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Transforming correspondence learning through a smart assistant system to improve student outcomes and engagement

IAES International Journal of Artificial Intelligence · Vol. 15 No. 4 (2026) · hlm. 3218–3227

DOI
10.11591/ijai.v15.i4.pp3218-3227
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

The insufficient feedback in business correspondence education at the higher education level necessitates innovation in adaptive and responsive learning resources. This study seeks to create and evaluate the efficacy of an artificial intelligence (AI)-driven correspondence learning assistant (CORLA) to enhance students' correspondence abilities. The study employs a research and development (R&D) methodology by utilizing the Dick and Carey model, which has ten phases of instructional development. The participants in the study were students enrolled in Digital Office Administration Study Program, Universitas Negeri Jakarta. Data were gathered by observation, interviews, questionnaires, and assessments (pre-test and post-test), and evaluated by three experts in materials, learning design, and media. The findings indicated that CORLA demonstrates a significant degree of feasibility, practicality, and efficacy. CORLA's advanced features encompass AI-driven automatic feedback, letter composition simulation, learning progress monitoring, discussion forums, and an intuitive user interface (UI). This study advances the creation of an effective and practical AI-based learning media model tailored to the requirements of teaching business correspondence abilities in higher education.

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  • Universitas Airlangga
  • Universitas Gadjah Mada
  • State University of Jakarta
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Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Nova Syafira AriyantiAfiliasi tidak diketahui5
Maisyaroh MaisyarohAfiliasi tidak diketahui4
Radhiah RadhiahAfiliasi tidak diketahui2
Ibrahim BafadalAfiliasi tidak diketahui2
Ahmad NurabadiAfiliasi tidak diketahui2
Juharyanto JuharyantoAfiliasi tidak diketahui2
Siti RusdianaAfiliasi tidak diketahui1
Syaiful HamdiAfiliasi tidak diketahui1
Nurmaulidar NurmaulidarAfiliasi tidak diketahui1
Intan SyahriniAfiliasi tidak diketahui1
Mahmudi MahmudiAfiliasi tidak diketahui1
T. Murdani SaputraAfiliasi tidak diketahui1
Siti Nada FitriaaAfiliasi tidak diketahui1
Jusuf IriantoUniversitas Airlangga1
Imam GunawanAfiliasi tidak diketahui1
Bambang Budi WiyonoAfiliasi tidak diketahui1
Muhammad Imran QureshiAfiliasi tidak diketahui1
Suharyanto SuharyantoUniversitas Gadjah Mada1
Suryaman SuryamanAfiliasi tidak diketahui1
Robinson SitumorangAfiliasi tidak diketahui1
Etin SolihatinState University of Jakarta1
Akhmad Arif MusadadAfiliasi tidak diketahui1
Nur Fatah AbidinAfiliasi tidak diketahui1
Dadan Adi KurniawanAfiliasi tidak diketahui1
Raden Bambang SumarsonoAfiliasi tidak diketahui1
Agus TimanAfiliasi tidak diketahui1
Djum Djum Noor BentyAfiliasi tidak diketahui1
Anabelie Villa ValdezAfiliasi tidak diketahui1
Bagus Rachmad SaputraAfiliasi tidak diketahui1
Laili KomariyahAfiliasi tidak diketahui1
Christian Wiradendi WolorAfiliasi tidak diketahui1
Mustiningsih MustiningsihAfiliasi tidak diketahui1
Rudy AnsarAfiliasi tidak diketahui1
Sri UntariAfiliasi tidak diketahui1
Tutut ChusniyahAfiliasi tidak diketahui1

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">Transforming correspondence learning through a smart assistant system to improve student outcomes and engagement</dc:title>
	<dc:creator>Marsofiyati, Marsofiyati</dc:creator>
	<dc:creator>Faslah, Roni</dc:creator>
	<dc:creator>Adha, Maulana Amirul</dc:creator>
	<dc:creator>Ikhwan, Muhammad</dc:creator>
	<dc:creator>Madli, Faerozh Bin</dc:creator>
	<dc:subject xml:lang="en-US"></dc:subject>
	<dc:subject xml:lang="en-US">Artificial intelligence; Correspondence learning; Higher education; Learning media development; Smart assistance; Writing skills</dc:subject>
	<dc:description xml:lang="en-US">The insufficient feedback in business correspondence education at the higher education level necessitates innovation in adaptive and responsive learning resources. This study seeks to create and evaluate the efficacy of an artificial intelligence (AI)-driven correspondence learning assistant (CORLA) to enhance students' correspondence abilities. The study employs a research and development (R&amp;D) methodology by utilizing the Dick and Carey model, which has ten phases of instructional development. The participants in the study were students enrolled in Digital Office Administration Study Program, Universitas Negeri Jakarta. Data were gathered by observation, interviews, questionnaires, and assessments (pre-test and post-test), and evaluated by three experts in materials, learning design, and media. The findings indicated that CORLA demonstrates a significant degree of feasibility, practicality, and efficacy. CORLA's advanced features encompass AI-driven automatic feedback, letter composition simulation, learning progress monitoring, discussion forums, and an intuitive user interface (UI). This study advances the creation of an effective and practical AI-based learning media model tailored to the requirements of teaching business correspondence abilities in higher education.</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>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijai.iaescore.com/index.php/IJAI/article/view/30132</dc:identifier>
	<dc:identifier>10.11591/ijai.v15.i4.pp3218-3227</dc:identifier>
	<dc:source xml:lang="en-US">IAES International Journal of Artificial Intelligence (IJ-AI); Vol 15, No 4: August 2026; 3218-3227</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/30132/15286</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2026 Marsofiyati, Roni Faslah, Maulana Amirul Adha, Muhammad Ikhwan, Faerozh Bin Madli</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>