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1 – 10 of 174Monica Gallant and Pranab Kumar Pani
The aim of this paper is to explore the behavior pattern, perceptions, and motivations of students towards academic misconduct in a Business School with a view to mitigating its…
Abstract
Purpose
The aim of this paper is to explore the behavior pattern, perceptions, and motivations of students towards academic misconduct in a Business School with a view to mitigating its occurrence.
Design/methodology/approach
The survey was conducted among a batch of undergraduate students who responded to various dimensions of plagiarism through a structured questionnaire. Responses were measured on a Likert scale. Some non-parametric tests were done for statistical analysis.
Findings
From the perception of the prevalence of plagiarism committed by others, the authors found that the majority tend to believe that it happens in spite of the existence of preventive policies. Based on the findings, the authors conclude that the students who are more prone to cheating/plagiarism are male, with low grade point average, and are not on scholarship. Parental disapproval is found to be one of the dominant deterrent factors that have the potential to restrain unethical behavior.
Practical implications
The findings demonstrate that the managers of graduate programs should include parental roles in the deterrent mechanism to improve the quality of education.
Originality/value
Very little evidence exists about the perception of academic dishonesty among the students of a multicultural academic institution located in a middle-east country. There are not many studies that analyze the effectiveness of deterrents from a student’s perspective. In this paper, the authors have attempted to assess the value of various deterrents and their effectiveness as perceived by the students.
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Hashem Alshurafat, Mohannad Obeid Al Shbail, Allam Hamdan, Ahmad Al-Dmour and Waed Ensour
This study aims to explore the factors that contribute to student academic dishonesty through an examination of the misuse of AI language models. Using the fraud triangle theory…
Abstract
Purpose
This study aims to explore the factors that contribute to student academic dishonesty through an examination of the misuse of AI language models. Using the fraud triangle theory, which posits that opportunity, rationalization and pressure are key factors for fraudulent behavior, this study investigates how these elements interact and contribute to academic dishonesty among students.
Design/methodology/approach
In this study, data on how accounting students used ChatGPT to cheat was acquired from 279 accounting students in Jordanian public universities over the course of two months, from January 2023 to March 2023, through previously tested and validated questionnaires. The main tool for gathering data was a questionnaire distributed online using Microsoft Forms.
Findings
The results show that all of the fraud triangle factors are significant determinants of student academic dishonesty and student misuse of ChatGPT. The findings of this research can be used to guide the development of technology-based preventative measures.
Originality/value
This study provides valuable insights into the motivations and factors that drive students to engage in academic dishonesty and sheds light on the broader issue of technology-assisted academic dishonesty and its impact on the educational system. This study’s contribution is significant, as it sheds light on a pressing issue in education and provides valuable information for educators and policymakers to address the problem and improve academic standards.
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Margarida Rodrigues, Rui Silva, Ana Pinto Borges, Mário Franco and Cidália Oliveira
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…
Abstract
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 implications
This 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.
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Komal Kamran, Akbar Azam and Mian Muhammad Atif
This study aims to investigate the situational factors that intensify the impact of leader bottom-line mentality (BLM) on employee pro-self-unethical behavior. In particular, the…
Abstract
Purpose
This study aims to investigate the situational factors that intensify the impact of leader bottom-line mentality (BLM) on employee pro-self-unethical behavior. In particular, the moderating role of contingent rewards and punishments is evaluated under the lens of situational strength theory.
Design/methodology/approach
Data were collected from 218 full-time employees working in the USA in a time-lagged study and analyzed using SPSS Process Macro.
Findings
Statistical analysis reveal contingent rewards and punishments significantly moderate the positive relationship between BLM and pro-self-unethical behavior.
Practical implications
This paper highlights the need for more balanced reward systems that incorporate moral conduct into work performance. It also emphasizes the role of robust accountability and monitoring systems in minimizing employees’ unethical behavior.
Originality/value
To the best of the authors’ knowledge, this is the first study to investigate the moderating role of contingent rewards and punishments on the relationship between leader BLM and subordinate pro-self-unethical behavior. Moreover, it provides significant empirical support to situational strength theory.
