Academic Integrity In Higher Education Research Articles

Leveraging Oral Assessments to Enhance Learning and Integrity in Teaching Data Analytics

The rapid advancement of generative AI tools, like ChatGPT, has significantly impacted academic integrity in higher education. This paper explores the integration of oral assessments with traditional project evaluation in data analytics courses to address these challenges. While oral assessments cannot completely prevent cheating, they enable examiners to probe students' understanding more deeply. We present an overview of our assessment design and processes rather than detailed student results. We compare the implementation of oral assessments in a fully online professional course and a face-to-face undergraduate course. Moreover, we compare results before and after oral assessment training and explore AI’s role in efficiently generating individualised questions. Our findings demonstrate that oral assessments reduce academic dishonesty, enhance comprehension, and increase assessment rigour.

Evolving intersections: AI, disability, and academic integrity in higher education

Evolving intersections: AI, disability, and academic integrity in higher education

Desarrollo de una declaración de uso de inteligencia artificial con una perspectiva de integridad académica en educacióN MéDica y Ciencias De la Salud

IntroductionArtificial intelligence (AI), through tools like ChatGPT, is transforming higher education with more and more students and teachers incorporating AI into daily practice. Along these lines, new challenges emerge in the educational field, where the need for a balance between efficiency and originality, and a deep analysis with a focus on academic integrity is required. AimsThis article discusses the relationship between AI and academic integrity in higher education and describes the process of developing an academic integrity statement adapted to the use of AI. Methodology: Using a methodology that includes analysis of relevant AI tools and expert evaluations, a framework for the ethical and responsible adoption of AI is proposed. ResultsThe results show an effective integration of the statement in academic works, promoting transparency and honesty. Discussion and ConclusionsThe discussion highlights the variability in adoption of the statement across academic levels, suggesting the need for a more personalized approach. In conclusion, the role of the declaration in promoting ethical practices and preparing for future challenges at the intersection of technology and education should be emphasized.

Examining AI Guidelines in Canadian Universities: Implications on Academic Integrity in Academic Writing

Academic integrity is a crucial aspect of higher education that fosters intellectual honesty and upholds the principles of fairness and trustworthiness (Stoez & Eaton, 2020; Kang, 2022; Eaton, 2022). As the introduction and integration of artificial intelligence (AI) technologies becomes increasingly prevalent in educational settings, it is imperative to examine how Canadian universities are addressing the implications of AI on academic integrity (Eaton, 2022; UNESCO, 2023). This study aimed to examine the existing AI guidelines and policies developed and implemented by Canadian universities and analyze their alignments and gaps in relation to their academic integrity policies, particularly in the domain of academic writing in Canadian higher education contexts. In this research study, sixteen Canadian universities were selected for document analysis, and through an examination of their existing polices and guidelines on AI, results revealed insights into both challenges and opportunities for faculty, students and stakeholders around teaching academic writing while upholding academic integrity in higher education.

Top-ranked U.S. and U.K.’s universities’ first responses to GenAI: key themes, emotions, and pedagogical implications for teaching and learning

The emergence of ChatGPT, a Generative AI program, has sparked discussions about its teaching and learning value, and concerns about academic integrity in higher education (HE). An extant review of the literature indicates that a scarcity of research exists on GenAI, specifically a synthesis of the official views, guidelines and articles of top-ranked universities on the use, limitations, challenges, and opportunities brought by ChatGPT in the early phase when ChatGPT was released in 2022 until early May 2023, which can offer insights into the concerns and recommendations for educators. Using the corpus assisted discourse analysis approach, this study identified the key themes and emotions elicited by evaluations of the ChatGPT situation from a self-built corpus containing 151 articles from 47 top-ranked U.S. universities and 34 U.K. ones. Our findings indicated three prominent themes discussed on official websites, including ChatGPT as a text and content generator, use of ChatGPT in teaching and learning, and potential implications and opportunities of using ChatGPT in HE. Further examination revealed that bias, concern, worry, threat, fear, and trust were the prevailing emotions relating to ChatGPT. Illustrated with examples collected from our corpus, this paper offers an in-depth discussion of universities’ first responses to the use of ChatGPT. The insights gained have some pedagogical implications for academics, researchers and educators and may inform policy and practice in HE on the use of GenAI.

