Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal English Language Teaching Educational Journal Jurnal Wahana Pendidikan
Binar Winantaka, Binar
Unknown Affiliation
Arts Education Languange, Linguistic, Communication & Media Other

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

Found 2 Documents
Search

 1 
Classroom Evaluation of Deep Learning: Effects on Reading Comprehension among Seventh Graders in Indonesia Herda, Rozanah Katrina; Margana, Margana; Winantaka, Binar; Andika, Jeffri Dian; Syafruddin, Syafruddin; Suni, Fauziyyah Mufida; Subekti, Mutiara Angelina Octavia; Mat Shawal, Bazilah Raihan
Wahana Pendidikan Vol 13, No 1 (2026): Januari
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/jwp.v13i1.22149

Abstract

In Indonesian instructional design, the principles of mindful, meaningful, and joyful learning have guided efforts to create engaging learning experiences in a deep learning nuance. Building on this foundation, deep learning has been increasingly recognized for its potential to strengthen students’ comprehension skills. This study assesses the effectiveness of a deep learning approach in enhancing reading comprehension among seventh-grade students in Indonesia and examines students’ perspectives on learning. Employing a quasi-experimental one-group pretest–posttest design, the study was conducted at a state junior high school with 32 students and included quantitative data from pretests and posttests, followed by qualitative data from semi-structured interviews with students and teachers. The quantitative results showed a significant improvement in reading comprehension, indicating that the deep learning approach effectively enhanced students’ reading performance. Qualitative findings supported this outcome, revealing increased student confidence and participation. These findings suggest that structured deep learning activities, combined with a supportive environment, foster greater student engagement and reading comprehension.
Automated writing evaluation tools in Business English Writing: An experimental study among Indonesian undergraduates Winantaka, Binar; Efendi, Anwar; Putro, Nur Hidayanto Pancoro Setyo
English Language Teaching Educational Journal Vol. 9 No. 1 (2026)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Business English writing competence is increasingly critical for Indonesian university graduates navigating global professional environments, yet many students continue to experience persistent difficulties with grammar, coherence, and professional register. Automated Writing Evaluation (AWE) tools such as Grammarly and Grammark provide immediate, data-driven feedback that may support writing development beyond surface-level error correction (Barrot, 2021; Calma et al., 2022). This quasi-experimental study examined whether AWE integration in a Business English writing course improved Indonesian undergraduates' perceived usefulness, ease of use, motivation, self-regulated learning (SRL), and writing self-efficacy (WSE), relative to conventional instructor feedback. Sixty undergraduate students were randomly assigned to an AWE group (n = 30) or a control group (n = 30). A validated 38-item Likert questionnaire and open-ended reflective prompts were administered post-intervention. Three key findings emerged: (1) AWE significantly enhanced perceived usefulness (d = 2.92) and ease of use (d = 2.74); (2) motivation, self-regulated learning, and writing self-efficacy increased substantially in the AWE group; and (3) students unanimously recommended a hybrid AWE–teacher feedback model to address AWE's limitations in higher-order writing development (Thi & Nikolov, 2022). These findings suggest that AWE integration holds considerable promise for Indonesian EFL Business English instruction, particularly when systematically complemented by expert human feedback.
Co-Authors Andika, Jeffri Dian Anwar Efendi Margana Margana Mat Shawal, Bazilah Raihan Nur Hidayanto Pancoro Setyo Putro Rozanah Katrina Herda, Rozanah Katrina Subekti, Mutiara Angelina Octavia Suni, Fauziyyah Mufida Syafruddin Syafruddin