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Grace Enriquez, Victoria Gill, Gerald Campano, Tracey T. Flores, Stephanie Jones, Kevin M. Leander, Lucinda McKnight and Detra Price-Dennis
The purpose of this paper is to provide a transcript of a dialogue among literacy educators and researchers on the impact of generative aritficial intelligence (AI) in the field…
Abstract
Purpose
The purpose of this paper is to provide a transcript of a dialogue among literacy educators and researchers on the impact of generative aritficial intelligence (AI) in the field. In the spring of 2023, a lively conversation emerged on the National Council of Research on Language and Literacy (NCRLL)’s listserv. Stephanie initiated the conversation by sharing an op-ed she wrote for Atlanta Journal-Constitution about the rise of ChatGPT and similar generative AI platforms, moving beyond the general public’s concerns about student cheating and robot takeovers. NCRLL then convened a webinar of eight leading scholars in writing and literacies development, inspired by that listerv conversation and an organizational interest in promoting intergenerational collaboration among literacy scholars.
Design/methodology/approach
As former doctoral students of two of the panel participants, webinar facilitators Grace and Victoria positioned themselves primarily as learners about this topic and gathered questions from colleagues, P-16 practitioners and those outside the field of education to assess the concerns and wonderings that ChatGPT and generative AI have raised. The following webinar conversation was recorded on two different days due to scheduling conflicts. It has been merged and edited into one dialogue for coherence and convergence.
Findings
Panel participants raise a host of questions and issues that go beyond topics of ethics, morality and basic writing instruction. Furthermore, in dialogue with one another, they describe possibilities for meaningful pedagogy and critical literacy to ensure that generative AI is used for a socially just future for students. While the discussion addressed matters of pedagogy, definitions of literacy and the purpose of (literacy) education, other themes included a critique of capitalism; an interrogation of the systems of power and oppression involved in using generative AI; and the philosophical, ontological, ethical and practical life questions about being human.
Originality/value
This paper provides a glimpse into one of the first panel conversations about ChatGPT and generative AI in the field of literacy. Not only are the panel members respected scholars in the field, they are also former doctoral students and advisors of one another, thus positioning all involved as both learners and teachers of this new technology.
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James Ewert Duah and Paul McGivern
This study examines the impact of generative artificial intelligence (GenAI), particularly ChatGPT, on higher education (HE). The ease with which content can be generated using…
Abstract
Purpose
This study examines the impact of generative artificial intelligence (GenAI), particularly ChatGPT, on higher education (HE). The ease with which content can be generated using GenAI has raised concerns across academia regarding its role in academic contexts, particularly regarding summative assessments. This research makes a unique contribution to the literature by examining university student and staff perceptions of current and future issues pertaining to the role of GenAI in universities.
Design/methodology/approach
A qualitative method involving five one-to-one semi-structured interviews with four students and a lecturer explored the ethical and practical issues of GenAI text generation in academia. An inductive thematic analysis was chosen as it provided nuanced insights aligned with the study’s goals.
Findings
Use of GenAI was discussed within the context of a range of topics, including perceptions of academic misconduct, authorial integrity and issues pertaining to university policies. Participants universally defined traditional classifications of academic misconduct but were unable to provide clear definitions where the use of GenAI was included for writing summative assessments. Students showed a more open engagement with GenAI, considering it a tool for overcoming obstacles rather than a means to plagiarise. Educators were generally more cautious and less optimistic about the academic role of GenAI. Lack of clear institutional policies surrounding such tools also contributed to ethical ambiguities.
Originality/value
The study highlights diverging perspectives between students and academics, which necessitate a forum for dialogue, ensuring the need to develop clear policies to steer the integration of GenAI in a manner that is beneficial for students and academics.
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Abhishek N., Abhinandan Kulal, Divyashree M.S. and Sahana Dinesh
The study is aimed at analyzing the perceptions of students and teachers regarding the effectiveness of massive open online courses (MOOCs) on learning efficiency of students and…
Abstract
Purpose
The study is aimed at analyzing the perceptions of students and teachers regarding the effectiveness of massive open online courses (MOOCs) on learning efficiency of students and also evaluating MOOCs as an ideal tool for designing a blended model for education.
Design/methodology/approach
The analysis was carried out by using the data gathered from the students as well as teachers of University of Mysore, Karnataka, India. Two separate sets of questionnaires were developed for both the categories of respondents. Also, the respondents were required to have prior experience in MOOCs. Further, the collected data was analyzed using statistical package for social sciences (SPSS).
Findings
The study showed that MOOCs have a more positive influence on learning efficiency, as opined by both teachers and students. Negative views such as cheating during the assessment, lack of individual attention to students and low teacher-student ratio were also observed.
Practical implications
Many educational institutions view that the MOOCs do not influence learning efficiency and also do not support in achieving their vision. However, this study provides evidence that MOOCs are positively influencing the learning efficiency and also can be employed in a blended model of education so as to promote collaborative learning.
