Enterprise AI Analysis

Theoretical Framework

Academic writing is fundamental to university education, requiring clarity, logical coherence, and academic rigor. Students frequently struggle with grammar, coherence, vocabulary, and critical thinking. AI offers a strategy to improve self-learning and academic writing development.

Constructivist Learning Theory

This theory posits that learners actively construct knowledge through interaction with their environment. In academic writing, it emphasizes authentic writing activities and revision with feedback. Vygotsky's social constructivism adds that AI can act as scaffolding, providing timely feedback and supporting learning in the Zone of Proximal Development (ZPD), fostering autonomy and independence.

Cognitive Load Theory (CLT)

Developed by Sweller, CLT focuses on managing working memory limitations to optimize learning. It distinguishes between intrinsic, extraneous, and germane cognitive loads. AI tools, such as chatbots and large language models, can act as scaffolding mechanisms to reduce cognitive load by providing immediate feedback and aiding task completion, freeing up working memory for relevant processing. This promotes efficient understanding and productive learning.

Pedagogical Basis: Process Writing Approach

The process writing approach, based on cognitive and constructivist theories, views writing as an iterative meaning-making process including pre-writing, drafting, revising, editing, and publishing. It reinforces language skills, critical thinking, and self-regulation. Integrating AI into this approach amplifies its benefits by providing real-time feedback for brainstorming, idea organization, grammar correction, and editing. This creates a balanced pedagogical framework that merges established strategies with innovative technologies for academic writing development.

Legal Basis

This research is supported by international guidelines and national regulations ensuring ethical academic practices. UNESCO (2022) emphasizes that AI technologies should empower students and teachers, enhancing their experience while preserving relational and social aspects of education. Ecuador's Constitution (2008) grants citizens the right to scientific progress benefits, aligning with AI integration to provide advanced learning resources and promote equitable academic outcomes. MINEDUC (2024) highlights AI's potential for personalized learning, identifying reinforcement areas, and suggesting support activities, especially valuable in academic writing for structuring ideas and managing cognitive load.

Methodological Framework

This research explores how AI tools influence students' writing skills in grammar, structure, coherence, and confidence. It adopts an applied qualitative and phenomenological approach to uncover insights into the effectiveness and challenges of integrating AI tools into academic writing, facilitating a deeper understanding of students' lived experiences and perceptions.

Research Method: Qualitative & Phenomenological Studies

The study uses a qualitative research method, focusing on participants' perspectives and lived experiences to examine complex phenomena and understand how individuals interpret meaning in their academic context. It is categorized as a phenomenological study, aiming to capture the essence of students' interaction with AI tools, identifying opportunities and challenges in academic writing skill development.

Technique & Instrument: One-on-one Interviews & Semi-Structured Questionnaire

Data was collected through one-on-one interviews using a semi-structured questionnaire. This approach allows for detailed exploration of unique experiences, open expression of thoughts without peer influence, and uncovering individual nuances and specific challenges. The questionnaire includes eight open-ended questions covering AI's advantages, disadvantages, impact on confidence and independence, effect on writing abilities, and responsible use recommendations.

Population Sample

The research focused on five 7th Semester students from the Pedagogy of National and Foreign Languages program at Universidad Estatal Península de Santa Elena. This purposive sample was chosen due to their active use of AI tools in academic writing tasks, including planning, drafting, and refining assignments, and their close connection to language learning and academic writing.

Analysis of Findings

The analysis revealed four main categories from students' responses: AI as support for academic writing, AI as a source of feedback and correction, AI to enhance writing skills and autonomy, and AI as a tool with challenges and strategies for responsible use. These categories frame the understanding of how AI supports, complements, or limits the writing process. Students reported that AI helps overcome "writer's block," organize ideas, and receive initial recommendations, while still emphasizing that AI's role should be complementary. Immediate feedback on grammar, sentence structure, and vocabulary was highly valued, improving confidence and autonomy. However, concerns about dependency, plagiarism, and inaccuracies were also highlighted, underscoring the need for ethical and responsible use.

Key Findings: AI in Academic Writing

Category	Student Perceptions (Answers)	Supporting Literature (Authors)
AI as a support for academic writing	AI is perceived as a support or guidance tool that facilitates the writing process, helps overcome "writer's block," obtain examples of structure, organize ideas, and receive initial recommendations. However, its role should be complementary, not replacing personal effort.	This view coincides with Lin (2024), who highlights human-AI co-writing as linguistic and structural support while maintaining students' responsibility for critical thinking and argumentation.
AI as a source of feedback and correction	Feedback from AI is very helpful for grammatical correction, sentence structure, and vocabulary improvement. The immediacy of corrections and explanations is highly valued.	This perception coincides with Infante Vera et al. (2024), who highlight that AI-based tools offer real-time feedback through natural language processing, providing an interactive and efficient learning experience superior to traditional methods.
AI to enhance writing skills and autonomy	AI tools strengthen grammar, coherence, and organization. Students are aware that AI should promote autonomy rather than dependence.	This is supported by Jaramillo et al. (2025), who demonstrate significant improvements in grammatical accuracy, textual coherence, and structure through automated real-time feedback and collaborative workshops, leading to increased student confidence and autonomy.
AI as a tool with challenges and strategies for responsible use	AI is practical for saving time, organizing tasks, and accessing resources, complementing traditional methods. However, challenges include plagiarism, dependency, and the need for regulation.	This relates to Al-Zubaidi et al. (2024), who identify benefits like grammatical correction and time management but warn of risks such as plagiarism and excessive dependence, highlighting the need for clear ethical guidelines.

Conclusions

Students perceive AI as a valuable support for academic writing, helping to ease writing challenges, arrange thoughts, and structure texts more efficiently, thereby increasing confidence. AI serves as an instant resource for feedback on grammar, vocabulary, and coherence, with explanations enhancing motivation and practice. While AI significantly supports academic writing skill development, participants recognized the potential risk of dependency, emphasizing its role as a complement to promote autonomy, not a substitute for independent learning. Major shortcomings include outdated content, inaccuracy, over-reliance, and plagiarism, highlighting the need for ethical management through awareness and reflective use.

Recommendations

1. University students should use AI tools as complementary aids, not substitutes. Drafting independently before consulting AI helps identify weaknesses and strengthens critical thinking.
2. Data from AI tools must be checked for accuracy, paraphrased, and properly cited to promote responsible use and academic integrity, discouraging direct copying.
3. Instructors must teach responsible AI use, including ethics of plagiarism, content evaluation, and originality, through well-understood guidelines and weighing pros and cons.
4. Training sessions and workshops should be provided to teach practical strategies for AI use, reducing academic over-reliance and helping universities harness AI's educational value while mitigating risks.

In conclusion, this research adds to English language teaching scholarship by providing deeper understanding of how university students use AI for academic writing. AI assists in developing grammar, structure, and argumentation, fostering greater autonomy. The study underscores the necessity of responsible AI use, ensuring its merits do not outweigh its risks.