Professors’ Perceptions on the Use of ChatGPT in Higher Education: a case study in Brazil

The rapid adoption of generative artificial intelligence (GenAI) technologies in higher education has raised concerns about academic integrity, assessment practices and student learning. Banning or blocking GenAI tools has proven ineffective, and punitive approaches ignore the potential benefits of these technologies. As a result, assessment reform has become a pressing topic in the GenAI era. This paper presents the findings of a pilot study conducted at British University Vietnam exploring the implementation of the Artificial Intelligence Assessment Scale (AIAS), a flexible framework for incorporating GenAI into educational assessments. The AIAS consists of five levels, ranging from “no AI” to “full AI,” enabling educators to design assessments that focus on areas requiring human input and critical thinking. The pilot study results indicate a significant reduction in academic misconduct cases related to GenAI and enhanced student engagement with GenAI technology. The AIAS facilitated a shift in pedagogical practices, with faculty members incorporating GenAI tools into their modules and students producing innovative multimodal submissions. The findings suggest that the AIAS can support the effective integration of GenAI in higher education, promoting academic integrity while leveraging technology’s potential to enhance learning experiences. Implications for practice or policy: Higher education institutions should adopt flexible frameworks like the AIAS to guide ethical integration of GenAI into assessment practices. Educators should design assessments that leverage GenAI capabilities, while supporting critical thinking and human input. Institutional policies related to GenAI should be developed in consultation with stakeholders and regularly updated to keep pace with technological advancements. Policymakers should prioritise research funding into the impacts of GenAI on higher education to inform evidence-based practices.

This paper presents a systematic review of the role of prompt engineering during interactions with Generative Artificial Intelligence (GenAI) in Higher Education (HE) to discover potential methods of improving educational outcomes. Drawing on a comprehensive search of academic databases and relevant literature, key trends, including multiple framework designs, are presented and explored to review the role, relevance, and applicability of prompt engineering to purposefully improve GenAI-generated responses in higher education contexts. Multiple experiments using a variety of prompt engineering frameworks are compared, contrasted and discussed. Analysis reveals that well-designed prompts have the potential to transform interactions with GenAI in higher education teaching and learning. Further findings show it is important to develop and teach pragmatic skills in AI interaction, including meaningful prompt engineering, which is best managed through a well-designed framework for creating and evaluating GenAI applications that are aligned with pre-determined contextual educational goals. The paper outlines some of the key concepts and frameworks that educators should be aware of when incorporating GenAI and prompt engineering into their teaching practices, and when teaching students the necessary skills for successful GenAI interaction.

Title of Document: FACTORS AFFECTING THE ACADEMIC ACHIEVEMENT AND PERSISTENCE OF QUOTA STUDENTS IN STEM: A CASE STUDY OF A PUBLIC UNIVERSITY IN BRAZIL Porsha Yasmin Childs, Doctor of Philosophy, 2015 Directed By: Dr. Nelly Stromquist, International Education Policy, Department of Counseling, Higher Education, and Special Education In order to maintain competitiveness in the global economy nations around the world are heavily investing in access to higher education and more specifically the production of skilled workers in science, technology, engineering, and math (STEM). Whereas upper social-class majority males have traditionally dominated this field, the expansion of university enrollments as well as the presence of rapidly growing minority populations signals a shift in which a larger number of minorities and women will add to the STEM talent pool. To date, much of the research on underrepresented minorities in STEM has focused on women and underrepresented racial and ethnic minorities in universities in the U.S. (Espinoza & Cole, 2008; Museus et al., 2011; St. John & Musoba, 2011). Few studies have focused on the persistence and academic achievement of underrepresented minorities in countries and institutions outside of the Unites States and none have specifically targeted minority students who are beneficiaries of affirmative action policies. The current study seeks to explore factors that affect the academic performance and persistence of quota students majoring in STEM fields in a public university in Brazil. The major research questions guiding this study were: (1) In what ways do institutional factors affect quota student persistence and academic performance in STEM fields? (2) To what extent does campus climate affect the academic performance of quota students in STEM fields? (3)What barriers (major academic, social, and financial concerns) do quota students in STEM fields face after admission and how do student and faculty perceptions of these barriers differ? (4) What institutional services are available to support quota STEM students and which of these services do STEM students use most frequently? Using qualitative methods and an ethnographic case study design, semi-structured interviews were conducted with ten undergraduate quota students, two graduate students, and six university personnel. In addition, the researcher observed students on campus, both in and out of class. Additional observations were made of location students frequented such as the residence hall, library, campus restaurants, and the physics, chemistry, and engineering buildings. Findings revealed four broad themes: pre-college experiences, college experiences, college outcomes, and barriers to graduation and institutional responses. Participants indicated that their pre-college academic experiences had the largest effect on their academic achievement and persistence. Quota students in STEM disciplines routinely reported having failed their core math and science courses during the first year and experiencing difficulty with others as they matriculate. This was largely attributed to the fact that they entered with a lack of a strong academic base. Additional barriers students faced were lack of finances, and a lack of family support and cultural capital. While the university has implemented various financial supports to address quota students’ needs, they lack structured academic supports such as bridge programs, supplemental instruction, and tutoring. FACTORS AFFECTING THE ACADEMIC ACHIEVEMENT AND PERSISTENCE OF QUOTA STUDENTS IN STEM: A CASE STUDY OF A PUBLIC UNIVERSITY IN BRAZIL By Porsha Y. Childs Dissertation submitted to the Faculty of the Graduate School of the University of Maryland, College Park, in partial fulfilment of the requirements for the degree of Doctor of Philosophy 2015 Advisory Committee: Dr. Nelly Stromquist, Professor and Dissertation Chair Dr. Jing Lin, Professor Dr. Alberto Cabrera, Professor Dr. William Strein, Professor Dr. Jennifer Turner, Associate Professor © Copyright by Porsha Yasmin Childs 2015

