and every idea, norm and institution of our international community.

This dynamic wave is also opening up new forms of dialogue for the future of Olympism. Moreover, as can be seen through the study of its age-long history, the Olympic Ideal has always been conceived and formed according to the wider conditions prevailing during different periods in time. The birth, the prosperity, the decline and the revival of the Olympic Games have all been the reflection of the wider cultural conditions that shaped each era.

The speculations and potentials still evolving out of the Olympic Movement are naturally arising in the realization process of such an Ideal. “Olympism,” after all, in the words of Pierre de Coubertin, “is not a system, it is a state of mind. It can permeate a wide variety of modes of expression and no single race or era can claim to have the monopoly of it.”

The International Olympic Academy provides a unique opportunity for students, academics, athletes, artists and officials from all over the world to exchange ideas and share this “state of mind” in Ancient Olympia.

The wide variety of educational sessions, academic programs and in-depth research studies that are offered, all aim towards serving the vision of the International Olympic Academy for the new century: to explore and enhance the contribution of Olympism to humanity.

### Mission

The mission of the IOA is:

1. To function as an International Academic Centre for Olympic Studies, Education and Research.
2. To act as an International Forum for free expression and exchange of ideas among the Olympic Family, intellectuals, scientists, athletes, sport administrators, educators, artists and the youth of the world.
3. To bring together people from all over the world, in a spirit of friendship and cooperation.
4. To motivate people to use the experiences and knowledge gained in the IOA productively, in promoting the Olympic Ideals in their respective countries.
5. To serve and promote the Ideals and principles of the Olympic Movement.
6. To cooperate with and assist the National Olympic Academies and any other institutions devoted to Olympic Education.
7. To further explore and enhance the contribution of Olympism to humanity.

### History

Officially inaugurated on 14 June 1961, the IOA initially limited its function to organizing the International Session for Young Participants. In 1967, an IOC commission was created to coordinate relations among the IOA, the Olympic Movement, and Olympic Solidarity. This same year, the first permanent premises for the IOA were constructed at the site of Ancient Olympia.

By 1970, the educational programs of the IOA had expanded to cover all aspects of the Olympic Movement. Special sessions for institutions involved with Olympism were established, including National Olympic Committees (NOC), National Olympic Academies (NOA), International Sport Federations (FIEP), Sport Medical Societies, Unions of Coaches, Sports Administrators, and Teachers.

Growing out of ancient Greek civilization, Olympism is a philosophy of life that blends sport, culture, and education to produce a balanced character strong in body, mind, and will. Convening at Ancient Olympia infused with this dramatic lineage is important to the spirit of the conferences, and the campus exerts a profound effect on all who visit and study there.

“We are in a haven of peace and balance, where centuries remain engraved on the stones…the beauty of the vegetation, and the serenity which pervades this unique place, Olympia, where sport started on its most glorious and finest course.” – Juan Antonio Samaranch, Former Honorary President of the IOC and IOA

Many of these ancient traditions continue today. Two of the most powerful ceremonies are the laying of wreaths at the monument where Pierre de Coubertin’s heart is buried to honor the man who revived the Ancient Games, and the Lighting of the Olympic Flame to inaugurate the official Olympic Games.

In Ancient Greece, a person needed well-rounded training to be considered cultured. Sport was part of man’s education that aimed at cultivating harmonious intellectual, mental, and physical faculties. Young students were taught art, philosophy, and music, as well as sports, based on the spirit of fair competition and high ethics.

Held every four years, the Ancient Olympic Games were an integral part of the balanced way of life. With its origins in the mists of Greek mythological tales of gods and goddesses, the honor of victory at the Olympic Games carried sacred blessings and immense prestige. The Olympic Games went through many reversals of fortune due to political changes over the long history. From circa 400 AD to the late 1800s, no organized Olympic Games existed. Then in 1896, Pierre de Coubertin succeeded in reviving the tradition, and the first modern Olympic Games were held in Athens.

In 1927, Coubertin originated the idea for adding an international Olympic academy in his efforts to spread Olympic values. In the IOA, the realization of his vision continues to grow as a result of the dedicated contributions of many people over decades. Now overseen by the IOC, the International Olympic Movement (IOM) has been formed to functionally implement Olympic ideals through a conglomeration of organizations and individuals. Recognizing education as the backbone of the Olympic Movement, the IOC supports the IOA and other institutions devoted to Olympic education.

The current IOA houses many priceless resources, such as an archeological museum, a modern Olympic Games museum, a research library, the Coubertin Grove, and the excavated ruins of Ancient Olympia’s temples, gymnasium, and Sanctuary constructed by Alexander the Great in 338 B.C. These exalted settings, sacred to the Greek god, Zeus, offer a cornucopia of contemporary sports media conferences, research studies, special sessions for dignitaries, gatherings of Olympic medalists, the Olympic Studies Master’s Degree Program, and other courses for international students of the IOA.

2020-06-02T13:33:19-05:00June 28th, 2011|Contemporary Sports Issues, Sports Facilities, Sports Management|Comments Off on Introduction to the Vision, Mission and History of the International Olympic Academy

Olympic Edition 2011

### The Second Annual Olympic Edition

**International Olympic Academy: 11th Joint International Session for Presidents or Directors of National Olympic Academies and Officials of National Olympic Committees**

#### Table of Contents

1. [Foreward – The Sport Journal](#forward)
2. [Introduction to the Vision, Mission and History of the International Olympic Academy](/article/introduction-vision-mission-and-history-international-olympic-academy)
3. [Opening Remarks of the 11th Joint International Session for Directors of National Olympic Academies by Mr. Isidoros Kouvelos](/article/ioa-president-s-opening-remarks-11th-joint-international-session-directors-national-olympic-)
4. [Medicine and the Olympic Games of Antiquity by Dr. Spyros Retsas](/article/medicine-and-olympic-games-antiquity)
5. [The Importance of New Forms of Technology in the Dissemination of Humanistic Ideas by Dr. T.J. Rosandich](/article/importance-new-forms-technology-dissemination-humanistic-ideas)
6. [The Digital Revolution Impact to Olympic Education by Dr. Axel Horn](http://thesportjournal.org/article/digital-revolution-impact-olympic-education)
7. [Interdisciplinary Approach of the Teaching of Olympic Principles to the Students by Dr. A M. Najeeb](/article/interdisciplinary-approach-teaching-olympic-principles-students)
8. [Teaching the Olympic Values within the Educational System by Dr. Yohan Blondel](/article/teaching-olympic-values-within-educational-system)
9. [Youth Olympic Games – From Vision to Success by Mr. Ng Ser Miang](/article/youth-olympic-games-vision-success)
10. [The Role of Olympic Education in Today’s Sport World by Dr. Margaret Talbot](/files/olympic-edition/2011/The_Role_of_Olympic_Education_in_Today_s_Sport_World_by_Dr._Margaret_Talbot.pdf)
11. [Two United States Olympic Committee Olympism Programs](/article/two-united-states-olympic-committee-olympism-programs-team-usa-ambassador-program-and-olympi)
12. [IOA Closing Remarks on Behalf of the Lecturers by Dr. T.J. Rosandich](/article/closing-remarks-behalf-lecturers)
13. [IOA President’s Closing Remarks on the 11th Joint International Session for Directors of National Olympic Academies by Isidoros Kouvelos](/article/ioa-president-s-closing-remarks-11th-joint-international-session-directors-national-olympic-)


#### Forward

This second annual special Olympic Edition from the United States Sports Academy’s _The Sport Journal_ is dedicated to the International Olympic Academy (IOA) and its worldwide programs.

In May, the International Olympic Academy held its 11th Joint International Session for Presidents or Directors of National Olympic Academies and Officials of National Olympic Committees in Ancient Olympia, the birthplace of the Olympics. Dignitaries from around the world gave presentations on the issues vital to “Olympism,” with a special focus on the youth and the future of Olympism in an ever-changing global world.

