Curb cheating in Master's project

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dc.contributor.author Bellows, Scott
dc.date.accessioned 2018-07-12T15:26:23Z
dc.date.available 2018-07-12T15:26:23Z
dc.date.issued 2018-06-27
dc.identifier.uri http://erepo.usiu.ac.ke/11732/3902
dc.description A Newspaper article by Scott Bellows, an Assistant Professor in the Chandaria School of Business at USIU-Africa en_US
dc.description.abstract In conclusion of the Business Talk mini series on Kenyan higher education, graduate student research supervisors should incorporate the following techniques into their assessment of projects and theses to significantly reduce the high prevalence of master’s project cheating. First, nearly all students do not know how to do the quantitative analysis portion of the project. Business statistics courses often show pre-computer formulas and do not provide step-by-step instruction on how to conduct and interpret robust quantitative analysis. Instead of supervisors making the false assumption that students know how to write the analysis section of their thesis by the time they get assigned a research supervisor, the supervisor should rather know that the master’s student likely does not comprehend how to already do analysis and, unless shown by the supervisor how to do it, will likely cheat to get it done by using third party paid writers. Inasmuch, supervisors should require students to show them all the physical hard copies of the filled-out surveys along with the signing sheet where questionnaire respondents provide their names, signatures, and sometimes identification numbers. Supervisors should check against false completion whereby the same handwriting, pen, and unnatural patterns appear in the surveys, indicating that the sample population did not really fill them out. Second, the supervisor should do a spot check of the student’s data entry accuracy. Compare several original surveys and the data entered into Excel, Nvivo, Stata, or SPSS. Then the supervisor should check the data entry parameters to make sure the student entered the right type of data, such as ordinal, nominal, or scale and the correct width and decimals. In quantitative projects, the supervisor can then quickly and easily on a one by one basis show the student how to do descriptive statistics, Cronbach’s alpha reliability tests, create summated scales, run correlations matrix, variance components, t-statics, and multiple regressions. More complicated exploratory factor analysis and confirmatory factor analysis in structured equation modelling requiring AMOS or Mplus software is usually reserved for doctoral students. en_US
dc.publisher Business Daily en_US
dc.subject Society en_US
dc.title Curb cheating in Master's project en_US
dc.type Article en_US

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