ChatGPT Unveiled: Understanding Perceptions of Academic Integrity in Higher Education - A Qualitative Approach

AbstractThe purpose of this research is to gain a complete understanding of how students and faculty in higher education perceive the role of AI tools, their impact on academic integrity, and their potential benefits and threats in the educational milieu, while taking into account ways to help curb its disadvantages. Drawing upon a qualitative approach, this study conducted in-depth interviews with a diverse sample of faculty members and students in higher education, in universities across Lebanon. These interviews were analyzed and coded using NVivo software, allowing for the identification of recurring themes and the extraction of rich qualitative data. The findings of this study illuminated a spectrum of perceptions. While ChatGPT and AI tools are recognized for their potential in enhancing productivity, promoting interactive learning experiences, and providing tailored support, they also raise significant concerns regarding academic integrity. This research underscores the need for higher education institutions to carefully navigate the integration of AI tools like ChatGPT. It calls for the formulation of clear policies and guidelines for their ethical and responsible use, along with comprehensive support and training. This study contributes to the existing literature by presenting a comprehensive exploration of the perceptions of both students and faculty regarding AI tools in higher education, through a qualitative rich approach. By delving into the intricate dynamics of ChatGPT and academic integrity, this study offers fresh insights into the evolving educational landscape and the ongoing dialogue between technology and ethics.

Technological innovations in education: a scoping review on the impact of AI on academic integrity

This study presents a systematic review on the impact of artificial intelligence (AI) on academic integrity in higher education. The main objective was to understand how technological innovations, particularly those related to AI, influence the teaching and learning process. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PAGE et al., 2021) guidelines, the methodology involved searching various databases, including IEEE, SAGE, Scopus, ERIC, ACM, Semantic Scholar, and Web of Science. Out of the 3,484 articles initially retrieved, 31 were considered for discussion. The results highlight a growing trend of research regarding the proposed theme with emphasis on ChatGPT and cheating behavior detection systems, demonstrating concern for ethical issues in the academic environment.

Evaluation of AI content generation tools for verification of academic integrity in higher education

Evaluation of AI content generation tools for verification of academic integrity in higher education

Strengthening and Preserving a Culture of Academic Integrity in Global Higher Educational Settings

Despite efforts to eradicate academic dishonesty in educational settings, the phenomenon persists and cheating is increasingly becoming easier due to the advancement of information technology. Factors like peer pressure, time constraints, stress, and workload contribute to dishonest behavior among students. This article emphasizes the importance of academic integrity in higher education, aiming to prevent dishonesty, understand its effects, and discourage fraudulent activities. Solutions to this problem include fostering a culture of academic integrity throughout institutions and encouraging students to critically evaluate theories, maintain morality, produce unique work, and properly credit sources contributes to preserving a culture of academic integrity. Text-matching and proctored software can aid in detecting offenders and reinforces academic integrity

Academic Integrity Training Module for Academic Stakeholders: IEPAR Framework

The global surge in academic misconduct during the COVID-19 pandemic, exacerbated by remote teaching and online assessment, necessitates a comprehensive understanding of the multidimensional aspects and stakeholders' perspectives associated with this issue. This paper addresses the prevalent use of answer-providing sites and other types of academic misconduct, underscoring the challenge of detecting all or most of the student misconduct. Exploring factors such as faculty inexperience in remote teaching and assessment, the paper advocates for proactive measures to preserve integrity in education. Emphasizing the need for a culture of integrity beyond traditional classrooms, the paper reviews existing models, then details steps to create a framework using the International Labour Organization (ILO)’s TREE training method. It presents the IEPAR framework (Inspiration, Education, Pedagogical considerations, Assessment design, Response and Restorative practice), and assesses its effectiveness. Incorporating faculty feedback, the paper concludes with evidence-based findings, positioning the IEPAR framework as a robust approach for addressing academic misconduct and fostering a culture of academic integrity in higher education through responsible training of all stakeholders.

