ELT Voices Indiaeltvoices.in/Volume3/Issue_4/EVI_34_4.pdf · 2013. 8. 31. · Personality Psychology, the Science of Individuality (1998), Nathan Brody and Howard Ehrlichman, defined

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ELT Voices – India Volume 3 Issue 4 | August 2013

ISSN 2230-9136 (Print) 2321 – 7170 (Online)

© Ignite (India) Publishing, Bhavnagar, Gujarat – India

www.eltvoices.in

ELT Research Paper 4

The Correlation between Creativity and Openness to Experience and Iranian EFL College Students' Reading Comprehension

AzraTajhizi, Mahdi Araghi, Ph.D. & Amir Reza NematTabrizi, Ph.D. Department of English, Ahar Branch, Islamic Azad University, Tabriz, Iran.

AzraTajhizi, Mahdi Araghi & Amir Reza NematTabrizi: The Correlation between Creativity and Openness to

Experience and Iranian EFL College Students' Reading Comprehension

44 | E L T V o i c e s – I n d i a ( V o l . 3 I s s u e 4 ) | A u g u s t 2 0 1 3 I S S N 2 2 3 0 - 9 1 3 6 ( P r i n t ) 2 3 2 1 – 7 1 7 0 ( O n l i n e )

Abstract

The present study was designed to investigate the possible relationship between

creativity and openness to new experience and Iranian EFL college students’ Reading

Comprehension skill. A total of 100 intermediate learners (all female) studying at

Urmia and Salmas Universities participated in this study. At the first step, two

questionnaires of creativity and openness to new experiences were distributed to the

participants. At the next step, Reading Comprehension Test was given to them.

Through a detailed collection of data, using Pearson Correlation Coefficient, the

following findings were obtained: 1) There was a positive relationship between

creativity and Iranian EFL college students’ Reading Comprehension skill; 2) There

was a positive relationship between openness to new experiences and Iranian EFL

Reading Comprehension skill.

Key Words: Openness to experience, Creativity, Reading Comprehension




Introduction

In psychology, the Big Five personality traits are five broad domains or dimensions of

personality that are used to describe human personality. The theory based on the Big Five

factors is called the Five Factor Model (FFM). The FFM comprises five trait domains:

neuroticism (N), extroversion (E), openness (O), agreeableness (A) and conscientiousness

(C). Each dimension has subscales (facet scores) within the overall construct. The FFM is

assessed using either the 240-item NEO Personality Inventory (Costa & McCrae, 1992), or a

shorter, facet-score free 60-item NEO-Five Factor Inventory (Costa & McCrae, 1992). The

FFM has been widely demonstrated cross-culturally (Schmitt, McCrae & Benet-Mart´ınez,

2007), and has substantial cross-situational and longitudinal consistency (Murray et al.,

2003).

The idea of five major dimensions encompassing much of personality is long standing (Fiske,

1949; Norman, 1963). Openness to experience is one of the domains which are used to

describe human personality in the Five Factor Model. Openness involves active imagination,

aesthetic sensitivity, attentiveness to inner feelings, preference for variety, and intellectual

curiosity. A great deal of psychometric research has demonstrated that these qualities are

statistically correlated. Thus, openness can be viewed as a global personality trait consisting

of a set of specific traits, habits, and tendencies that cluster together. Openness tends to be

normally distributed with a small number of individuals scoring extremely high or low on the

trait, and most people scoring moderately. People who score low on openness are considered

to be closed to experience. They tend to be conventional and traditional in their outlook and

behavior. They prefer familiar routines to new experiences, and generally have a narrower

range of interests. Openness has moderate positive relationships with creativity, intelligence

and knowledge (McCrae & John, 1992). Openness to experience correlates with creativity, as

measured by tests of divergent thinking (McCrae, 1987). Openness has been linked to both

artistic and scientific creativity as professional artists and scientists have been found to score

higher in openness compared to member of the general population ( Feist, 1998).

