Exploring Rogeting: Implications for academic integrity

Poor paraphrasing can be a sign of underdeveloped writing skills that can lead to plagiarism. One example of poor paraphrasing is Rogeting, which is the substitution of words with their synonyms using Roget’s thesaurus or other digital synonym providers. In this position paper, we discuss Rogeting as a form of poor paraphrasing that may lead to academic integrity breaches, such as plagiarism. We discuss methods of identifying Rogeted text, concluding with practical recommendations for educators about how to better support student writers so they can avoid Rogeting in favour of developing their writing skills

Style features in the programming process which can help indicate plagiarism

[EN] In the new situation, where more and more final programming assignments are performed outside the classroom, it is necessary to pay more attention to the possibilities of understanding whether a student has created the solution on their own. To do this, it is possible to use a programming environment that logs user actions. One such environment is Thonny, which also allows the programming process to be replayed. The aim of this study is to identify style features of different learners, based on solution logs of introductory programming courses, and to explore how permanent these features are and can these indicate whether learners have solved the tasks without external aids. It can be said that non-programming style features, like the order of writing brackets or quotation marks, are more permanent and can be used to detect plagiarism. However, programming style features, such as the use of variable names or increment, are very variable between courses, and students participating in introductory courses do not have an established style. They are greatly influenced by the style features of teaching materials and solutions of sample tasks. Therefore, programming style features cannot be used to automatically check if a student has solved a task on their own.Meier, H.; Lepp, M. (2021). Style features in the programming process which can help indicate plagiarism. En 7th International Conference on Higher Education Advances (HEAd'21). Editorial Universitat Politècnica de València. 623-630. https://doi.org/10.4995/HEAd21.2021.13072OCS62363

Text Similarity from Image Contents using Statistical and Semantic Analysis Techniques

Plagiarism detection is one of the most researched areas among the Natural Language Processing(NLP) community. A good plagiarism detection covers all the NLP methods including semantics, named entities, paraphrases etc. and produces detailed plagiarism reports. Detection of Cross Lingual Plagiarism requires deep knowledge of various advanced methods and algorithms to perform effective text similarity checking. Nowadays the plagiarists are also advancing themselves from hiding the identity from being catch in such offense. The plagiarists are bypassed from being detected with techniques like paraphrasing, synonym replacement, mismatching citations, translating one language to another. Image Content Plagiarism Detection (ICPD) has gained importance, utilizing advanced image content processing to identify instances of plagiarism to ensure the integrity of image content. The issue of plagiarism extends beyond textual content, as images such as figures, graphs, and tables also have the potential to be plagiarized. However, image content plagiarism detection remains an unaddressed challenge. Therefore, there is a critical need to develop methods and systems for detecting plagiarism in image content. In this paper, the system has been implemented to detect plagiarism form contents of Images such as Figures, Graphs, Tables etc. Along with statistical algorithms such as Jaccard and Cosine, introducing semantic algorithms such as LSA, BERT, WordNet outperformed in detecting efficient and accurate plagiarism.Comment: NLPTT2023 publication, 10 Page

Iniciación científica: conceptualización, metodologías y buenas prácticas

Iniciación científica: conceptualización, metodologías y buenas prácticas” como resultado de una investigación colaborativa, presenta cada uno de sus ejes en clave multidisciplinaria, regional, y sistemática; que de manera reflexiva brinda estrategias para la cualificación de la experiencia de inmersión en el mundo de la investigación formativa y sus diversos procesos, enfoques y elecciones. La primera expedición por los contenidos de la obra, desarrollan el concepto de iniciación científica desde la epistemología de la investigación; La segunda expedición, ahonda en las metodologías, procesos y elementos necesarios para adelantar procesos de investigación formativa con alta calidad; y, La tercera expedición, comparte las buenas prácticas y los escenarios de investigación formativa implementados en diversas Instituciones de Educación Superior

7th International Conference on Higher Education Advances (HEAd'21)

