On Assessment of Students' Academic Achievement Considering Categorized Individual Differences at Engineering Education (Neural Networks Approach)
• 2013
معلومات البحث
المؤلفون
Hassan M. H. Mustafa
1
, Ayoub Al-Hamadi
2
, Mohamed M. Hassan
3
, Saeed A. Al-Ghamdi
4
and Adel A.
Khedr
3
الكلمات المفتاحية
Not Available
المجلة العلمية
Not Available
الناشر
Not Available
المجلد
Not Available
العدد
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الصفحات
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publication.type
International
رابط البحث
Not Available
المواد المرفقة
Not Available
الملخص
This work introduces analysis and evaluation of an interesting, challenging,
and interdisciplinary, pedagogical issue. That's originated from
categorization of the achievement diversity of students' (individual
differences), equivalently students' Structure of the Observed Learning
Outcome (SOLO). This students' academic diversity affected in classrooms
by three interactive learning/teaching approaches (orientations) namely:
surface, deep, and strategic.
Assessment of these approaches has been performed via realistic simulation
adopting Artificial Neural Networks (ANN
s
) modeling considering Hebbian
rule for coincidence detection learning. That modeling results in interesting
mathematical analogy of two effective learning performance factors with
students' achievement individual differences.
Firstly, the effect of two brain functional phenomena; namely long term
Potentiation (LTP) and depression (LTD). That's in accordance with opening
time for crossing N-methyl-D-aspartate NMDA observed at hippocampus
brain area.
Secondly, the effect of neurons' number associated with diverse
learning/teaching environments comprise the dichotomy
(extroversion/introversion).This dichotomy has been investigated as the
external and internal environmental learning conditions. The obtained
simulation results concerned with student's diversity attitudes
(extroversion/introversion). They shown to be in well agreement with
recently published results after performing a casestudy at an engineering
institution in Egypt. Finally, introduced study, aims mainly to present
interesting analysis of brain's functional development based students'
individual differences, and learning abilities.
Copy Right, IJAR, 2013,. All rights reserved.
and interdisciplinary, pedagogical issue. That's originated from
categorization of the achievement diversity of students' (individual
differences), equivalently students' Structure of the Observed Learning
Outcome (SOLO). This students' academic diversity affected in classrooms
by three interactive learning/teaching approaches (orientations) namely:
surface, deep, and strategic.
Assessment of these approaches has been performed via realistic simulation
adopting Artificial Neural Networks (ANN
s
) modeling considering Hebbian
rule for coincidence detection learning. That modeling results in interesting
mathematical analogy of two effective learning performance factors with
students' achievement individual differences.
Firstly, the effect of two brain functional phenomena; namely long term
Potentiation (LTP) and depression (LTD). That's in accordance with opening
time for crossing N-methyl-D-aspartate NMDA observed at hippocampus
brain area.
Secondly, the effect of neurons' number associated with diverse
learning/teaching environments comprise the dichotomy
(extroversion/introversion).This dichotomy has been investigated as the
external and internal environmental learning conditions. The obtained
simulation results concerned with student's diversity attitudes
(extroversion/introversion). They shown to be in well agreement with
recently published results after performing a casestudy at an engineering
institution in Egypt. Finally, introduced study, aims mainly to present
interesting analysis of brain's functional development based students'
individual differences, and learning abilities.
Copy Right, IJAR, 2013,. All rights reserved.
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