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This research was conducted to see if using ChatGPT prompts students to think more deeply through reflection reports. The case study method and qualitative research methodology were used to carry out this study. Five graduate students in the Curriculum and Instruction department at Aksaray University's Social Sciences Institute who were teachers in various subjects and employed at various state school levels participated in the study. It was found that the majority of participants accepted all of the information presented by ChatGPT based on a citation as true, did not feel the need to control data reliability, and could be manipulated by ChatGPT while doing self-evaluation. Additionally, despite the fact that they prepared reflective reports in which they compared their essays with ChatGPT and included questions that prompted them to think critically and reflectively, as well as the fact that they had taken a graduate-level course on the teaching of higher order thinking skills, it was acknowledged that they could not demonstrate the expected performance in using higher order thinking skills other than to a limited extent. The onus should be on educators to pioneer positive examples of how to utilize ChatGPT and provide direction on how to harness its potential, supported by critical thinking, rather than to avoid using it and identify it as a tool to be avoided.

In this paper we describe a framework for teaching students when they should, or should not use generative AI such as ChatGPT. Generative AI has created a fundamental shift in how students can complete their class assignments, and other tasks such as building resumes and creating cover letters, and we believe it is imperative that we teach students when the use of generative AI is appropriate, and when it is not appropriate (i.e., considered cheating). Framework development is based off the 2x2 Product-Market matrix introduced by Ansoff in 1965. Our initial pass at the framework was piloted with colleagues, and then followed with a focus group of students to refine the framework. We then used the framework in an MBA class to test its efficacy and gather qualitative feedback. Using the results, we further refined the framework and then used it to teach two general undergraduate business classes as a rudimentary test of generalizability across students. The qualitative results were positive. The framework helps educators understand when to use, or not use ChatGPT, and provides a way to teach students about the same. We have found that using the framework in class generates interesting discussions about the use of generative AI.

This study delves into the opportunities and challenges associated with the deployment of AI tools in the education sector. It systematically explores the potential benefits and risks inherent in utilizing these tools while specifically addressing the complexities of identifying and preventing academic dishonesty. Recognizing the ethical dimensions, the paper further outlines strategies that educational institutions can adopt to ensure the ethical and responsible use of AI tools. Emphasizing a proactive stance, the paper suggests that by implementing these strategies, schools can harness the benefits of AI tools while mitigating the risks associated with potential misuse. As the adoption of AI tools in education continues to expand, all stakeholders must stay abreast of the latest developments in the field. This knowledge equips educators to navigate the opportunities and challenges posed by AI tools, fostering a learning environment that is both secure and conducive to empowering students to realize their full potential.

This research study focuses on the growing concern of academic misconduct in distance education courses. A quasi-experimental study was conducted to measure the impact of introducing webcam recording software as an online supervision tool for high-stakes exams in two separate online courses (Management and Accounting). Results revealed that overall performance decreased following implementation of the software, and persisted after taking potential confounding factors into account. Additionally, the explanatory power of the regression analysis was higher for scores under supervision, which suggests that cheating was occurring before online supervision was introduced. It can be concluded from this study that online supervision is an effective tool to combat academic dishonesty in distance education courses.

Implementation of online education pedagogy and practice has expanded rapidly at colleges and universities in recent years, most notably in response to COVID-19. This innovative teaching/learning modality provides benefits to both faculty and students through dynamic teaching/learning content, immense flexibility, and technological investments to support teaching and learning. Academic dishonesty in higher education is a persistent concern emphasized and extensively explored in traditional face-to-face courses, less so in online learning environments. The present work, drawing on a large sample of students and faculty (n=1,640) at a Midwestern university, employs an esurvey and both qualitative and quantitative responses on cheating behavior in the emergent area of online courses/online education. Results expose significant faculty and student disagreement and uncertainty about cheating behaviors in the online environment. Academic integrity is essential to fair and equitable high-quality higher education. The stakes are high to better understand the transformative shifts in academic dishonesty occurring in the online educational environment.

The release of ChatGPT and other Artificial Intelligence (AI) tools has raised significant and challenging questions around the ethics of artificial intelligence in higher education. The initial concerns regarding AI in higher education centered on academic integrity, and the literature reflects this initial response. However, the multifaceted nature of higher education institutions means that there are many domains that will be ethically impacted by the application and implementation of AI. The purpose of this literature review is to examine these many domains and stakeholders in terms of ethical impact to surface questions, concerns, and concepts that may help practitioners navigate this complex construct of education, technology, and ethics. The literature identifies several implications for practice, including academic integrity, assessment (including the concept of cognicy and the practice of authentic assessment), policies and syllabi, and frameworks, principles, and tools. It concludes with a rumination on how the work of ethics is often accomplished through questions, as well as with the recognition that, at this stage in the evolution of AI, it is difficult to identify black-letter answers. We must be prepared to adapt and evolve even as AI does.

In the realm of language acquisition, the integration of Artificial Intelligence (AI) presents a promising frontier. However, gaps exist in understanding the practical application of AI-driven tools, particularly in second language learning contexts. This study delves into the usability of ChatGPT, an advanced AI language model, within the domain of second language acquisition. This paper synthesizes existing literature on ChatGPT's multifaceted capabilities, its effectiveness, its associated challenges, and the potential solutions to these challenges in language learning environments. This review demonstrates ChatGPT's substantial potential in enhancing language learning outcomes, including fostering learner autonomy, improving motivation, and developing language proficiency. Yet, nuanced challenges such as preserving academic integrity and difficulties in crafting effective prompts emerge as crucial considerations. To address these issues, possible solutions including enhancing AI literacy among learners and educators are discussed. This paper sheds light on the complex dynamics of AI-assisted language education, urging ongoing research and refinement to fully utilize these technologies in enhancing second language learning.

