Mayeli Jaime-deAza

Prof. Mayeli Jaime-deAza


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
14 January 2026 in Trends in Higher Education
Verified
Journal Article
Open access
PDF file
PGPAZ PEÑA GARCIA
PAZ PEÑA GARCIA
MJMayeli Jaime-deAza
Mayeli Jaime-deAza
RFRoberto Feltrero
Roberto Feltrero
Artificial Intelligence (AI) systems typically inherit biases from their training data, leading to discriminatory outcomes that undermine equity and inclusion. This issue is particularly significant when popular Generative AI (GAI) applications are used in educational contexts. To respond to this challenge, the study evaluates the effectiveness of dialogic reflection-based training for educators in identifying and mitigating biases in AI. Furthermore, it considers how these sessions contribute to the advancement of algorithmic justice and inclusive practices. A key component of the proposed training methodology involved equipping educators with the skills to design inclusive prompts—specific instructions or queries aimed at minimizing bias in AI outputs. This approach not only raised awareness of algorithmic inequities but also provided practical strategies for educators to actively contribute to fairer AI systems. A qualitative analysis of the course’s Moodle forum interactions was conducted with 102 university professors and graduate students from diverse regions of the Dominican Republic. Participants engaged in interactive activities, debates, and practical exercises addressing AI bias, algorithmic justice, and ethical implications. Responses were analyzed using Atlas.ti across five categories: participation quality, bias identification strategies, ethical responsibility, social impact, and equity proposals. The training methodology emphasized collaborative learning through real case analyses and the co-construction of knowledge. The study contributes a hypothesis-driven model linking dialogic reflection, bias awareness, and inclusive teaching, offering a replicable framework for ethical AI integration in higher education.

1 July 2021 in Ciencia, Ambiente y Clima
Verified
Journal Article
Open access
PDF file
MJMayeli Jaime-deAza
Mayeli Jaime-deAza
JRJosé Guillermo De la Rosa
José Guillermo De la Rosa
HBHéctor Julio Santos Báez
Héctor Julio Santos Báez
Se reporta por primera vez la especie Trametes hirsuta sobre tronco de Hura crepitans L., en el Refugio de Vida Silvestre Laguna Mallén. T. hirsuta es un hongo fitopatógeno del orden de los polyporales que causa pudrición blanca en madera. Su carpóforo es de color blanquecino a pardoamarillento, con un margen de tonalidad marrón. Son productores de lacasas y degradadores de lignina. Se asientan sobre madera de angiospermas.