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Background and Introduction

Preventing cheating and handling intellectual theft is a debatable topic in the academic sector, and most professors do not like dealing with it (Gamage, Silva &Gunawardhana, 2020).However, to protect academic integrity and ensure that original Research Products And Breakthroughs are published in the academic forums, professors and academicians often resort to plagiarism detection software. Academic journals and universities have started relying on cheating detectors that use algorithms (Tripathi & Patel, 2021). This has created a debate regarding the use of cheating detectors and the responsibilities of editors. Plagiarism detectors use "black box" algorithms for producing a number or an "originality score" that shows how much the text matches other papers. These systems have been successful in finding many cases of plagiarism and hence created a misguided notion that they appropriatelydocument every case.

Thesis statement: Cheating detection software has several drawbacks, is unethical and hinders scientific progression by restricting it through fear.

Several researchers have reported their experiences of rejection that were caused due to overly reliance on cheating detectors. The journals have shifted towards depending too much on plagiarism detection software rather than investing in the keen criticism of an editor. The journals depend on a single plagiarism report without seeking a second opinion from an editor. These reports often have several drawbacks, such as most times, they are incorrect and are difficult to transcribe (Weber-Wulff, 2019). The detectors produce numbers known as "non-unique quotient" or "originality score",which are often hard to assess without a proper context. For instance, these detectors often compute false positives for names of countries, names of institutions, medical or financial jargon and common phrases. Additionally, the software lacks accuracy in detectingplagiarism in translations and information gathered from different sources. Another significant drawback of cheating detectors is they only highlight text duplication, which means that they identify a compilation of three or more words appearing together in a different manuscript. In such instances, plagiarism detectors fail at detecting legitimate plagiarism. The cheating detectors also have no ability to capture and detect theft of ideas, use of data and figures without acknowledgment and rephrasing of original findings of other papers without attribution (Meo& Talha, 2019). A manual editor has the ability to fix these issues since they read and study the entire manuscript for detecting inconsistencies. Many manuscripts get rejected on the basis of flagged content marked by the software detectors, such as references, citations, methods and affiliations of authors. Such errors in the detection system could have been avoided if there had been a manual editor to review the manuscripts. Eliminating the editor from the process gives the system that depends on algorithms full autonomy. Sometimes cases of plagiarism go undetected through the software when the source of the text has spelling errors, is not digitized orunavailable to the software database (Adithan&Surendiran, 2018). Some systems that detect random samplesproduce different outcomes for the same paper. Hence limitations and drawbacks are endless, and the reliability of the results cannot be based simply on the cheating software without a manual editor in place.

Drawbacks of Cheating Detection Software

Most universities have plagiarism checkers built into their coursework, and the students are required to enter their assignments, coursework and papers into the database that permits the cheating detectors to check the works and compare them with others' works. Some researchers have raised concerns over the ethicality of the rights the software companies have over the works of the students that get stored in their database (Regan & Jesse, 2019). This gives rise to the question regarding student privacy. Many researchers and some educationists argue that plagiarism detection tools are, in themselves, perpetratorscommitting a mass scale intellectual theft. These tools profit hugely from the large student paper database as the students are compelled to submit their papers in those databases. The large number of papers that get submitted to their databases makes for an argument in their case regarding the worth of their service. Many instructors and professors believe that there can be an alternative to these detection tools. It is the responsibility of the lecturers and course instructors to make the students aware of the consequences of cheating and how they can handle it or look for methods to detect it themselves. Students should be encouraged to understand the ways of properly sourcing materials and citing them within their manuscripts (Graham, 2019).Educators should provide them with resources and guidance to help them complete their work without taking any unethical means. Students take the unethical route when they do not fully understand the consequences it can bring in their future careers or when they are being compelled to submit their work by any means on time (Sim, 2021). With so much pressure on their coursework, they often unknowingly commit intellectual fraud. Providing students with a safe environment to grow and hone their skills is one of the main responsibilities of an educator. Professors can tweak the assignments or make them unique so that students are unable to cheat. Cheating detectors and plagiarism checkers might be used to corroborate academic integrity; however, it should not be bankedsolely upon above various other authentic and ethical preventive means.

Writing is an exploration of the intellect and requires thinking, researching and learning. It is the responsibility of an educationist to foster the critical thinking of the students. Intellectual exploration cannot develop and grow if there is distrust. Freedom of the mind cannot thrive where there is fear. It is the teacher's responsibility to make the students aware regarding an issue or a topic that has been there for a long time, to let them know that they have the freedom to gather and collect information regarding the topic and add their own voice to it, and that the collective research is uniqueirrespective of the ideas that been thought of previously (Ross & Macleod, 2018). As a thinker and a writer,they are only gathering ideas in ways unique to them and that no one before them has. The teacher must educate the students on ways to achieve this and to, address others' ideas through citations and how convey to the readers that they are presenting their own thoughts and ideas. Giving them honest feedback on their work can help them polish their skills and present a better piece of work. Over the history of academic education, hundreds of pupils have been thrown into silence by their fear regarding grammatical mistakes and sentence constructionmistakes; and plagiarism detection tools might bring about a new fear, a fear of matching ideas of other authorsunknowingly, fear that a string of words or use of common phrases becoming an exact match to another's work, and finally the fear of getting caught. The cheating detection software is a method of holding a student guilty and accountable before they are proven innocent (Mphahlele& McKenna, 2019). The students'papers go through the plagiarism detection software before the professor reads them, immediately flagging them as something to be concerned about. This hinders the process of intellectual exploration, and students are forced to give in to the mechanized system that binds them and their work.

