Criminal intent or cognitive dissonance: how does student self plagiarism fit into academic integrity?

The discourse of plagiarism is speckled with punitive terms not out of place in a police officer's notes: detection, prevention, misconduct, rules, regulations, conventions, transgression, consequences, deter, trap, etc. This crime and punishment paradigm tends to be the norm in academic settings. The learning and teaching paradigm assumes that students are not filled with criminal intent, but rather are confused by the novel academic culture and its values. The discourse of learning and teaching includes: development, guidance, acknowledge, scholarly practice, communicate, familiarity, culture. Depending on the paradigm adopted, universities, teachers, and students will either focus on policies, punishments, and ways to cheat the system or on program design, assessments, and assimilating the values of academia. Self plagiarism is a pivotal issue that polarises these two paradigms. Viewed from a crime and punishment paradigm, self plagiarism is an intentional act of evading the required workload for a course by re-using previous work. Within a learning and teaching paradigm, self plagiarism is an oxymoron. We would like to explore the differences between these two paradigms by using self plagiarism as a focal point

Ethics and decision making in publishing journal: Issues to be taken into account

One of the most prioritized questions of publishing a new journal in the almost similar fields covered by many other journals warrants certainly some clarification which needs to be addressed in the inaugural issue. A very straight response to this query is promoting business and management science in the country as well as in the region. The unique aim of IJBMR is to focus on quantitative aspects of business and management research. IJBMR has envisioned a future for IJBMR to surrogate the research works that centre around business and management problems of this century with a quantitative view. In this editorial ethical issues in publishing journal articles has been discussed from the perspective of editor, author and reviewer. For decision making in journal publication a new method has been proposed which is known as the SAFA system. the SAFA stands for the "Standardized Acceptance Factor Average". The SAFA of the articles included in this issue are also analyzed.Standardized Acceptance Factor Average, the SAFA system, IJBMR, ethics, PR-PR dilemma, Texoplagiarism

Ethical practices in the college classroom: teaching and learning from the next generation about academic honesty

Academic honesty is a perennial concern at the university. Faculty, who endeavor to maintain ethical practices in their own work, may struggle to communicate with new generations of students about important aspects of academic honesty. Communication about this construct is often reduced to a syllabus statement warning students about penalties for plagiarism. Institutional responses are similarly narrowly focused on committees and procedures for the assignment of penalties for breaches of college academic honesty policies. Teaching faculty may benefit from more information and support in conveying to their students the crucial importance of developing and communicating original ideas as well as reporting on the ideas and words of others in an ethical manner. This chapter is framed by a real but anonymized incident from the author’s experience. It reviews current literature on academic honesty, plagiarism, and related issues, as well as historical attitudes on what we now call plagiarism. Also explored are the impact of new media and contemporary student conceptions of academic honesty. Special concerns related to increased use of adjunct faculty to teach university classes and the special challenges contingent faculty encounter when trying to model ethical behavior and mentor students toward academically honest practice are highlighted. Recommendations are drawn from these explorations

TF-IDF Inspired Detection for Cross-Language Source Code Plagiarism and Collusion

Several computing courses allow students to choose which programming language they want to use for completing a programming task. This can lead to cross-language code plagiarism and collusion, in which the copied code file is rewritten in another programming language. In response to that, this paper proposes a detection technique which is able to accurately compare code files written in various programming languages, but with limited effort in accommodating such languages at development stage. The only language-dependent feature used in the technique is source code tokeniser and no code conversion is applied. The impact of coincidental similarity is reduced by applying a TF-IDF inspired weighting, in which rare matches are prioritised. Our evaluation shows that the technique outperforms common techniques in academia for handling language conversion disguises. Further, it is comparable to those techniques when dealing with conventional disguises

Didactic evolution of similarity detection software : the example of Compilatio

Since 2005, Compilatio has been offering tools to help detect and prevent plagiarism. Users of similarity detection software were initially attracted by the ability to track down cheaters. They are now more aware of the tools and services offered to create an environment that encourages the adoption of integrity and citizenship values, especially digital ones. They are aware that plagiarism is not a passing evil to be eradicated, but a deep-seated temptation that each individual must learn to overcome. The technology used to help teachers spot cheating has also evolved. The approach was initially syntactic, comparing texts formally to detect similarities. It then became semantic, using so-called artificial intelligence techniques to find similarities between different words with the same meaning. The issues related to plagiarism prevention illustrate how technology and pedagogy can be used together to train individuals for their future professional and civic life

A framework of power:Shaping the 'critical' in human resource development

As a field, human resource development (HRD) is still relatively new. Although the concepts and functions associated with HRD can be traced to historic approaches to work-related learning, the field emerged as a distinct entity out of training and development efforts during and after World War II. For much of the field’s history, scholars and practitioners emphasized a bottom-line interest in improving performance and productivity through development activities (organization development, career development, and training and development). Early admonitions to engage in ‘training revolutionaries’ remained dormant until contemporary scholars began to offer alternative perspectives that challenged the managerialism in HRD. These new perspectives, called Critical Human Resource Development (CHRD), focus on the processes of engaging human and organizational systems that relate, organize, learn, and change in ways that optimize not only organization advancement, but also human interest and social impact. Crucial to advancing CHRD is understanding the power interests that frustrate and facilitate these processes. To that end, this dissertation compiles five published articles which, collectively, address issues of where power lies within a given context, who benefits (and suffers) from the application of power, and how (and why) power is enacted. The core articles contain explorations of the power of ideology to define beliefs, thoughts, and behaviors. This work contributes to the broader field of HRD in at least three ways. First, it provides a framework for a new way of viewing HRD from a critical perspective through practices of relating, organizing, learning, and changing. Second, it offers insight into how power can be understood within the field of HRD as defining, using, and resisting. And, finally, it addresses how CHRD can engage in the power to that leads to activism by HRD professionals

UNEARTHING ENTANGLEMENTS: HUMAN/MACHINE COLLABORATION IN THE WRITING CLASSROOM

This dissertation focuses on the dynamics between teachers and machines at the intersections of design, teaching labor, and pedagogy when automation is deployed in writing classrooms. The sites of analysis are Eli Review and Turnitin, two technologies that represent different design approaches that center around “informating” or “automating” data about student work. The exigence for this project emerges out of the labor crisis currently enveloping higher education. Traditionally, in times of labor crises, automation and machines are used to replace scarce or imperfect human labor. However, balanced and purposeful design of automated technology has the potential to enhance humans’ labor and protect workers. Using holistic and provisional coding, combined with object interviews, this dissertation analyzes data collected from a national survey distributed to composition instructors and nine interviews about their personal experiences with Eli Review and Turnitin. The data and findings from these methods suggests beneficial relationships between humans and machines are possible in the writing classroom through careful design, integration, and management of educational and learning technologies