Reversed Roulette Wheel Selection Algorithms (RWSA) and Reinforcement Learning (RL) for personalizing and improving e-Learning system: the case study and its implementation

Journal article published in The International Journal of E-Learning and Educational Technologies in the Digital Media (IJEETDM)Various mechanisms to improve learning process with the objective of maximizing learning and dynamically selecting the best teaching operation to achieve learning goals have been done in the field of personalized learning. However, instructional strategists have failed to address the necessary corrective measures to remediate immediately learning difficulties. It is necessary that an alternative, more realistic, simpler and a real time multi-based performance for personalized learning sequence be developed and implemented. Three major contributions can be asserted by the study: it personalized the learning sequence using reversed roulette wheel selection algorithm and linear ranking; the fitness value is based on real time, multi-based performance system; and it implements the reinforcement and mastery learning to motivate students and to improve their learning output. Result shows that the personalized learning sequence (PLS) were dynamic and heuristic and considers the curriculum difficulty level and the curriculum continuity of successive curriculum while producing individualized and personalized learning sequence. Data collected during 18 weeks experimental sessions, from 34%, a 54% increased has been achieved, making the overall passing rate to 88%. Digital transcripts based on students’ perceptions and experiences in using the prototype positively correlates with theme analysis having a score of +.321 with positive attitude such as: very happy, friends, motivate, improve, understanding, knowledge and good were extracted from document analysis

Personalizing E-learning curriculum using: reversed roulette wheel selection algorithm

Conference paperE-learning poses a challenge in a pedagogical perspective such as finding ways on how to motivate the students to learn in spite of the absence of a human instructor. Many researchers in the field have proposed and implemented various mechanisms to improve the learning process such as individualization and personalization. The main objectives is to maximize learning by dynamically selecting the closest teaching operation in order to achieve the learning goals. In this paper, a revolutionary technique has been proposed and implemented to perform individualization and personalization using reversed roulette wheel selection algorithm that runs at O(n). The technique is simpler to implement and is algorithmically less expensive compared to other revolutionary algorithms since it collects the dynamic real time performance such as examinations, reviews and study matrices. Results show that the implemented system is capable of recommending new learning sequences that lessens time of study based on their prior knowledge and real performance matrix

The proposed computer engineering curriculum for the YLFI-Emilio Aguinaldo College: A response towards global competitiveness

This paper describes the proposed Computer Engineering Curriculum for the YLFI-Emilio Aguinaldo College conceptualized and developed by the College of Engineering and Technology Committee on Instruction. The enhancement made is geared towards developing a greater number of competent computer engineers and increasing the population of the college. The enhancement of the present curriculum of the Computer Engineering course was made by considering the Commission on Higher Education\u27s mandate for the course; the (TESDA) ladderization program; the needs of the industry; and the 2004 Curriculum Guidelines for Undergraduate Degree Programs in Computer Engineering developed by the Institute of Electrical and Electronics Engineers - Computer Society (IEEECS). It is hope that this proposed curriculum would help produce computer engineers who are not only globally competent but also responsive to the needs of the academe, industry and research

Proceedings of First Conference for Engineering Sciences and Technology: Vol. 1

This volume contains contributed articles of Track 1, Track 2 & Track 3, presented in the conference CEST-2018, organized by Faculty of Engineering Garaboulli, and Faculty of Engineering, Al-khoms, Elmergib University (Libya) on 25-27 September 2018. Track 1: Communication and Information Technology Track 2: Electrical and Electronics Engineering Track 3: Oil and Chemical Engineering Other articles of Track 4, 5 & 6 have been published in volume 2 of the proceedings at this lin