Skip to content
#generative ai Open access

Lived Experiences of Senior High School English Teachers in Teaching Writing in the Advent of Generative AI Applications in Senior High Schools in San Mateo, Rizal

Oct 2026 · Aloysian Interdisciplinary Journal of Social Sciences, Education, and Allied Fields
Artificial Intelligence in Education

Abstract

The study uncovered the dilemma of English Senior High School Teachers in teaching writing with the prevalence of using Generative AI. The study employed qualitative phenomenological research design to unravel the lived-experiences of the English teachers in Senior High Schools in San Mateo, Rizal. There were 8 participants who were interviewed through an in-depth interview to convey their personal perspectives on teaching writing in the advent of Generative AI. The emerging themes from the study are as follows: (1) Recognizing AI-Influenced through Familiarity and Inconsistency; (2) Navigating Uncertainty in Establishing Authenticity; (3) AI-Assistance and the Preservation of Student Writing; (4) Reconfiguring Writing Pedagogy and Assessment to Preserve Student Thinking; (5) Developing Teacher Preparedness through Experiences, Self-Learning and Professional Development; and (6) Reconstructing Academic Integrity through Ownership, Boundaries, and Transparency. The study revealed that the roles of the English teachers in teaching writing is diversified with the changing landscape of education and the integration of technology in teaching. English Senior High School Teachers reconciled the use of AI in teaching writing and look at AI tools that support learning. The participants in this study understood that the goal of technological advancements in schools in sustaining learning and successful integration of AI tools necessitates simultaneous advancement of technical skills, pedagogical flexibility, and the reconciliation of ethical judgement, while maintaining authenticity and academic integrity. The implications of this study support a context-driven and moderated use of AI in Senior High School Writing. Specific type of Generative AI used for writing, AI assisted writing, assessments using AI and integrity in AI-generated writing may be pursued in subsequent researches.

View source

Similar papers

#artificial intelligence Conference Open access Apr 2020

ECCOLA - a Method for Implementing Ethically Aligned AI Systems

The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.

Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson · 64 citations · ⚡6
#computer vision Review Apr 2024

AI-powered Code Review with LLMs: Early Results

The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.

Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al. · 62 citations · ⚡3
#computer vision Open access Mar 2024

LLM-based agents for automating the enhancement of user story quality: An early report

The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.

Zheying Zhang, M. Rayhan, Tomas Herda et al. · 48 citations · ⚡4
#computer vision Review Mar 2024

System for systematic literature review using multiple AI agents: Concept and an empirical evaluation

This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.

Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al. · 44 citations · ⚡2
#computer vision Feb 2024

Can Large Language Models Serve as Data Analysts? A Multi-Agent Assisted Approach for Qualitative Data Analysis

The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.

Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al. · 41 citations

Related blog posts

MIT News · Artificial Intelligence Oct 15, 2026

AI model decodes the language cells use to communicate

A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.

GPT-Lab Oct 14, 2026

Building trustworthy AI: The role of AI harnesses, intent contracts and evals

AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post Building trustworthy AI: The role of AI harnesses, intent contracts and evals appeared first on GPT-Lab.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.