As artificial intelligence (AI) transforms workplaces, understanding how future graduates engage with AI technologies is crucial for enhancing employability. This study investigates higher education students’ familiarity with and perceptions of generative artificial intelligence (GenAI) in their learning. Using the Technology Acceptance Model (TAM) and incorporating personal innovativeness in information technology, we examined factors influencing students’ adoption of GenAI. An online survey was conducted between April 30 and May 11, 2024, with 233 students from a college in northern Israel completing the questionnaire. Results revealed significant positive correlations, supporting the study’s theoretical framework. Personal innovativeness was strongly related to TAM variables. Perceived usefulness, perceived ease of use, attitude toward use and behavioural intention to use the technology were each significant predictors of actual GenAI use. Gender and field of study influenced adoption, with both males and students studying information systems and economics showing higher usage rates. To the best of our knowledge, this study is the first to integrate TAM with personal innovativeness and demographic factors to assess student engagement with GenAI. The findings provide a theoretical and empirical foundation for understanding student responses to new technologies in higher education. The identified gender gap and field-based differences suggest that tailored approaches are necessary to enhance student engagement with GenAI tools. Overall, the findings imply that teaching practices should include scaffolded, inclusive strategies that foster GenAI literacy, adaptability and ethical awareness. Such approaches may strengthen students’ preparedness for AI-enhanced workplaces and support higher education’s role in assuring graduate employability.

Purpose This study explored the themes and sentiments of online learners regarding the use of Generative Artificial Intelligence (AI) or “generative AI” technology in higher education. Design/methodology/approach English-language tweets were subjected to topic modelling and sentiment analysis. Three prevalent themes were identified and discussed: curriculum development opportunities, lifelong learning prospects and challenges associated with generative AI use. Findings The results also indicated a range of topics and emotions towards generative AI in education, which were predominantly positive but also varied across male and female users. Originality/value The findings provide insights for educators, policymakers and researchers on the opportunities and challenges associated with the integration of generative AI in educational settings. This includes the importance of identifying AI-supported learning and teaching practices that align with gender-specific preferences to offer a more inclusive and tailored approach to learning.

The advancements in Generative Artificial Intelligence (GenAI) can provide opportunities for enriching educational experiences, but at the same time raise concerns regarding academic integrity. Many educators have expressed anxiety and hesitation when it comes to integrating GenAI in their teaching practices. Thus, recommendations and guidance from institutions are needed to support instructors in this new and emerging GenAI era. In response to this need, this study explores different U.S. universities' academic policies and guidelines regarding the use of GenAI tools (e.g., ChatGPT) for teaching and learning, and from there, gains understanding of how these universities respond and adapt to the development of GenAI in their academic contexts. Data sources include academic policies, statements, guidelines, and relevant resources provided by the top 100 universities in the U.S. Results show that the majority of these universities adopt an open but cautious approach towards GenAI. Primary concerns lie in ethical usage, accuracy, and data privacy. Most universities actively respond and provide diverse types of resources, such as syllabus templates, workshops, shared articles, and one-on-one consultations; focusing on a range of topics, namely general technical introduction, ethical concerns, pedagogical applications, preventive strategies, data privacy, limitations, and detective tools. The findings provide four practical pedagogical implications for educators when considering GenAI in teaching practices: 1) accepting GenAI presence, 2) aligning GenAI use with learning objectives, 3) evolving curriculum to prevent misuse of GenAI, and 4) adopting multifaceted evaluation strategies. For recommendations toward policy making, the article suggests two possible directions for the use of GenAI tools: 1) establishing discipline-specific policies and guidelines, and 2) managing students' sensitive information in a transparent and careful manner.

