An ANFIS model of quality of experience prediction in education
Journal
Applied Soft Computing
Date Issued
2015-09-01
Author(s)
Vasileva-Stojanovska, Tatjana
Vasileva, Marina
Malinovski, Toni
Trajkovik, Vladimir
Abstract
This paper presents a Quality of Experience (QoE) prediction model in a student-centered blended learning environment, equipped with appropriate technologically enriched classroom. The model uses ANFIS
technique to infer the QoE from the individual subjective factors and the objective technical factors
which altogether influence the perceived QoE. We explored the influence of subjective personality traits
extroversion and neuroticism, as well as the learning style on QoE. The objective factors included in the
model are technically measurable parameters latency, jitter, packet loss and bandwidth affecting Quality
of Service (QoS) of the underlying technology. The findings presented in this paper are obtained from
a case study which involved 8 teachers and 142 students from second and sixth grade in five primary
schools in the Republic of Macedonia. The teachers involved in the project introduced game-based learning strategies in classes, including on-line videoconferences, streamed video content and classical face
to face gaming. We constructed three ANFIS systems with seven and four input variables and compared
their performances using the RMSE, MAPE and R
2 measurements. The results showed that perceived QoE
can be reliably predicted by the student’s personality traits and learning style as subjective factors and
network jitter as an objective factor.
technique to infer the QoE from the individual subjective factors and the objective technical factors
which altogether influence the perceived QoE. We explored the influence of subjective personality traits
extroversion and neuroticism, as well as the learning style on QoE. The objective factors included in the
model are technically measurable parameters latency, jitter, packet loss and bandwidth affecting Quality
of Service (QoS) of the underlying technology. The findings presented in this paper are obtained from
a case study which involved 8 teachers and 142 students from second and sixth grade in five primary
schools in the Republic of Macedonia. The teachers involved in the project introduced game-based learning strategies in classes, including on-line videoconferences, streamed video content and classical face
to face gaming. We constructed three ANFIS systems with seven and four input variables and compared
their performances using the RMSE, MAPE and R
2 measurements. The results showed that perceived QoE
can be reliably predicted by the student’s personality traits and learning style as subjective factors and
network jitter as an objective factor.
Subjects
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