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A Genre Analysis of English Supplementary Workbook for Seventh Grade Indah Nuraeni; Didin Nuruddin Hidayat; Nida Husna; Zakila Mardatila Ersyad; Dinnisa Haura Zhafira Hidayat
Jurnal Onoma: Pendidikan, Bahasa, dan Sastra Vol. 11 No. 2 (2025)
Publisher : Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/onoma.v11i2.5155

Abstract

This study investigates the alignment of a 7th-grade English workbook with the Merdeka curriculum syllabus, focusing on the representation of genre-based text components. Employing content analysis, the research examines the workbook's material against the syllabus requirements and genre analysis theory. The instruments used include the 7th-grade workbook, the Merdeka curriculum syllabus, and genre analysis frameworks. The findings reveal significant gaps in the workbook's content, particularly regarding the text structure of conversational and procedural texts, the minimal presence of language features, and the absence of explicit social functions. These shortcomings indicate that the workbook, in its current state, requires substantial improvement to effectively support English language learning in accordance with the Merdeka curriculum. The analysis concludes that the workbook only covers 40% of the competencies outlined in the syllabus. To ensure its suitability for classroom use, teachers need to develop supplementary materials that address the identified gaps and align with the curriculum's objectives.
Testing the Bilingual–AI Pedagogical Framework (BAIP Model): A Structural Equation Modeling Approach in English for Educational Technology Programs Zakila Mardatila Ersyad; Luthviza Nabila Putri Ersyad; Like Raskova Octaberlina; Andi Asrifan; K. J. Vargheese; Sajed S. Ingilan
IJECA (International Journal of Education and Curriculum Application) Vol 9, No 2 (2026): August
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/ijeca.v9i2.39557

Abstract

In multilingual higher education settings, English for Specific Purposes (ESP) instruction necessitates pedagogical frameworks that can tackle language obstacles and the rising demand for AI-enhanced learning; nonetheless, empirical data on the amalgamation of bilingual pedagogy and AI is still scarce, especially within English for Educational Technology programs. This study investigated the effectiveness of the Bilingual–AI Pedagogical Framework (BAIP Model) in English for Educational Technology programs, focusing on the impact of bilingual scaffolding and AI pedagogical support on student learning outcomes in multilingual higher education settings. The study investigated the effects of multilingual scaffolding and AI-assisted pedagogy on student engagement, academic self-efficacy, and learning performance, both directly and indirectly. A quantitative explanatory cross-sectional design was employed, encompassing 218 undergraduate students from both public and private universities in South Sulawesi, Indonesia. Data were collected using a validated 5-point Likert-scale questionnaire evaluating five latent domains and analysed by PLS-SEM in SmartPLS 4, with initial screening performed in SPSS 29. The results indicated that bilingual scaffolding was a significant predictor of student engagement (β = .42) and learning performance (β = .16), whereas AI pedagogical assistance had the most substantial impact on academic self-efficacy (β = .47) and learning performance (β = .28). Mediation analysis substantiated the notable indirect impacts of student involvement (β = .13) and academic self-efficacy (β = .17), with the model accounting for 61% of the variance in learning performance (R² = .61). This study not only validates these structural correlations but also presents the BAIP Model as a cohesive instructional framework that amalgamates bilingual pedagogy and AI-assisted learning into a singular explanatory model for ESP education. This study theoretically expands the previous literature by illustrating that bilingual scaffolding and AI pedagogical support serve as complimentary processes that collectively improve engagement, self-efficacy, and learning performance in multilingual higher education settings.