The rapid growth of online education, especially since the pandemic, is presenting educators with numerous challenges. Chief among these is concern about academic dishonesty, especially on unproctored online exams. Students cheating on exams is not a new phenomenon. The topic has been discussed and debated within institutions of higher learning, and significant levels of cheating have been reported in the academic literature for over sixty years. Much of this literature, however, has focused on student behavior in a classroom utilizing proctored, in-class exams. Grades on exams usually determine most of a student's final grade in a course, and GPAs are used by employers and graduate schools to indicate a student's subject matter mastery. As more conventional colleges and universities expand their online course offerings it is natural to wonder if academic dishonesty is more prevalent in online classes than in face-to-face classes. In particular, are students more likely to cheat when no one is watching (i.e., on unproctored assessment assignments) than they do when someone is watching (i.e., on proctored assessment assignments)? The purpose of this study is to investigate whether students cheat more on unproctored online exams than they do on proctored in-classroom exams, and if so, is there any pattern to their cheating behavior. Our findings are derived from careful empirical analysis of 741 undergraduate students who completed three unproctored online exams, several collaboration-encouraged assignments, and a proctored in-class comprehensive final exam in the same course with the same instructor. Additionally, we collected demographic and human capital data for every student. Using bivariate and regression analysis, we find significant evidence of more cheating on unproctored online exams than on proctored in-class exams even though students were given stern honor code violation warnings. Moreover, we discover that student cheating increased with each unproctored online exam, implying that students learn how to cheat as they become more familiar with taking online assessment assignments. Finally, we find that students with certain demographic and human capital characteristics tend to cheat more than others. This research strongly supports the use of proctoring for all evaluation assignments in online classes to ensure that grades in these classes properly reflect student aptitude as opposed to merely reflecting their ability to cheat.

This study explores the integration of Artificial Intelligence (AI) in high school education, focusing on its implications for student motivation and learning through the framework of Self-Determination Theory. As AI technologies like ChatGPT4 become more prevalent in educational settings, their potential to enhance learning by catering to students' needs for competence is significant. However, this investigation also highlights the challenges associated with AI misuse, which can undermine students' autonomy and relatedness, leading to academic dishonesty and superficial learning. The research underscores the importance of balancing technological advancements with ethical engagement and intrinsic motivation. Through qualitative analysis, including interviews and thematic analysis of student and teacher feedback, the study reveals a nuanced picture of AI's role in education. It suggests that while AI offers considerable benefits, its integration requires careful consideration of ethical use, digital literacy, and the cultivation of intrinsic motivation. The findings advocate for educational policies and practices that not only leverage AI's potential to enrich learning experiences but also address the challenges posed by its misuse. This study contributes to the ongoing discourse on technology in education, emphasizing the need for a balanced approach to AI integration that supports ethical standards and promotes a meaningful educational experience.

Artificial Intelligence (AI) and related technologies have a long history of being used in education for motivating learners and enhancing learning. However, there have also been critiques for a too uncritical and naïve implementation of AI in education (AIED) and the potential misuse of the technology. With the release of the virtual assistant ChatGPT from OpenAI, many educators and stakeholders were both amazed and horrified by the potential consequences for education. One field with a potential high impact of ChatGPT is programming education in Computer Science (CS), where creating assessments has long been a challenging task due to the vast amount of programming solutions and support on the Internet. This now appears to have been made even more challenging with ChatGPT's ability to produce both complex and seemingly novel solutions to programming questions. With the support of data collected from interactions with ChatGPT during the spring semester of 2023, this position paper investigates the potential opportunities and threats of ChatGPT for programming education, guided by the question: What could the potential consequences of ChatGPT be for programming education? This paper applies a methodological approach inspired by analytic autoethnography to investigate, experiment, and understand a novel technology through personal experiences. Through this approach, the authors have documented their interactions with ChatGPT in field diaries during the spring semester of 2023. Topics for the questions have related to content and assessment in higher education programming courses. A total of 6 field diaries, with 82 interactions (1 interaction = 1 question + 1 answer) and additional reflection notes, have been collected and analysed with thematic analysis. The study finds that there are several opportunities and threats of ChatGPT for programming education. Some are to be expected, such as that the quality of the question and the details provided highly impact the quality of the answer. However, other findings were unexpected, such as that ChatGPT appears to be "lying" in some answers and to an extent passes the Turing test, although the intelligence of ChatGPT should be questioned. The conclusion of the study is that ChatGPT have potential for a significant impact on higher education programming courses, and probably on education in general. The technology seems to facilitate both cheating and enhanced learning. What will it be? Cheating or AI-enhanced learning? This will be decided by our actions now since the technology is already here and expanding fast. [Note: The publication year (2023) shown in the citation on the PDF is incorrect. The correct publication year is 2024.]

This quantitative study is designed to help educational institutions and instructors make informed decisions regarding the use of online proctoring software. The researchers studied the impact of proctoring software in online courses by comparing the final grades of two groups of online, undergraduate students who took the same online course with the same professor who administered virtually the same content, with and without proctoring software. The overall sample included 252 students in six different undergraduate courses. When regressing all six courses together, the data did not show that the addition of proctoring software created a significantly lower course grade. The researchers then regressed the data of each individual undergraduate course, with the addition of independent variables, which had a mixed-bag of results. Interestingly, an undergraduate business course showed that the use of proctoring software reduced course grades while other courses produced interesting significant findings relative to gender and attendance status.

