A Proposed Framework to Explore Semantic Relations for Learning Process Management

Khedr, Ayman E.; Idrees, Amira M.; Alsheref, Fahad Kamal

doi:10.4018/ijec.2019100104

Cited by 10 publications

(8 citation statements)

References 39 publications

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“…Data as well as information analytics techniques play a vital role in smart testing that could successfully incorporate the personalization process into smart testing by the intervention of the behavioral students' data for tracing the suitable exam and facilitating the questions' characteristics selection [6]. On the other hand, data resources such as social networks, forums, and corporates' databases are the foundations for the personalization process for monitoring the personal behavior and characterize the student personality which consequently supports the smart testing process [7]. These resources are the pillar for revealing the student's primitive actions, his interaction preferences, as well as his trends.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Framework for Enhancing the Quality of Online Exams based on Students’ Personalization

khedr¹,

Almazroi²,

Idrees³

2022

IJACSA

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In education sector, personalization is an evolutionary term that gained a high attention due to its effectiveness in raising the enterprise competence level. This research aims at proposing a novel model for effective smart testing, which considers the student's Facebook activities in determining the students' personality and constructing his suitable exam. The aim of this examination perspectives to ensure the reliable student evaluation according to his gained knowledge to ensure that no other factor interferes which may negatively affect the reliable evaluation. The research also applies text analytics techniques to ensure the exam balance. The proposed model has been applied and evaluated with professors' percentage equal to 96.5 % and successfully reach students satisfaction percentage with average equal to 96.63%.

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Section: Introductionmentioning

confidence: 99%

Intelligent Framework for Enhancing the Quality of Online Exams based on Students’ Personalization

khedr¹,

Almazroi²,

Idrees³

2022

IJACSA

Self Cite

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show abstract

“…While in [14], the attributes' determination considered identifying the news' credibility with identifying each considered attribute, the research had no clarification for other non-considered attributes as the focus was for proving the credibility target. Other researches such as in [15] and [16] considered different fields but with the scope of identifying the effective attributes with following the attributes' semantic relations with no consideration of the individual impact for these attributes.…”

Section: Related Workmentioning

confidence: 99%

“…Finally, the deliverable of stage 1 is a set of consistent attributes associated with their average weight (defined in Eq. (16)) which was calculated through the consistent weighting techniques. As a result of the consistency, these attributes will contribute in the mining tasks.…”

Section: Explore Weighted Attributes' Consistency Level (Determine Atmentioning

confidence: 99%

A Proposed Method for Minimizing Mining Tasks’ Data Dimensionality

Idrees¹,

Gomaa²

2020

IJIES

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Knowledge discovery techniques have heavily contributed to many fields with significant success. However, with the continuous growth of data, these techniques suffer from bottlenecks in processing these data. One of the directions to hinder this effect is reducing the data dimensionality which focuses on eliminating the attributes which have no significant effect on the discovery technique accuracy. This research proposes a novel method for reducing data dimensionality. The proposed method is based on two main pillars, the first is applying the adapted Saaty method for determining the attributes' consistency with proposing further adaptation targeting more accurate accuracy determination. The second pillar is applying the clustering techniques on the consistent attributes to eliminate the least weighted attributes in each cluster which also have the least consistent measures. The result of applying the two steps is to highlight the most significant dataset attributes. The proposed method has been successfully applied on the Gastrology dataset which attributes have been reduced from 62 attributes to 31 attributes. A set of classification techniques have been applied on the dataset to prove that the dimensionality reduction has retained the classification task accuracy, the results presented that the Random Forest algorithm had an accuracy equal 95.36% when applied to the adopted dataset.

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“…Load balancing algorithms follow one of the two approaches, static and dynamic ( Elmasry, Khedr & Nasr, 2019 ). Algorithms that follow the static approach need to determine the system’s capabilities such as the system’s resources and the required communication time ( Khedr, Idrees & Alsheref, 2019 ). The algorithms that follow the static approach apply the round-robin algorithm, which is a simple technique with low resource utilization.…”

Section: Introductionmentioning

confidence: 99%

Enhancing the e-learning system based on a novel tasks’ classification load-balancing algorithm

Khedr

Idrees

Salem

2021

PeerJ Computer Science

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In the educational field, the system performance, as well as the stakeholders’ satisfaction, are considered a bottleneck in the e-learning system due to the high number of users who are represented in the educational system’s stakeholders including instructors and students. On the other hand, successful resource utilization in cloud systems is one of the key factors for increasing system performance which is strongly related to the ability for the optimal load distribution. In this study, a novel load-balancing algorithm is proposed. The proposed algorithm aims to optimize the educational system’s performance and, consequently, the users’ satisfaction in the educational field represented by the students. The proposed enhancement in the e-learning system has been evaluated by two methods, first, a simulation experiment for confirming the applicability of the proposed algorithm. Then a real-case experiment has been applied to the e-learning system at Helwan University. The results revealed the advantages of the proposed algorithm over other well-known load balancing algorithms. A questionnaire was also developed to measure the users’ satisfaction with the system’s performance. A total of 3,670 thousand out of 5,000 students have responded, and the results have revealed a satisfaction percentage of 95.4% in the e-learning field represented by the students.

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A Proposed Framework to Explore Semantic Relations for Learning Process Management

Cited by 10 publications

References 39 publications

Intelligent Framework for Enhancing the Quality of Online Exams based on Students’ Personalization

Intelligent Framework for Enhancing the Quality of Online Exams based on Students’ Personalization

A Proposed Method for Minimizing Mining Tasks’ Data Dimensionality

Enhancing the e-learning system based on a novel tasks’ classification load-balancing algorithm

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