The seven presentations at the conference spanned some 3,000 years of human existence, discussing medicine in the ancient Olympic Games to reaching youth about Olympism in today’s Information Age. A common theme was the role of education in spreading the Olympic ideals and values of fair play, respect, meritocracy and peace.

Students at the IOA use _The Sport Journal_ as reference material for their work more than any other journal. With more than 500,000 unique visitors per year, _The Sport Journal_ is the most read sport journal in the world.

These pieces are based on live presentations by experts from a variety of academic disciplines. Because they are being introduced here to a wide, general audience, _The Sport Journal_ has relaxed its standard rule requiring entries to adhere to American Psychological Association style.

We hope you enjoy reading the second annual Olympic Edition and learn valuable insights from the presentations by the Olympic scholars at the May 2011 session in Greece.

Duwayne Escobedo
_The Sport Journal_ Editor
United States Sports Academy

2016-04-01T09:14:29-05:00June 28th, 2011|Contemporary Sports Issues, Sports Management|Comments Off on Olympic Edition 2011

Olympic Edition 2010

### International Olympic Academy: 10th Joint International Session for Presidents or Directors of National Olympic Academies and Officials of National Olympic Committees

#### Table of Contents

1. [President’s Forward – Dr. Thomas P. Rosandich](#forward)
2. [Introduction to the International Olympic Academy – Anne Kent Rush, Editor](/article/introduction-international-olympic-academy)
3. [National Olympic Academies – National Olympic Committees Parallel Paths, Intertwined Paths – Mr. Isidoros Kouvelos](/article/national-olympic-academies-national-olympic-committees-parallel-paths-intertwined-paths)
4. [The National Olympic Committee: Its Role and Position at the Dawn of the 21st Century – Mr. Giannis Papadogiannakis](/article/national-olympic-committee-its-role-and-position-dawn-21st-century)
5. [The Place and Role of Olympism in Higher Education – Prof. Dr. Antonin Rychtecky](/article/place-and-role-olympism-higher-education)
6. [The Institutional Framework for the Development of Olympic Education and the Role of the National Olympic Academy – Mr. Alexandre Mestre](/article/institutional-framework-development-olympic-education-and-role-national-olympic-academy)
7. [How to Spread and Develop Joint International Programs about Olympic Education: Cultural and Communication Problems – Mr. Henry Tandau](/article/how-spread-and-develop-joint-international-programs-about-olympic-education-cultural-and-com)
8. [The Position of the Athlete in the Social Structure of Ancient Greece – Prof. Mark Golden](/article/position-athlete-social-structure-ancient-greece)
9. [The Use of Sport Art for the Development of Olympic Education: Passing the Visual Torch – Dr. Thomas P. Rosandich](/article/use-sport-art-development-olympic-education-passing-visual-torch)
10. [Closing Address and Olympic Anthem – Mr. Isidoros Kouvelos](http://thesportjournal.org/article/closing-address)
11. [IOA Master’s Degree Program Specifications](/article/international-olympic-academy-masters-degree-program-specifications)
12. [Olympic Values Education Programme (OVEP) Progress Report: 2005-2010](/article/olympic-values-education-programme-ovep-progress-report-2005-2010)


#### President’s Forward

This special issue of the Academy’s _Sport Journal_ is dedicated to the International Olympic Academy (IOA) and its worldwide programs.

This past May, I delivered a presentation in Greece at the International Olympic Academy for the 10th Joint International Session for Presidents or Directors of National Olympic Academies and Officials of National Olympic Committees. My presentation topic was the use of Olympic posters as a reflection of the role of sport art in Olympic culture. Dignitaries from around the world gave presentations on the issues vital to education in Olympism. Special emphasis was placed on challenges in collaboration among the National Olympic Academies, the National Olympic Committees, and the IOA.

Located in historic Olympia, south of Athens on the Peloponnese Peninsula, the IOA functions as an international Academic Centre for Olympic Studies and is an exceptional new resource for students around the globe. Operated jointly by the International Olympic Committee (IOC) and the Greek government, the IOA offers a wide variety of research studies and educational programs aimed at spreading the vision of Olympism.

As President, founder and CEO of the United States Sports Academy, and as a member of the International Olympic Committee’s Commission on Culture and Education, I share the IOA’s vision of Olympism. During my visit, I met with Isidros Kouvelos, President of the IOA; with Professor Konstantino Georgiadis, IOA Honorary Dean; and with Professor Dionyssis Gangas, IOA Director. We discussed the IOA, its projects, and the impressive, new master’s degree program: Olympic Studies, Olympic Education, and Organization and Management of Olympic Events.

Students at the IOA use _The Sport Journal_ as reference material for their work more than any other journal. With more than 500,000 unique visitors per year, _The Sport Journal_ is the most read journal in the world.

Since these pieces, the bases of live presentations by experts from a variety of academic disciplines, are hereby introduced to a wide, general audience, _The Sport Journal_ has relaxed its standard rule requiring entries to adhere to American Psychological Association style. This _Olympic Edition_ offers the presentations given by Olympic scholars at the May 2010 session in Greece.

Dr. Thomas P. Rosandich
President and CEO
United States Sports Academy

2015-10-30T13:27:48-05:00June 28th, 2011|Contemporary Sports Issues, Sports Management|Comments Off on Olympic Edition 2010

Do static-sport athletes and dynamic-sport athletes differ in their visual focused attention?

### Abstract

The goal of this study was to evaluate current attention tests in sport psychology for their practical use in applied sport psychology. Current findings from the literature suggest that measures of visual focused attention may show different performances depending on sport type and test conditions (33). We predicted differences between static- and dynamic-sport athletes (17) when visual focused attention is tested with random (unstructured) versus fixed (structured) visual search in two experimental conditions (quiet environment versus auditory distraction). We analyzed 130 nationally competing athletes from different sports using two measures of visual focused attention: the structured d2 test and the unstructured concentration grid task. Compared to static-sport athletes, dynamic-sport athletes had better visual search scores in the concentration grid task in the condition with auditory distraction. These findings suggest that the results of attention tests should be differentially interpreted if different sport types and different test conditions are considered.

**Key words:** d2 test, concentration grid task, auditory distraction

### Introduction

The study reported here was motivated by recent calls within the applied field of sport psychology for a broad diagnostic framework in the domain of talent selection (7,35) as well as the ongoing evaluation for professional standards of the techniques that are used by practicing sport psychologists (14).

An increasing number of researchers have argued that psychological variables remain often unnoticed within talent identification models (1). However, among a range of other physical and technical variables, psychological variables have been identified as a significant predictor of success (18,27,34). For instance, during athletic performance attention is seen as one of the most important psychological skills underlying success because of the ability to exert mental effort effectively is vital for optimal athletic performance (12,22,27).

In cognitive psychology, attention is seen as a multidimensional construct. According to different taxonomies of attention, at least three distinct dimensions of attention have been identified (21,28,39). The first is _selectivity_. It includes selective attention as well as divided attention. The second dimension of attention refers to the aspect of _intensity_, which can include alertness and sustained attention. The third dimension is _capacity_ and refers to the fact that controlled processing is limited to the amount of information that can be processed at one time.

Individuals’ attentional performance in one or more of the aforementioned dimensions can be assessed in several ways (3, for an overview see 39). The selectivity aspect can, for instance, be approached with tasks involving either focused or divided attention. In focused attention tasks there are usually irrelevant stimuli, which must be ignored. In divided attention tasks, all stimuli are relevant, but may come from different sources and require different responses (39). Intensity requirements can be approached with tasks involving different degrees of difficulty, or with tasks that have to be carried out over longer periods of time. Finally, dual-task procedures, memory span tests, or other processing tasks are used to approach the capacity aspect (26). Practicing sport psychologists most often use standardized tests, which are easily administered in a paper-pencil form and therefore are easy to use in the field.