Higher education institutions (HEI) are increasingly challenged by plagiarism, which threatens their academic standards and integrity. This is due to the fact that students have access to an overwhelming amount of information online, making it easier for them to copy and paste without giving proper credit or attribution. Additionally, the prevalence of technology has made it easier to copy and paste without detection. The study aimed to analyze the trends in plagiarism in academic writing by using bibliometric analysis, which is a technique that can measure and analyze the use of published documents. This analysis was used to identify any potential changes in the prevalence of plagiarism in academic writing over time and to identify potential factors that could be influencing it. The data is extracted from Scopus database with Boolean and proximity search strategy and found 579 related journal articles. There are tabulations of results ranging from descriptive analysis, citation analysis, co-citation analysis, and co-word analysis. The descriptive findings revealed that 'academic integrity', despite not being included in the search string, was the most commonly occurring word with 284 indicating a significant relationship between plagiarism in academic writing in HEIs. In addition, citation analysis for the top ten documents was presented. The findings of co-citation analysis highlight factors, new trends of academic integrity, and mitigation plans against plagiarism, while co-word analysis are thematically presented in three prominent clusters which is academic misconduct study, ethics and academic integrity. In most prominent articles cited by many authors, contract cheating is the new trend of plagiarism. As a result, it sheds light on the fact that academic integrity issues go beyond a new phenomenon that needs to be taken seriously. This study has both theoretical and practical implications for minimizing future plagiarism risks as well as identifying and recommending potential solutions to the problem.

During the COVID pandemic, universities around the globe had to move not only their content delivery online, but also their assessments. Due to COVID causing significant upheaval in Higher Education (HE), this enforced experiment also afforded an opportunity to reflect on traditional, invigilated, closed book exams (ICBE) resulting in research and advice in this area. A systematic review of this academic and grey literature was performed concentrating on maths heavy physics examinations to investigate what guidance is given to examination writers, educators who prepare students for exams and HE examinees themselves. The literature review results were divided into: Advice for examiners who need to provide an uinvigilated open book exam (UOBE), discussions on cheating, advice for students and case studies. It was found that ICBEs were good at examining lower order cognitive skills, e.g. recall and understanding, but higher order skills, such as analysing and synthesising, are better examined with access to a larger range of resources. Guidance on making academic misconduct more difficult also suggested using higher order thinking skills in exam questions as responses to these types of tasks are more individual and getting outside help may be more difficult in a time constrained UOBE. Furthermore, literature encouraged reflection on the motivation for cheating and suggested that overly demanding assessment may encourage students to seek inappropriate help. The advice for students highlighted the need to prepare as thoroughly for a UOBE as they would for a traditional exam. Probably the thrust should change from pure memorization to students preparing their notes so that they can efficiently access their material to locate relevant parts for synthesis during a UOBE. Some of the case studies used statistical methods to investigate comparability of grades between UOBEs and ICBEs and some of the studies found them comparable, so a large shift of results may be due to other factors rather than the exam type. Other studies describe their approach and include stakeholder reflections. The main recommendation to exclude lower cognitive skills can pose a problem for maths heavy exams as they mainly assess how well an examinee has mastered these skills before building on them. However, it seems advisable to climb higher up Bloom's taxonomy if possible. Also, it may be conceivable to break up exams into shorter sections that require individual uploading before access to the next part is granted to reduce the possibility of outside help. Furthermore, individualised maths type problems could be achievable by using different data sets for a question. Student advice should highlight the differences between UOBEs and ICBEs so that they can prepare appropriately.

Purpose: Flexible learning is a delivery modality associated with positive outcomes, but its use at the height of the COVID-19 pandemic has been associated with dark student experiences, such as poor interest and dishonesty among students. To understand how and why many tertiary students lost their motivation and became disengaged in pandemic-era flexible learning, this qualitative research was designed. Methodology: A total of 27 tertiary students in five separate groups volunteered to be interviewed. A focus group discussion protocol was developed based on the propositions of Self-Determination Theory (SDT) and this protocol produced about eight hours of narrative data in audio form. The researcher performed thematic analysis to make sense of the transcriptions of the data, and the initial codes and themes were subjected to an external audit for purposes of methodological integrity. Findings: Eight need-thwarting behaviors of key social agents emerged, such as instructors' rigid and negligent behaviors, peers' indifferent and selfish behaviors, and burdensome behaviors of people at home. These behaviors were tied to participants' cognitive appraisals of psychological need frustration that emerged in eight themes, which comprised having problems balancing school and home obligations, believing that outputs were misevaluated, and feelings of disconnection from peers. These appraisals could be related to seven themes of motivation and engagement issues reported by participants, notably amotivation, poor concentration, low effort, and dishonesty. Significance: The findings highlight the importance of addressing these need frustrations in order to improve tertiary students' motivation and engagement in academic tasks delivered through flexible learning in higher education.

This study examines the perceptions and responses of Vietnamese teachers of English as a Foreign Language (EFL) to academic integrity concerns that arise from the use of AI, specifically chatbots like ChatGPT, in foreign language education. The study employed an open-ended survey to collect data from 31 Vietnamese EFL teachers who were asked to share their views on AI-based academic dishonesty, identify perceived causes, outline consequences for students engaging in AI-based plagiarism, and articulate their pedagogical responses to the issue. The study found that teachers primarily attributed students' AI-driven plagiarism to a deficiency in original ideas, poor learning attitudes and motivation, and students' linguistic competencies. The over-reliance on AI was identified as a hindrance to the development of knowledge and skills such as critical thinking and language proficiency. In response to academic dishonesty, teachers advocated for increased regulations, the implementation of AI-based plagiarism detectors, and education on responsible AI use. The findings underscore the importance of adapting language teaching pedagogies and assessments to incorporate personalised learning and process-oriented teaching approaches that support critical thinking and genuine learning motivation. The insights derived from this research contribute to a deeper understanding of EFL educators' perspectives, offering valuable input for the development of policies and practices aimed at promoting academic integrity in the AI era. [Note: The page range (28-47) shown on the PDF is incorrect. The correct page range is 28-48.]

