Banca de QUALIFICAÇÃO: RENATA CORDEIRO MACIEL

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
STUDENT : RENATA CORDEIRO MACIEL
DATE: 23/05/2025
TIME: 09:00
LOCAL: SALA DE ATOS DA FE 1 - HÍBRIDO - RNP
TITLE:

APPROPRIATIONS OF ARTIFICIAL INTELLIGENCE IN HYBRID WRITTEN TEXTS IN STRICTO SENSU GRADUATE EDUCATION: SILENCES, RESISTANCES, AND CONDITIONS OF ADMISSIBILITY

KEY WORDS:

Generative Artificial Intelligence; Academic and Scientific Integrity; Hybrid Text; Scientific Production; Graduate Studies.

PAGES: 133
BIG AREA: Ciências Humanas
AREA: Educação
SUBÁREA: Fundamentos da Educação
SPECIALTY: Sociologia da Educação
SUMMARY:

This research aims to analyze the reasons behind and the prospective perceptions of master’s and doctoral students, as well as their supervisors, in Stricto Sensu Graduate Programs in Education regarding the appropriation of generative Artificial Intelligence (AI) in the process and product of hybrid texts (human and AI). It is a qualitative, descriptive, and exploratory study, grounded in the methodological assumptions of Content Analysis (Bardin,2011) and data triangulation as proposed by Triviños (1987). Data were collected through semi-structured interviews with 24 participants, including 12 graduate students and 12 faculty supervisors, from two Graduate Programs in Education at Brazilian public institutions. For this qualification stage, preliminary analyses are presented based on 14 interviews, whose data were systematized into analytical categories. The theoretical framework articulates concepts of AI (Santaella, 2023), authorship and appropriation (Chartier, 1998a, b; 2002), hybrid text (Lopes; Forgas; Cerdà-Navarro, 2024), academic integrity (Mainardes, 2023a, b; Tedesco; Ferreira, 2023), along with contributions from critical constructivism of technology (Feenberg, 1999, 2002, 2013a, b, c, d, e; 2022) and techno informational capital (Freitas, 2002, 2004; Bocic; Galassi, 2017). Preliminary findings point to two main positions regarding AI: resistance and conditional admissibility, with ethics, authorship, and originality being the most frequently cited criteria. Graduate students show greater openness to using AI, while supervisors, more cautious, emphasize the urgency of institutional policies that ethethically regulate and guide this practice in graduate education.

COMMITTEE MEMBERS:
Interna - 1151554 - ANDREA CRISTINA VERSUTI
Interno - 1651994 - CARLOS ALBERTO LOPES DE SOUSA
Externa à Instituição - FABIA MAGALI SANTOS VIEIRA - UNIMONTES
Externo à Instituição - JEFFERSON MAINARDES - UEPG