The aim of this interactive workshop is to demonstrate the ease and speed with which Multiple Choice Tests can be implemented, and their power to contribute to student learning, class quality, and administrative efficiency, especially for UAs.
There are a plethora of reasons for conducting assessment: certification (perhaps the most important in terms of our core business), understanding student progress, helping the student understand their progress and so on. However, most assessment practices tend to focus on one or the other, often with inconsistent resource utilisation. In many cases, the “horse has bolted” by the time students receive the feedback needed to improve grades in the next round of assessments.
The six-week timeframe of the SCU Model places considerable pressure on the assessment regime and especially on the teachers who have to mark students’ work and return it to them before the next assessment.
The use of Multiple Choice Tests (MCTs) is debated to some extent (Butler, 2018): they are seen as superficial and encouraging only surface-level learning. Whilst this can happen, it does not have to be so. It is possible to develop sophisticated and complex MCTs that assess the student’s knowledge, analysis and reflection. Also, when used in low-risk assessments for knowledge recall, MCTs are particularly helpful. And, with the advent of GenAI tools like ChatGPT4, this can be done quickly and efficiently. Finally in this part of the introduction, given that students can access GenAI tools, MCTs, like all other assessments, can only be secured when done in real-time and under supervision – i.e. in class, and ideally, early in the class.
In BlackBoard, our Learning Management System, teachers can quickly set up a MCT (especially if the questions are generated via GenAI). Also, the system can automatically assess the students providing immediate feedback on their results. Better still, the diagnostics built into BlackBoard can provide the teacher with a whole of class assessment of their level of knowledge in almost real-time. This information can then prove valuable in shaping the direction of the class.
In this presentation, I will demonstrate:
- How GenAI can quickly produce a 10 question MCT.
- How the MCT can be administered early in the class.
- How the MCT immediately marks students’ answers – which they can see. AND
- How the MCT diagnostics can be used by the teacher to shape the focus of that class.
Critically, the MCT diagnostics can be shared with the students and used to provide focus for that class whilst the assessment activity and its content is fresh in their minds.
As a result of this workshop colleagues will have an insight to, and better understanding of, how they can fine tune their assessment regime and F2F classes to improve student learning outcomes.
Postscript: since this submission, BlackBoard has introduced an integrated GenAI tool to support teachers with unit content and assessment.
Butler, A. C. (2018). Multiple-choice testing in education: Are the best practices for assessment also good for learning? Journal of Applied Research in Memory and Cognition, 7(3), 323–331. https://doi.org/10.1016/j.jarmac.2018.07.002