Data obtained through questionnaires sometimes respond to the items presented by social norms, so sometimes they do not suit themselves. High social desirability (SD) in non-cognitive measurements will cause item bias. Several ways are used to reduce item bias, including freeing respondents from not writing their names or being anonymous, explaining to the participants to respond to each statement honestly, as they are or according to themselves, and responding to the questionnaire online or offline. This research aims to prove that several methods can minimize the possibility of item bias SD and academic dishonesty (AD). The research was carried out with an experimental study using a factorial design. There were 309 respondents who were willing to be involved in this research. Data analysis was carried out using multivariate ANOVA. The research results show differences for all variables, Self-Deceptive Enhancement (SDE), Impression Management (IM), and AD in the anonymous group. There are differences in AD in the groups that provide a complete explanation and do not explain, and there is an interaction between the average AD based on the anonymous and explanation group.

Background/purpose: The integration of ChatGPT at Ho Chi Minh City University of Technology and Education (HCMUTE) aims to transform teaching and learning dynamics. This research evaluates ChatGPT's impact on student learning behaviors, exploring its potential to enhance educational outcomes while addressing ethical concerns. Materials/methods: A mixed-methods approach was used, involving 73 first and second-year students from HCMUTE selected through stratified random sampling. Data were collected via electronic surveys and semi-structured interviews with 15 faculty members. Quantitative data were analyzed using IBM's SPSS, while qualitative data were thematically analyzed. Results: ChatGPT is widely adopted by students for learning and information searches, with many also finding it reliable for academic tasks such as idea generation and assignment completion. However, concerns about overreliance were noted, which may hinder independent thinking and critical evaluation skills. Issues related to academic dishonesty, reduced creativity, and ethical problems such as plagiarism and information security were also identified. Conclusion: ChatGPT significantly impacts student learning behaviors. Whilst it offers benefits in accessibility and efficiency, its integration requires a balanced approach in order to maximize benefits whilst mitigating risks. This study highlights the need for stringent policies to ensure ethical usage and to promote independent learning. Future research should focus on the long-term impacts of AI tools on educational outcomes and ethical implementation frameworks.

This study examines the academic dishonesty tendencies, created metaphors and opinions on the "ethics" and "science and research ethics" and "opinions on the taken course" of prospective teachers who took the science and research ethics course. Embedded mixed design was preferred. Academic dishonesty tendency scale, semi-structured interview form and metaphor form were used as data collection tools. With the two-stage clustering performed, the average scores of the academic dishonesty tendency scale were divided into three clusters. It was found that the majority of prospective teachers have a low level of academic dishonesty tendency. According to the results obtained from semi-structured interviews, teacher candidates have expressed their views on the concept of "ethics" under the categories of instructor, student, and administrator. Their views on the concept of "science and research ethics" have been explained under the categories of determination of the subject, conducting studies, and publication of studies. It has been revealed that the course on science and research ethics contributes to the educational processes, personal development, and professional development of teacher candidates. Different metaphors were developed for the concepts of ethics, and science and research ethics. In addition, the metaphors developed regarding the concept of ethics were generally related to guiding and mentoring. The metaphors developed regarding the concept of science and research ethics are related to the things to be considered in a scientific study process, the way to be followed in scientific studies, and the importance of ethics in scientific studies. [Note: The page range (23-46) shown on the PDF is incorrect. The correct page range is 23-48.]

Academic dishonesty is a major issue in education. Perhaps more so in the online environment where may times students are on their honor to complete exams without the use of the Internet, notes, or other prohibited materials. The age range of 18-24 encompasses the traditional aged student body. The non-traditional students are over the age of 25 and may be married, have children, full time jobs and other obligations. Age and the concomitant responsibilities associated with married life, children and working full time work may have advanced the maturity of these students and may allow them to look at the bigger picture and become less tolerant on issues of academic dishonesty. An analysis of the grade records in business classes at a mid-Atlantic comprehensive university provided the data for this study. All class were online and covered the period from 2017-2021. A total of 455 participants (134 traditional aged students and 321 non-traditional aged students) took either two or three exams each, equating to a total of 1227 test scores being analyzed. To determine if cheating was occurring faculty began utilizing the capabilities of the Respondus Lockdown Browser® which records both sound and video while the student is taking the exam. The results were surprising. Implications for practice are also included.

This research utilizes a unique, validated, multiple-choice exam design that allows researchers to observe and measure the degree to which students copy answers from their peers. Using data collected from the exam, this study investigates whether asking students to sign an honor code at the start of the exam reduced instances of cheating relative to a control group. Empirical results demonstrate that the classroom of students who signed the honor code had less overall copying of answers and also fewer individual students who engaged in cheating. This study contributes to the literature by conducting analysis on a sample that measures actual cheating frequency, as opposed to relying on reported cheating in surveys, and by demonstrating that a positive intervention can effectively discourage unethical behavior.