However, several authors (38) as well as diagnosticians in youth talent diagnostic centers in Germany have expressed a number of subjective impressions concerning the performance of athletes on attention tests (e.g., influence of sport type, test context, or expertise level) that are insufficiently indicated by the existing test norms. Therefore, the goal of the present study was to examine the influence of two essential factors (sport type and environmental context) on athlete’s performance in two different attention tests.

Boutcher’s multilevel approach (3) integrates relevant aspects of research and theory on attention from different perspectives. In his framework, internal as well as external factors, like enduring dispositions, demands of the task, and environmental factors, interact with attentional processes during performance. These factors are thought to initially influence the level of physiological arousal of the individual, which in turn influences controlled and automatic processing. When performing a task, the individual either uses controlled processing, automatic processing, or both, depending on the nature and the demands of the task. An optimal attentional state can be achieved by reaching or attaining the exact balance between automatic and controlled processing, essential for a particular task (3).

A sudden external distraction (e.g., auditory noise) is expected to hamper performance because it may disrupt the current attentional state by causing the individual to reach a level of arousal such that an imbalance in controlled and automatic processing occurs. However, individual differences may exist regarding the effect of internal or external distractions on attentional state. For instance, a gymnast normally performs his or her routine in a quiet environment in competition whereas during a basketball game the player is confronted with auditory noise. Unexpected auditory distractions may disrupt the attentional state of the gymnast but not the state of the basketball player because he is used to it.

There has been extensive research on different aspects of attentional performance in athletes. For instance, researchers examined attentional differences between athletes and non-athletes (5,20,23), between athletes on different expertise levels (8), as well as with regard to other factors, such as athlete type, sport type and gender (17,19,24,33) by using a variety of attentional tasks. Athletes are able to distribute their attention more effectively over multiple locations and better able switch their attention rapidly among locations than non-athletes (25). Furthermore, attentional performance seems to vary with the kind and amount of training provided by a sports environment so that athletes trained in more visually dynamic sports show better attentional control than athletes trained in less visually dynamic sports (24).

When using specific tests to assess attention performance, one should expect differences in test performance between athletes that vary in one or more of the aforementioned factors. In this context, Lum et al. highlight the need to examine athlete’s visual attention by using a variety of visual attention tasks (17, see also 20). Furthermore, existing test norms should account for the aforementioned differences to provide athletes with a reliable feedback on their individual attention performance.

For instance, to evaluate the visual focused attention performance of athletes, two common tests are used in the field of applied sport psychology, the d2 test and the concentration grid test (3, 4). Visual focused attention is usually operationalized as visual search so that target stimuli have to be found in a field of distractor stimuli (39). For instance, in the d2 test, participants need to select “d” letters with two dashes above them in an array of “d” and “p” letters with zero, one, or two dashes over or under each letter. The structure of reading letters from left to right provides an environment in which relevant stimuli need to be selected and irrelevant stimuli need to be ignored. The gaze searches throughout the visual array not in a random way but rather in a structured fashion. In contrast, in the concentration grid task, participants see a block of randomly distributed numbers, in which they need to search for numbers in sequence, such as number 01, then 02, 03, and so on. The concentration grid task is often administered as a training exercise in the field of applied sport psychology, and it has been proposed, that it works by developing the athlete’s ability to scan a visual array for relevant information, and to ignore irrelevant stimuli (11).

Given the different demands of these two tasks and the empirical evidence so far, one may speculate that athletes who have experience performing visual searches for relevant cues and making decisions in dynamic environments (which is typical for team sport athletes), will do better on the concentration grid test than on the d2 test (29). Athletes from individual sports who are exposed to a mostly static environment with one or a small number of stimuli should do better on the d2 test than on the concentration grid test.

Maxeiner compared, for instance, 30 gymnasts and 30 tennis players in their performance on the d2 test and on a reaction time task in which they were asked to press a pedal with their foot as soon as a square appeared on a computer monitor (19). Participants were tested under either a single-task condition, such that only the d2 test or the reaction time task had to be performed, or a multiple-task condition, in which both the d2 test and the reaction time task had to be carried out simultaneously. Reaction times showed a significantly stronger increase under the multiple-task condition for the gymnasts (about 28%) whereas no differences between gymnasts and tennis players were found for single-task conditions. The author concluded from this result, that tennis players have a better distributive ability of attention than gymnasts. However, the total number of items worked on the d2 test as well as the error rates did not differ between gymnasts and tennis players in either the single-task or multiple-task condition.

Tenenbaum, Benedick, and Bar-Eli conducted a similar study and found opposing results (33). The authors compared 252 young athletes from different sports disciplines in their d2-test performance. All athletes performed the d2 test in a quiet classroom with no distractions. Results indicate that the number of d’s the subjects have crossed (quantitative capacity) differed significantly by type of sport in females. High quantitative capacity scores in the d2 test were found for female athletes from sports such as tennis or volleyball, but not for female athletes from gymnastics. A similar pattern of results was found in male athletes, although only showing a tendency for rejecting the null hypothesis (p = .06). The authors found an additional effect for type of sport on error-rate. The largest error-rates were found in tennis and volleyball players whereas the smallest error-rates were found in track and field athletes. The authors concluded that concentration is individual and sport-type dependent and state that “Concentration should be further investigated with relation to motor performance” (p. 311).

Maxeiner and Tenenbaum et al. found opposing results in athletes from different sport domains in the d2 test (19,33). First, the authors assessed different parameters of the d2 test. Maxeiner quantified the total number of items worked on the d2 test, whereas Tenenbaum et al. quantified the number of d’s the subjects have crossed. The number of items worked on the d2 test is a reliable criterion for working speed (4), whereas the number of crossed d’s is related to both working speed and working accuracy. Assessing different parameters in the d2 test could lead to different results, therefore masking possible differences between participants from different sport domains. Following the suggestions of Brickenkamp, the practitioner should assess the concentration-performance score (number of marked d’s minus the number of signs incorrectly marked) in the first instance, because this value is resistant to tampering, such that neither the skipping of test parts nor the random marking of items increases the value (4).

Furthermore, Tenenbaum et al. had participants from tennis, fencing, volleyball, team-handball, track and field, and gymnastics indicating an unequal distribution of participants with regard to other criteria like kind of training provided by a sports environment (33). As mentioned above, attentional performance seems to vary with the kind and amount of training provided by a sports environment (24); the question arises whether athletes should be classified according to kind of training provided by a sports environment, rather than sport discipline per se when assessing their attentional performance.

Greenlees, Thelwell, and Holder examined the performance of 28 male collegiate soccer players in the concentration grid exercise (13,15). The players were assigned to either a 9-week concentration grid training or a control condition. During three test sessions the athletes were asked to complete a battery of concentration tasks, including the aforementioned concentration grid test. The results showed a significant main effect for training condition but not for test session, indicating that the concentration training group was superior to the control group but did not exhibit any improvement during the 9-week training interval. However, Greenless et al. assessed only soccer players with a playing experience of 10.45  2.31 years, which indicates that they already possess substantial experience in performing visual searches for relevant cues in dynamic environments (13). This could at least in part explain why the participants of the concentration training group did not improve their performance on the concentration grid task as compared to the participants of the control group. Additionally, the two groups were not homogeneous in their concentration grid performance at the study onset, which may in part explain the main effect for training condition. The findings of Greenless et al. highlight the need for further research on the concentration grid test, especially examining the extent to which the task reflects sport-specific concentration skills and therefore support the need for ongoing evaluation of this technique in diagnostics and intervention.

