The situation I have in mind is concerned with teaching introductory probability and statistics to business students, and there may be similar situations in other fields. Because of the risks associated to cheating in exams where computers are allowed, exams are restricted to basic hand-held calculators and datasets are consequently very small : compute mean and standard deviation for less than 10 data points, etc. As the material gets more complex (regression analysis) the sole option is to ask about analysis of printed computer output.
As a consequence, a lot of time is spent both in class and in student study time on learning such useless skills as computing standard deviations with a calculator (even I get it wrong half the time). This in turn leaves less time to teach what actually is useful : doing basic analysis with the computer (Excel, to start with). Another consequence is that it turns the students off any interest for the material as they understand that what is taught in class has little relevance for practice.
- time is wasted on outdated methods
- useful skills remain untested and mostly unlearned
- relevance is lost (course is "boring")
I would rather avoid complex, time-consuming and costly methods of computer surveillance. Blocking wifi (jamming) internet access during exams is not an option due to local legislation and there is no access to a lab (students have to have their own laptops). Having the students use their computers as cheat-sheets is less of a concern.
So my question is: how can I improve the situation?
The main objective is to bring in more computer-assisted skills while limiting the opportunities for cheating.