Generative artificial intelligence (GAI) has emerged as one of the most disruptive technologies in higher education, transforming how students learn, write, research, and complete assessments. While GAI offers significant academic benefits, including improved access to information, writing support, personalized assistance, and productivity enhancement, its rapid use in higher education has generated serious concerns regarding academic integrity and misconduct. The ability of GAI tools to produce essays, summaries, code, answers, and other forms of academic content has challenged long-standing assumptions about authorship, originality, independent learning, and fair assessment. This article examines the academic integrity and misconduct risks associated with GAI in higher education. Using a narrative literature review approach, the study synthesizes recent scholarship on institutional policies, student behaviors, misconduct patterns, personality predictors, ethical concerns, and preventive strategies related to GAI use in academic contexts. The review finds that GAI-related misconduct is not limited to plagiarism but includes unauthorized assistance, concealed authorship, fabrication, contract-like substitution of academic labor, manipulation of assessments, and misuse of AI-generated content in research and publication. The findings further show that misconduct risks are shaped by institutional ambiguity, weak policy enforcement, assessment design flaws, student perceptions, personality traits, and uneven AI literacy. The article argues that academic integrity in the age of GAI must be addressed through a comprehensive framework that combines authentic assessment, clear governance policies, ethical literacy, early-warning systems, due process, and context-sensitive enforcement mechanisms. It concludes that higher education institutions must move beyond narrow anti-cheating responses and adopt a broader academic integrity strategy that recognizes the complexity of GAI use while preserving fairness, originality, trust, and educational purpose.

The rapid implementation of generative artificial intelligence (AI) in higher education has emphasized the necessity to comprehend the factors that impact its acceptance among students. This study examines the influence of digital media literacy on attitudes toward generative AI acceptance in higher education. Utilizing a cross-sectional survey design, a quantitative research methodology was implemented. The research sample included 451 undergraduate students from Kazan Federal University. The assessment of digital media literacy encompassed five sub-dimensions: Device Access, Content Access, Technical Understanding, Critical Understanding, and Create. The acceptance of generative AI was assessed using a scale modified from prior studies. The study employed structural equation modeling to analyze the connections between the sub-dimensions of digital media literacy and attitudes toward accepting generative AI. The results indicated that Content Access and Create had a noteworthy positive influence on attitudes toward accepting generative AI, whereas Technical Understanding had a considerable negative effect. The implementation of Device Access yielded a modest yet noteworthy positive effect, while the introduction of Critical Understanding did not result in a substantial impact. This study contributes to the expanding body of literature on digital media literacy and its influence on the acceptability of technology in higher education. The results underscore the significance of cultivating digital media literacy skills, particularly those related to content access and creation, to prepare students for the complexities and opportunities presented by generative AI in higher education. The study offers recommendations for educators, policymakers, and academics while acknowledging its limitations and suggesting directions for future research.

A scoping literature review of prompt engineering for bridging students AI literacy in higher education

The introduction of generative artificial intelligence (GenAI) has been met with a mix of reactions by higher education institutions, ranging from consternation and resistance to whole-hearted acceptance. Previous work has looked at the discourse and policies adopted by universities across the U.S. as well as educators, along with the inclusion of GenAI-related content and topics in higher education. Building on previous research, this study reports findings from a survey of engineering educators on their use of and perspectives toward generative AI. Specifically, we surveyed 98 educators from engineering, computer science, and education who participated in a workshop on GenAI in Engineering Education to learn about their perspectives on using these tools for teaching and research. We asked them about their use of and comfort with GenAI, their overall perspectives on GenAI, the challenges and potential harms of using it for teaching, learning, and research, and examined whether their approach to using and integrating GenAI in their classroom influenced their experiences with GenAI and perceptions of it. Consistent with other research in GenAI education, we found that while the majority of participants were somewhat familiar with GenAI, reported use varied considerably. We found that educators harbored mostly hopeful and positive views about the potential of GenAI. We also found that those who engaged more with their students on the topic of GenAI, both as communi-cators (those who spoke directly with their students) and as incorporators (those who included it in their syllabus), tend to be more positive about its contribution to learning, while also being more attuned to its potential abuses. These findings suggest that integrating and engaging with generative AI is essential to foster productive interactions between instructors and students around this technology. Our work ultimately contributes to the evolving discourse on GenAI use, integration, and avoidance within educational settings. Through exploratory quantitative research, we have identified specific areas for further investigation.

