Proposal Models for Personalization of e-Learning based on Flow Theory and Artificial Intelligence

Abstract

This paper presents the comparison of the results of two models for the personalization of learning resources sequences in a Massive Online Open Course (MOOC). The compared models are very similar and differ just in the way how they recommend the learning resource sequences to each participant of the MOOC. In the first model, Case Based Reasoning (CBR) and Euclidean distance is used to recommend learning resource sequences that were successful in the past, while in the second model, the Q-Learning algorithm of Reinforcement Learning is used to recommend optimal learning resource sequences. The design of the learning resources is based on the flow theory considering dimensions as knowledge level of the student versus complexity level of the learning resource with the aim of avoiding the problems of anxiety or boredom during the learning process of the MOOC.

Authors and Affiliations

Anibal Flores, Luis Alfaro, José Herrera, Edward Hinojosa

Keywords

Related Articles

Helpful Statistics in Recognizing Basic Arabic Phonemes

The recognition of continuous speech is one of the main challenges in the building of automatic speech recognition (ASR) systems, especially when it comes to phonetically complex languages such as Arabic. An ASR system s...

Building a Penetration Testing Device for Black Box using Modified Linux for Under $50

This study analyzes the use of a Raspberry Pi (RPi) as part of a Penetration Tester’s toolkit. The RPi’s form factor, performance to cost ratio, used in conjunction with modified Linux, allows the RPi to be a very versat...

Novel Geo-Location Technique for Tourism Guide and Emergency Evacuation at Grand Mosque Al Haram Makkah

Grand Mosque AL Haram is always crowded with pilgrim. The most concentration of crowd happens during Hajj season. Even the grand mosque is already furnished with a lot of route sign board, exit or emergency sign boards....

Personalized Recommender by Exploiting Domain based Expert for Enhancing Collaborative Filtering Algorithm :PReC

The large amount of information available on the internet initiated various Recommender algorithms to act as an intermediate between number of choices and internet users. Collaborative filtering is one of the most tradi...

A Comparative Study of White Box, Black Box and Grey Box Testing Techniques

Software testing is the process to uncover requirement, design and coding errors in the program. It is used to identify the correctness, completeness, security and quality of software products against a specification. So...

Download PDF file
  • EP ID EP611392
  • DOI 10.14569/IJACSA.2019.0100752
  • Views 104
  • Downloads 0

How To Cite

Anibal Flores, Luis Alfaro, José Herrera, Edward Hinojosa (2019). Proposal Models for Personalization of e-Learning based on Flow Theory and Artificial Intelligence. International Journal of Advanced Computer Science & Applications, 10(7), 380-390. https://europub.co.uk/articles/-A-611392