Academic Writing Process in the Age of Artificial Intelligence: A Correlational Analysis of Student Practices and Perceptions at the Fundación Universitaria Antonio de Arévalo (Unitecnar) in Cartagena
Abstract
The advent of Generative Artificial Intelligence (GAI) has disrupted the dynamics of text
production in higher education, radically transforming traditional academic literacy
processes. This applied research article analyzes the correlations between the variables of
knowledge, use, motivation, commitment, and ethical perception of Artificial Intelligence
(AI) tools in the writing process of undergraduate students at the Antonio de Arévalo
University Foundation (Unitecnar) in Cartagena de Indias. A cross-sectional, correlational,
quantitative study was conducted with a representative sample of 580 students from the
faculties of Economics, Social Sciences, and Design and Engineering. For data analysis,
seven fundamental variables were operationalized within an extended explanatory model of
the Technology Acceptance Model (TAM): Knowledge of AI (KAI), Frequency of Use
(FAI), Perceived Impact on Writing (PIW), Collaborative Perspective (COL), Academic
Motivation (MOT), Cognitive Engagement and Autonomy (ENG), and Ethical Perception
and Plagiarism (ETH).
The statistical results calculated using Spearman's rank correlation coefficient (ρ)
demonstrate a strong positive association between cognitive engagement (ENG) and the
perception of a favorable impact on writing quality (PIW) (ρ = 0.65), as well as a very close
link between this engagement and intrinsic motivation (MOT) (ρ = 0.71). However, a critical
ethical dissonance emerged: the frequency of use of these technologies (FAI) did not
correlate significantly with ethical and plagiarism concerns (ETH) (ρ=0.08), revealing that
pragmatic academic demands act as a driver of AI use independently of students' moral
considerations. It is concluded that there is an urgent need to move from restrictive policies
toward institutional frameworks for digital literacy and process-based writing assessment.
References
Inteligencia Artificial para la escritura académica en investigación. Ciencia Latina
Revista Científica Multidisciplinar, 7(4), 4604-4618. 12
● Flower, L., & Hayes, J. R. (1981). A Cognitive Process Theory of Writing. College
Composition and Communication, 32(4), 365-387. 2
● Garay Angarita, M. L., Pinzón, M. I., & Del Campo Machado, R. M. (2025). El
Uso de la Inteligencia Artificial en el Desarrollo de Habilidades Escriturales en
inglés en Estudiantes Universitarios. Ciencia y Reflexión, 4(4), 1137-1165. 20
● Liang, J., Khan, S., & Thao, T. (2024). Exploring EFL Student Acceptance of
Grammarly: An Extended Technology Acceptance Model (TAM) Perspective. Journal
of Educational Technology Systems, 52(3), 205-228. 18
● Neira Martínez, A., & Ferreira Cabrera, A. (2011). Escritura académica: un modelo
metodológico
efectivo basado en tareas y enfoque cooperativo. Literatura y Lingüística, (24), 143
159. 2
● Vera, F. (2023). Integración del ChatGPT en la Educación Superior: Una
aproximación empírica desde las prácticas de lectura y escritura en la adquisición
de lenguas meta. Scientia et Technica, 28(2), 85-96. 5
● Viñas, R., Secul Giusti, C., Viñas, M., & Cammertoni, M. (2023, septiembre). La
escritura académica y el rol de la Inteligencia Artificial (IA). Primer Congreso
Internacional WEDUCI de Wikimedia, Educación y Culturas Digitales.
Universidad Nacional de La Plata. 1
