Faculty Advisor or Committee Member
Prof Neil Heffernan, Advisor
Identifier
etd-042518-225911
Abstract
Prerequisite skill structure graphs represent the relationships between knowledge components. Prerequisite structure graphs also propose the order in which students in a given curriculum need to be taught specific knowledge components in order to assist them build on previous knowledge and improve achievement in those subject domains. The importance of accurate prerequisite skill structure graphs can therefore not be overemphasized. In view of this, many approaches have been employed by domain experts to design and implement these prerequisite structures. A number of data mining techniques have also been proposed to infer these knowledge structures from learner performance data. These methods have achieved varied degrees of success. Moreover, to the best of our knowledge, none of the methods have employed extensive randomized controlled trials to learn about prerequisite skill relationships among skills. In this dissertation, we motivate the need for using randomized controlled trials to refine prerequisite skill structure graphs. Additionally, we present PLACEments, an adaptive testing system that uses a prerequisite skill structure graph to identify gaps in students’ knowledge. Students with identified gaps are assisted with more practice assignments to ensure that the gaps are closed. PLACEments additionally allows for randomized controlled experiments to be performed on the underlying prerequisite skill structure graph for the purpose of refining the structure. We present some of the different experiment categories which are possible in PLACEments and report the results of one of these experiment categories. The ultimate goal is to inform domain experts and curriculum designers as they create policies that govern the sequencing and pacing of contents in learning domains whose content lend themselves to sequencing. By extension students and teachers who apply these policies benefit from the findings of these experiments.
Publisher
Worcester Polytechnic Institute
Degree Name
PhD
Department
Computer Science
Project Type
Dissertation
Date Accepted
2018-04-25
Copyright Statement
All authors have granted to WPI a nonexclusive royalty-free license to distribute copies of the work. Copyright is held by the author or authors, with all rights reserved, unless otherwise noted. If you have any questions, please contact wpi-etd@wpi.edu.
Accessibility
Unrestricted
Repository Citation
Adjei, S. A. (2018). Refining Prerequisite Skill Structure Graphs Using Randomized Controlled Trials. Retrieved from https://digitalcommons.wpi.edu/etd-dissertations/177
Subjects
Prerequisite Skills, Knowledge Components, Skills, Randomized Controlled Trials, Prerequisite Structure Graphs