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p-Index From 2021 - 2026
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All Journal International Journal of Education Studies in Learning and Teaching
Cabuquin, Jomar C.
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Arts Humanities Education Languange, Linguistic, Communication & Media Mathematics Physics Social Sciences Other

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SECONDARY STUDENTS’ PROFILE AND SCHOLASTIC PERFORMANCE DURING COVID-19: THE CASE OF A LABORATORY SCHOOL IN THE PHILIPPINES Cabuquin, Jomar C.; Brun, Richard S.; Mercado, Henry Alwayne R.
International Journal of Education Vol 16, No 2 (2023): August 2023
Publisher : Kantor Jurnal dan Publikasi Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ije.v16i2.51379

Abstract

Students' performance in the classroom can be viewed as vital since an aptitude for learning and intelligence can pave the way for their future success in both the workplace and the economy. This study examined the secondary students' profile and scholastic performance during the COVID-19 pandemic at a laboratory school in Eastern Visayas, Philippines. It utilized the quantitative approach to ascertain the variation among the specified study variables involving 620 secondary students from different grade levels. Secondary data on students' profile variables and scholastic performance were obtained from the school's Learner Information System (LIS). The T-test for two independent samples was likewise utilized to examine the significant difference in the performance of male and female students according to grade levels. Based on the results, majority of the students used mobile data and broadband as means to access the internet. Moreover, the online and blended learning were the student's preferred learning modalities. However, the inadequacy of gadgets available, insufficient load, intermittent mobile or internet access, existing health conditions, difficulty in self-regulated learning, conflict with other activities, and high electrical consumption and distractions were among the challenges students faced during the pandemic. Meanwhile, the students displayed very satisfactory to outstanding scholastic performance amidst COVID-19. Likewise, the study found no significant performance difference between male and female students in grades 8 and 12, in contrast to other grade levels. Therefore, creating flexible and responsive teaching practices in the current and post-pandemic educational environment and the enhancement of internet connectivity is recommended. 
Improving English Speaking Skills Through AI-Based Voice Chatbots: A Systematic Review of Vocational Education Studies Halimah, Adik Nur; Budianto, Aris; Hoesny, Mariana Ulfah; Cabuquin, Jomar C.; Ulfa, Saida
Studies in Learning and Teaching Vol. 6 No. 3 (2025): December
Publisher : CV Sinergi Ilmu dan Publikasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46627/silet.v7i1.684

Abstract

Artificial intelligence offers teachers the opportunity to improve English-language skills among vocational high school students, enabling them to compete globally. This study aims to evaluate the effectiveness of AI-based voice chatbots through a systematic literature review. Following the PRISMA protocol, 16 articles were comprehensively analyzed after rigorous screening of 374 studies from the Scopus and ScienceDirect databases. The findings revealed a diverse range of platforms, with Duolingo dominating as the primary learning medium. The integration of voice chatbots has been shown to significantly improve students' oral performance, particularly in pronunciation, grammatical accuracy, coherence, and fluency. This improvement in speaking skills is driven by automated feedback based on repeated practice. AI-based chatbots have also been shown to increase motivation by enhancing Willingness to Communicate (WTC) and learning enjoyment through gamification elements and a non-judgmental interaction environment. Practically, vocational high school teachers are advised to integrate AI as a partner in authentic communication simulations. The study recommends learning designs that combine instant AI feedback with specific scenarios to create an adaptive and low-stress learning ecosystem.
Co-Authors Aris Budianto, Aris Brun, Richard S. Halimah, Adik Nur Mercado, Henry Alwayne R. Moechammad Sarosa Saida Ulfa