Abstract
There is strong support for formative assessment inclusion in learning processes, with the main emphasis on corrective feedback for students. However, traditional testing and Computer Adaptive Testing can be problematic to implement in the classroom. Paper based tests are logistically inconvenient and are hard to personalize, and thus must be longer to accurately assess every student in the classroom. Computer Adaptive Testing can mitigate these problems by making use of Multi-Dimensional Item Response Theory at cost of introducing several new problems, most problematic of which are the greater test creation complexity, because of the necessity of question pool calibration, and the debatable premise that different questions measure one common latent trait. In this paper a new approach of modelling formative assessment as a Multi-Armed bandit problem is proposed and solved using Upper-Confidence Bound algorithm. The method in combination with e-learning paradigm has the potential to mitigate such problems as question item calibration and lengthy tests, while providing accurate formative assessment feedback for students. A number of simulation and empirical data experiments (with 104 students) are carried out to explore and measure the potential of this application with positive results.
Highlights
Formative assessment have been proposed to make education more accessible and more effective [1,2,3,4]
We start by presenting a set of simulations to systematically explore different properties of formative assessment using Upper-Confidence Bound (UCB) algorithm
At quiz lengths between 10 and 32 questions a substantial portion (4–38%) of students were assessed very poorly implies that using shorter assessments is morally questionable, as the majority of the students will receive a very accurate guidance, while the rest will be tutored on topics which they already know. This presents a problem for more important formative assessments. This property of the algorithm can be offset my small increase in quiz length as seen in Presented in this paper novel approach to formative assessment based on UCB algorithm shows promising results when compared to traditional assessment methods
Summary
Formative assessment have been proposed to make education more accessible and more effective [1,2,3,4]. The distinction between summative and formative roles of assessment was first proposed by Scriven [5] and applied to students by Bloom [6,7]. Formative assessment is intended to generate feedback on performance to improve and accelerate competency acquisition as opposed to summarizing the achievement status of a student [8,9]. Any learning activity has potential value as formative assessment from oral discourse to conventional quizzes [10]. Formative assessment should be viewed as an integral part of instruction, and it should be used in real time for guiding learning process. The material provided to students should depend on their current state of knowledge
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