In the face of the multiple transformations made in global scale in the social, political, economic, geographic and cultural fields, from the ongoing processes of the capitalist restructuring, globalization and neoliberalism, giving privilege to the market relations, the educational institutions had to redefine their roles over the new pattern of labor organization, of the labor’s profile as well as the types of formation. The study is bounded to the line of research “Saberes e Práticas Educativas”. The thesis argues that the pedagogical practice of the pedagogues who teach the subject Didactics in the public higher education institutions in Piaui corresponds to what the specialists in university teaching consider important as regards the conceptions of teaching and didactic dimensions. Therefore, the general purpose of this study is to investigate, study and comprehend which are the conceptions of teaching and didactic dimensions that the university professors, initially graduated in Pedagogy who work in Pedagogy courses and other degrees from public higher education institutions in the State of Piaui, have over their teaching practice in the higher education. It aims to display the interactions that these teachers establish among themselves and with the organization of their teaching work through the categories of study: conceptions of teaching and didactic dimensions. The research approaches a quantitative and qualitative methodology, in its priority is not only the data collection in its numeric form and percentage/ graphic and the opinion of the subjects in order to respond the following questions: 1 What are conceptions of teaching and didactic dimensions that the university professors, initially graduated in Pedagogy who work in Pedagogy courses in public higher education institutions in the State of Piaui, have over their teaching practice in the higher education? 2. What are the interactions that these teachers establish among themselves and with the organization of their teaching work through the categories of study: conceptions of teaching and didactic dimensions? Two Brazilian public universities that serve the whole state of Piaui, Universidade Federal Do Piaui (UFPI) – and in its 05 campuses, and the Universidade Estadual do Piaui (UESPI) – in its 11 campuses where there is the Pedagogy Course were chosen as research locations. were chosen as research locations. The used research instrument was a structured questionnaire developed in the Google Docs platform with closed questions disposed on a 5-point Likert-type scale and an opened one. We used the descriptive statistics to analyze the quantitative data and the analysis of the content by Bardin to analyze the qualitative ones. 40 professors who teach the Didactics subject in Pedagogy courses and other degrees in the public universities of the state of Piaui. The results allowed deducing that the pedagogue professors who teach the Didactics subject in Pedagogy courses and other degrees in the public universities of the state of Piaui, in their teaching practice in higher education, give privilege to a multidimensional perspective of education and teaching, therefore, think over the Didactics embedded to its epistemological principles, promoting critical reflections on the complexity about teaching, including, however, the analysis of the sociocultural, political, economic, technical, ethical, cognitive, human that interconnect in the construction/reconstruction of the knowledge historically constituted. Furthermore, in their teaching practice, they realize the teaching permeated by the contradictions and dilemmas in the contexts, in which they are inserted. Therefore, Didactics contributes to the professors exercise their educative actions in a transforming perspective of the factors that complicate the realization of a public, democratic and good education.

How Can <i>IJDS</i> Authors, Reviewers, and Editors Use (and Misuse) Generative AI?

Learning in hybrid times: Comparing student experiences in traditional and GenAI-supported instruction

Generative artificial intelligence (GenAI) is emerging as a transformative technology in higher education, particularly in programming instruction. However, its impact on learning, motivation, and the educational environment must still be fully understood. This study aims to determine the capacity of GenAI to generate effective computer programming learning in STEM university students, comparing it with active learning methods based on video. An experiment was conducted with 40 computer engineering students divided into two groups: one using GenAI (Google Gemini 1.5) and another employing educational videos. Pre- and post-tests of knowledge and the Intrinsic Motivation Inventory (IMI) were applied to evaluate learning, intrinsic motivation, and the learning environment. No significant differences in learning were found between the groups. However, GenAI significantly increased perceived autonomy and reduced perceived effort and pressure, while video-based learning significantly improved perceived competence. These findings suggest that both methods seem to motivate in diverse ways and that they could complement each other in an integrated teaching approach, offering new perspectives for designing programming learning environments in higher education.

In the current globalized scenario, open innovation applied to the public sector is becoming increasingly prominent. This model allows organizations to achieve greater breadth of ideas, which, coupled with internal practices, expand the field of solutions to problems in society. Therefore, glimpses the adoption and use of technological platforms for the management of ideas and open innovation, in order to promote greater relationship and collaboration between governments and citizens. In this context, considering the potential contributions of technological platforms and crowdstorm processes in promoting innovations and improvements in organizations, the present work tries to understand the processes of adoption, implantation and use of a technological platform of ideas management associated with crowdstorm processes, applied to a public university in Brazil. The main objective is to describe the project, here called “Open University: Innovative Solutions”, involving all the processes related to the implantation and use of the PremioIdeia® Technology Platform associated with the crowdstorm approach in a Public University in Brazil. The numbers associated with the project and the themes challenges evidence that crowdstorming brought benefits to the university, such as a greater appreciation of collaborations, the commitment of participants and also a greater interaction among students, teachers and university management. Based on this, it is suggested that projects of this nature can be carried out in other public universities in order to meet a specific demand for academic and administrative improvements and, in this way, promote the growth and evolution of the country’s public universities.