SAKAGURU: Journal of Pedagogy and Creative Teacher

Artificial Intelligence: Implications for English Language Teaching

2025-10-09T23:27:03+07:00

Artificial intelligence (AI) has made significant changes in several fields. It covers many applications and is still a rather multidisciplinary and emerging field. English Language Teaching (ELT), which is a branch of applied linguistics, is one of those fields that has received a huge impact from advanced AI empowerment technologies and applications, such as chatbots and tutoring systems. This study, therefore, examines the impact of AI on ELT, and the various ways that AI influences ELT. It explores the new future roles of teachers and learners in English classrooms, which will be AI-driven. The study is qualitative in nature, which explores emerging trends and themes in AI and ELT and examines potential developments. Through qualitative analysis of recent scholarly publications, the research identified key and emerging techniques for integrating AI in ELT classrooms. It employed thematic analysis to examine the data collected, focusing on experts' perspectives regarding future opportunities, trends, and prospects in AI and ELT. AI technologies and applications provide innovative techniques that cater to each 21^st century learner’s needs, autonomy, and engagement with different proficiency levels, and give effective feedback to English teachers. They also foster language acquisition, can help identify the strengths and weaknesses of learners, and offer English teachers opportunities to customize lessons and enhance their teaching strategies. All these make the English learning process operative, more appealing, and tailored. This paper, therefore, provides valuable implications and insights for practitioners, learners, applied linguists, and higher educational institutions in developing relevant teaching materials and training programs for teachers.

The Future of Learning: Pedagogical Paradigms in the Age of Artificial Intelligence through the Advent of ChatGPT as an Innovative Digital Tool in the Era of Technology

2025-10-09T23:27:06+07:00

The rapid emergence of Generative Artificial Intelligence (AI) tools, particularly ChatGPT, has reshaped contemporary education by addressing the growing demands of the 21st century, where traditional teaching methodologies are no longer sufficient to meet learners’ evolving needs. This study aims to examine the pedagogical and ethical implications of integrating ChatGPT into English as a Second Language (ESL) instruction, situating the analysis within UNESCO’s Sustainable Development Goal 4 on quality education. Employing a qualitative, literature-based design, this paper synthesizes recent empirical and conceptual research published between 2018 and 2025 to evaluate both the opportunities and limitations of AI-enhanced pedagogy. The findings reveal that ChatGPT supports language acquisition by enhancing interaction, scaffolding productive and receptive skills, and fostering learner autonomy and creativity. However, issues related to ethics, digital equity, and responsible use remain significant challenges. The study concludes that successful integration of ChatGPT requires evidence-based pedagogical frameworks and unified AI policies to ensure ethical, inclusive, and sustainable educational transformation.

Mapping the Landscape of AI-Enhanced Collaborative Learning: Evolution and Constraints

2025-10-09T23:27:07+07:00

This study maps the scientific evolution of AI-enhanced collaborative learning over the past decade (2014–2024) through a comprehensive bibliometric analysis using the Bibliometrix R-package. A total of 660 documents retrieved from the Scopus database were analyzed to identify publication trends, key authors, thematic clusters, and research collaborations. Results indicate exponential growth since 2021, coinciding with the democratization of generative and machine-learning technologies. The field is marked by strong interdisciplinarity—bridging computer science, education, and engineering—and by geographic concentration in the United States and China. Thematic mapping reveals three consolidated lines of inquiry: technological innovation, pedagogical applications, and ethical-social challenges, with a clear transition toward advanced topics such as federated and adversarial learning. Despite this progress, regional inequality and limited empirical validation persist. The study contributes a structured overview of the field, highlighting both conceptual consolidation and critical gaps, and proposes future directions for developing inclusive, context-aware, and ethically responsible frameworks for AI-mediated collaborative education.

Implementation and Constraints of Diagnostic Assessment in the Independent Curriculum Towards Deep Learning-Based Biology Learning in High Schools

2025-10-09T23:27:44+07:00

The implementation of diagnostic assessments in the Independent Curriculum is a crucial step in mapping students' initial abilities and designing appropriate learning strategies. This study aims to identify obstacles to the implementation of diagnostic assessments in deep learning-based biology learning in public senior high schools in Bandar Lampung City, encompassing the planning, implementation, and follow-up stages. The study used a descriptive qualitative approach with a purposive sampling technique. The sample consisted of three public senior high schools, four biology teachers, and 69 tenth-grade students studying Biodiversity. Data were obtained through interviews, observations, questionnaires, and documentation. Data were analyzed through data reduction, data presentation, and conclusion drawing. The results showed that the implementation of diagnostic assessments was not optimal. Only two schools had implemented cognitive and non-cognitive diagnostic assessments, while one school had not implemented them at all. The main obstacles lay in limited school facilities and the low level of socialization regarding the Independent Curriculum, particularly the implementation of diagnostic assessments in innovative, deep learning-oriented biology learning. However, limited understanding and institutional support remained a significant obstacle. This study recommends improving teacher training, providing supporting facilities, and implementing more systematic assessment follow-up policies