Information and communication technologies together with new teaching paradigms are reshaping the learning environment.The International Conference on Higher Education Advances (HEAd) aims to become a forum for researchers and practitioners to exchange ideas, experiences,opinions and research results relating to the preparation of students and the organization of educational systems.Doménech I De Soria, J.; Merello Giménez, P.; Poza Plaza, EDL. (2021). 7th International Conference on Higher Education Advances (HEAd'21). Editorial Universitat Politècnica de València. https://doi.org/10.4995/HEAD21.2021.13621EDITORIA

Digital annotations: an exploration of experiences

Digital texts and learning platforms introduce possibilities of forms of reading and writing that can be contrasted with pre-digital understandings of how readers and writers interact with texts. In current Higher education contexts, there is a requirement to embrace the use of digital technologies to access study materials and engage with academic practices; these technologies are often selected and supported by university computing support, or staff creating the course of study, and those participating are expected to accept and grasp the potential for their own work. At the same time students and staff, who can be from diverse language and cultural contexts, are expected to conform to the visible academic, linguistic and cultural practices for writing, submitting texts, and taking part in learning discussions. Study practices also include various forms of notes, comments and annotations to texts that are sometimes private and sometimes exchanged in various ways, including digital formats. Although constraints are placed on what is acceptable in the visible academic settings, the digital choices available to staff and students are extensive. Concurrent to this, changes in course design, resources and support (for staff and students) are being subtly changed in a way that may seem routine (Goodfellow & Lea, 2013) but are gradually and significantly changing the way reading and writing are regarded. This study explores the use of modifications to texts which are variously labelled as digital notes, comments or annotations, with a focus on how these are valued and how they can change perceptions of reader, writer and text in Higher education study practices. These modifications often (but not necessarily) take the form of additions that are marked, separated, or indicated by colour/emphasis to indicate that they are not part of the original text; however, the original digital text has been changed by these modifications, and the resulting text now incorporates the original with layers of new text. This creates a new digital text, which can, of course, undergo further transformation if the process is repeated. In the context of this study, the term “digital annotations” is used for modifications that are created digitally (using different modalities, so could include graphic, photographic as well as written and audio texts) and therefore become part of the creation of new texts. The study draws on theories of literacy, applied linguistics, and social semiotics. The main research questions for the study are “How do users evaluate, use and contribute to digital annotations?” and “what perceived value is placed on modified texts following the creation of digital annotations?” In answering these questions, the conclusions lead to greater understanding of the practical concerns as well as the theoretical questions connected to the process of interacting with digital texts. Using digital annotations to make sense and meaning from digital texts implicates the reader as a writer but also involves the form or mode of the text in a way that demonstrates this is more than an arbitrary choice. Activity Theory (Engestrom, 2000) was used to identify the tensions and contradictions in these choices. A survey and conversations (semi-structured interviews) were used to provide data, and analysis was done using thematic and narrative enquiry. Conclusions show that the choices made by users are subject to the affordances offered by the digital tools, but also their own familiarity with the digital tools, their perceptions of public and private study practices, and the languages they can utilize to probe and create meaning. This has implications for the ways in which digital technologies are promoted in educational contexts, and for the ways in which digital innovations guide and steer institutions, staff and students in an increasingly global world

Detecting Plagiarism based on the Creation Process

All methodologies for detecting plagiarism to date have focused on the final digital “outcome”, such as a document or source code. Our novel approach takes the creation process into account using logged events collected by special software or by the macro recorders found in most office applications. We look at an author's interaction logs with the software used to create the work. Detection relies on comparing the histograms of multiple logs' command use. A work is classified as plagiarism if its log deviates too much from logs of “honestly created” works or if its log is too similar to another log. The technique supports the detection of plagiarism for digital outcomes that stem from unique tasks, such as theses and equal tasks such as assignments for which the same problem sets are solved by multiple students. Focusing on the latter case, we evaluate this approach using logs collected by an interactive development environment (IDE) from more than 60 students who completed three programming assignments