Artificial intelligence: threat or asset to academic integrity? A bibliometric analysis

Purpose This study aims to address a systematic literature review (SLR) using bibliometrics on the relationship between academic integrity and artificial intelligence (AI), to bridge the scattering of literature on this topic, given the challenge and opportunity for the educational and academic community.Design/methodology/approach This review highlights the enormous social influence of COVID-19 by mapping the extensive yet distinct and fragmented literature in AI and academic integrity fields. Based on 163 publications from the Web of Science, this paper offers a framework summarising the balance between AI and academic integrity.Findings With the rapid advancement of technology, AI tools have exponentially developed that threaten to destroy students' academic integrity in higher education. Despite this significant interest, there is a dearth of academic literature on how AI can help in academic integrity. Therefore, this paper distinguishes two significant thematical patterns: academic integrity and negative predictors of academic integrity.Practical implicationsThis study also presents several contributions by showing that tools associated with AI can act as detectors of students who plagiarise. That is, they can be useful in identifying students with fraudulent behaviour. Therefore, it will require a combined effort of public, private academic and educational institutions and the society with affordable policies.Originality/value This study proposes a new, innovative framework summarising the balance between AI and academic integrity.

ALGORITHM AND SOFTWARE IMPLEMENTATION OF MODELS FOR PROGRAM CODE COMPARISON ON THE EXAMPLE OF C-LIKE PROGRAMMING LANGUAGES

This scientific work introduces an innovative algorithm and its software implementation for addressing the issue of detecting code similarities and identifying instances of code borrowings in software solutions. This development, pre sented in both finished and abstract forms, has the potential to revolutionize the way educators and institutions approach evaluating the creative solutions of student-programmers. The algorithm is designed to automate checks on software solutions submitted by students for various programming challenges, competitions, and Olympiads. The tool provides an effective means of detecting code similarities and flagging potential instances of plagiarism, allowing instructors to ensure that the submissions are original and the result of conscientious efforts. The work presents two examples of creative tasks that require careful evaluation for code similarity, providing concrete illustrations of how the algorithm works in practice. The algorithm itself is described in detail, and parts of the software code implementation in C# programming language are provided, enabling interested parties to explore the tool's technical workings. The results of testing and analysis of the algorithm are presented, with the work highlighting the potential of the tool to automate time-consuming and resource-intensive evaluations of software solutions. Visualizations of the test results provide clear and concise insights into the efficacy of the algorithm, enabling educators to assess the originality of the solutions with ease. Overall, the work is an invaluable contribution to the field of software development, providing educators with an innovative tool for ensuring the originality of software solutions submitted by students. With the growing need for transparency and academic integrity in higher education, this development has significant potential to transform the way institutions approach software solution evaluations, empowering students to pursue creative problem-solving with confidence. All of this can be achived by this algorithm being implemented in the future in bigger application as it`s main or side feature.

Academic Integrity in Higher Education: Understanding and Addressing Plagiarism

This article delves into the profound implications of plagiarism, extending beyond its role as an academic transgression to challenge the foundational principles of truth, originality, and integrity upon which the academic world is built. Plagiarism's extensive consequences ripple through students, educators, and educational institutions, posing a substantial threat to the integrity of the educational system. The primary aim of this study is to comprehensively address the complexities of plagiarism in higher education, emphasizing the need for effective strategies to safeguard and promote academic integrity. Academic institutions, designed to cultivate knowledge and character development, confront the unsettling presence of plagiarism, necessitating an in-depth exploration of its multifaceted causes and motivations for meaningful mitigation. The study identifies academic pressure, time constraints, lack of knowledge about citation rules, and the digital age as significant contributors to the prevalence of plagiarism. It underscores the far-reaching consequences of this issue and highlights the pivotal role of prevention and detection strategies, notably plagiarism detection software such as Turnitin, Grammarly, and Copyscape, in the ongoing battle to preserve academic honesty and the sanctity of scholarly work.

