Page 27 - 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. 27
Contributors of High Achieving Students’ Linguistic Competence
The first factor was labelled ‘Linguistic Features’ due to the high loadings
by the following items: Speed of Textual Comprehension, Depth of Textual
Comprehension, Speech Adaptability, Strong Interest in the Syllabus, Speech
Accuracy, Perseverance, Extracurricular Reading, Vocabulary Level and ex-
plained 30.2 of the variance.
The second factor yielded by the analysis was labelled ‘Creativity Features.’
This factor was labelled as such due to the high loadings by the following
items: Restless Spirit, Sense of Humour, Nonconformity, Originality of Re-
sponses, Responsiveness to Higher Order Questioning and Interdisciplinary
Connections. The variance explained by this factor was 12.2.
The third factor was labelled ‘Motivation Features’ due to the high loadings
by items such as: Repeated Text Reviewing, Request for Advanced Reading
Resources and Task Commitment. This factor explained 8.9 of the variance.
The communalities of the variables are relatively high, especially for Speed
of Textual Comprehension (0.710), Depth of Textual Comprehension (0.669),
and Task Commitment (0.658), suggesting that almost 70 of speech recep-
tion and task commitment items variability is being accounted for by the
three factor model. This may indicate that these variables are strongly re-
lated with each other and perhaps an underlying pattern connecting speech
reception and motivation is being suggested.
Overall, these analyses indicated that three distinct factors were underly-
ing the sample’s students’ characteristics items and that these factors were
moderately internally consistent. These three tendencies are not indepen-
dent of one another.
Mean differences by Gender, Study Orientation and School Type
Prior to comparing means, the assumption of normality was tested and not
satisfied for all variables in relation to gender, study orientation and school
type (Shapiro-Wilk test was found significant for all variables). Homogene-
ity of variance was also tested by gender, study orientation and school type
and was not satisfactory for Problem Solving Questioning (F(14, 72) = 5.612,
p < 0.001), Originality of Responses (F(14, 72) = 2.079, p < 0.05), Non Confor-
mity (F(14, 72) = 1.944, p < 0.05), Task Commitment (F(14, 72) = 1.845, p < 0.05),
Speech Adaptability (F(14, 72) = 2.634, p < 0.05) and Speech Accuracy (F(14,
72) = 4.358, p < 0.001).
Therefore, due to the lack of homogeneity we proceeded with performing
the non parametric Kruskal-Wallis H test. Statistically different ranks by stu-
dents’ gender were observed between the two groups only in responsive-
ness to Problem Solving Questions in favour of boys (χ2(1) = 4.342, p < 0.05,
25
The first factor was labelled ‘Linguistic Features’ due to the high loadings
by the following items: Speed of Textual Comprehension, Depth of Textual
Comprehension, Speech Adaptability, Strong Interest in the Syllabus, Speech
Accuracy, Perseverance, Extracurricular Reading, Vocabulary Level and ex-
plained 30.2 of the variance.
The second factor yielded by the analysis was labelled ‘Creativity Features.’
This factor was labelled as such due to the high loadings by the following
items: Restless Spirit, Sense of Humour, Nonconformity, Originality of Re-
sponses, Responsiveness to Higher Order Questioning and Interdisciplinary
Connections. The variance explained by this factor was 12.2.
The third factor was labelled ‘Motivation Features’ due to the high loadings
by items such as: Repeated Text Reviewing, Request for Advanced Reading
Resources and Task Commitment. This factor explained 8.9 of the variance.
The communalities of the variables are relatively high, especially for Speed
of Textual Comprehension (0.710), Depth of Textual Comprehension (0.669),
and Task Commitment (0.658), suggesting that almost 70 of speech recep-
tion and task commitment items variability is being accounted for by the
three factor model. This may indicate that these variables are strongly re-
lated with each other and perhaps an underlying pattern connecting speech
reception and motivation is being suggested.
Overall, these analyses indicated that three distinct factors were underly-
ing the sample’s students’ characteristics items and that these factors were
moderately internally consistent. These three tendencies are not indepen-
dent of one another.
Mean differences by Gender, Study Orientation and School Type
Prior to comparing means, the assumption of normality was tested and not
satisfied for all variables in relation to gender, study orientation and school
type (Shapiro-Wilk test was found significant for all variables). Homogene-
ity of variance was also tested by gender, study orientation and school type
and was not satisfactory for Problem Solving Questioning (F(14, 72) = 5.612,
p < 0.001), Originality of Responses (F(14, 72) = 2.079, p < 0.05), Non Confor-
mity (F(14, 72) = 1.944, p < 0.05), Task Commitment (F(14, 72) = 1.845, p < 0.05),
Speech Adaptability (F(14, 72) = 2.634, p < 0.05) and Speech Accuracy (F(14,
72) = 4.358, p < 0.001).
Therefore, due to the lack of homogeneity we proceeded with performing
the non parametric Kruskal-Wallis H test. Statistically different ranks by stu-
dents’ gender were observed between the two groups only in responsive-
ness to Problem Solving Questions in favour of boys (χ2(1) = 4.342, p < 0.05,
25
