Ma Students' Viewpoints about Academic Misconduct, Its Reasons and Anti-Plagiarism Policies and Procedures in Iran
Bibliographic record
Abstract
IntroductionUniversity students can find all the information they need to do their assignments in the net and as a result this accessibility and popularity of the internet catapulted to a new height. In 2001 McCabe and his colleagues reported that roughly 82 percent of the students cheat. The most common definition of is using different sources without mentioning the source is called which is a problem in higher education. McCabe (2005) believed that the problem of is further aggravated by the advent of internet and the World Wide Web. Therefore, some certain rules must be observed to prevent the wanted or unwanted and academic misconduct.Plagiarism and academic misconducts appears to be steadily increasing not only across college and university campuses but also within other groups such as scholarly and scientific communities (Schrimsher, 2011). In the educational setting can attack the goal of academic integrity (Loutzenhiser, Pita & Reed, 2006). Plagiarism is not bound to a culture or country. Glendinng (2014) reported of a complete research undertaken for project Impact of Policies for Plagiarism in Higher Education across Europe (IPPHEAE). It is stated that Asian students have been proved of the largest number of students responding to (Introna, et al., 2003). As a result it is necessary for educators to have a comprehensive understanding of the status of and its related issues in Iran. In this line the main purposes of the present study are to find the familiarity of the students with academic misconduct and its different types, the most common reasons for doing plagiarism, and anti-plagiarism policies and procedures on the side of university and faculties in Iran.Review of literatureWith the popularity of the word plagiarism academic misconduct remains rife on universities worldwide. Scholars argue that attitudes toward academic misconduct are different in different cultures and countries. At western universities is widely assumed as ethically wrong and the risk of punishment is discovered (Wheeler, 2014). While Wheeler (2014) stated that in contrast negative connotations of do not extend beyond the west. He argued in East Asian societies there is little concept of word owner ship. As a result students don't hesitate to copy and paste or they think citing the original author is unnecessary. The author exemplifies Japanese students as a case in point.The first proposal for the Impact of Policies for Plagiarism in Higher Education across Europe (IPPHEAE) was developed during 2009. Before this time very little research had been conducted in European countries (Glendinning, 2014). McCabe (2005) reported data generated as part of Academic Integrity Assessment Project conducted by the Center For Academic Integrity at Duke University from 80,000 students and 12,000 faculty in the United states and Canada. The findings documented and cheating in those universities. To promote students' academic integrity he proposed honor code strategies.Marshal and Garry (2006) compared the attitudes and perceptions of non- English speaking background (NESB) with English speaking background (ESB). The results indicated that is not only common but also NESB students are more likely to engage in than ESB students.Academic misconduct can have different sources and can be considered from different aspects. Schrimsher (2011) gathered data from 681 students from Samford University about their attitude regarding plagiarism. The result indicated that faculty should clarify their expectations to prevent cheating or misconduct. The same results were obtained by Foltynek et al. (2014). It would appear that better understanding of student' educational need can help students to avoid in a more effective way.Moore (2014) researched on accuracy of referencing and patterns of in electronically published theses in Finland. …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".