Broken Circle: Exploring Indigenous Perspectives of Academic Integrity

Across the land now known as Canada, a growing body of research confirms the importance of academic integrity in higher education. Indigenous voices, though, are largely subsumed within the morass of dominant student and faculty perspectives or segregated alongside international student perspectives. Using the imagery of the Medicine Wheel as a framework, this session explores the views of Indigenous faculty, staff, administrators, and graduates affiliated with a mid-sized post-secondary institution in British Columbia. Findings from a small-scale research study reveal a holistic vision of academic integrity that emphasizes relationships with people and knowledge. As Wilson (2008) explains, “relationships do not merely shape reality, they are reality” (p.7). In this relational paradigm, academic integrity is inseparably grounded in the broader principles of integrity, and relies on reciprocal truth-telling to maintain the wholeness of the circle (Lindstrom, 2022). In this session, participants will gain insights into the ways dominant approaches to academic integrity can break the circle of integrity. The session will review similarities and differences between the experiences of Indigenous and non-Indigenous learners, and will consider how Indigenous views of relationality may foster a culture where stewardship of knowledge strengthens the bonds of integrity for all.

‘Words are Flowing Out Like Endless Rain Into a Paper Cup’: ChatGPT & Law School Assessments

ChatGPT is a sophisticated large-language model able to answer high-level questions in a way that is does not trigger conventional plagiarism detectors. Concerns have been raised that and similar forms of ‘generative AI’ pose a significant threat to academic integrity in higher education. To evaluate this risk in the context of legal education specifically, this project had ChatGPT (using the GPT3.5 model available in January 2023) generate answers to twenty-four different exams from an English-language law school based in a common law jurisdiction. It found that the system performed best on exams that were essay-based and asked students to discuss international legal instruments or general legal principles not necessarily specific to any jurisdiction. It performed worst on exams that featured problem-style or “issue spotting” questions asking students to apply an invented factual scenario to local legislation or jurisprudence. While the project suggests that for the most part conventional law school assessments are for the time being relatively immune from the threat generative AI brings, the project provides only a baseline snapshot of how large-language models tackle assessment in higher education. As both the technology improves and students learn how to harness it, increasingly fewer forms of assessment will be beyond its reach. However, rather than attempt to block students from using AI as part of learning and assessment, this paper instead proposes three ways students may be taught to use it in appropriate and ethical ways. While it is clear that generative AI will change how universities teach and assess (across disciplines), a solution of prevention or denial is no solution at all.

Academic integrity in higher education: manifestations and motivation factors

The article highlights the problems of ensuring academic integrity in higher education and the factors that determine them. The category "integrity" is considered not only in ethical and legal aspects, but also in an economic dimension. The peculiarities of such forms of dishonesty as plagiarism, methodological manipulation, abuse of self-citation and bias in further professional activities (using the profession of auditor as an example) are considered. It is substantiated that achieving the profitability of investments in national education to the level of foreign indicators requires the improvement of educational management and the introduction of a number of documents of an organizational and legal nature regarding incentives for conscientiousness. A comparative analysis of national and foreign experience in overcoming negative manifestations in university education is carried out. It is emphasized that the imperfection of the criteria system for determining the scientific rating affects to a large extent the violation of the integrity of universities’ academic staff. The productive role of the cooperation between the National Agency for Higher Education Quality Assurance and foreign institutions in the implementation of European experience in ensuring academic integrity, adapted to Ukrainian socio-economic realities, is emphasized. The expediency of involving international organizations in monitoring the state of corruption within the Ukrainian education is substantiated. It is proposed to supplement the evaluation of the state of academic integrity of the HEIs in the process of educational and scientific work with the applicants by evaluating it by means of the criteria of conscientiousness and productivity of graduates’ professional activity. It is proved that the training of applicants must necessarily include the projection of ethical principles and principles of academic integrity in the future profession, taking into account special requirements of international standards and professional codes of ethics. It is emphasized that elevating integrity to the level of immanent value of educational and scientific society is a guarantee for competitiveness of graduates of Ukrainian universities on the European market of knowledge.

Evaluating a pedagogical approach to promoting academic integrity in higher education: An online induction program.

