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All Journal Foreign Language Instruction Probe ELT Echo: The Journal of English Language Teaching in Foreign Language Context
Wakhid Nashruddin
UIN Siber Syekh Nurjati Cirebon
Education Languange, Linguistic, Communication & Media

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Mapping Digital Assessment Platforms in EFL Classrooms: A Qualitative Case Study at an Islamic Junior High School Edy Waloyo; Nida’ul Hasanah; Wakhid Nashruddin
Foreign Language Instruction Probe Vol. 4 No. 2 (2025): Principle in ELT
Publisher : STIT Buntet Pesantren Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54213/flip.v4i2.1012

Abstract

The growing integration of digital technology into English language education has encouraged teachers to adopt various digital platforms for classroom assessment. However, previous studies have predominantly examined the effectiveness of individual applications, with limited attention to how teachers employ multiple digital assessment platforms within their professional assessment practices. This study aimed to identify the digital assessment platforms employed by English teachers in an Islamic junior high school. A qualitative case study was conducted at an Islamic junior high school in Cirebon, Indonesia, involving two English teachers selected through purposive sampling. Data were collected through semi-structured interviews, classroom observations, and document analysis and analyzed using Braun and Clarke's thematic analysis. The findings identified three complementary categories of digital assessment platforms: institutionalized assessment platforms, gamified assessment platforms, and flexible web-based assessment platforms. These findings suggest that teachers employed different digital assessment platforms to fulfill complementary roles within classroom assessment rather than relying on a single application. The study contributes a thematic categorization of digital assessment platforms that broadens the understanding of teachers' digital assessment practices in EFL classrooms. Future research should examine these platform categories across diverse educational contexts and investigate how institutional policies and pedagogical considerations influence teachers' selection of digital assessment platforms.
DESIGNING SEQUENTIAL SPEAKING SYLLABI FOR HIGHER EDUCATION THROUGH AI-ENHANCED PBL Listiana Ikawati; Wakhid Nashruddin
ELT Echo : The Journal of English Language Teaching in Foreign Language Context Vol. 10 No. 2 (2025): DECEMBER 2025
Publisher : UIN Siber Syekh Nurjati Cirebon

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Abstract

Indonesia's persistently low English Proficiency Index (EPI) is caused by limited literacy and traditional pedagogies, resulting in weak speaking competency. This study aimed to create sequential speaking course syllabi incorporating Artificial Intelligence (AI) into Project-Based Learning (PBL) to enable enhanced speaking skills in higher education. Employing a Research and Development (R&D) design streamlined from Borg and Gall into three phases consisting of preliminary study, development, and validation. The study collected data through focus group discussions, interview, document analysis, and expert verification. Three syllabi were constructed on Speaking for Daily Purposes, Speaking at Workplace, and Speaking for Academic Purposes that were aligned with CEFR levels B1, B2, and C1. Validation employed two experts: an AI expert and a PBL-speaking expert. Scores indicate high feasibility, 90, 91, and 89 in AI expert scores, and 79.7 in PBL-speaking expert scores across syllabi, which are in the "Very Good" category. Revisions were done to order material, incorporate projects, and coordinate assignments to sufficiently address speaking skills. The originality lies in incorporating CEFR-based progression and AI tools in PBL to create oral competence as well as digital literacy and autonomous learning. These syllabi present a model for incorporating technology-supported, student-centered approaches into language teaching. Future research should examine effectiveness through classroom trials and broader implementation to gauge learning impacts and scalability.
Co-Authors Edy Waloyo Listiana Ikawati Nida’ul Hasanah