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Approaches to studying across culturally contrasting groups: implications for security education

Domalewska D.

Security and Defence Quarterly

2017

Vol. 16, No. 3

3--19

The problem of increased migration and integration of migrant children in schools has become a serious challenge for Security Education, especially the question of how to teach increasingly varied groups of students and whether students that come from culturally contrasting groups differ in their preferred learning style. Th is study sets out to analyse how students of various cultural backgrounds approach learning tasks, which is of utmost importance nowadays given that modern schools face the challenge of educating culturally diverse students. To this end, the Approaches and Study Skills Inventory for Students (ASSIST) was administered to 450 Thai students in a Thai university. The correlation between the learning approaches and individual diff erences (age, GPA and major) was assessed. Th en, the results of the study were compared with the results of similar studies carried out in diff erent cultures. Th e results show that the students scoring higher on the deep approach have the highest academic performance, whereas the students who approach the learning material strategically achieve the lowest learning outcomes. Furthermore, the Th ai students did not diff er signifi cantly from their western peers (Norwegian, Egyptian, Portuguese and British); however, their results diff ered from the students from China, who generally scored lower on all subscales of the ASSIST scores. Thus, the fi ndings of the study prove that the integration of migrant children can be highly successful because both migrant and host society students adopt similar approaches and strategies that strive for academic excellence.

Learning style recognition based on an adjustable three-layer fuzzy cognitive map

Georgiou D. A., Botsios S., Mitropoulou V., Papaioannou M., Schizas C., Tsoulouhas G.

Journal of Artificial Intelligence and Soft Computing Research

2011

Vol. 1, No. 4

333--347

Identification of learning styles supports Adaptive Educational Hypermedia Systems compiling and presenting tutorials custom in cognitive characteristics of each individual learner. This work addresses the issue: identifying the learning style of students, following the Kolb’s learning cycle. To this purpose, we propose a three-layers Fuzzy Cognitive Map (FCM) in conjunction with a dynamic Hebbian rule for learning styles recognition. The form of FCMs is designed by humans who determine its weighted interconnections among concepts. But the human factor may not be as reliable as it should be. Thus, a FCM model of the system allowing the adjustment of its weights using additional learners’ characteristics such as the Learning Ability Factors. In this article, two consecutively interconnected FCM (in the form of a three layer FCM) are presented. The schema’s efficiency has been tested and compared to known results after a fine-tuning of the weights of the causal interconnections among concepts. The simulations results of training the process system verify the effectiveness, validity and advantageous characteristics of those learning techniques for FCMs. The online recognition of learning styles by using threelayer Fuzzy Cognitive Map improves the accuracy of recognition obtained using Bayesian Networks that uses quantitative measurements of learning style taken from statistical samples. This improvement is due to the fuzzy nature of qualitative characterizations (such as learning styles), and the presence of intermediate level nodes representing Learning Ability Factors. Such factors are easily recognizable characteristics of a learner to improve adjustment of weights in edges with one end in the middle-level nodes. This leads to the establishment of a more reliable model, as shown by the results given by the application to a test group of students.