Literature Review

The idea of personality traits may be as old as human language itself. In the 1940s many

investigators focused on intensive studies of individual traits. According to Allport’s (1937)

http://en.wikipedia.org/wiki/Big_Five_personality_traitshttp://en.wikipedia.org/wiki/Psychometrichttp://en.wikipedia.org/wiki/Normal_distributionhttp://en.wikipedia.org/wiki/Creativityhttp://www.britannica.com/EBchecked/topic/453033/personality-traithttp://www.britannica.com/EBchecked/topic/16636/Gordon-W-Allport




textbook, traits represent structures or habits within a person. Psychological traits are

characteristics that describe ways in which people are different from each other. Saying that

someone is shy is to mention one way in which he or she differs from others who are more

outgoing. Traits also define ways people are similar. For example, people who are shy are

similar to each other in that they are anxious in social situations, particularly situations in

which there is an audience focusing attention on them.First, they help everyone to describe

people and help they understand the dimensions of difference between people. Second, traits

are useful because they may help they explain behavior. The reasons people do what they do

may be partly a function of their personality traits. Third, traits are useful because they can

help they predict future behavior—for example, the sorts of careers individuals will find

satisfying, who will tolerate stress better, and who is likely to get along well with others.

Thus, personality is useful in describing, explaining, and predicting differences between

individuals. Gordon Allport, the father of modern personality theory, very briefly defined

personality as an organization of psychodynamic processes that creates the person’s

characteristic patterns of behavior, thoughts, and feelings. He wrote the influential book,

“Personality” in 1937. He developed his ideas about “traits” viewing these as the basic

structural elements of personality. According to Allport (1937), traits have an actual physical

location in the nervous system; they are inferred their existence because of consistency of

behavior. He also made the distinction as to whether traits could be used to describe people in

general or just a single individual. Nomothetic traits were trait units that could be applied to

all people. Idiographic traits were those unique to the individual. Applying this concept to

personality, Allport and Odbert (1936) were looking at “natural language.” In 1936 Gordon

Allport and H. S. Odbert hypothesized that those individual differences that are most salient

and socially relevant in people’s lives will eventually become encoded into their language;

the more important such a difference, the more likely is it to become expressed as a single

word. This statement has become known as the Lexical Hypothesis. The Five Factor Model

is a theory of personality assessment and measurement which was founded in factor analysis.

In the process of factor analysis the researcher gathers a large number of subjects for a broad

study.

The subjects are all tested in the same manner, and from the test results, the theorist searches

for common variables/factors. In other words, the theorist attempts to first isolate broad




similarities or underlying factors. This step is called "reloading'' or "factor loading''. After

factor loading, the theorist then measures the extent to which a subject/subjects are affected

by the individual underlying factors. Once the underlying factors are determined and are

categorized, the theorist can devise a more efficient system than the original factor analysis

for measuring the underlying factors. The extent to which given subjects rate among these

five factors is determined through analysis of trait adjectives, factor analysis, and analysis of

existing personality inventories (often made by other theorists).

The usual test for this is called the Revised NEO Personality Inventory (NEO-PI-R). Through

this process of factor analysis Tupes and Christal first originated the theory of five underlying

factors which are the basis of personality measurement in 1961. Big five taxonomy is a

scientific classification system. It involves ordering, naming and systematically

distinguishing between things. Should help individuals understand how things differ. In

Personality Psychology, the Science of Individuality (1998), Nathan Brody and Howard

Ehrlichman, defined personality in this way that the term personality implies the existence of

a living being with an inner mental life consisting of thoughts, feelings, desires, and goals as

well as behaviors.

Personality is not merely a description of behavior, but involves processes in the person that

are responsible for this behavior. People behave as they do, at least in part, because of their

personalities. To say a person is sociable or aggressive or honest is to say there are inner

characteristics that cause him or her to be sociable or aggressive or honest. The field of

psychology is filled with numerous personality models. To some extent, the many models

seem similar to a roadway filled with various vintages of automobiles. As technology

improves, automobile designs change; and likewise, as research improves, personality models

change. To say that any particular personality model is right or wrong seems similar to saying

that a particular automobile design is right or wrong. Instead, most engineers develop

different automobile designs based on the technology available at the time of development.