Taken together, we can identify two main factors that need to be considered when assessing athletes’ visual focused attention. First, a broad application of attention tests that are sensitive to the athlete’s experience in different types of sports should be made. This means, in particular, recognizing that different sport environments (static vs. dynamic), encouraging different visual search and decision strategies (fixed or structured vs. random or unstructured), and realizing that the same tests do not necessarily capture both types of strategies. Second, the environmental context (with or without distraction) can increase or decrease performance, respectively.

We adapted the dichotomy of Lum et al. and hypothesized that static-sport athletes and dynamic sport-athletes would not differ in d2 scores but would differ in concentration grid scores due to their different perceptual experiences (17). This finding would not only help to clarify previous results (19,33) but would extend them to different concentration tasks (d2 test vs. concentration grid) following the conclusions of Greenlees et al. as well as Tenenbaum et al. (13,33). We furthermore hypothesized that auditory distraction would have a detrimental effect on performance in both the d2 test and the concentration grid test because it may disrupt the current attentional state (3). We therefore compared performances in the d2 test and the concentration grid test with and without auditory distraction.

### Method

#### Participants

A sample of 130 athletes (students of Sport Science, German Sport University) were recruited to participate in the study (n = 44 women, mean age = 22 years and n = 86 men, mean age = 22 years). Ages ranged from 19 to 33 years, with a mean age of 22 years (SD = 2.4 years). Of these, 66 students (n = 15 women and n = 51 men) competed in 6 different sports with a dynamic visual environment (i.e., soccer, volleyball) and 64 (n = 29 women and n = 35 men) competed in another 6 different sports with mostly static visual environment (i.e., track and field athletics, gymnastics). All students had been performing their sport for at least 7 years with 19.2% (n = 25) of them reporting national experience (German championships or national league) and 11.5% (n = 15) also reporting international experience. All participants were informed about the purpose and the procedures of the study and gave their written consent prior to the experiment. Participants reported to have no prior experience with either the d2 test or the concentration grid test.

We recruited an additional sample of n = 25 students of sport science in order to evaluate the reliability of the d2 test and the concentration grid test and to estimate the validity of the concentration grid test. This was necessary because, first, we applied modified versions of the original tests and second, there were no reliability or validity statistics available in the current literature for the concentration grid test.

#### Tasks and Apparatus

##### d2 Test of Visual Focused Attention.

The d2 test was used to assess visual focused attention (4,39). It is seen as a reliable and valid instrument, most commonly being used in the fields of cognitive, clinical, and sport psychology. In the standardized version of this task, 14 lines consisting of 47 letters each are presented to the participant. The letters can be a “p” or a “d” with zero, one, or two small dashes above or below it. The task is to process all items (letters) of a line in a sequential order and to mark every “d” with two dashes above or below. All other letters are to be left unmarked.

The visual search pattern in the d2 test is guided by the structure of the stimulus field (fixed visual search). To avoid ceiling effects, there is a temporal restriction of 15 seconds to process each line. After 15 seconds there is a verbal instruction to proceed to the next line. Norms are available for age groups between 9 and 60 years. Reliability coefficients of the test range from r = .84 to r = .98 (4).

In the present study, 7 lines of the d2 test had to be dealt with under each experimental condition with each line consisting of 47 letters. This test reduction was applied for practical reasons, particularly to match the working time of the concentration grid task. Prior to the study, we analyzed d2-test results of 7 lines (Version A) and 14 lines (Version B) in a test–retest design with a temporal delay of 1 week. The results indicate a significant product–moment correlation between the two versions of the test in a sample of 25 students of sport science (r = .80; p < .05). Therefore, we believed that the use of 7 instead of 14 lines should be adequate for the purposes of this study. From the performance of each participant in the d2 test, two parameters were obtained: a concentration-performance score and the error rate. The concentration-performance score is the number of d letters the subject marked minus the number of signs (dashes) incorrectly marked. The error rate is the number of signs incorrectly marked plus the number of correct signs missed.

##### Concentration Grid Task

Two versions of the concentration grid test were used as a second measure of visual focused attention, and in particular, visual search (15,21). They were modified from the concentration grid exercise, which can be found in Harris and Harris (1984). The first version (CG1) used in this study consisted of 7 horizontal and 7 vertical squares arranged in a grid of 49 squares altogether. A unique two digit-number (from 00 to 49) was placed randomly in the center of each square. The second version (CG2) of the concentration grid was identical to the first except for a different placement of the numbers. To ensure comparability, the relative distance from each number to the following number was the same in the two grids. We also examined the reliability of the concentration grid task. In a test–retest design with a temporal delay of a 1-week interval, a significant product-moment correlation of r = .79 (p < .05) was found in a sample of 25 students of sport science.

In the concentration grid task the participants were instructed to mark as many consecutive numbers (starting from 00) as possible within a 1-min period under each experimental condition. The resultant number of correctly processed items was used for further data analysis. In comparison to the d2 test, the participants’ visual search pattern in the concentration grid is not entirely guided by the structure of the stimulus field; instead, the participant is advised to scan the grid (random visual search). We calculated the product-moment correlation between the concentration grid scores and the d2 test results in the aforementioned sample of 25 students of sport science to estimate the construct validity of the concentration grid. The analysis revealed a non-significant product-moment correlation of r = .10 (p = .62), indicating that the concentration grid test captures a different aspect of visual focused attention than the d2 test.

#### Procedures

A trained research assistant introduced the experimental tasks to each individually tested participant. The participant was given a practice trial of 20 seconds for the concentration grid exercise (altered version of the original CG1) and a practice trial of two lines for the d2 test to become familiarized with the two experimental tasks. The participant had to perform each of the two tasks under two different experimental conditions, that is, in different environmental contexts (for a total of four experimental phases: d2 test and concentration grid task under normal and auditory distraction conditions, respectively). In one condition no sensory distractions were present. The participant completed the tasks in the quiet laboratory environment. In the other condition an auditory distraction was present. The participant wore headphones that enclosed the whole ear. A mixture of distracting, sport-specific environmental sounds was played back at 90 dB. We used ambient sound recordings of the audience and the players from the last 3 minutes of two first division basketball matches in which both teams played head to head until the end of the match. We compiled the sound recordings to fit the two 1-min periods for the auditory distraction condition (d2 test and concentration grid task) in such a way that the played back sound recording comprised the audience’s and the player’s sounds of three offense and three defense situations. In all tasks the participant sat at a worktable with a head–table distance of 40 cm. The test order was counterbalanced for the participants and the experimental tasks required approximately 20 minutes to complete.

### Results

A significance criterion of α = .05was established for all results reported (9). Prior to testing the main hypothesis, moderating effects of age, sex, and experimental sequence were assessed. We conducted separate analyses of variance on the dependent variables, first, with sex as categorical factor (male versus female), second, with age as continuous predictor, and third, with experimental sequence as categorical predictor (auditory distraction following no distraction versus no distraction following auditory distraction). There were no significant effects of sex, age, or experimental sequence on any of the dependent variables (p < .05).

A correlation analysis indicated that there was no significant product–moment correlation between the concentration-performance score of the d2 test and the number of correctly processed items in the concentration grid task (r = -.01; p = .68), nor between the concentration-performance score and the error rate in the d2 test (r = -.02; p = .47). To assess differences in the dependent variables, we conducted 2 × 2 (Environmental Context × Sport Type) univariate analyses of variance (ANOVAs) with condition being the repeated measure. Post hoc analyses were carried out using the Tukey HSD post hoc test. Cohen’s f was calculated as an effect size for all analyzed F values higher than 1 (6). Additionally, we conducted single sample t-tests to compare our study sample to the age matched normative sample. This was done for each participant’s d2 test performance (concentration-performance score and error rates) but not for the concentration grid task, because norms were available only for the d2 test. Cohen’s d was calculated as an effect size for all analyzed t values higher than 1.

