Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Paedagoria : Jurnal Kajian, Penelitian dan Pengembangan Kependidikan Priviet Social Sciences Journal
Trionanda, Stevanus
Unknown Affiliation
Economics, Econometrics & Finance Education Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
An analysis of using code mixing on interaction between homogeneous pair in collaborative writing Veniati, Veniati; Indriati, Titin; Trionanda, Stevanus
Priviet Social Sciences Journal Vol. 5 No. 12 (2025): December 2025
Publisher : Privietlab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55942/pssj.v5i12.1013

Abstract

Code-mixing is a procedure that involves the insertion of components from one language into another. Therefore, this study aimed to identify the types of code-mixing utilized by the students in homogeneous pairing interaction in collaborative writing and investigate the frequencies of code-mixing used by the students in homogeneous pairing interaction in collaborative writing. In this study, a descriptive qualitative research approach was applied. Furthermore, the types and frequencies of code-mixing utilized by students in homogenous paired interaction in collaborative writing are the focus of this study. The subjects were fifth-semester students in Central Java, Indonesia. To collect data, the researchers used audio recordings of student interactions. In analyzing the data, the researchers used Hoffman’s (1991) theory on types of code-mixing. According to the findings, there are three types of code-mixing: intra-sentential code-mixing (28), intra-lexical code-mixing (29), and code-mixing requiring a change in pronunciation (30). (5). There are numerous types of code-mixing for each form. Thus, intra-lexical code-mixing is the most prevalent type of code-mixing in student interactions, while code-mixing involving a change in pronunciation is the least common.
Attitudes Towards an AI-Augmented Pedagogy in Enhancing English Academic Writing Proficiency: Empirical Evidence from Electrical Engineering Students Indriati, Titin; Veniati, Veniati; Trionanda, Stevanus; Yahya, Ilham Nur Dimas; Manto, Manto
Paedagoria : Jurnal Kajian, Penelitian dan Pengembangan Kependidikan Vol 17, No 2 (2026): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/paedagoria.v17i2.37865

Abstract

This quantitative survey study investigates the perceptions of Electrical Engineering students toward the integration of Artificial Intelligence (AI)-augmented pedagogy in improving English academic writing proficiency. A total of 48 students majoring in electrical engineering at Bangka Belitung State Manufacturing Polytechnic participated in the study. Data were collected through close-ended questionnaires. The data were analyzed using SPSS 25, revealing strong internal consistency (Cronbach’s α = 0.92. The findings revealed that students’ overall attitudes toward the integration of AI were strongly positive (M = 79.69, SD = 11.07), with all three attitudinal dimensions namely cognitive (M = 40.33, SD = 5.18), affective (M = 20.37, SD = 2.97), and behavioral (M = 18.98, SD = 3.34) which also falling within the positive category. These findings reflect the students’ preparedness to engage in technology-supported language learning. Moreover, the study concludes that AI-augmented pedagogy holds significant potential to strengthen students’ academic writing proficiency, particularly in technical and vocational education. Hence, it is recommended that AI tools be integrated into writing instruction while simultaneously fostering the students’ critical digital literacy and sense of ethical awareness.
Co-Authors Manto, Manto Titin Indriati Veniati, Veniati Yahya, Ilham Nur Dimas