Thesis (Ph.D.)--University of Maryland, College Park, 2007. / Adviser: Thomas Kunkel. Includes bibliographical references.

Thesis (M.A.)--University of Alberta, 2009. / A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Master of Arts English and Film Studies. Title from pdf file main screen (viewed on July 27, 2009).

Thesis (Ph.D.)--Syracuse University, 2008. / "Publication number: AAT 3345016."

A dissertation submitted to the Faculty of Education in partial fulfillment of the Requirements for a Master of Educational Psychology in the department of Educational Psychology and special in the Faculty of of Education at the University of Zululand, 2018. / This is a qualitative study aimed at exploring the factors influencing students to engage on risks of academic cheating and plagiarism at the University of Zululand The specific objectives of the study are: To establish the factors influencing students to take risks on academic cheating during examinations and plagiarism. To explore the extent of the awareness on the consequences of engaging in risky behaviors with regards to plagiarism and academic cheating.

No description available.

Modern educational institutions use static methods e.g. tests in computer-based knowledge assessment systems. Tests have pattern questions with limited number of answers. Use of such methods does not guarantee objective knowledge assessment – numbers of the right answers could be guessed or memorized in advance. Practical skills can be tested by assigning programming tasks. In order to complete practical tasks students need good knowledge in the fields examined. This leads to better assessment of student knowledge in theory and practice. Teachers get better feedback. However practical tasks need considerable amount of time to be examined in detail which most teachers do not have. When assignments are tested superficially students tend to plagiarize and so the problem gets even deeper. A survey by Donald McCabe of approximately 6000 students revealed that 74% of engineering students reported engaging in some form of academic dishonesty. The goal of this work was to build a computer-based system to assess software quality and detect plagiarism. The system was designed and implemented. Experimental tests have shown good results. The system is intended to be used in future courses and gradually improved by other students.

Yes / Plagiarism is a vexed issue for Higher Education, affecting student transition, retention and attainment. This paper reports on two initiatives from the University of Bradford library aimed at reducing student plagiarism. The first initiative is an intensive course for students who have contravened plagiarism regulations. The second course introduces new students to the concepts surrounding plagiarism with the aim to prevent plagiarism breaches. Since the Plagiarism Avoidance for New Students course was introduced there has been a significant drop in students referred to the disciplinary programme. This paper discusses the background to both courses and the challenges of implementation.

Ever since we entered the digital communication era, the ease of information sharing through the internet has encouraged online literature searching. With this comes the potential risk of a rise in academic misconduct and intellectual property theft. As concerns over plagiarism grow, more attention has been directed towards automatic plagiarism detection. This is a computational approach which assists humans in judging whether pieces of texts are plagiarised. However, most existing plagiarism detection approaches are limited to super cial, brute-force stringmatching techniques. If the text has undergone substantial semantic and syntactic changes, string-matching approaches do not perform well. In order to identify such changes, linguistic techniques which are able to perform a deeper analysis of the text are needed. To date, very limited research has been conducted on the topic of utilising linguistic techniques in plagiarism detection. This thesis provides novel perspectives on plagiarism detection and plagiarism direction identi cation tasks. The hypothesis is that original texts and rewritten texts exhibit signi cant but measurable di erences, and that these di erences can be captured through statistical and linguistic indicators. To investigate this hypothesis, four main research objectives are de ned. First, a novel framework for plagiarism detection is proposed. It involves the use of Natural Language Processing techniques, rather than only relying on the vii traditional string-matching approaches. The objective is to investigate and evaluate the in uence of text pre-processing, and statistical, shallow and deep linguistic techniques using a corpus-based approach. This is achieved by evaluating the techniques in two main experimental settings. Second, the role of machine learning in this novel framework is investigated. The objective is to determine whether the application of machine learning in the plagiarism detection task is helpful. This is achieved by comparing a thresholdsetting approach against a supervised machine learning classi er. Third, the prospect of applying the proposed framework in a large-scale scenario is explored. The objective is to investigate the scalability of the proposed framework and algorithms. This is achieved by experimenting with a large-scale corpus in three stages. The rst two stages are based on longer text lengths and the nal stage is based on segments of texts. Finally, the plagiarism direction identi cation problem is explored as supervised machine learning classi cation and ranking tasks. Statistical and linguistic features are investigated individually or in various combinations. The objective is to introduce a new perspective on the traditional brute-force pair-wise comparison of texts. Instead of comparing original texts against rewritten texts, features are drawn based on traits of texts to build a pattern for original and rewritten texts. Thus, the classi cation or ranking task is to t a piece of text into a pattern. The framework is tested by empirical experiments, and the results from initial experiments show that deep linguistic analysis contributes to solving the problems we address in this thesis. Further experiments show that combining shallow and viii deep techniques helps improve the classi cation of plagiarised texts by reducing the number of false negatives. In addition, the experiment on plagiarism direction detection shows that rewritten texts can be identi ed by statistical and linguistic traits. The conclusions of this study o er ideas for further research directions and potential applications to tackle the challenges that lie ahead in detecting text reuse.