Naturally, if a person decides to drive across the country in the twenty-first century, that

person will probably choose a late-model automobile. Prior to World War II, personality

models were based entirely on inference. These inference theories started with Socrates

around 2500 years ago and continued through the time of Jung in the early to Mid-1900s. The




Socrates model measures personality across four factors (choleric, melancholic, phlegmatic,

and sanguine) based on the level of four body fluids. Some twentieth century personality

models use similar factors. Despise the common use of these personality terms, absolutely no

empirical research validates his model or any of the inference models. By the Mid-1930’s,

however, several personality theorists started to develop phenomenological theories. These

theories explain what is seen and observed rather than what is inferred. Allport (1937)

initiated modern personality assessment by observing the words used in language. James

Beck (1999) explains the logic of the linguistic approach such as this manner that with a little

reflection, one can see the simple logic of using a linguistic approach.

Language reflects human experience. When people want to communicate with each other

about some new observation, they invent words and grammar through which they

communicate that material to others. For instance, if an ancient ruler was selecting members

of the court who could advise and counsel the ruler, some assessment of the personality

strengths and weaknesses of the prospective advisors would undoubtedly take place. Officials

would likely have to assess the person’s trustworthiness, reliability and honesty, among other

things. So, a growing and developing language to describe all of these personality attributes

would facilitate the task. The older and more developed the language, the more it would have

the ability to describe these subtleties of personality.

The biblical languages of Hebrew and Greek both contain a large number of nouns,

adjectives and verbs that provided the writers with vocabulary with which to describe people

and their behavior. In 1936, Gordon Allport culled 17,936 adjectives that describe personality

from an unabridged English dictionary. After eliminating duplicate words or words that did

not describe personality unambiguously, he derived 4,504 descriptive terms. However, the

state of statistical science remained inadequate to reduce the number of terms any further. In

1942, British researcher Raymond Cattell implemented a newly developed statistical

technique called factor analysis. In spite of all its complexities, factor analysis is simply a

statistical method that identifies the common factors that describe a large body of data. Since

computers were not yet invented, Cattell employed an army of graduate students to perform a

laborious hand-computed factor analysis on the personality terms. Cattell identified twelve

factors to which he added on his own four additional factors (John, 1990). The resulting

sixteen factors became very well known as the 16PF (personality factors).Later investigators




re-analyzed Cattell’s data using the computational power of modern computers. However, no

research has substantiated Cattell’s twelve factors. Although Cattell’s manual calculations

identified twelve factors, his data yields only five factors when a factor analysis is performed

on a computer (Digman, 1996).

In 1961, Ernest Tupes and Raymond Christal (in a project sponsored by the U. S. Air Force)

attempted the first computer-based factor analysis of Allport’s terms. Their factor analysis

found that as few as five factors describe personality: Openness, Conscientiousness,

Extraversion, Agreeableness, and Neuroticism. These are often remembered with the acrostic,

OCEAN. Soon afterward, an independent analysis by Norman (1963) reconfirmed the Five-

Factor Model (FFM). Since the late 1970’s, researchers have demonstrated that five broad

personality factors explain the full range of personality differences more completely than any

of the previous theories. Factor analysis research in 28 different languages has consistently

found five personality factors in analyses of Arabic, Croatian, Czech, Dutch, Estonian,

Finnish, French, German, Italian, Hebrew, Icelandic, Japanese, Korean, Tagalog, Mandarin,

Cantonese, Norwegian, Polish, Portuguese, Russian, Spanish, Norwegian and Swedish,

among others. Recent research findings in languages from five distinct language families

strongly suggest that personality trait structure is universal (McCrae & Costa, 1997). Thus,

the FFM seems to provide a language-independent and culture-independent personality

assessment instrument. The FFM seems so broad, compared to other models, that it provides

the ability to explain nearly every other personality model. It is the only model that is derived

from research, instead of inference or theory. In summary, the English language includes

thousands of terms to describe aspects of personality, and analysis after analysis has found

five similar factors (Costa & McCrae, 1992).The FFM is not the sum total of what is needed

to know about personality, but everything that presently should be known about personality is

explained in the FFM. The FFM provides the most accurate, most comprehensive, and most

robust tool available to understand the individual, including an assessment of each

individual’s strengths, weaknesses and information relevant to interpersonal style, character,

levels of emotional well-being, aspiration levels, and a wide range of other psychologically

relevant information (Piedmont, 1998). It also provides a means for a clinical differential

diagnosis, a means for empathy and rapport, and a means to match treatments to clients.