It can be concluded that cheating detection software and plagiarism checkers are not only unethical but have several drawbacks and hinders the process of intellectual exploration. There are several methods to create an environment where students' works and ideas are honored and promoted,ultimately promoting their growth. Thoughtful, unique and meaningful designing of assignments may be one of such methods. Other methods may be assigning early drafts, annotated bibliographies, research proposals and meeting with students to discuss their feedbacks are good ways to ensure the students do not plagiarize. Multiple feedback and peer reviews can help improve the quality of content and create an environment where there is mutual respect instead of fear. 

Reference

Adithan, C., &Surendiran, A. (2018). Plagiarism Software. Thesis Writing for Master's and Ph. D. Program, 305-317. https://d1wqtxts1xzle7.cloudfront.net/64364744/thesis-writing-for-masters-and-phd-with-cover-page-v2.pdf?Expires=1649327700&Signature=bk1h2fXVI4IT7R0Rm55A2kmCuPsIvTZ3LwaTtzN3rOBM9xiOh1vmpvfiDLYCybc64HUHo74gOCqwg3qggz4Z93E6Z10JkFhk0zh5Uz3yzqOl5fIWPw9ppfnVOk5wH-LqVBlXjZSwsepkj3uRKBP99~WBym6O5pRdYygsWbrsisKqOvcypfgOLuuA~zexvxVCQ8xrusRBheKwb9oUfb3J41LFDAQ7YIqYFOImXA6aoZO1~MmsOaQyAEaykEkE94Ke3VuhibjDC3oi9I7F47kJ3sx5eEqF12LU6jly240bv1bU9aLwrvrEr6jM4nPjbMbqRs8nooDiYC~LiVCVcthB3A__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA#page=303

Gamage, K. A., Silva, E. K. D., &Gunawardhana, N. (2020). Online delivery and assessment during COVID-19: Safeguarding academic integrity. Education Sciences, 10(11), 301. https://www.researchgate.net/profile/Nanda-Gunawardhana/publication/344883864_Online_Delivery_and_Assessment_during_COVID-19_Safeguarding_Academic_Integrity/links/61334656c69a4e48797a6767/Online-Delivery-and-Assessment-during-COVID-19-Safeguarding-Academic-Integrity.pdf

Graham, S. (2019). Changing how writing is taught. Review of Research in Education, 43(1), 277-303. https://journals.sagepub.com/doi/pdf/10.3102/0091732X18821125

Meo, S. A., & Talha, M. (2019). Turnitin: Is it a text matching or plagiarism detection tool?. Saudi journal of anaesthesia, 13(Suppl 1), S48. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6398291/

Mphahlele, A., & McKenna, S. (2019). The use of turnitin in the higher education sector: Decoding the myth. Assessment & Evaluation in Higher Education, 44(7), 1079-1089. https://www.researchgate.net/profile/Sioux-Mckenna/publication/331106055_The_use_of_turnitin_in_the_higher_education_sector_Decoding_the_myth/links/60cc099c458515dc178cc525/The-use-of-turnitin-in-the-higher-education-sector-Decoding-the-myth.pdf

Regan, P. M., & Jesse, J. (2019). Ethical challenges of edtech, big data and personalized learning: Twenty-first century student sorting and tracking. Ethics and Information Technology, 21(3), 167-179. https://www.equalityproject.ca/wp-content/uploads/2018/12/Forthcoming-Ethical-Challenges-of-Edtech-.pdf

Ross, J., & Macleod, H. (2018). Surveillance,(dis) trust and teaching with plagiarism detection technology. In Proceedings of the 10th international conference on networked learning. https://www.networkedlearningconference.org.uk/abstracts/papers/ross_25.pdf

Sim, C. T. (2021). Barriers To Faculty Adoption Of Plagiarism Detection Software At A Canadian University https://dt.athabascau.ca/jspui/bitstream/10791/354/7/BARRIERS_TO_FACULTY_ADOPTION_OF_PLAGIARISM_DETECTION_SOFTWARE_AT_A_CANADIAN_UNIVERSITY%28REV6%29.pdf

Tripathi, S., & Patel, D. (2021). Academic integrity: looking beyond plagiarism. Annals of Library and Information Studies (ALIS), 68(2), 190-197. https://14.139.47.23/index.php/ALIS/article/view/46032/465479211

Weber-Wulff, D. (2019). Plagiarism detectors are a crutch, and a problem. Nature, 567(7749), 435-436. https://www.nature.com/articles/d41586-019-00893-5

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