FIT Scholarly Articles

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http://hdl.handle.net/11071/3896

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Browsing FIT Scholarly Articles by Author "Ateya, Ismail Lukandu"

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    Applying reinforcement and mastery learning: how it works based on personalized e-learning curriculum?
    (The Society of Digital Information and Wireless Communications (SDIWC), 2014) Ballera, Melvin; Ateya, Ismail Lukandu; Omar, Aziza E.
    Many researchers in the field of personalized learning or topic sequencing have proposed and implemented various mechanisms to improve the learning process with the main objectives of maximizing learning and dynamically selecting the closest teaching operation in order to achieve the learning goals. However, upon recommending the personalized learning sequence, based on literature review, the e-learning instructional strategists failed to perform or address the corrective measures to immediately remediate the learning difficulty. This paper presents the combination of the reinforcement learning concepts in the area of artificial intelligence and the mastery learning in educational psychology to remediate learning difficulties of the learners. The results show that based on the presented corrective measures, which are based on students’ background performance matrixes that are collected during the learning process and summative examination, the students are able to correct their learning difficulties and improved their learning performances. The end semesters’ results show the guarantee that almost all of the students who undergo the reinforcement and mastery learning procedures can successfully pass the e-learning course.
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    Improving learning throughput in e-learning using interactive-cognitive based assessment
    (The Society of Digital Information and Wireless Communications (SDIWC), 2014) Ballera, Melvin; Ateya, Ismail Lukandu; Abdalla, Radwan
    An e-learning website is not sufficient to fully attain the results of online education. There also is a need to align the educational objectives into the design of the assessment to improve and develop cognition, critical thinking and problem-solving skills. Previous studies have explored the potentials of the assessment models but few ventured into their implementation. Others only proposed and introduced conceptual frameworks. The implementation of these proposals, however, revealed that the question type in the assessment phase neglected to align their questionnaire formats into a cognitive schema. At present, the standard multiple-choice question is the most frequently used of the question type of e-learning assessments. However, if this type is the only format adopted by e-learning developers, then the potentially rich and embedded assessment of the computer platform will be given up. This paper focuses on the design of assessment questions, which is created and guided by the hierarchical Bloom cognitive taxonomy and by utilizing rich media formats. Results conducted for eighteen weeks show a dramatic increase in the academic performance of the students. Likewise, digital transcripts converted from the collected perceptions after training undergoes sentiment analysis have correlated with the student improved academic throughput.