Piedmont notes that matching treatments to clients probably provides the most important

contribution. The most widely known version of the FFM generally takes 60-70 minutes to




complete. Recognizing that 60-70 minutes per assessment translates into a substantial cost

when applied across the tens of thousands of military recruits, Raymond Christal and the Air

Force Research Laboratory developed a research project to reduce the required assessment

time. After seven years of research using many thousands of subjects, they developed a new

FFM instrument in 1994. The new software enables a personality assessment within 15 to 20

minutes, depending on the reading speed of the individual. Thus, the project shortened the

entire assessment process to about 1/3 of the time required for other FFM instruments while

refining and retaining measurement of the finer facets that comprise each factor.

Research Methodology

This section describes the research methodology used in this study. Included are descriptions

of the participants, assessment instruments, procedures, research design, and statistical

analysis.

Participants

Participants in this study were students studying Teaching English as a Foreign Language at

Islamic Azad University, Urmia and Salmas Branches. 100 students took part in this study.

They included 100 females and no male with ages ranging from 19-22 years old. These

totally 100 learners were randomly selected from among the students of 5 Reading

Comprehension classes. They were voluntarily ready to take part in this study.

Instruments

The instruments in this study included two questionnaires of Creativity and Openness to new

experiences and one Reading Comprehension Test.

Neo-five factor inventory (NEO-FFI ) college form S

The Persian adaptation of NEO Five Factor Inventory (Costa and McCrae, 1999) was used

for measuring personality. The NEO-FFI is a self-report paper and pencil questionnaire

which covers the five main domains of the Big Five model. The five dimensions of




personality measured by this inventory are: Neuroticism, Extraversion, Openness,

Agreeableness, and Conscientiousness. The inventory consists of 60 items that are scored

according to the Likert- type scale of five points ranging from “strongly disagree” to

“strongly agree”. Each personality dimension on this inventory is measured by 12 items. Here

the purpose of this study was to consider 12 items of openness to experience domain. The

NEO-FFI is a 60 item survey that takes approximately 30 minutes to complete. The scoring

method of the items is like Likert-type scale that has five answer options that respectively

included these: (0) strongly disagree, (1) disagree, (2) I don’t have any idea, (3) agree, and (4)

strongly agree. Some questions are graded in the reversed way. This is the grading method of

this inventory.

Creativity questionnaire

Dr. Azam Abedi’s creativity questionnaire has 60 items with 3 answer options from “A” to

“C’’. The options show creativity level from low to high that scores respectively from 0 to 2

are belonged to the items.

The option ‘A’ in each item has posed the lack of ability in performing activity that 0 score

will be given to this answer option.

The option ((B)) in each item has posed the ability in performing activity that 1 score will be

given to this answer option.

The option ((C)) in each item has posed the ability in performing the full performance that it

reveals creativity and a score of 2 is assigned to it.

These scores are collected in four groups and thus a total score can be obtained for creativity

subjects with the sum of these four scores. The range of scores in this test is between 0 to 120

and the participants were scored according to the following five levels. Those who score

below 50 have very low level of creativity. Those who score between 50-75 have low level of

creativity. Those who score 75-85 have intermediate level of creativity. Those who score

between 85-100 have high level of creativity. Those who score between 100-120 have very

high level of creativity.

This questionnaire has been divided into four sections. The first section (fluency) has been

included 22 questions. The second section (elaboration) has been included 11 questions, the




third section (creativity) has been included 16 questions, and the last section openness to

experience (flexibility) has been included 11 questions.

Reading Comprehension Test

At the final step the Reading Comprehension Test was given to the learners. This test was

chosen from TOEFL Test Practices Book by Keith S. False. They were totally included 20

multiple choice questions.

Procedures

Firstly, in order to determine the learners’ creativity level, DR. Abedi’s creativity short

version 60 items questionnaire was given to them. Then the openness to experience

questionnaire was completed by the learners. In this study ‘NEO-FFI self-report short version

inventory’ is used, which has 60 items with 5 domain scales and each domain included 12

items but the aim of this study is to measure only the openness to experience domain by

making statements relating to openness and having participants rate the statements in relation

to themselves: from "strongly agree" to "strongly disagree. After that, their reading

comprehension performance was measured by reading comprehension test. And finally the

correlation between Iranian EFL learners’ creativity and openness to experience and reading

comprehension was demonstrated.