#### d2 Test of Visual Focused Attention

Descriptive statistics for the concentration-performance scores and the error rate of the d2 test are shown in Table 1. First, we assumed that d2 scores would not differ between the two groups reflecting static-sport athletes and dynamic-sport athletes. A 2 × 2 (Sport Type × Environmental Context) ANOVA with repeated measures on the second factor was conducted, taking the concentration-performance score as the dependent variable. The results showed that the two groups did not differ in their concentration-performance scores, F(1, 128) = .004, p = .94, achieved power = .94. Our second assumption was that auditory distraction would have a detrimental effect on concentration performance. To our surprise, the ANOVA revealed a significant main effect for environmental context, F(1, 128) = 66.02, p < .05, Cohen’s f = 0.72, reflecting higher concentration-performance scores for the auditory distraction condition for both dynamic-sport and static-sport athletes (see Table 1). The effect size indicates a large effect (6). Furthermore there was no significant interaction effect for Sport Type × Environmental Context, F(1, 128) = .01, p = .76, achieved power = .98.

To determine if participants from our study sample differed from the general population in concentration performance, we calculated single sample t-tests. The results show that in the normal condition, neither static-sport athletes, t(63) = 1.56, p = .12, Cohen’s d = 0.19, nor dynamic-sport athletes, t(65) = 1.81, p = .07, Cohen’s d = 0.22, differed in their concentration performance from the normative sample’s mean. However, in the auditory distraction condition both groups differed significantly from the normative sample’s mean (static-sport athletes, t(63) = 3.17, p = .002, Cohen’s d = 0.39; dynamic-sport athletes, t(65) = 3.37, p = .001, Cohen’s d = 0.42).

Second, a 2 × 2 (Sport Type × Environmental Context) ANOVA with repeated measures on the first factor was conducted, taking the error rate in the d2 test as the dependent variable. There were no significant main effects, neither for sport type, F(1, 128) = 3.71, p = .06, Cohen’s f = 0.17, achieved power = .61, nor for environmental context, F(1, 128) = 1.50, p = .22, Cohen’s f = 0.11, achieved power = .75. In addition, the interaction effect Sport Type × Environmental Context showed no statistical significance, F(1, 128) = 2.02, p = .16, Cohen’s f = 0.13, achieved power = .95. Dynamic-sport athletes did not make more mistakes on the d2 test in comparison to static-sport athletes, neither in the normal nor in the auditory distraction condition.

To determine if participants from our study sample differed from the general population in error rate, we calculated single sample t-tests. The results show that in the normal condition, dynamic-sport athletes, t(65) = -2.88, p = .005, Cohen’s d = 0.35, but not static-sport athletes, t(63) = -1.41, p = .16, Cohen’s d = 0.17, made on average fewer mistakes than the participants from the normative sample. The same pattern of results was found for participant’s error rates in the auditory distraction condition (static-sport athletes, t(63) = 0.36, p = .71, Cohen’s d = 0.05; dynamic-sport athletes, t(65) = -3.17, p = .002, Cohen’s d = 0.39).

#### Concentration Grid Task

We assumed that concentration grid scores would differ between the two groups reflecting static-sport athletes and dynamic-sport athletes. The second assumption was that auditory distraction would have a detrimental effect on concentration performance. A 2 × 2 (Sport Type × Environmental Context) ANOVA with repeated measures on the second factor was conducted, taking the concentration grid score as the dependent variable. The ANOVA revealed no significant main effects for either sport type, F(1, 128) = 1.40, p = .24, Cohen’s f = 0.11, or environmental context, F(1, 128) = 0.27, p = .60. We assume that we can rely on the two findings because of a test power greater than .90. To our surprise the interaction effect Environmental Context × Sport Type showed statistical significance, F(1, 128) = 4.54, p = .04, Cohen’s f = 0.19. Post hoc analysis revealed that participants in the dynamic-sport group scored higher in the concentration grid task under the auditory distraction condition, whereas participants in the individual-sport group scored lower under the auditory distraction condition, compared to the normal condition (see Figure 1).

### Discussion

The goal of this study was to evaluate two attention tests in sport psychology in terms of their application in athletes who are trained in more visually dynamic sports compared to athletes trained in visually less dynamic sports with regard to different environmental contexts. Visual focused attention was examined with random (concentration grid task) versus fixed (d2 test) visual search in a quiet environment and under auditory distraction (4,15).

The results extend current findings on attention performance of athletes with regard to sport type, environmental context, and task dependency. Dynamic-sport athletes did not differ in their concentration performance from static-sport athletes, neither in the d2 test nor in the concentration grid task under quiet laboratory environmental conditions. This result confirms our first hypothesis with regard to the d2 test and supports the findings of Maxeiner (19). We assume that the different perceptual experience of dynamic-sport athletes does not account for their visual search performance in the d2 test. On the one hand, this implies a fairly stable underlying ability to focus attention in simple tasks when a fixed (structured) visual search is a constraint of the task. On the other hand, it can be speculated that attention abilities manifest themselves in a sport-specific way on a more strategic level when integrating basic (attention) abilities in different skills that are not assessed by the d2 test.

Our second hypothesis was that auditory distraction would have a detrimental effect on attention performance in both the d2 test and the concentration grid task. To our surprise the results of the d2 test indicate higher concentration performance scores for the auditory distraction condition for dynamic-sport athletes as well as static-sport athletes. The scores were not only higher when compared between both experimental conditions but also when compared with the corresponding normative sample of the d2 test. This finding supports the assumptions of Tenenbaum et al. and Wilson, Peper, and Schmid, that visual search performance in unstructured contexts is task dependent, especially under auditory distraction conditions (33,38).

From the viewpoint of Boutcher’s multilevel approach to attention, it seems possible that in the auditory distraction condition the participants’ attentional states were optimized (3). This optimization helped the participants achieve higher scores in the relatively simple d2 test, regardless of their sport type. However, whether the supposed optimization was due to changes in arousal level, changes in controlled or automatic processing, or both, cannot be concluded from our results. In addition, the results of the concentration grid task (where an unstructured visual search is an inherit component of the task) show that participants in the dynamic-sport group scored higher in the auditory distraction condition in comparison to the participants in the static-sport group. Changes in arousal level and therefore in attentional state are known to influence visual control (16,32). It is reasonable that an increased amount and/or increased amplitude of saccades, when scanning the concentration grid, can lead to ignoring the actual target or finding it later than under normal conditions. This could explain the decrease in performance in the concentration grid task for static-sport athletes, because they are normally not trained to deal with such a situation in their sport. To further examine the gaze behavior in performing different attention test, eye-tracking methodology should be integrated into the experimental design.

The increase of the concentration grid scores of the dynamic-sport athletes in the auditory distraction condition could also be explained by differences in information processing. Dynamic-sport athletes seem to be able to allocate their attention capacity to more crucial aspects of the task (37). When scanning the concentration grid they could, for instance, pre-cue remaining numbers in specific areas of the grid in advance, in order to find these numbers faster at a later point in time. However, this aspect is open for further investigation. We assume that dynamic-sport athletes benefit from their sport-specific perceptual experience especially in the concentration grid task under auditory distraction conditions.

We are aware of some critical issues in our design that need to be taken into account in further experiments, and want to highlight three specific aspects. First, the differentiation of dynamic- versus static-sport athletes could be more closely specified. This could be done by examining athletes from different sport disciplines that have different sport-specific structures (e.g., coactive vs. interactive sports). One can, for instance, hypothesize that athletes in coactive sports such as bowling or rowing may differ in their attention ability from athletes of interactive sports such as basketball or soccer due to different task demands. Subsequent analyses could also focus on different team positions, especially in interactive sports. For instance, it is likely that a goalkeeper differs in concentration ability from a playmaker (30,31).

