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All Journal Briliant: Jurnal Riset dan Konseptual Indonesian Journal of Educational Science (IJES)
A. Bohang, Muthmainnah Bahri
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Other

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The Feedback-Motivation Connection: Driving Better Speaking Outcomes for Students Alfian, Heri; Dakka, Litha Nesidekawati; Khartha, Aqzhariady; A. Bohang, Muthmainnah Bahri
Indonesian Journal of Educational Science (IJES) Vol 7 No 2 (2025): Indonesian Journal of Educational Science (IJES)
Publisher : Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/ijes.v7i2.4846

Abstract

This study was aimed to find out the correlation between corrective feedback, students' motivation, students’ speaking performance, and how they interplay with each other. The researcher used a mixed-method, a qualitative and quantitative design. The sample of this study was 34 third grade students of SMAN 1 Tirawuta. In collecting data, questionnaires, observation, and interviews were used. The findings showed that (1)there is a significant correlation between corrective feedback and students’ speaking performance, indicated by sig 2-tailed 0.005. (2) There is a significant correlation between students’ motivation and students’ speaking performance, indicated by sig 2-Tailed 0.003. (3) There is also a significant correlation between corrective feedback and students’ motivation and students’ speaking performance simultaneously, indicated by sig 2-tailed 0.003. The correlation between corrective feedback, students’ motivation, and students’ speaking performance were in the gravity of moderate level, R 0.559, and the R square was 0.313. This implies that 31.3 % variation of students’ speaking performance can be predicted through corrective feedback and students’ motivation, while 68.7% can be predicted through other factors. Last but not least, (4) Teacher’s feedback motivated students through their errors in improving their speaking performance
Next-Gen Vocabulary Tools: How Chatbots Elevate Technical English for Computer Science Students Alfian, Heri; Putra, Eko; A. Bohang, Muthmainnah Bahri; Mustari, Sri Hariati; Pratiwi, Alifiah
BRILIANT: Jurnal Riset dan Konseptual Vol 10 No 4 (2025): Volume 10 Nomor 4, November 2025
Publisher : Universitas Nahdlatul Ulama Blitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/briliant.v10i4.2367

Abstract

This study examined how well chatbot-enhanced training can help computer science students understand technical vocabulary. Semi-structured interviews were combined with a pre-test and post-test design as part of a mixed-methods strategy. With a substantial effect size (Cohen's d = 1.59) and a mean increase of 12.7%, quantitative data showed a statistically significant improvement in vocabulary scores, suggesting major practical implications. A thematic analysis of qualitative responses identified three main themes: usability limits, motivation and involvement, and perceived benefits. Students commended the chatbot's ability to offer real-time, contextual feedback and promoted deeper learning by using examples that are interwoven with coding situations. The conversational tone, individualized contact, and emotional engagement of the chatbot were credited with increasing motivation. However, some students pointed up issues including repeating outputs, overuse of synonyms, and complex instances, highlighting the necessity of adaptive content calibration. These results demonstrated that, with careful integration, AI-powered chatbots can function as efficient, customized vocabulary instructors; nevertheless, wider adoption will require enhancements to content delivery systems.
Co-Authors Aqzhariady Khartha eko putra, eko Heri Alfian Litha Nesidekawati Dakka Mustari, Sri Hariati Pratiwi, Alifiah