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All Journal Parole: Journal of Linguistics and Education Al Lughawiyaat
Irfiana, Khusna
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Education Languange, Linguistic, Communication & Media

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English Graduate Students’ Motivation in the Emergency Remote Learning amidst Pandemic in a Public University in Indonesia Irfiana, Khusna
PAROLE: Journal of Linguistics and Education Vol 13, No 1 (2023): Volume 13 Number 1 April 2023
Publisher : Master Program in Linguistics, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/parole.v13i1.%p

Abstract

Keeping students motivated is the key to adding to the quality of the process and learning outcomes. However, due to the coronavirus outbreak disruption, students have to move to temporary remote instruction. Moving through a changing time has significantly influenced the motivation of students. The research investigated the students' motivation towards remote learning and the factors that influenced their motivation. The investigation method was qualitative descriptive using questionnaires involving 38 English graduate students at one of the public universities in Indonesia. Interviews and document analysis were carried out to further explore the participants' answers to the questionnaire. The findings showed that regardless of the pandemic disruption, the student's learning motivation was relatively high, as indicated by students' willingness to learn, students' beliefs about learning outcomes, students' participation in online learning, and student's performance on course assignments. Various factors, such as the environment, the school system, and social life, have also influenced their education. The lack of interaction between teacher and student has affected their understanding during the learning process. Hence, the study recommends institutions' involvement in a cooperative learning program that can assist students in need of additional support and reinforce their English learning motivation during emergency remote learning.
AI Use Through Wallace and Wray's Critical Reading Framework: Evidence from Pre-Service English Teachers Miftachudien, Satria; Anggraeni, Grace; Febry, Agung Is Hardiyana; Bahrudin, Imam; Irfiana, Khusna
AL LUGHAWIYAAT Vol. 7 No. 3 (2026): October
Publisher : UNIVERSITAS ISLAM NEGERI KENDARI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31332/alg.v7i3.15532

Abstract

Artificial intelligence (AI) is becoming increasingly common in academic reading, but its role in supporting students’ critical reading skills remains unclear. This study explored the critical reading performance of 30 pre-service English teachers taking a Critical Academic Reading course at UIN Sunan Gunung Djati Bandung. Using a qualitative exploratory design, the study applied Wallace and Wray’s Elements of Critical Reading to five reading tasks completed with AI available. The tasks focused on identifying the author’s ideology and purpose, recognizing language bias, understanding explicit and implicit meanings, and developing balanced conclusions. Students’ responses were analyzed using the adapted version of Winston-Salem State University’s critical reading criteria and grouped into four performance categories. The findings showed that many students struggled to identify ideological assumptions, evaluate bias, interpret implied meanings, and develop evidence-based, balanced conclusions, even with AI assistance available. These results show that access to AI does not necessarily mean students can use it critically. The study extends Wallace and Wray’s framework to AI-assisted reading and highlights the need to combine AI literacy with critical reading instruction. Students need to learn how to evaluate AI-generated responses, check information against textual evidence, and form their own judgments. These principles also connect with Iqra’, which emphasizes inquiry, reflection, and responsible learning. However, because the study involved only 30 students from one institution and did not include a comparison group or pretest–posttest assessment, the findings describe students’ performance rather than changes caused by AI.
Co-Authors Anggraeni, Grace Bahrudin, Imam Febry, Agung Is Hardiyana Miftachudien, Satria