Educational Concerns Case Study-Free-Samples-Myassignmenthelp.com

Questions: 1.What Should She Do? 2.With Whom Should She Discuss The Issue, If Any ? 3.Is There A Designated Person At Your Institution To Deal With Such Issues? Answers: 1I would like to suggest that she should not allow that research to be published in its current state until when real data is found to undo the analysis. .should face her advisor fessed up as a means to stop the publication of the fake data because honestly is the only way forward as far as this case is concerned, since she hopes that it will be a Ph.D. dissertation. Of course her advisor will be pretty angry at first but since she hopes it will be her Ph.D. dissertation research he might sympathize. It will be very uncomfortable at first, but in the end things will probably work out. The alternatives to be found out at some point for a dishonest publication. It is illegal or rather risky for anyone to weasel his /her way out of academic fraud (simonsohn,2013). The best way out is to practice the ethical thing. She can also consider to change her username and profile picture to avoid considerable splash damage when he goes down. Anonymity is your friend here due to the issue at hand or else back off. Also his bad reputation is going to stain your career and it will be at risk. Since she has controvertible evidence of his fabricated data, it is more than enough to ascertain his academic dishonesty. If she can afford to report, then she should do it because he is robbing legitimate researchers of their funding and he will make people lose their money and time. 2.I suggest that she should contact restactionwatch.com, they run a well-known blog that deals with academic and scientific fraud. 3.Yes. Their core value is to ensure integrity and honesty in the institutional publications. References Simonsohn, U. (2013). Just post it: The lesson from two cases of fabricated data detected by statistics alone. Psychological science, 24(10), 1875-1888. Hill, T. P. (1996). A note on distributions of true versus fabricated data. Perceptual and Motor Skills, 83(3), 776-778.