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All Journal IJoLE: International Journal of Language Education Brilliance: Research of Artificial Intelligence Automotive Experiences
Dwi Novia Al Husaeni
Universitas Pendidikan Indonesia, Indonesia
Aerospace Engineering Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Other

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How Language and Technology Can Improve Student Learning Quality in Engineering? Definition, Factors for Enhancing Students Comprehension, and Computational Bibliometric Analysis Dwi Fitria Al Husaeni; Dwi Novia Al Husaeni; Risti Ragadhita; Muhammad Roil Bilad; Abdulkareem Sh. Mahdi Al-Obaidi; Asep Bayu Dani Nandiyanto
International Journal of Language Education Vol 6 No. 4, 2022
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/ijole.v6i4.53587

Abstract

The research aims to review developments in language and technology research that can improve the quality of teaching and learning in engineering. Several factors that can influence the teaching and learning process are explained, supported by a bibliometric analysis (with keywords “Language” AND “Engineering Learning” from Google Scholar from 2020 to 2022). The review includes the definition of engineering education with technology's advantages in engineering education. We also explained about purpose and service of language with what considerations in making strategies in language and technology for teaching and learning engineering education. Explanations about formal and informal learning as well as education level to learn engineering and curriculum development were also added. The application of technology in media and laboratories is also the main factor in improving literacy and language's impact on students. All factors cannot be separated from language and student characteristics, motivation, teacher-student relationships, therapy, and psychological condition. We also added information regarding language barriers for students with special needs and new language-improving technology for teaching. The results of the co-occurrence analysis expressed several points to be considered, including children, mathematics, STEM, education, and educators’ terms. Thus, it obtained that the principle of engineering education refers to the process of teaching and learning about scientific concepts, principles, and practices, and technology plays an important role because it is closely related to scientific principles and investigative methods. Language has an important role in supporting students' understanding and abilities in this subject since it conveys learning information. This paper can be used as a reference for educators to understand current conditions regarding the importance of language in the teaching and learning in the engineering field.
Progress in the Developments of Heat Transfer, Nanoparticles in Fluid, and Automotive Radiators: Review and Computational Bibliometric Analysis Asep Bayu Dani Nandiyanto; Dwi Novia Al Husaeni; Abdulkareem Sh. Mahdi Al Obaidi; Belkheir Hammouti
Automotive Experiences Vol. 7 No. 2 (2024)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ae.10580

Abstract

This research aims to determine the development of the number of scientific publications in the field of particulate matter; the number of publications from each country that publish articles on heat transfer, nanoparticles, and automotive radiators; articles with the highest number of citations; and visualization publication development map based on keywords. To achieve this goal, quantitative descriptive research was carried out using bibliometric analysis with the help of the publish or perish (PoP) application to collect data and VOSviewer to visualize related research topics. The article data taken is limited to 2018-2023. In addition, the terms heat transfer, nanoparticles, and automotive radiators are used as keywords in collecting article data using the pop application. Research on heat transfer, nanoparticles, and automotive radiators has increased in 2020 and India has become one of the countries that has contributed many publications on this topic. From the mapping results, research on heat transfer, nanoparticles, and automotive radiators is still being carried out frequently, especially in early 2020-2021. This research can help academics determine which problems to research and can be used as a reference for further research.
Machine Learning-Based Clustering for Program Learning Outcomes in Higher Education: A Systematic Review W. Wahyudin; Lala Septem Riza; E. Erlangga; Dwi Novia Al Husaeni
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.5953

Abstract

This study aims to systematically review the application of machine learning-based clustering algorithms in the evaluation of Graduate Learning Outcomes (CPL) in higher education. The review was conducted using the PRISMA approach on articles published in the Scopus database during the period 2020–2025. A total of 52 articles were analyzed to identify trends in the algorithms used, implementation challenges, and their contributions to curriculum development. The findings show that algorithms such as K-Means, Hierarchical Clustering, and Fuzzy C-Means are frequently used in mapping student competencies. However, their implementation in practice remains limited due to insufficient model validation, lack of justification for algorithm selection, and a disconnect between analytical results and academic decision-making. This situation reflects a broader issue in the integration of machine learning into educational contexts, where the technical potential of algorithms has not yet been fully translated into meaningful pedagogical impact. As a conceptual contribution, this study develops a machine learning-based computational model that includes the stages of CPL data collection, preprocessing, cluster modeling, result evaluation, and integration into curriculum policy. The proposed model is designed to enhance transparency, adaptability, and evidence-based decision-making in curriculum management systems. This study also highlights the need for the development of soft clustering techniques, integration with digital learning systems, and attention to the ethics and transparency of algorithms in data-based evaluation. Thus, this study emphasizes the importance of bridging the gap between algorithmic analysis and applicable educational strategies within higher education institutions.
Co-Authors Abdulkareem Sh. Mahdi Al Obaidi Abdulkareem Sh. Mahdi Al-Obaidi Al Husaeni, Dwi Fitria Asep Bayu Dani Nandiyanto Asep Bayu Dani Nandiyanto Belkheir Hammouti E. Erlangga Lala Septem Riza Muhammad Roil Bilad Ragadhita, Risti W. Wahyudin