Design

This study was employed a cross-sectional descriptive and paper-pencil survey research

design. Especially the Pearson Correlation technique was used. A set of brief descriptive

coefficients that summarizes a given data set, which can either be a representation of the

entire population or a sample. The measures used to describe the data set are measures of

central tendency and measures of variability or dispersion. Measures of central tendency

include the mean, median and mode, while measures of variability include the standard

deviation (or variance), the minimum and maximum variables. Descriptive statistics provide

a useful summary of data when performing empirical and analytical analysis.




Data Collection

Results from this research study were analyzed with the Statistical Package for the Social

Sciences (SPSS) software Version 20 using Pearson Correlation. SPSS is one of the most

popular statistical analysis software packages available.

Description of data

The data in this study is consisted of 100 female students’ answer samples of creativity and

openness to experience questionnaires and the reading comprehension test. In this section

data analysis are described.

Data analysis

Table1. The descriptive statistics indexes of openness to experience variable

Frequencies

Openness

N Valid 100

Mean 27.3300

Median 27.0000

Mode 29.00

Std. Deviation 5.08723

Variance 25.880

Minimum 17.00

Maximum 39.00

In table 1descriptive statistics indexes of Openness to experience variable was reported. The

mean, median, mode of its scores are respectively equal with 27/33, 27, and 29. The Standard

deviation and variance of its scores are respectively 5/09, and 25/88. The minimum and

maximum of scores are 17 and 39.




Figure1. Histogram diagram and scores distribution of openness to experience variable

In figure 1-1, histogram diagram and normal distribution of Openness to experience scores

were reported. According to the values of central indexes (mean, median, and mode), the

scores curve distribution figure of Openness to experience had a negative slope.

Table 2. The descriptive statistics indexes of creativity variable

Frequencies

Statistics

Creativity

N Valid 100

Mean 71.9100

Median 74.0000

Mode 79.00





Variance 175.840

Minimum 36.00

Maximum 96.00

In table 2 descriptive statistics indexes of creativity variable was reported. The values of

central indexes (mean, median, and mode) of creativity scores are respectively: 71/91, 74,

and 79. The values of standard deviation and variance of creativity scores are 13/29 and

175/84. The minimum and maximum of the scores are respectively 36 and 96.

Creativity

Figure2. Histogram diagram and normal distribution of creativity scores

In figure 2 histogram diagram and normal distribution of creativity scores was reported. With

regard to the figure of diagram and values of central indexes, scores had a negative slope. It

means that most of them had high creativity scores rather than mean score.

Table 3.The descriptive statistics indexes of reading comprehension variable scores

Frequencies

Statistics




Reading

N Valid 100

Mean 6.9300

Median 7.0000

Mode 7.00


Variance 5.035

Minimum 2.00

Maximum 10.00

In table 3 descriptive statistics indexes of reading comprehension scores were reported. The

values of central indexes (mean, median, and mode) respectively are: 6/93, 7, and 7.The

values of standard deviation and variance of the reading scores are 2/24, and 5. The minimum

and maximum of the reading scores are respectively: 2 and 10.

Reading

Figure 3.Histogram diagram and normal distribution of reading comprehension scores

In figure 3histogram diagram and normal distribution of reading comprehension scores were

reported. The scores had a negative slope with regard to the values of central indexes (mean,




median, and mode) and the shape of diagram, and it means that most of individuals had high

scores rather than mean score.

Table4. The descriptive statistics indexes of reading comprehension and openness to experience scores

Correlations

Descriptive statistics

Mean Std. Deviation N

Openness 27.3300 5.08723 100

Reading 6.9300 2.24398 100

In table 4descriptive statistics indexes of openness to experience and reading comprehension

scores were indicated. As shown in this table the mean and standard deviation for openness to

experience scores are respectively: 27.33, and 5.09, and the mean and standard deviation for

reading comprehension scores are respectively: 6.83, and 2.24.

Table 5. The correlation coefficient of reading comprehension and openness to experience scores

Correlations

Openness Reading

Openness

Pearson Correlation 1 .582**

Sig. (2-tailed) .000

N 100 100

Reading

Pearson Correlation .582** 1


N 100 100

For examining the hypothesis, the correlation coefficient test as is given in table 5 is used.

