Document Type
Paper presentation
School Name
De La Salle Santiago Zobel Br. Rafael Donato FSC Night High School
School Code
NA
Track/Strand
Elevating Excellence in Education
Abstract / Executive Summary
The 2020 global pandemic made academics realize that online learning is a viable educational delivery mode. However, along with the persistence of schools to craft necessary learning frameworks comes the age-old issue of academic dishonesty. While technology has been seen to be pivotal in instruction, the same has also been used to commit academic misconduct, especially during distance learning. Following Dinneen (2021) and Park (2004), the study explored the level of familiarity of selected students of the different taxonomies of academic dishonesty. Then, through focus group discussions with the students and content subject teachers, the study was able to get insights regarding the impact of artificial intelligence and digitals tools to the authenticity of student outputs, independent learning, and accuracy of performance assessment and evaluation. The results showed that the students were aware of the taxonomies “usage of one's work with or without consent,” “back translation,” and “commission.” However, they were not aware that “cross-language plagiarism” and “article spinning” are types of academic dishonesty. Moreover, the student-respondents believe that as long as they are the “brains” behind their outputs, their work is still authentic, and they are independent learners. The students’ integrity, manifested in their academic undertakings and honed by transformative education, is associated with global citizenship. On the other hand, teacher-participants emphasized the need to redefine academic integrity following the influx of AI in the classroom. Finally, the study suggested a few instructional modifications which included the "Authenticity Report" apart from the "References section" for every submission.
Keywords:
artificial intelligence, authenticity, digital tools, written outputs, academic dishonesty
Academics intensified (A.I.): Safeguarding the authenticity of student outputs through streamlined pedagogical modifications
The 2020 global pandemic made academics realize that online learning is a viable educational delivery mode. However, along with the persistence of schools to craft necessary learning frameworks comes the age-old issue of academic dishonesty. While technology has been seen to be pivotal in instruction, the same has also been used to commit academic misconduct, especially during distance learning. Following Dinneen (2021) and Park (2004), the study explored the level of familiarity of selected students of the different taxonomies of academic dishonesty. Then, through focus group discussions with the students and content subject teachers, the study was able to get insights regarding the impact of artificial intelligence and digitals tools to the authenticity of student outputs, independent learning, and accuracy of performance assessment and evaluation. The results showed that the students were aware of the taxonomies “usage of one's work with or without consent,” “back translation,” and “commission.” However, they were not aware that “cross-language plagiarism” and “article spinning” are types of academic dishonesty. Moreover, the student-respondents believe that as long as they are the “brains” behind their outputs, their work is still authentic, and they are independent learners. The students’ integrity, manifested in their academic undertakings and honed by transformative education, is associated with global citizenship. On the other hand, teacher-participants emphasized the need to redefine academic integrity following the influx of AI in the classroom. Finally, the study suggested a few instructional modifications which included the "Authenticity Report" apart from the "References section" for every submission.