Letter grading systems in education have been widely accepted as a strong medium to assess the educational performance of students across the world. It has been a successful system for many years because it can motivate students to achieve satisfactory grades in a course. However, recent studies indicate that grades can also foster anxiety and demotivate students to learn. This fact can be challenging because many investigators claim that motivation and student engagement are key to student success, especially in online education. This situation is even more problematic with the recent outbreak of COVID-19. There has been a major shift in the education sector from face-to- face instruction to online instruction. To mitigate the negative effects of the grading system, incorporating a partial student self-grading model in remote learning is proposed. The partial self- grading student model can potentially increase motivation, positive attitude and decrease the temptation to cheat on assignments. Another benefit of this system is that it can create a platform where students and instructors can discuss the grades given, thus creating a two-way learning system instead of a one-way learning system. The powerful impacts and benefits of the partial student self-grading model in online education are explored and discussed.

The hasty adoption of remote teaching (RT) by educational institutes in response to the COVID-19 pandemic has drastically impacted teaching, learning, and assessment. With most institutes unprepared for sudden lockdowns, and many educators lacking online teaching and assessment experience, old methods of assessment continued to be used, at least initially. When concerns about academic integrity soon followed, new pedagogical concepts and modes were trialed in the hopes of addressing perceived inadequacies. This study, using a mixed-method design, investigates teacher-participants' perceptions of online assessment and academic integrity. It explores the challenges they believed had a detrimental effect on the latter -- technical difficulties, problems due to lack of physical presence, student behavioral issues, and concerns about assessment design and process. This study also discusses teacher-participants' suggested approaches to safeguarding against dishonesty, including modifications in design, conduct, and evaluation of quizzes and exams. Finally, it ends with teacher-participants' recommendations and suggestions for policy-level changes to help minimize the adverse effects of prolonged RT.

Scientific research is supposed to acquire or generate knowledge, but such a purpose would be severely undermined by instances of research misconduct (RM) and questionable research practices (QRP). RM and QRP are often framed in terms of moral transgressions by individuals (bad apples) whose aberrant acts could be made conducive by shortcomings in regulatory measures of organizations or institutions (bad barrels). This notion presupposes, to an extent, that the erring parties know exactly what they are doing is wrong and morally culpable, but had nonetheless proceeded to commit wrongful acts. However, a confession of intent to deceived is often not readily admitted by perpetrators of RM. I posit that beyond the simplistic notion of conscious moral transgression, deficits in epistemic virtues and/or the prevalence of epistemic vices have important roles to play in initiating and driving RM/QRP. For the individual perpetrator, deficits in epistemic virtues could lead to or amplify errors in one's desperate attempt to be accomplished or to excel, and pushes one across the ethical line or down the slippery slope of misconduct. Likewise, a lack of epistemic virtue within perpetrators' institution or organization could make it conducive for deceitful acts and suppress indications and warning signs for the former. Furthermore, epistemic vices exhibited by reviewers, editors and journals could also promote RM/QRP. In this view, epistemic failings, rather than widespread moral deficiencies of individuals within the research ecosystem, may underlie the prevalence of RM/QRP.

The purpose of this study is to examine the impact of artificial intelligence (AI) on online assessment in the context of opportunities and threats based on the literature. To this end, 19 articles related to the AI tool ChatGPT and online assessment were analysed through rapid literature review. In the content analysis, the themes of "AI's assistance role", "automatic grading and feedback", "improving assessment" and "time benefit" were obtained in the opportunities category, while the themes of "academic integrity concern", "reliability issues" and "adaptability issues" were obtained in the threats category. The impact of AI on online assessment was explained within the scope of these themes. The results revealed that the most emphasis was placed on "improving assessment" themes in the opportunities category, and "academic integrity concern" themes in the threats category. At the end of this preliminary review, it was revealed that more studies investigating the integration of AI to online assessment are needed and all educational institutions, especially distance education institutions, should take measures to ensure the ethical use of AI.

This study examined the degree to which students indulge in six prominent misconducts in Distance Education Institutions (DEIs). The study also quantified how class size, instructional delivery and institutional policies predict students' indulgence in sharp practices using a general linear modelling approach. A sample of 871 participants was drawn from 1,742 final-year students across two DEIs in Nigeria. A structured questionnaire was used for data collection. The questionnaire had acceptable psychometric estimates of dimensionality, content and construct validity, as well as reliability. Sharp practices such as cheating, plagiarism, falsification, impersonation, and arm-twisting were more prevalent in large classes, whereas only inducement was higher in small classes. Class size influenced students' indulgence in sharp practices in DEIs. Instructional delivery and institutional policies negatively predicted students' indulgence in the six sharp practices. Almost all the six sharp practices correlated positively and significantly, except for impersonation and inducement. Therefore, distance education students who cheat, plagiarize, arm-twist, falsify records, induce lecturers, and promote impersonation are more likely to indulge in other forms of sharp practices. It was concluded that large class sizes, poor instructional delivery, and poorly implemented institutional policies promote sharp practices among distance education students. Based on this conclusion, key policy and research implications are discussed.