Second, the type of distraction could be more differentiated. Athletes have to deal with different distractions in competition such as comments from the coach and other athletes, or different forms of either expected or unexpected noise. These distractions could have different effects on attention performance. One could, for example, examine the impact on attention performance of different distractions with different structures, such as visual versus auditory distraction with a sport-specific structure versus no structure. One can hypothesize that structured distractions of a sport-specific nature would have no impact on concentration performance at all, because athletes are normally habituated to such distractions. In our study we speculated that the impact of the auditory distraction on the attentional state of the athletes would be to enhance their performance in the d2 test. To control this aspect, measurements of arousal level (e.g., heart rate or galvanic skin response) should be integrated into further studies.

Third, we adopted the concentration grid test as a measure for visual focused attention, because visual focused attention is usually operationalized as visual search (39). Research suggests a close link between working memory capacities and the selectivity dimension of attention (10). We acknowledge that when performing the concentration grid test, a participant could potentially optimize his or her visual search by selectively memorizing the position of stimuli that have to be found after preceding stimuli have been marked. However, participants were not instructed to memorize the position of the stimuli but rather to actively scan the grid and mark as many consecutive numbers (starting from 00) as possible within a 1-min period. Subsequent studies could compare participant’s performance in working memory tests (10), as well as in other tests of visual attention (39), with their concentration grid test scores to evaluate if the concentration grid is more a measure of visual focused attention or working memory.

### Conclusions

The findings of the current study suggest that the results of attention tests should be differentially interpreted if different sport types and different test conditions are considered in the field of applied sport psychology or applied sport science. Their predictive power for sport-specific attention skills, however, may only be seen with regard to different factors such as sport type, environmental context, and task.

### Applications in Sport

There are some practical consequences and implications of this study. First, non-specific concentration tests only seem to be able to differentiate between athletes from more visually dynamic sports and athletes from more visually static sports when they mimic a sport-specific environmental context together with sport-specific demands of the task. Therefore, one may need more specific tests for specific sports to diagnose not only fundamental aspects of attention, but attention abilities on a more strategic level (2). These tests should then be integrated in a systematic talent diagnosis with test norms for specific sports (7). In a talent diagnostic, however, psychological variables remain often unnoticed (1), even if they have been identified as significant predictors of success (27). They could serve as an intrapersonal catalyst in the developmental process of talented youngsters (35). However, their impact on performance may change throughout the development process of the individual. When administering attention tests, this development needs to be taken into account. It is, for instance, questionable whether young gymnasts can be compared to young soccer players in their ability to focus attention, because of different attentional demands in both sports. Second, it would be very useful to conduct longitudinal or to combine analysis of performance in tests with analysis of performance criteria (33). A final issue that should be addressed is the impact of specific interventions on attention performance, especially if attention training is used that is similar to the structure of the concentration test itself (13, 38).

### Acknowledgments

The author thanks Mr. Konstantinos Velentzas and for assistance with data collection and Mrs. Lisa Gartz for her critical and helpful comments on the manuscript.

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### Tables and Figures

#### Table 1
Means (M) and standard deviations (SD) for the concentration-performance scores and the error rate of the d2 test with regard to environmental context and sport type (n=130). The terms of static and dynamic refer to the visual environment in which the athletes from different types of sport usually perform.

Environmental context
Normal Auditory distraction
M SD M SD
Concentration-performance score
Static sports 137.28* 69.26 153.05*+ 73.93
Dynamic sports 138.59* 66.34 153.23*+ 71.05
Error rate
Static sports 11.21 8.79 13.26 10.72
Dynamic sports 9.52+ 9.16 9.36+ 8.72

* p < .05 (according to Tukey HSD post hoc test).
+ p < .05 (according to single sample t-test between the study sample and the corresponding normative sample, cf., 4).

#### Figure 1
![Mean concentration grid performance as a function of sport type and environmental context](/files/volume-14/415/figure1.jpg)
Mean concentration grid performance as a function of sport type and environmental context (error bars represent the standard error of the mean; * = significant difference at p < .05 between experimental and control group according to Tukey HSD post hoc analysis).

### Corresponding Author

Dr. Thomas Heinen
German Sport University Cologne
Institute of Psychology
Am Sportpark Müngersdorf 6
50933 Cologne
GERMANY
Tel. +49 221 4982 – 5710
Fax. +49 221 4982 – 8320
Email: <t.heinen@dshs-koeln.de>

### Author’s Affiliation and Position
German Sport University Cologne, Institute of Psychology

2013-11-25T16:23:44-06:00June 3rd, 2011|Contemporary Sports Issues, Sports Coaching, Sports Management, Sports Studies and Sports Psychology|Comments Off on Do static-sport athletes and dynamic-sport athletes differ in their visual focused attention?

A Study on the Self-Efficacy of Elite Coaches Working at the Turkish Coca-Cola Academy League

### Abstract

As defined by Bandura, self-efficacy is an individual’s belief about her/his ability to perform well in a given situation. The purpose of this study was to determine the levels of self-efficacy amongst elite professional Turkish soccer coaches. One-hundred twenty-three coaches from 41 professional soccer clubs in four different regions of Turkey, training U14 and U15 age groups voluntarily participated in this study. This study used the Coaching Efficacy Scale (CES) comprising four specific efficacies (motivation (ME), game strategy (GSE), teaching technique (TTE) and character building (CBE). According to the total coaching efficacy scale, results suggested that participating coaches’ self-belief in efficacy was at highest levels (M=8.26, SD=.49). Coaches’ self-belief in the sub-scale of character development efficacy was at highest (M=8.60, SD=.54), whereas self-belief in game strategy was at lowest levels (M=8.03, SD=.61). One of the most important findings of the study was that coaches’ self belief in the sub-scale of motivation efficacy differed according to the category in which they work (t=2.049, p<.05). Game strategy efficacy differed significantly according to marital status (t=2.417, p<.05); and type of coaching certificate (t= 2.186, p<.05). A higher degree of self-belief regarding motivation efficacy amongst coaches training young teams compared to professional-level coaches was due to the athletes they worked with. In many cases, it is easier to motivate young players rather than professionals. Coaches’ self-improvement in motivation will definitely have a decisive impact on their success in professional sports.

**Key words:** coaching efficacy, elite coaches, professional sport, soccer

### Introduction

Extensive research about the behavior exhibited by individuals throughout their lives suggests the existence of many factors influencing human behavior. One of these factors is self-efficacy (4,5). The social cognitive theory focuses on how the individual learns new information and behaviors by observing, imitating an individual or by taking the individual as a model (1). This theory suggests that one of the most important roles in the individual expression of personal behavior is the individual’s level of self-efficacy.

First mentioned by Bandura (4), the concept of self-efficacy is defined as one’s belief in his or her own ability to perform a certain type of task. Self-efficacy is specific to a certain task and is dynamic (10,14). In other words, it is open to change over time with new information, experience and learning (14). The individual makes a comparison between expected performance and his or her own capacity (12). In the scope of the concept of self-efficacy, the need for a high degree of self-belief to be successful in a specific behavior stands out as one of the most important factors in exhibiting that behavior.

Sometimes knowledge and skill might not be adequate for successful behavior. On most occasions people may know the correct course of action, yet be unable to act accordingly. Self-efficacy stands out as an important bridge between knowledge and behavior. Personal level of self-efficacy influences an individual’s perspective and behavior toward the action. Positive or negative feedback received by the individual in response to his or her abilities and competence results in the strengthening or weakening of the individual’s own belief in his or her self-efficacy (18). Studies suggest that individuals with high self-efficacy tend to be more resilient in the face of obstacles to accessing sports activities (6). They also have heightened levels of social skills (2) and are more eager to take bigger risks (16,17).

