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LeadEval: aI-driven personalized assessment

The integration of advanced AI technologies into educational systems has the potential to revolutionize the learning and assessment process. This paper presents the development of LeadEval which is specially designed for the Leadership and Administration Excellence course at the Faculty of Economics...

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Main Authors: Yazid, Zaleha, Wan Salleh, Wan Muhamad Salahudin, Abd. Rahim, Nour El Huda
Format: Proceeding Paper
Language:English
English
English
English
Published: Pengajaran-UKM, Universiti Kebangsaan Malaysia 2024
Subjects:
AI Indexes (General)
L Education (General)
Online Access:http://irep.iium.edu.my/114321/49/114321_LeadEval%20Al-Driven%20personalized%20assessment.pdf
http://irep.iium.edu.my/114321/27/114321_LeadEval%20AI-Driven%20personalized%20assessment_slides.pdf
http://irep.iium.edu.my/114321/25/114321_LeadEval%20AI-Driven%20personalized%20assessment_book%20programmed.pdf
http://irep.iium.edu.my/114321/28/114321_LeadEval%20AI-Driven%20personalized%20assessment_abstract.pdf
http://irep.iium.edu.my/114321/
https://www.ukm.my/knovasi/
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spelling my.iium.irep.1143212024-09-10T02:28:45Z http://irep.iium.edu.my/114321/ LeadEval: aI-driven personalized assessment Yazid, Zaleha Wan Salleh, Wan Muhamad Salahudin Abd. Rahim, Nour El Huda AI Indexes (General) L Education (General) The integration of advanced AI technologies into educational systems has the potential to revolutionize the learning and assessment process. This paper presents the development of LeadEval which is specially designed for the Leadership and Administration Excellence course at the Faculty of Economics and Management, Universiti Kebangsaan Malaysia. The system aims to facilitate the course coordinator's role by automating quiz creation and assessment. Using state-of-the-art natural language processing capabilities, LeadEval generates Multiple Choice Questions (MCQ), Multiple True-False (MTF), and Case Studies questions aligned with the course's learning outcomes. This innovation is expected to enhance the efficiency of course management and improve the assessment process, thereby contributing to the overall educational experience of the students. By leveraging AI, educators can focus more on teaching and less on administrative tasks, leading to a more engaging and effective learning environment. LeadEval’s ability to continuously learn and adapt to new content ensures that it remains a valuable tool in the ever-evolving educational landscape. The results from initial implementations indicate a significant improvement in the quality and relevance of quiz questions, highlighting the potential of AI in transforming educational assessment. Pengajaran-UKM, Universiti Kebangsaan Malaysia 2024 Proceeding Paper NonPeerReviewed application/pdf en http://irep.iium.edu.my/114321/49/114321_LeadEval%20Al-Driven%20personalized%20assessment.pdf application/pdf en http://irep.iium.edu.my/114321/27/114321_LeadEval%20AI-Driven%20personalized%20assessment_slides.pdf application/pdf en http://irep.iium.edu.my/114321/25/114321_LeadEval%20AI-Driven%20personalized%20assessment_book%20programmed.pdf application/pdf en http://irep.iium.edu.my/114321/28/114321_LeadEval%20AI-Driven%20personalized%20assessment_abstract.pdf Yazid, Zaleha and Wan Salleh, Wan Muhamad Salahudin and Abd. Rahim, Nour El Huda (2024) LeadEval: aI-driven personalized assessment. In: International University Carnival On E-Learning (IUCEL 2024) X Kongres Dan Pertandingan Inovasi Pengajaran & Pembelajaran Ukm (kNOVASI 2024), 5 Sept 2024, Bangi Avenue Convention Centre. https://www.ukm.my/knovasi/
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
English
English
topic AI Indexes (General)
L Education (General)
spellingShingle AI Indexes (General)
L Education (General)
Yazid, Zaleha
Wan Salleh, Wan Muhamad Salahudin
Abd. Rahim, Nour El Huda
LeadEval: aI-driven personalized assessment
description The integration of advanced AI technologies into educational systems has the potential to revolutionize the learning and assessment process. This paper presents the development of LeadEval which is specially designed for the Leadership and Administration Excellence course at the Faculty of Economics and Management, Universiti Kebangsaan Malaysia. The system aims to facilitate the course coordinator's role by automating quiz creation and assessment. Using state-of-the-art natural language processing capabilities, LeadEval generates Multiple Choice Questions (MCQ), Multiple True-False (MTF), and Case Studies questions aligned with the course's learning outcomes. This innovation is expected to enhance the efficiency of course management and improve the assessment process, thereby contributing to the overall educational experience of the students. By leveraging AI, educators can focus more on teaching and less on administrative tasks, leading to a more engaging and effective learning environment. LeadEval’s ability to continuously learn and adapt to new content ensures that it remains a valuable tool in the ever-evolving educational landscape. The results from initial implementations indicate a significant improvement in the quality and relevance of quiz questions, highlighting the potential of AI in transforming educational assessment.
format Proceeding Paper
author Yazid, Zaleha
Wan Salleh, Wan Muhamad Salahudin
Abd. Rahim, Nour El Huda
author_facet Yazid, Zaleha
Wan Salleh, Wan Muhamad Salahudin
Abd. Rahim, Nour El Huda
author_sort Yazid, Zaleha
title LeadEval: aI-driven personalized assessment
title_short LeadEval: aI-driven personalized assessment
title_full LeadEval: aI-driven personalized assessment
title_fullStr LeadEval: aI-driven personalized assessment
title_full_unstemmed LeadEval: aI-driven personalized assessment
title_sort leadeval: ai-driven personalized assessment
publisher Pengajaran-UKM, Universiti Kebangsaan Malaysia
publishDate 2024
url http://irep.iium.edu.my/114321/49/114321_LeadEval%20Al-Driven%20personalized%20assessment.pdf
http://irep.iium.edu.my/114321/27/114321_LeadEval%20AI-Driven%20personalized%20assessment_slides.pdf
http://irep.iium.edu.my/114321/25/114321_LeadEval%20AI-Driven%20personalized%20assessment_book%20programmed.pdf
http://irep.iium.edu.my/114321/28/114321_LeadEval%20AI-Driven%20personalized%20assessment_abstract.pdf
http://irep.iium.edu.my/114321/
https://www.ukm.my/knovasi/
_version_ 1811679628288327680
score 13.211869

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