Recent developments in AI technologies and the increasing accessibility of AI tools, such as ChatGPT, have raised concerns about academic integrity in higher education. Thus, this research aims to shed light on the challenges faced by English as a Second Language (ESL) lecturers in identifying AI-generated texts, and highlighting the skills and resources needed to enhance their detection capabilities. In this qualitative study, data were collected from six ESL lecturers working in a higher educational institution in Cyprus. Participants evaluated four academic essays at C1 level to determine which, if any, of the sample had been fully or partially AI-generated, and these results were then compared to results from four AI detectors. Findings reveal that participants tended to exploit a deficit model of assessment that focuses on error as an indicator of L2 writing output, with high levels of technical and grammatical accuracy and sophisticated language use as indicators of AI-generated text. Moreover, findings suggest that limited awareness of the characteristics and metrics used by ChatGPT, as well as lack of attention to the veracity of facts and references generated by ChatGPT, were features of participants' evaluations. This study identifies the growing challenges encountered by ESL lecturers and underlines the need for digital literacy training, targeted professional development, the use of advanced detection tools and a review of assessment policies and practices in relation to AI. Additionally, this study highlights the importance of reviewing and reinforcing institutional policies and practices that safeguard academic integrity and ensure quality higher education.

Cheating in examinations across the globe is an issue of growing concern. This study argues that the culture of cheating in exams in Balochistan has reduced the efficiency of human resource and has resulted in producing students with high qualifications but less potential in the province. Therefore, it is very important to explore the factors contributing to cheating in exams and to suggest a course of action to mitigate the menace it poses. A quantitative research method was employed for this study. Similarly, statistical techniques such as correlation and logistic regression were conducted for statistical analysis and explanation of the study using SPSS. Theoretically, the study is inspired by rational choice theory. The findings of the study show a significant relationship between personal, institutional, and situational factors. Personal factors that contribute to cheating were found to be students' desire to excel, low GPA, and slow learning. Institutional factors include the weak administrative role of institutions, poor academic policies, overload on students, and weak performance of the teachers. Situational factors such as the poor management strategy of the examiner, time pressure, and technological tools were found to be instigating students towards cheating. The study suggests that an appropriate exam hall setting, effective monitoring, concept-oriented exams, and a strong honor code can decrease cheating.

Background/purpose: ChatGPT is an artificial intelligence program released in November 2022, but even now, many studies have expressed excitement or concern about its introduction into academia and education. While there are many questions to be asked, the current study reviews the literature in order to reveal the potential effects of ChatGPT on education as a whole. The potential implications, possibilities, and concerns about the use of ChatGPT in education are disclosed as mentioned in the literature. Materials/methods: The data of the study were collected and then subjected to a systematic review. Research findings were analyzed according to the themes and categories identified. Results: The results of this research were examined under themes according to the positive and negative aspects of ChatGPT. The positive categories and sub-categories of ChatGPT's integration into education were determined, and the relationship between education and artificial intelligence determined. Similarly, the negative category highlighted the potential negative impact of artificial intelligence on educational processes. Conclusion: The reviewed research evaluated and discussed the impact of AI on education and training processes. In conclusion, this review revealed the critical applications of ChatGPT for educational settings and the potential negative impact of its application. The findings established how ChatGPT and its derivatives would create a new paradigm in education as a whole.

Online education became widespread during the COVID pandemic and is likely to continue to have an important role in our education into the future. A notable aspect of the shift from traditional classroom to virtual teaching has been the collegiate challenge of extending a learning environment founded on mutual trust and academic endeavor, remotely. This study examines the attitudes of students towards violations of academic integrity in online English courses, as attitude can be a trigger for behavior. Student attitudes concerning cheating were assessed for exams, assignments and online sessions. To this end, a questionnaire was implemented with faculty and vocational school students located in the west of Turkey. The participants were two groups of students who attended online English courses and delivered online assignments. One of the groups was comprised of faculty students who attended traditional exams while the other group was tested online. The attitudes of both groups were compared and the results indicated similarity in the most and the least frequently preferred behaviors in general. The most frequently acknowledged violations were using a dictionary during online exams, getting help from translation websites for online assignments and pretending to attend online courses with the camera or microphone turned off. On the other hand, students didn't show willingness to use remote connection software or give account details to a friend to get help in online courses. Although, students in both groups had similar attitudes towards academic misconduct, some item-based differences were revealed that may influence the delivery of language courses in the online setting.

The application of electronic assessments (e-assessment) has become inevitable with the expansion of distance education, and learners' perceptions should be considered when designers improve the system to meet their needs and facilitate their acceptance of the system. This mixed descriptive study investigated university students' perceptions about e-assessment system. Data were collected from 308 students at King Saud University during the second semester of 2021, by using a questionnaire that consisted of 34 Likert scale items and two open-ended questions on students' opinions. The results showed the suitability of e-assessment to the university courses, and the importance of rendering guidance to students before the e-exam by providing a user manual, mock exam, and furnishing clear instructions; ensuring flexibility of use; supplying quick academic and technical support during the e-test; and providing immediate feedback to increase students' motivation and learning retention. The findings highlighted students' concerns regarding the type of exam questions, cheating, and techniques of monitoring and verifying their identities. These findings expected to guide administrators, decision makers, researchers, and system developers to design or customize some features of assessment systems for the achieving best practice of evaluation and measurement of higher education students.

Background/purpose: Little attention is being put forward to the lesser-known type of curriculum--that is, hidden curriculum--most especially in the Philippine context. This study explored the positive and negative lessons from the hidden curriculum in higher education, with a Philippine state university as the research setting. Materials/methods: This study used qualitative case study. The data were obtained using online focused interviews and focus group discussions from Filipino college students. The data were analyzed using thematic analysis. Results: For the positive lessons, college students implicitly imbibed the value of being compassionate. They also acquired behaviors and attitudes that are healthy for the development of their personality. Seeing that many people helped each other, they also learned to collaborate with people. For the negative lessons, college teachers acted as a cause of academic discord. They also were reported to have a lack of sympathy toward student circumstances. Toxic behavior, collective cheating, and high-pressure work environment were observed. Conclusion: If there is a group of people, such as in the university setting, there must be a hidden curriculum. By that, we pertain that the social environment always offers a hidden curriculum. The hidden curriculum offers both positive and negative lessons. Observed or not, it is impactful to students and other stakeholders. Further, the development of hidden curriculum undergoes an iterative cycle-- hidden curriculum influences the collective, then the collective influences the hidden curriculum, "ad infinitum."

