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Never got it. Never really got it. Why do we have tests at school? Why do we measure the performance of training after the training by means of a summative assessment? The ones given at the end of a term to measure mastery of the content that was taught. The multiple-choice tests, or short essay questions, that result in a good or bad grade.
Sure, the lion’s share of students dislike taking pop quizzes, tests, and exams. I was one of those students. But even looking back as a former (!) student, now being an instructor and trainer myself, in hindsight I still do not understand why we so often measure the success of training mainly through these final assessments.
The primary reason why I don’t understand tests is that they generally do not give feedback that is timely or specific enough to improve learning while it is happening. Ultimately, the goal of the learning process is to learn as much as is needed to meet the goals of the training. The outcome of a test is often a single overall score, whereas what is needed is item-level feedback. I should not know only that I was wrong overall; I am supposed to know what went wrong, where. At least as importantly, if I were not able to keep up with the other students in my cohort on the goals of the teaching materials, I am not supposed to find out after the fact, but during the process itself.
And both the lack of on-time assessment as well as the lack of item-level feedback during that process are the problems I have with most tests, particularly summative assessments. That is the problem, but what is the solution?
Stealth Assessment
Imagine being tested without being aware of the fact that you are being tested. No test anxiety, no learning for the test, but simply determining whether you were able to keep up or not. There are various ways to implement an assessment under the radar: stealth assessment.
For instance, one can measure performance not through asking somebody what they know and what they do not know, but by monitoring their performance while conducting a task through physiological or behavioral signals. One could record brain activation and identify measures of mental workload. Wearing an EEG scanner that monitors brain activation, one could, for instance, monitor workload. We know that mental workload being too low (boredom) or too high (stress or overload) does not yield optimal performance. We could also track eye gaze and determine whether students pay attention to the relevant parts of the content they are supposed to pay attention to. We could even find out whether they are confused by monitoring whether they move their eyes erratically across the content. We could monitor heart rate, breathing patterns, or skin responses.
Now one could rightly argue these measures are hardly “under the radar.” In fact, they seem quite intrusive. But there are also less intrusive measures that can be used in training. For instance, one could monitor reading skills by computationally monitoring how a child moves a finger across the lines of a page. Young readers often scan their finger from word to word. Those finger movements may provide a useful proxy for aspects of reading fluency. One could monitor facial expressions or speech, or even how somebody sits in a chair. Such signals may reveal aspects of learning, even if they are not direct measures of learning itself.
These kinds of stealth assessments address the on-time assessment problem I identified earlier. They might also diminish test anxiety, but as an assessment tool they do not yet fully address the feedback problem.
Adaptive Training
What if the stealth assessment is linked to the training itself? Based on whether I can keep up with the learning content, the learning content adapts itself. In traditional classroom education, this is hardly feasible because the content is presented the same way for everybody at the same time. But if the content were to change based on my performance, measured by stealth assessment, a perfect feedback loop emerges.
These feedback loops are often labelled as brain-computer interfaces, technologies that use neurophysiological signals and send them directly to external devices. Although such systems are not yet widely implemented in educational environments, they have been used in flight training in virtual reality. The advantage of VR is that it provides personalized learning and allows for different experiences for individual learners. By continuous monitoring of the level of performance of the learner in stealth mode, the VR simulation can adjust itself to the trainee. If I do not keep up with the performance on a particular task, but already excel on another task, then the VR system will offer me more training opportunities on the task I do not quite excel at yet.
Whether or not these systems will be applied in the educational system is uncertain. But thinking about them is exciting because it requires rethinking the educational system. Poor performance is no longer merely an observation at the end of the process, but becomes an opportunity to adapt learning while it is happening. The end of the learning process is not that some pass and some fail, but that most perform at the optimal level aimed for. At the very least, it would resolve that one long-standing learning problem: my inability to understand tests.
