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Integration of artificial intelligence technology in learning evaluation using the ADDIE method

IAES International Journal of Artificial Intelligence · Vol. 15 No. 4 (2026) · hlm. 3068–3080

DOI
10.11591/ijai.v15.i4.pp3068-3080
ISSN
2252-8938, 2089-4872
Terbit
2026-08-01
Penerbit
Institute of Advanced Engineering and Science
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Artificial intelligence offers significant potential to enhance learning evaluation, yet implementing fair and objective assessments remains a challenge. This study developed an artificial intelligence-based learning evaluation system to improve assessment inclusivity and efficiency. Employing the research and development method with the analysis, design, development, implementation, and evaluation (ADDIE) model, the system features a virtual assistant chatbot and an automated grading tool artificial intelligence assessment. The product underwent validation by media and material experts, followed by field trials with 20 secondary school teachers. The results demonstrated high feasibility, with validation scores of 96% by user interface/user experience (UI/UX) and 91.2% by material experts, and an implementation feasibility score of 94.4%. The system successfully assisted teachers in reducing administrative burdens and providing personalized feedback based on student learning styles. Future developments should expand subject coverage and support diverse assessment formats.

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11 penulis · 31 tautan kepenulisan bersama · 5 lintas organisasi

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  • State University of Malang
  • University of Brawijaya
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  • Organisasi berbeda
  • Organisasi sama
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Rekan penulisOrganisasiArtikel bersama
Ratna EkawatiState University of Malang1
Davina AureliaAfiliasi tidak diketahui1
Slamet ArifinAfiliasi tidak diketahui1
Davina AureliaState University of Malang1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) http://ijai.iaescore.com/index.php/IJAI/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Integration of artificial intelligence technology in learning evaluation using the ADDIE method</dc:title>
	<dc:creator>Wahyudi, Adip</dc:creator>
	<dc:creator>Arifin, Slamet</dc:creator>
	<dc:creator>Solikhin, Mukhammad</dc:creator>
	<dc:creator>Sahrina, Alfi</dc:creator>
	<dc:creator>Maulana, Feri Fahrian</dc:creator>
	<dc:creator>Ainur Roziqin, Mohammad Firzon</dc:creator>
	<dc:creator>Shrestha, Maria Emerita Indraningrum</dc:creator>
	<dc:subject xml:lang="en-US"></dc:subject>
	<dc:subject xml:lang="en-US">ADDIE; Artificial intelligence; Chatbot; Learning evaluation; Technology</dc:subject>
	<dc:description xml:lang="en-US">Artificial intelligence offers significant potential to enhance learning evaluation, yet implementing fair and objective assessments remains a challenge. This study developed an artificial intelligence-based learning evaluation system to improve assessment inclusivity and efficiency. Employing the research and development method with the analysis, design, development, implementation, and evaluation (ADDIE) model, the system features a virtual assistant chatbot and an automated grading tool artificial intelligence assessment. The product underwent validation by media and material experts, followed by field trials with 20 secondary school teachers. The results demonstrated high feasibility, with validation scores of 96% by user interface/user experience (UI/UX) and 91.2% by material experts, and an implementation feasibility score of 94.4%. The system successfully assisted teachers in reducing administrative burdens and providing personalized feedback based on student learning styles. Future developments should expand subject coverage and support diverse assessment formats.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2026-08-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:identifier>https://ijai.iaescore.com/index.php/IJAI/article/view/29595</dc:identifier>
	<dc:identifier>10.11591/ijai.v15.i4.pp3068-3080</dc:identifier>
	<dc:source xml:lang="en-US">IAES International Journal of Artificial Intelligence (IJ-AI); Vol 15, No 4: August 2026; 3068-3080</dc:source>
	<dc:source>2252-8938</dc:source>
	<dc:source>2089-4872</dc:source>
	<dc:source>10.11591/ijai.v15.i4</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/view/29595/15274</dc:relation>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/downloadSuppFile/29595/4563</dc:relation>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/downloadSuppFile/29595/4565</dc:relation>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/downloadSuppFile/29595/4566</dc:relation>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/downloadSuppFile/29595/4567</dc:relation>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/downloadSuppFile/29595/4568</dc:relation>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/downloadSuppFile/29595/4569</dc:relation>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/downloadSuppFile/29595/4570</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2026 Adip Wahyudi, Slamet Arifin, Mukhammad Solikhin, Alfi Sahrina, Feri Fahrian Maulana, Mohammad Firzon Ainur Roziqin, Maria Emerita Indraningrum Shrestha</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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