One of the biggest challenges for online learning is upholding academic integrity in online assessments. In particular, institutions and faculties attach importance to exam security and academic dishonesty in the online learning process. The aim of this study was to compare the test-taking behaviors and academic achievements of students in proctored and unproctored online exam environments. The log records of students in proctored and unproctored online exam environments were compared using visualization and log analysis methods. The results showed that while a significant difference was found between time spent on the first question on the exam, total time spent on the exam, and the mean and median times spent on each question, there was no significant difference between the exam scores of students in proctored and unproctored groups. In other words, it has been observed that reliable exams can be conducted without the need for proctoring through an appropriate assessment design (e.g., using multiple low-stake formative exams instead of a single high-stake summative exam). The results will guide instructors in designing assessments for their online courses. It is also expected to help researchers in how exam logs can be analyzed and in extracting insights regarding students' exam-taking behaviors from the logs.

Those involved in higher education have been concerned about students' academic dishonesty for many years and there are concerns that the coronavirus pandemic led to even more academic dishonesty across the disciplines. Therefore, this study focused on hospitality and tourism students' views on academic dishonesty, or cheating behaviors, before and during the height of the pandemic. The results of two online surveys of hospitality management students in the southeastern United States found that students felt that academic dishonesty increased, they experienced more stress, and their views varied by their perceptions of online education. Suggestions for de-creasing academic dishonesty to enhance learning include communicating with students about it, making changes in assignments and pedagogy, and getting to know students better.

The aim of this research study was to analyse the relationship among answer-copying tendency, academic self-efficacy, and fear of negative evaluation. To this end, we formed a structural equivalence model, and we evaluated the mediating role of academic self-efficacy between answer-copying tendency and fear of negative evaluation. A total of 562 university students participated in the study. We used the following as data collection tools: The Brief Fear of Negative Evaluation Scale, Academic Self-Efficacy Scale, and Answer-Copying Tendency Scale. For the analysis of the data, first the measurement model was tested, then the Structural Equation Model was established and estimations were made with Maximum Probability Estimation. According to the results, academic self-efficacy plays the role of a mediatory variable between fear of negative evaluation and answer-copying tendency. As can be seen from the impact of fear of negative evaluation on answer-copying tendency, there is a meaningful, positive correlation between the two variables. When we included academic self-efficacy in the model as a mediatory variable, we observed that the relationship between fear of negative evaluation and answer-copying tendency weakened and became less noteworthy. In the light of these observations, we can assert that the tendency of individuals with high academic self-efficacy to cheat in academic contexts is lower even if they have a fear of negative evaluation.

This study aimed to examine whether the tendency to cheat and interpersonal cognitive distortions have a predictive effect on the marital satisfaction level of married teachers. The sample of the study consisted of 107 (28.1%) male and 271 (71.9%) female married teachers working in Gaziantep. In the study, a Personal Information Form was used to collect data on the demographic characteristics of married teachers, the Marriage Life Scale to measure marital satisfaction level, the Cheating Tendency Scale to measure the level of infidelity tendency, and the Interpersonal Cognitive Distortions Scale to measure interpersonal cognitive distortions. A survey model was used in this study. The Pearson Correlation Coefficient and Multiple Regression analysis methods were used in the analysis process of the obtained data. As a result of the research, it was concluded that the tendency to cheat and interpersonal cognitive distortions were significant predictors of marital satisfaction. As a result of the analysis, it was concluded that the tendency to cheat and interpersonal cognitive distortions explained 30% of married teachers' marital satisfaction. At the same time, there is a negative and significant relationship between marital satisfaction and the tendency to cheat; a positive and significant relationship exists between the tendency to cheat and interpersonal cognitive distortions. It has been determined that there is a negative and significant relationship between interpersonal cognitive distortions and marital satisfaction.

Shifting to an e-learning style forced students to learn many skills and competencies to benefit from their experience in an e-learning environment. Ethical competencies play a crucial role in ensuring the fairness of students' assessments and the overall educational process. During the COVID-19 pandemic, the research used a questionnaire to evaluate the ethical understanding of students enrolled in Sultan Qaboos University's Information Studies Department using a quantitative methodology. The findings of this study reveal a significant lack of basic ethical competencies among students in the e-learning environment which negatively impacts their educational experience. The responses obtained indicate a low level of awareness regarding ethical practices in e-learning as well as a lack of knowledge concerning learning misconduct practices. The study suggests the implementation of an educational program that addresses academic ethical practices and e-learning misconduct across all educational levels. The outcomes of this research contribute to a better understanding of current e-learning practices among students, raise awareness about the importance of ethical competencies in e-learning and provide guidance for students to develop ethical digital competencies.

At the University of Montenegro, increasing emphasis has recently been placed on academic integrity. Academic integrity is based on the principles of honesty, objectivity, openness, freedom in teaching and research, and responsibility to academia and society/the community. One of the basic principles of academic integrity is honesty. The present study is based on examining the perception of students and teachers of the University of Montenegro concerning different segments of academic honesty. The aim of the research was to "examine ethical behaviour related to respect for someone else's work (using and referring to literature) and copying as well as using illicit means in exams." The research was conducted using quantitative research on a sample of 200 students and 50 teachers at the University of Montenegro. For this purpose, the authors used a Likert-type assessment scale. The findings suggest that the respondents understand the importance of academic integrity, that is, honesty as its principle, but that they do not recognise all of the segments that it covers in the same way. For example, different answers were received regarding the claim that students copy papers without paraphrasing, and despite the observed negative attitude towards the disciplinary procedure in both groups, teachers seem to lead in this attitude.