Performance build-up in soccer requires long periods of time. What constitutes the fundamental elements required by soccer training throughout this long process is a topic of enduring discussion (3). The most important issues in this context are accurate organizational structures; correct training models; adequate club facilities; environmental conditions and, maybe more than anything, coaching efficacy. It is stated that the athlete’s learning process becomes much more rapid, efficient and thorough, if the format of competitions and training participated in by children are developed with consideration to their mental, psychological and motor abilities (24). At this point, while it is fundamental for a coach to believe in his or her self-efficacy in the context of building up athlete performance (20), this characteristic demands constant enhancement (19).

Based on the notion that coaches can be perceived as teachers, the Coaching Efficacy Scale (CES), developed by Feltz, Chase, Moritz & Sullivan (8), is the only published scale to date that is used frequently in studies on coaching efficacy (11,16,17). D.L. Feltz, et al., (8) define coaching efficacy as coaches’ self-belief in their capacity to influence an athlete’s level of performance and learning. Consisting of 24 items and four sub-scales, the psychometric characteristics of the scale are supported by exploratory and confirmatory factor analysis (8).

The majority of studies on the topic have been conducted on individuals in the United States. Others include Tsorbatzoudis, Daroglou, Zahariadis & Grouios’s study (22) on professional team coaches in Greece and Gencer, Kiremitci & Boyacioglu’s study (9) on Turkish coaches in the disciplines of basketball, soccer, tennis and handball. This latter concludes validity and reliability findings coherent with Feltz et al.’s study (8). The present study addresses significance in terms of CES examining the self-efficacy levels of Turkish elite professional soccer coaches.

### Method
#### Participants

The study group consisted of 123 coaches working for the U14 and U15 age groups within the Turkish Coca-Cola Academy Leagues, founded in the 2008-2009 soccer season. Coaches actively work for 41 professional soccer clubs distributed amongst five regions established for this league; all participated voluntarily in the study. The sample group participating in the study consisted of males only, with ages varying between 22 and 60 (M=38.6, SD=7.9).

#### Coaching Efficacy Scale (CES)

Data for the study was collected using the Coaching Efficacy Scale (CES) developed by Feltz et.al. (8). Total Coaching Efficacy (TCE) consists of 24 items within four sub-scales including: (a) Motivation Efficacy (ME – 7 items), (b) Game Strategy Efficacy (GSE – 7 items), (c) Teaching Technique Efficacy (TTE – 6 items), and (d) Character Building Efficacy (CBE – 4 items). Items were scored on a 10-point Likert scale ranging from 0 (not at all confident) to 9 (extremely confident), and each item was preceded with a prefix, “How confident are you in your ability to …” The scale contains items such as “How confident are you in your ability to motivate your athletes?” identified by ME; “How confident are you in your ability to understand competitive strategies?” identified by GSE; “How confident are you in your ability to detect skill errors?” identified by TTE; and “How confident are you in your ability to instill an attitude of fair play among your athletes?” identified by CBE.

Scale validity and reliability for the sample of Turkish coaches has been conducted by Gencer et. al. (9). Exactly identical to the original, the Turkish adaptation of the scale, grouped under four sub-scales, reached significantly similar results to the original scale (8) with a variance rate of 59.8%. Although the Cronbach’s alpha coefficients for factors creating the scale were relatively coherent (between .80 and .87) with original scale values, the Cronbach’s coefficient for the entire scale was exactly identical. Values (x2=468,21, df=238, normed chi-square (NC, x2/df)=1.97, p<.05; RMSEA=0.069, S-RMR=0.062, GFI=0.84, AGFI=0.80, CFI=0.91, NNFI=0.89) obtained from confirmatory factor analysis of the scale indicate that the model adapts to data at admissible levels.

### Procedure

Using a face-to-face interview method, researchers personally presented coaches with AYÖ, the Turkish version of the Coaching Efficacy Scale and the scale forms containing questions collecting information on coaches. Researchers provided detailed information to participating coaches about the purpose of the study and how the questionnaire should be completed, although this information was delivered in writing on the documents. Researchers distributed questionnaires on the third day of a training seminar and collected them the same day.

### Data Analysis

Obtained data was subject to t-test using the SPSS 15.0 program in order to clarify whether there was a statistically significant difference between the Total Coaching Efficacy (TCE) and its sub-scales: Motivation Efficacy (ME), Game Strategy Efficacy (GSE), Teaching Technique Efficacy (TTE), and Character Building Efficacy (CBE), or differences among it and age groups, marital status, education level, athletic career, coaching certificate, coaching level and years in coaching. Coaches’ ages, sporting backgrounds and coaching backgrounds were divided in to two groups after taking sample group averages.

### Results

Sample group average age was considered for data analysis and samples were gathered under two age groups, age 39 and less, and age 40 and over. Pursuant to this grouping, 78 (63.4%) of participant soccer coaches were age 39 and under and 45 (36.6%) were age 40 and over. A total of 100 (81.3%) soccer coaches were married and 23 (18.7%) were single. An investigation on coaches’ levels of education indicated that the majority of participating coaches were university graduates (n=77, 62.6%). (Table 1)

All coaches participating in the study played soccer as licensed athletes in their past sports careers. While 47 (38.2%) of the coaches played at an amateur level, 76 (61.8%) of them played at a professional level. An investigation on coaching certificates showed that 87 (70.7%) of the coaches hold UEFA B Licenses while 36 (29.3%) hold UEFA A Licenses. A majority of coaches work for the youth teams of professional soccer clubs (n=95, 77.2%).

Coaches participating in the study had been working in this profession between 1 and 23 years (M=7.87, SD=5.88). The sample group’s average years in the career were considered for data analysis and samples were gathered under two groups; eight years and fewer, and nine years and more. According to this grouping 78 coaches (63.4%) with less than eight years experience, and 45 (36.6%) with more than nine years experience, participated in the study (Table 1).

Coaches’ average belief in self-efficacy was determined to be M= 8.26, SD=.49. The level of Character Building, one of the sub-scales rendering beliefs on self-efficacy, was found to be at highest levels (M=8.6, SD=.54). The Character Building sub-scale was respectively followed by Teaching Technique (M= 8.22, SD= .58), Motivation (M= 8.17, SD= .57) and Game Strategy (M= 8.03, SD= .61) (Table 1).

The t-test results obtained from the study reveal that the efficacy and efficacy-related sub-scales of coaches participating in the study did not differ by age group, level of education, athletic career or years in soccer coaching. However, coaches’ belief in efficacy, when related to the strategy sub-scale, revealed significant difference by marital status (t= 2.417, p=.021) and coaching license (t=2.186, p=.032). Similarly, belief in efficacy when related to the motivation sub-scale differed significantly as well by the category coaches worked in (t= 2.049, p=.046) (Table 1).

Table 2 presents the correlations between total coaching efficacy (TCE) and coaching efficacy sub-scales. Correlations among dimensions of coaching efficacy ranged from 0.46 to 0.80, and correlations of TCE with dimensions of coaching efficacy ranged from 0.75 to 0.92 (Table 2). These relationships are coherent with the hierarchical structure suggested by previous studies (8,16).

### Discussion

Studies have shown that there is a positive relation between individuals’ increasing level of education and occupational efficiency, and that an individual’s contribution to the society was directly proportionate to the level of education. Based on population, Turkey ranked 15th in the world for level of education (7). Approximately 62.6% of coaches participating in our study were university graduates, suggesting that the education levels of these coaches were considerably above the national average.

Besides the high level of education among coaches participating in the study, the fact that most of them (61.8%) had previously played soccer at a professional level, along with the fact that 70.7% held a UEFA B License and 29.3% held a UEFA A License, was perceived as the reason for a considerably high degree of self-efficacy (M=8.26, SD=.49). In 2008, the Turkish Soccer Federation started an initiative to update certificates in accordance with UEFA (Union of European Football Associations) criteria and with this objective gave priority to developing the competence of coaches joining the Turkish Coca-Cola Academy League. Being informed on latest updates and receiving relevant training has contributed positively to the self-efficacy of coaches comprising our study group, and, in comparison with other studies (8,15,23), they presented a higher level of self-efficacy.

