Prilagođavanje Felder-Silverman modela stila učenja za primenu u adaptivnom elektronskom obrazovanju

Abstract

U ovom radu prikazan je jedan pristup prilagođavanju Felder-Silverman modela stila učenja za primenu u razvoju adaptivnih sistema elektronskog obrazovanja. Glavni cilj rada je poboljšanje postojećih kurseva elektronskog učenja razvojem metoda za adaptaciju na osnovu stilova učenja. Predloženi metod zasniva se na analizi podataka o studentima i primeni koncepta personalizacije u kreiranju elektronskih kurseva od strane nastavnika. Istraživanje je realizovano na Fakultetu organizacionih nauka u Beogradu, u zimskom semestru školske 2009/10 godine na uzorku od 318 studenata. Studenti eksperimentalne grupe su podeljeni u tri klastera, na osnovu podataka o njihovim stilovima učenja utvrđenih primenom prilagođenog upitnika Feldera i Silvermanove. Podaci o stilovim učenja prikupljeni tokom istraživanja koriste se za utvrđivanje karakterističnih grupa studenata, a zatim za klasifikaciju studenata u grupe. Klasifikacija je izvršena primenom data mining tehnika. U skladu sa rezultatima analize podataka, izvršena je adaptacija elektronskih kurseva. Nakon evaluacije, utvrđeno je da postoji značajna statistička razlika u rezultatima studenata koji su pohađali kurs adaptiran korišćenjem prikazanog metoda u odnosu na rezultate studenata koji su pohađali neadaptirani kurs.

This paper presents an approach for adjusting Felder-Silverman learning styles model for application in development of adaptive e-learning systems. Main goal of the paper is to improve the existing e-learning courses by developing a method for adaptation based on learning styles. The proposed method includes analysis of data related to students characteristics and applying the concept of personalization in creating e-learning courses. The research has been conducted at Faculty of organizational sciences, University of Belgrade, during winter semester of 2009/10, on sample of 318 students. The students from the experimental group were divided in three clusters, based on data about their styles identified using adjusted Felder-Silverman questionnaire. Data about learning styles collected during the research were used to determine typical groups of students and then to classify students into these groups. The classification was performed using data mining techniques. Adaptation of the e-learning courses was implemented according to results of data analysis. Evaluation showed that there was statistically significant difference in the results of students who attended the course adapted by using the described method, in comparison with results of students who attended course that was not adapted.