Academic integrity is at the heart of excellent education. However, resources explaining the concept tend to be definition-driven, while using complex language and sometimes even an austere tone designed to discourage students from breaches. This study aims to design and evaluate an online module at a UK University across 2 years, designed to improve students’ understanding of concepts of academic integrity and practice. The module includes a range of interactive resources (e.g., gamified quizzes and e-booklets) and was made available to a large cohort of postgraduate students (448). The study adopts a mixed-methods approach composed of three sequential phases involving first collecting students’ views on existing academic integrity resources (7 students participating in a focus group and 39 competing a questionnaire), then developing a range of new ones based on students’ feedback to form the content of the module, and finally gathering students’ evaluation on the newly created resources (sample size: 361 students). Results illustrate a clear improvement in relation to the accessibility, usefulness and understandability of new resources. Results also highlight a remarkable increase in student confidence levels regarding academic integrity. Students also considered the new module as more appealing and informative. This manuscript offers a good example of a pedagogical approach aimed at promoting academic integrity in an innovative and engaging fashion.

The Scholarship of Technology Enhanced Cheating

The Scholarship of Technology Enhanced Learning, and the Scholarship of Learning and Teaching more broadly, tends to focus on positive stories of things that work (Dawson & Dawson, 2018). We have an interest in learning and want to share strategies we have found to be successful. A similar parallel can be drawn with the field of academic integrity, in that it too is a field with a focus on a positive thing: students’ capabilities and actions that demonstrate they can and do act in the way we want them to.
 Delving into the negative is unpleasant. It can require an adversarial mindset (Dawson, 2021), similar to the type used in cybersecurity (Craigen et al., 2014). Scholars of cheating can be portrayed by the media as undercover sleuths (e.g. Cook, 2018). On the flipside, those who question the technologies used to detect or deter cheating can face legal action by vendors. In my own work I have had to step very carefully, having been warned that studies where I try to empirically check if anti-cheating technologies work may not be legal without the support of their vendors. Cheating and anti-cheating scholarship is a charged, risky place to be.
 This presentation explores cheating and technology. Drawing on a recent synthesis of research from cybersecurity, artificial intelligence and game studies (Dawson, 2021), it discusses what the current state of cheating is, and where it is likely to be in the near future – as well as the types of scholarship that we need to address the problem of technology-enhanced cheating.
 References
 Cook, H. (2018, 13 November 2018). Academics go undercover to spot the telltale signs of a cheater. The Age. https://www.theage.com.au/national/victoria/academics-go-undercover-to-spot-the-telltale-signs-of-a-cheater-20181113-p50fng.html
 Craigen, D., Diakun-Thibault, N., & Purse, R. (2014). Defining cybersecurity. Technology Innovation Management Review, 4(10), 13-21.
 Dawson, P. (2021). Defending assessment security in a digital world: preventing e-cheating and supporting academic integrity in higher education. Routledge.
 Dawson, P., & Dawson, S. L. (2018). Sharing successes and hiding failures: ‘reporting bias’ in learning and teaching research. Studies in Higher Education, 43(8), 1405-1416. https://doi.org/10.1080/03075079.2016.1258052

Promoting Academic Integrity in Institutions of Higher Learning: What 30 Years of Research (1990-2020) in Australasia Has Taught Us

This article reviews and evaluates the academic integrity research conducted in Australasia over a 30-year period from 1990–2020. It presents an analysis of studies on academic integrity including those on contract cheating as an increasing area of concern in higher education. The authors divide the research according to the diverse stakeholders—students, faculty, staff, and institutions of higher learning. Keeping in mind that maintaining and promoting a culture of academic integrity is everyone’s business, and that there is no simple solution, the authors recommend a combination of strategies to promote and maintain a culture of academic integrity in higher education now and into the future.

Research integrity: learning from collective action in Nepal

Early career researchers in developing countries like Nepal have faced many barriers while learning and practicing research integrity. Having easy access to appropriate resources for learning research integrity is essential to ensure academic integrity in higher education in Nepal and promote responsible research practices. This paper presents an approach to collective learning that will help stakeholders initiate learning and foster research integrity at their own level. Methodologically, the learning interventions were conducted in four phases: preparation, planning, implementation, and learning. Throughout the process of each phase, social exchange theory and collaboration in social learning were considered as new literacy models to promote research integrity knowledge. The interpretation of experiential learning interventions led to the development of the 4Co collective learning model. This model is contextually applicable for gaining deeper knowledge and skills and new networks of research integrity. With the purposes of awareness and development, this article is divided into two sections: the first part explores the actions taken and the second explores experiential learning that provides insights about the 4Co collective learning model.