Originality/value
Technology is playing a pivotal role in all fields of life and the education sector is not an exception. It can be rightly said that the technology-based education models such as MOOCs are the need of the hour. This study may help higher education institutions to adopt MOOCs as part of their blended model of education, and, if already adopted, the outcome of the present study will help them to improve the effectiveness of the MOOCs they are offering.
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Mingke Gao, Zhenyu Zhang, Jinyuan Zhang, Shihao Tang, Han Zhang and Tao Pang
Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and…
Abstract
Purpose
Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and cooperative obstacle avoidance.
Design/methodology/approach
This study draws inspiration from the recurrent state-space model and recurrent models (RPM) to propose a simpler yet highly effective model called the unmanned aerial vehicles prediction model (UAVPM). The main objective is to assist in training the UAV representation model with a recurrent neural network, using the soft actor-critic algorithm.
Findings
This study proposes a generalized actor-critic framework consisting of three modules: representation, policy and value. This architecture serves as the foundation for training UAVPM. This study proposes the UAVPM, which is designed to aid in training the recurrent representation using the transition model, reward recovery model and observation recovery model. Unlike traditional approaches reliant solely on reward signals, RPM incorporates temporal information. In addition, it allows the inclusion of extra knowledge or information from virtual training environments. This study designs UAV target search and UAV cooperative obstacle avoidance tasks. The algorithm outperforms baselines in these two environments.
Originality/value
It is important to note that UAVPM does not play a role in the inference phase. This means that the representation model and policy remain independent of UAVPM. Consequently, this study can introduce additional “cheating” information from virtual training environments to guide the UAV representation without concerns about its real-world existence. By leveraging historical information more effectively, this study enhances UAVs’ decision-making abilities, thus improving the performance of both tasks at hand.
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Faiqa Mansoor, Kanwal Ameen and Alia Arshad
The role of academic libraries in dissemination of information and facilitating research of academic community is well-established world over. However, a significant role of…
Abstract
Purpose
The role of academic libraries in dissemination of information and facilitating research of academic community is well-established world over. However, a significant role of libraries in ensuring fair use of information to promote an ethical research culture at the higher education institutes is also flourishing. This study aims to explore the perceived causes of unethical use of literature by university scholars and deterrents to plagiarism in universities of Pakistan.
Design/methodology/approach
The design of the study was qualitative, and interviews were conducted on nine university library heads in Pakistan who were officially administrating anti-plagiarism (Turnitin) software service at their universities and were providing “similarity index certification” of PhD and MPhil research work through the software. They were purposively selected for the interviews because of their direct interaction with the researchers and faculty on matters of information searching as well as its ethical use. The study is based on PhD thesis work of the first author.
Findings
The findings of the study depicted that conceptual unawareness of plagiarism, lack of information skills, socio-cultural factors and weak policies were the prime reasons for unethical research practices among graduate scholars. Participants were positive that a role of university library in combating plagiarism through provision of anti-plagiarism software and guidance could prove more beneficial for both the researchers and libraries.
Originality/value
Multiple studies have been conducted, in and out of south Asian region, to gather the views of the students and faculty on the matters of academic misconduct. However, no study was found presenting the views of the other stakeholders in promotion of academic integrity. To the best of the authors’ knowledge, this study is first of its kind in South Asian context and provided observation-based views of a group of university library heads who are also administrating anti-plagiarism service in their universities on the causes and deterrents to plagiarism.
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In recent years, negative spokesperson incidents have raised significant concerns in academia and industry. While several studies have addressed celebrity endorser scandals…
Abstract
Purpose
In recent years, negative spokesperson incidents have raised significant concerns in academia and industry. While several studies have addressed celebrity endorser scandals, comprehensive analyses of current knowledge are lacking. Therefore, this study systematically reviewed the related literature to better understand trends and suggest future research directions for advancing this field.
Design/methodology/approach
This study employs the theory–context–characteristics–methodology (TCCM) framework to examine 76 articles on celebrity endorser scandals.
Findings
Utilizing the TCCM framework, this study presents a comprehensive research framework, revealing that (1) the celebrity endorser scandal effect primarily includes associative learning, attribution of responsibility, and moral reasoning; (2) entertainment celebrities and athletes have received significant research attention; (3) both individual- and relationship-level characteristics serve as crucial moderators, with focal brand and related brand being the primary outcome variables. Additionally, this study outlines enterprise response strategies, encompassing the reformation of existing spokesperson relationships and the establishment of future spokesperson connections; and (4) quantitative approaches dominate the field.
Originality/value
This study integrates and expands existing research on celebrity endorser scandals while proposing future research opportunities to advance the field.
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