When compared to other sub-scales that constitute coaches’ belief in self-efficacy, Character Building was found to be at the highest levels (M=8.6, SD=.54). This finding is supportive of findings from other studies (8, 11, 15, 16, 23) conducted on coaching efficacy. One of the fundamental purposes of establishing the Coca-Cola League was exemplified by the slogan “Good Individual, Good Citizen, Good Athlete.” Bearing this slogan in mind, and considering the group coaches work for, highest levels of perceived self-efficacy in this sub-scale was highly significant. As a matter of fact, Lidor (13) underlined the necessity for ensuring the execution of plans and procedures directed at character-building within sports activities. Considered from a social perspective, character-building is undoubtedly very significant.

The Character Building sub-scale was respectively followed by Teaching Technique (M=8.22, SD=.58), Motivation (M=8.17, SD= .57), and Game Strategy (M=8.03, SD=.61). Mean values determined for these three sub-scales were calculated to be higher than those given in other related studies (8, 11, 15, 16, 23). The positive values, classified under these four sub-scales as the positive values which successful coaches are expected to have, were valuable in terms of their contribution to athletes. Game Strategy-related self-efficacy perception of coaches was identified to be lower than other sub-scales, which is important in regard to game strategy, being a decisive factor in game results.

Obtained t-test results revealed that the efficacy and efficacy-related sub-scales of coaches participating in the study did not differ by age group, level of education, sports career or years in soccer coaching. These findings are unsupportive of Tsorbatzoudis et al.’s finding (22) that, unlike inexperienced coaches, experienced coaches perceive themselves to be technically more competent in terms of coaching experience. However, this condition could be explained by the fact that coaches participating in our study had a higher level of experience. Teams joining the Turkish Coca-Cola League are some of the most elite clubs in Turkey, and these clubs are rigorous in choosing coaches. These two factors were considered to be the reason for such a result.

Coaches’ belief in efficacy related to the GSE revealed significant differences by marital status (t=2.417, p=.021) and coaching certificate ownership (t=2.186, p=.032) (Table 1). Familial responsibilities of married coaches might lead them to believe that they are more competent than do single coaches in the strategy sub-scale. In fact, strategy is very closely related to experience. That coaches with UEFA A License have further experience in the game of soccer than UEFA B License holders might help explain the difference emerging once again in the strategy development sub-scale.

It is interesting to note that belief in efficacy related to the motivation sub-scale differed significantly by the category coaches worked in (t=2.049, p=.046) (Table 1). Youth team coaches having more self-efficacy than professional team coaches in the motivation sub-scale is completely relative to experiences coaches have with soccer players. It is perhaps easier to motivate youth team players aspiring to become professionals for upcoming games than it is to motivate those who have already reached the professional level. Concepts of fame and money that engage in professional sports, after a while, cause a gradual sense of fulfillment, and this presents itself as coaches having difficulty in motivating players. More so, compared with youth team coaches, professional team coaches face further difficulties due to various other responsibilities and diversifying interests of older players. Therefore, considering experiences, it appears logical that youth team coaches perceive themselves to be more competent in terms of motivation than do professional team coaches.

### Conclusion

Besides being well educated, elite soccer coaches participating in the study also had good careers as athletes and coaches, explaining the high degree of self-efficacy among them. It was interesting to see that the degree of GSE, the capacity of directing the team during a game, was higher amongst married coaches than those who were single. It was logical to see a higher degree of GSE in coaches holding a UEFA A certificate compared to UEFA B certificate holders. The most interesting result from the study was the varying degree of motivation among coaches depending on their position. This suggests coaches’ need for knowledge and experience about the concept of motivation increased parallel to the significance of the league they worked for.

### Applications in Sport

Self-efficacy is an effective structure demanding improvement for efficiency from the coach. The fact that this effective structure transforms over time in light of newly acquired information and experiences demonstrates the need for meticulously organized coach training programs and even coach appointments. Respective federations and/or organizations have a great deal of responsibility in this matter.

### Acknowledgments

The author wishes to express his sincere thanks to Assistant Professor Dr. Melih Balyan for his support and cooperation in this study.

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### Tables

#### Table 1. Descriptive statistics of coaches and t-test results related to the Coaching Efficacy Scale

Motivation Efficacy Game Strategy Efficacy Teaching Technique Efficacy Character Building Efficacy Total Coaching Efficacy
n % M SD M SD M SD M SD M SD
Age
39 & less 78 63.4 8.19 .58 8.01 .62 8.28 .60 8.57 .54 8.26 .50
40 & over 45 36.6 8.15 .56 8.06 .60 8.13 .53 8.64 .54 8.24 .48
t-value .420 -.480 1.439 -.763 .171
Marital Status
Married 100 81.3 8.21 .56 8.1 .6 8.26 .54 8.61 .55 8.29 .48
Single 23 18.7 8.03 .61 7.76 .6 8.08 .72 8.52 .51 8.1 .53
t-value 1.264 2.417* 1.121 .759 1.627
Education Level
High school & lower 46 37.4 8.17 .57 8.1 .58 8.23 .56 8.63 .54 8.28 .49
University & higher 77 62.6 8.17 .57 8 .62 8.22 .59 8.58 .54 8.24 .49
Sporting Background
Amateur 47 38.2 8.17 .56 7.98 .58 8.18 .62 8.63 .49 8.24 .47
Professional 76 61.8 8.18 .58 8.07 .63 8.25 .55 8.58 .57 8.27 .50
t-value -.062 -.777 -.593 .537 -.295
Coaching Certificate
UEFA B 87 70.7 8.15 .59 7.96 .62 8.19 .61 8.57 .55 8.21 .50
UEFA A 36 29.3 8.23 53 8.21 .55 8.31 .48 8.66 .50 8.35 .45
t-value -.731 2.186* -1.171 -.883 -1.451
Coaching Level
Youth 95 77.2 8.23 .57 8.03 .61 8.26 .57 8.64 .51 8.29 .48
Professional 28 22.8 7.98 .55 8.04 .61 8.1 .60 8.45 .60 8.14 .50
t-value 2.049* -.009 1.258 1.540 1.389
Coaching Background
8 years & less 78 63.4 8.18 .57 8 .62 8.24 .60 8.57 .57 8.25 .50
9 years & more 45 36.6 8.17 .58 8.1 .58 8.19 .54 8.64 .49 8.28 .47
t-value .087 -.944 .484 -.796 -.337
Total 123 100 8.17 .57 8.03 .61 8.22 .58 8.6 .54 8.26 .49

* p < .05

#### Table 2. Pearson correlations between dimensions of coaching efficacy and total coaching efficacy

Game Strategy Efficacy Teaching Technique Efficacy Character Building Efficacy Total Coaching Efficacy
Motivation Efficacy 0.80 0.74 0.60 0.92
Game Strategy Efficacy 0.71 0.46 0.88
Teaching Technique Efficacy 0.75
Character Building Efficacy 0.75
Total Coaching Efficacy

p < .001

### Corresponding Author

**R.Timucin Gencer, PhD**
University of Ege
School of Physical Education and Sports
Bornova, Izmir, Turkey, 35100
<timucin.gencer@ege.edu.tr>
+90 232 3425714 (office)
+90 532 3030610 (mobile)

### Author Bio

R.Timucin Gencer, PhD, is an assistant professor in the Department of Sport Management at the University of Ege. He played basketball as a professional from 1990-1997. He was also the assistant coach of the Turkish National Basketball Team U-16 men who won the European Championship Title in 2005.

2013-11-25T16:26:52-06:00May 25th, 2011|Sports Coaching, Sports Facilities, Sports Management, Sports Studies and Sports Psychology|Comments Off on A Study on the Self-Efficacy of Elite Coaches Working at the Turkish Coca-Cola Academy League
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