Software Development for Educational Information Services Using Multilayering Semantics Adaptation

Rukhiran, Meennapa; Buaroong, Somchai; Netinant, Paniti

doi:10.4018/ijssmet.307153

Cited by 9 publications

(12 citation statements)

References 68 publications

(76 reference statements)

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“…By combining the digital number of 32 criteria bits from the example in Figure 4, the binary number 01000000000101110000000010011100 represents the integer value 107,524,930,81010. Conversion from binary to base-10 is: 010000000001011100000000100111002 = (0 × 2 31 ) + (1 × 2 30 ) + (0 × 2 29 ) + (0 × 2 28 ) + (0 × 2 27 ) + (0 × 2 26 ) + (0 × 2 25 ) + (0 × 2 24 ) + (0 × 2 23 ) + (0 × 2 22 ) + (0 × 2 21 ) + (1 × 2 20 ) + (0 × 2 19 ) + (1 × 2 18 ) + (1 × 2 17 ) + (1 × 2 16 ) + (0 × 2 15 ) + (0 × 2 14 ) + (0 × 2 13 ) + (0 × 2 12 ) + (0 × 2 11 ) + (0 × 2 10 ) + (0 × 2 9 ) + (0 × 2 8 ) + (1 × 2 7 ) + (0 × 2 6 ) + (0 × 2 5 ) + (1 × 2 4 ) + (1 × 2 3 ) + (1 × 2 2 ) + (0 × 2 1 ) + (0 × 2 0 ) = 107524930810.…”

Section: Samplesmentioning

confidence: 99%

“…F1-score is a practical aim to achieve a balance between the two. The F1-score can be calculated using Equation (8).…”

Section: Recall =mentioning

confidence: 99%

“…Users are increasingly exposed to the entirety of the digital universe [7,8] through the prism of their information, knowledge, behaviors, activities, preferences, and interests using recommendation systems [9]. Due to the increase in online information and database systems, a recommender system employing a powerful information filtering technology that allows users to make their own decisions to increase user satisfaction [10] has attracted considerable interest.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Multi-Criteria Decision Making of Graduate Admission Recommender System: AHP and Fuzzy AHP Approaches

2023

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The optimal management of personal resources impacts everyone’s quality of life. An investment in graduate education is a sustainable opportunity for improved outcomes in human life, including cognition, behavior, life opportunities, salary, and career. Advanced technology dramatically reduces the risk of personal resources in graduate program admission recommendations that depend on multiple individual needs and preferences. In the digital age, a dynamic recommender system enhances the suitably effective solution for students’ university selections. This study focused on designing, developing, and testing a recommender system for graduate admission using a dynamic multi-criteria AHP and fuzzy AHP approach. The explicit multi-criteria recommender system was a platform as a service (PaaS) web application created to aid in graduate admissions management and decision-making. The design proposed that the bit representation store a dynamic explicit multi-criteria data structure. The recommendations adopting dynamic multi-criteria were validated by comparing them to the programs to which the students were actually admitted and enrolled. They individually ranked the evaluation outcomes of dynamic explicit multi-criteria and alternative preferences to provide graduate admission recommendations. Eighty graduate students in information technology evaluated the recommender system. Using top-1, top-2, and F1-score accuracy, the effective system accuracy performance on the dynamic multi-criteria recommender system was evaluated using AHP and fuzzy AHP approaches. The fuzzy AHP demonstrated marginally greater practical accuracy than the AHP method.

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Section: Samplesmentioning

confidence: 99%

“…F1-score is a practical aim to achieve a balance between the two. The F1-score can be calculated using Equation (8).…”

Section: Recall =mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Dynamic Multi-Criteria Decision Making of Graduate Admission Recommender System: AHP and Fuzzy AHP Approaches

2023

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“…People are increasingly dependent on digital content in their daily lives. The digital information content is unquestionably faster, more convenient, and more environmentally friendly than paper content (Rukhiran et al, 2022a). To the benefit of the public, digital content can improve portability, take advantage of network distribution, and simplify downloading and reading (Gu et al, 2020).…”

Section: Digital Contentmentioning

confidence: 99%

Development of Mobile Learning English Web Application

Rukhiran

Phokajang

Netinant

2022

International Journal of Information Technology and Web Engineering

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E-learning has become an important part of distance education to comprehend students' skills and knowledge during the COVID-19 pandemic. The adoption of e-learning for kindergarten children is a challenging key for design and development that must be involved in parental care during the use of e-learning. This research aims to design and evaluate a digital learning English system based on a web application for kindergarten students who require additional attention from instructors and parents. The study investigates students' learning achievement and end-user perceptions based on the extended technology acceptance model. The results contribute and confirm a significant positive to technology adoption of the digital teaching and learning framework by offering real-time learning, assessments, achievement records, and learning session activities using web applications on mobile. Perceived ease of use, perceived usefulness, and attitude positively influence behavioral intention to use the proposed learning web application.

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“…However, the examination system is one of the most important factors in determining each student's academic achievement. Although many educational institutions have incorporated an electronic system into examination tasks, such as web-based examinations [9], online testing [10], and online examination systems [11], previous research has focused primarily on how to manage basic information and general tasks [12]. Student verification is the examination's most important and primary procedure for identifying the correct candidate for school, class, and examination authentications.…”

Section: Introductionmentioning

confidence: 99%

IoT-Based Biometric Recognition Systems in Education for Identity Verification Services: Quality Assessment Approach

2023

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Traditional identity verification of students based on the human proctoring approach can cause a scam identity verification and ineffective processing time, particularly among vast groups of students. Most student identification cards are outdated personal information. Several biometric recognition approaches have been proposed and can be adopted to strengthen students' identity verification. Most educational adoption technology struggles with evaluation and validation techniques to ensure that biometric recognition systems are unquestionably suitable for utilization and implementation to fulfill student identity verification. This study presents the internet of things to develop flexible biometric recognition systems and an approach to assess the quality of biometric systems for educational use by investigating the effectiveness of identity verification of various biometric recognition technologies compared to the traditional verification method. The unimodal, multimodal, and semi-multimodal biometric technologies were tested using the developed internet of things-base biometric recognition systems examined by applying the proposed quality metrics of scoring factors based on accuracy, error rate, processing time, and cost. Hundreds of undergraduate exam takers were a sample group. Key findings indicate that the designed and presented systems suitably attain identity verification of exam students using a unimodal biometric. A unimodal face biometric system promises excellent support. A unimodal fingerprint biometric system assures the second excellent aid for student identity verification. However, multimodal and semi-multimodal biometric systems provide better accuracy with few handling times and higher costs. This study contributes significantly to the knowledge of utilizing biometric recognition for identity verification in smart educational use.

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Software Development for Educational Information Services Using Multilayering Semantics Adaptation

Cited by 9 publications

References 68 publications

Dynamic Multi-Criteria Decision Making of Graduate Admission Recommender System: AHP and Fuzzy AHP Approaches

Dynamic Multi-Criteria Decision Making of Graduate Admission Recommender System: AHP and Fuzzy AHP Approaches

Development of Mobile Learning English Web Application

IoT-Based Biometric Recognition Systems in Education for Identity Verification Services: Quality Assessment Approach

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