Interest in plagiarism continues to generate debate both in the media and in the context of the academy. Opinions continue to differ not only about how plagiarism can be defined, but also about the nature of its causes and its possible solutions. Most universities have now developed websites to address the difficulties experienced by both students and staff in ascertaining exactly what kind of writing practices might constitute plagiarism. However more often than not, such websites tend to give undue emphasis to the mechanics of referencing and universal notions of ‘academic honesty’ in order to make their point. Little or no attention is given to providing well-developed guidelines on what constitutes ‘common’ knowledge, which is especially relevant currently given the growing cultural diversity of contemporary university classrooms. In addition, discussions about writer identity and authorship seem to be totally absent. This silence on such matters needs to be tackled as a matter of urgency. I have adopted a ‘critical ethnographic’ case study approach to this doctoral study in order to investigate how undergraduate university students from diverse language and disciplinary backgrounds have used the words and ideas of others in their written research-based assignments. The responses of academic staff to these students’ writing practices have also been explored. Three different sources of data from ten students and ten academic staff have been collected in order to allow for data analysis from multiple perspectives through a process of triangulation. Bakhtin’s concept of dialogism (1981, 1984, 1986), Kristeva’s writings on intertextuality and the subject-in-process-and-on-trial (1986a, 1986b, 1986c, 1996) and Howard’s work on patchwriting, textual ownership and writer development (1992, 1995, 1999) have been central to the construction of the analytical framework used in this study. I argue that, the notion of ‘plagiarism’ should be re-conceptualised in terms of transgressive and non-transgressive forms of intertextuality (see also Chandrasoma et al., 2004). My study also reveals how students react differently to the homogenising forces of the academy (Holton, 2000). Some feel alienated and have challenged or resisted these forces, while others have adopted an accommodationist position. Furthermore, this research shows that students are confused by unified and autonomous notions of textual ownership and originality that fail to conceptualise subjectivity and authorship as sociohistorically constructed and multi-voiced. I conclude that educators need to recognise the political nature of the processes involved in the construction of text/knowledge and writer identity and recommend a dialogic approach to pedagogy, which allows for textual ownership and authority to be circulated and negotiated between students and their lecturers.

This study examined faculty perceptions of plagiarism in the classroom using a qualitative case study methodology. A single university was used for the case study to locate all data under a single institutional culture. A purposive sample of eleven faculty were interviewed and content analysis was conducted on the data. The data were analyzed using Lave and Wenger’s theory of legitimate peripheral participation, a learning theory which proposes that all learning takes place in a community of practice and that learning takes place as a result of interactions between members of the community of practice. Because the data were analyzed using legitimate peripheral participation, faculty were asked to reflect on how they learned to write in their discipline, how they view their role in working with students as they become proficient in writing in their discipline, and what happens when students violate community practices. This study attempted to reframe scholarship that approaches plagiarism as a right vs. wrong issue and recast scholarship on plagiarism as an issue of students moving toward full participation in the community of practice of academic scholars under the tutelage of faculty members. Research participants saw themselves as mentors to students as they developed their academic writing standards and abilities, a philosophy in keeping with the tenets of legitimate peripheral participation. Research participants attributed violations of community standards to institutional constructs such as grades, social constructs such as culture or generation, or individual constructs such as moral character or upbringing.