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Individualised Project Assessments for Statistics Courses - the Best of Both Worlds?
| Content Provider | Semantic Scholar |
|---|---|
| Author | Grant, Robert Younis, Ahmed |
| Copyright Year | 2014 |
| Abstract | Examinations in statistics have been criticized for failing to assess analytical thinking and practical problem-solving skills. Project-based assessment is a widely used alternative, but detection of plagiarism is a concern as students should arrive at the same results. Definition of plagiarism is also difficult; sharing ideas on methods is a positive learning experience, while sharing results and computer output is not. Creating a different dataset for each student can resolve these problems but requires automation to be feasible. We describe the experiences gained from programming a general algorithm for this in R and SPSS and piloting in two years of postgraduate healthcare research methods students. There is potential to introduce unfairness if the requirements of analysis, such as post-hoc testing, are not identical in all datasets. Our algorithm creates multiple datasets that are constrained to differ enough to be identifiable, while also sharing exactly the same analytical requirements. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://icots.info/9/proceedings/pdfs/ICOTS9_C188_GRANT.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