This paper argues that legislative intervention rather than deontological rules could be an adequate tool to address academic integrity concerns, particularly in civil law jurisdictions, which is the case in the majority of European countries. The recently enacted Montenegrin law on academic integrity offers a promising foundation for developing such an intervention in the European context, along with suggested improvements drawing upon four years of the implementation experience. Analysis of the law is also conducted with regard to several provisions of the Council of Europe's recently adopted Recommendation on Education Fraud. The paper does not offer a ready-made concept, but its deliberation can serve as an inspiration for governments trying to improve existing rules on academic integrity. A legal approach will be taken in examining the problems and the relevant legislation.

This research study investigated the relationship between technostress creators (techno-complexity, techno-insecurity, techno-invasion, techno-overload, and techno-uncertainty) and faculty perceptions of student cheating in online classes. Data were collected from faculty members of the Management and Organizational Behavior Teaching Society (MOBTS), a member of the AACSB Business Education Alliance, the American Society of Business and Behavioral Sciences (ASBBS), an interdisciplinary professional organization comprised of faculty teaching in accounting, finance, management, marketing, organizational behavior, and computer information systems, and other research panels during 2021 (N = 94). Findings from regression analysis indicated that the techno-complexity subconstruct is positively related to a faculty's perception of student cheating in online classes. In contrast, the techno-insecurity subconstruct was marginally significant and positively related to the faculty's perception of student cheating in online classes. Techno-overload, techno-invasion, and techno-uncertainty subconstructs were not identified as statistically significant in predicting a faculty's perception of student cheating in online classes.

To reduce academic dishonesty and strengthen learning outcomes, I adopted in-depth oral examinations as my benchmark and summative assessments in a Human Anatomy & Physiology course taught in an online asynchronous setting. This decision led my students and me down the transformative path of mastery learning. This was a "threshold experience" for my students who were learning how to think and express themselves as physiologists. This was also a threshold experience for me as I explored the scope of the oral examination in promoting skill acquisition while nurturing a relationship-rich learning environment. By employing "deliberate practice" principles including basic drills, one-on-one weekly check-ins, and small group recitation sessions, students exceeded benchmarks for conceptual understanding, mastery of fundamentals, and application of concepts to clinical scenarios. Students consistently reported that they were happy within this learning environment. With meticulous planning, it is possible to motivate students to learn for mastery and acquire expertise by employing oral exams as the pivotal assessment strategy in an online course thereby also making academic dishonesty almost irrelevant.

The topic of cheating at the college level has received greater attention since the 2019 pandemic. This is in part because countless institutions of higher education switched many of their live/inperson classes to an online learning format. In comparing cheating in live classes to online classes during the 2020-2021 academic year, our survey study results showed a stronger prevalence of cheating in online classes, and more than half (53.2%) of the students reported knowing a classmate who cheated during the pandemic. The aspects of gender and class rank are also discussed related to cheating.

The higher education Spring semester of 2020 was heavily impacted by stakeholders' calls for a complete shutdown of in-person gatherings. This call to action forced instructors and students to transition from face-to-face education to the virtual, online classroom. Institutions were given a few days to 2 weeks for this transition. During this crisis, 14 faculty from across Georgia formed a research consortium to investigate the perspectives of instructors and students on multiple topics, including academic honesty. As part of a mixed method approach, surveys were distributed via email across the university system, which included both quantitative items and narrative, open-text response options. The results of thematic analysis and frequencies revealed the application of well-documented strategies from instructors for reducing the occurrence of cheating during assessments but also revealed new and challenging tactics of cheating by students. These perspectives from the instructors and students provide a rich description of how the shutdown impacted academic honesty in the higher education community. The authors detail these participant narratives and provide information on strategies to encourage academic honesty that move beyond creating more tests, such as revision, randomizing items, and proctoring to catch cheaters in the act.

The biology education literature includes compelling assertions that unfamiliar problems are especially useful for revealing students' true understanding of biology. However, there is only limited evidence that such novel problems have different cognitive requirements than more familiar problems. Here, we sought additional evidence by using chatbots based on large language models as models of biology students. For human physiology and cell biology, we developed sets of realistic and hypothetical problems matched to the same lesson learning objectives (LLOs). Problems were considered hypothetical if (i) known biological entities (molecules and organs) were given atypical or counterfactual properties (redefinition) or (ii) fictitious biological entities were introduced (invention). Several chatbots scored significantly worse on hypothetical problems than on realistic problems, with scores declining by an average of 13%. Among hypothetical questions, redefinition questions appeared especially difficult, with many chatbots scoring as if guessing randomly. These results suggest that, for a given LLO, hypothetical problems may have different cognitive demands than realistic problems and may more accurately reveal students' ability to apply biology core concepts to diverse contexts. The Test Question Templates (TQT) framework, which explicitly connects LLOs with examples of assessment questions, can help educators generate problems that are challenging (due to their novelty), yet fair (due to their alignment with pre-specified LLOs). Finally, ChatGPT's rapid improvement toward expert-level answers suggests that future educators cannot reasonably expect to ignore or outwit chatbots but must do what we can to make assessments fair and equitable.