Page 29 - Kukanja Gabrijelčič, Mojca, and Maruška Seničar Željeznov, eds. 2018. Teaching Gifted and Talented Children in A New Educational Era. Koper: University of Primorska Press.
P. 29
Contributors of High Achieving Students’ Linguistic Competence
Finally, in relation to study orientation (Humanities, Science, Technology)
significant differences were found only for Vocabulary Level (x2(1) = 6.173, p
< 0.05, η2 = 0.07). According to post hoc comparisons of the Kruskal-Wallis H,
significant differences in favour of students of Humanities against those of
Technology were found (x2(1) = 6.129, p < 0.05, η2 = 0.01)
Correlations among Creativity, Motivation and Linguistic Features
The strongest correlations across the three factors were found for the items
of Vocabulary Level which was correlated to Problem Solving Questioning
(Pearson r = 0.640, p < 0.01), Speech Adaptability was found to be strongly
correlated to Perseverance (Pearson r = 0.623, p = 0.000). Moreover, Speech
Accuracy was found to be correlated to the most creativity features as well as
to motivation features such as Task Commitment (Pearson r = 0.526, p < 0.01).
It should be mentioned that most of the creativity features are not correlated
significantly to motivation features, while they have a positive significant cor-
relation with linguistic features. So, it seems that there is a relationship mainly
among motivation and linguistic features as well as creativity and linguistic
features. Additionally, a multiple regression analysis was performed but did
not return meaningful results. Therefore, further study is required in order for
predictors of high language performance to be explored.
Discussion
The results of this study constitute a first exploratory approach to features
correlated with motivation, creativity and linguistic competence levels of
high achieving students in Greek secondary education. Also, the current
study provides guidelines for assessing creativity and motivation in Lan-
guage Arts, offering a deeper understanding between these two concepts
for educators who must rate creativity and motivation in the classroom in
order to support the linguistic needs of high ability students.
As regards the first research question, there is definitely a relationship
among creativity and motivation to the linguistic features of high achieving
students. The correlation matrix and the principal components analysis de-
picted that positive and significant correlations were found among the ma-
jority of the target items, suggesting that broad effect relationships emerge
among these item groups to linguistic features. Thus, the initial hypothesis is
confirmed. These findings indicate that creativity is related to high achieving
students’ writing abilities, as Sak (2004) found, but they also offer data that
suggest a connection between their motivation and linguistic features, an
aspect that has not been investigated before.
27
Finally, in relation to study orientation (Humanities, Science, Technology)
significant differences were found only for Vocabulary Level (x2(1) = 6.173, p
< 0.05, η2 = 0.07). According to post hoc comparisons of the Kruskal-Wallis H,
significant differences in favour of students of Humanities against those of
Technology were found (x2(1) = 6.129, p < 0.05, η2 = 0.01)
Correlations among Creativity, Motivation and Linguistic Features
The strongest correlations across the three factors were found for the items
of Vocabulary Level which was correlated to Problem Solving Questioning
(Pearson r = 0.640, p < 0.01), Speech Adaptability was found to be strongly
correlated to Perseverance (Pearson r = 0.623, p = 0.000). Moreover, Speech
Accuracy was found to be correlated to the most creativity features as well as
to motivation features such as Task Commitment (Pearson r = 0.526, p < 0.01).
It should be mentioned that most of the creativity features are not correlated
significantly to motivation features, while they have a positive significant cor-
relation with linguistic features. So, it seems that there is a relationship mainly
among motivation and linguistic features as well as creativity and linguistic
features. Additionally, a multiple regression analysis was performed but did
not return meaningful results. Therefore, further study is required in order for
predictors of high language performance to be explored.
Discussion
The results of this study constitute a first exploratory approach to features
correlated with motivation, creativity and linguistic competence levels of
high achieving students in Greek secondary education. Also, the current
study provides guidelines for assessing creativity and motivation in Lan-
guage Arts, offering a deeper understanding between these two concepts
for educators who must rate creativity and motivation in the classroom in
order to support the linguistic needs of high ability students.
As regards the first research question, there is definitely a relationship
among creativity and motivation to the linguistic features of high achieving
students. The correlation matrix and the principal components analysis de-
picted that positive and significant correlations were found among the ma-
jority of the target items, suggesting that broad effect relationships emerge
among these item groups to linguistic features. Thus, the initial hypothesis is
confirmed. These findings indicate that creativity is related to high achieving
students’ writing abilities, as Sak (2004) found, but they also offer data that
suggest a connection between their motivation and linguistic features, an
aspect that has not been investigated before.
27