According to the table, two ranges at the level %1 are significant because the calculated

values of correlation coefficient is (r = + %58), and (sig= 0.001




Reading

Figure4.Linear regression diagram of reading comprehension and openness to experience scores

Table 6. The descriptive statistics indexes of reading comprehension and creativity scores

Correlations

Descriptive Statistics

Mean Std. Deviation N

Creativity 71.9100 13.26048 100

Reading 6.9300 2.24398 100

In table 6 descriptive statistics indexes of creativity and reading comprehension scores

were reported. The mean and standard deviation of creativity scores are respectively:

17.91 and 13.5. The mean and standard deviation for reading comprehension scores

are respectively 6.93 and 2.24.

Table 7.The correlation coefficient of reading comprehension and creativity scores

Correlations

Creativity Reading

Creativity

Pearson Correlation 1 .578**





N 100 100

Reading

Pearson Correlation .578** 1


N 100 100

For examining the hypothesis, the Pearson correlation coefficient test as given in table 7 is

used. According to the table, the calculated value of correlation coefficient is (r= =0.578),

and therefore two ranges at level %1 are significant (sig= 0.001




Discussion:

There is a significant correlation between openness to experience and reading comprehension

scores. In table 4 descriptive statistics indexes of openness to experience and reading

comprehension scores were reported. The mean and standard deviation for openness to

experience scores respectively are: 27.33, and 5.09, and the mean and standard deviation for

reading comprehension scores respectively are: 6.83, and 2.24. For examining the hypothesis,

the correlation coefficient test as is given in table 5is used. According to this table, the

correlation between them at range (sig =2-tailed) at the level %1 are significant because the

calculated values of correlation coefficient is (r = + %58), and (sig= 0.001




Conclusion

The major aim of this study was to develop a model which could enable university

language learners to view reading comprehension skill from different perspective, it

means each learner can look to this skill from different viewpoints because each has

different character that is unique, and character of each learner consists of different

traits and each trait causes variety at learners and in learning environments.

Uniqueness also bring about to reach various outcomes at each performance. For this,

it will be good if instructors try to assess the students’ reading comprehension

performances from psychological view during stage of the reading comprehension

process. Richards and Schmidt (2002) define personality as those aspects of an

individual’s behavior, attitude, beliefs, thoughts, actions and feelings which are seen

as typical and distinctive of that person and recognized as such by that person and

others. Based on this definition, each person has a type of personality which is

exclusive to him/her. Ehrman (2003) indicates to the fact that in the recent years the

influence of personality variables on learning styles has increased greatly. Every

individual uses a series of learning strategies and styles that are grounded in his/her

personality to handle linguistic tasks and better to say language learning performance.

Likewise, researchers make use of learning style research with personality and

cognitive styles to determine ability, predict performance, e.g. in speaking or reading

comprehension, and improve classroom teaching and learning (Ehrman, 2001). Young

and Schinka (2001) stated that the five factor model of personality has become the

dominant model for the investigation of personality. In the current study, the

researcher chose to use this model because of the clarity of these factors, its

widespread acceptance, and the relative abundance of research on the FFM and its

component factors. The mostly widely used instrument to assess the five factors, the

NEO, was also used in the present study to assess the personality variables.




Pedagogical implications

The Personality plays an important role that effect academic achievement. Understanding the

factors influencing academic performance has always been a great concern for counseling

and educational psychologists. Many researchers are anxious to know in advance who will

perform well or not in any academic activity. Thus, identifying the factors determining

academic success is a major concern of researchers for the purpose of developing an

education curriculum aimed at improving levels of academic performance. This calls for

examining the reasons for individual differences in students’ academic performance. A

number of studies have identified a positive association between openness and academic

performance (Chamorro-Premuzic & Furnharm, 2005).The psychological literature suggests

that especially openness to experience is important predictor of educational success.

Openness to experience is akin to intelligence and bears on intellectual curiosity and

commitment to assignments (MacCrae& Costa, 1997). Creativity and resourcefulness are

aspects of openness that are also positively related to scholastic achievement. Therefore,

teachers should construct learning environments that take into consideration students’

individual differences and strengths.

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ELT Voices Indiaeltvoices.in/Volume3/Issue_4/EVI_34_4.pdf · 2013. 8. 31. · Personality Psychology, the Science of Individuality (1998), Nathan Brody and Howard Ehrlichman, defined