More tools for Canvas : Realizing a Digital Form with Dynamically Presented Questions and Alternatives

Abstract: At KTH, students who want to start their degree project must complete a paper form called “UT-EXAR: Ansökan om examensarbete/application for degree project”. The form is used to determine students’ eligibility to start a degree project, as well as potential examiners for the project. After the form is filled in and signed by multiple parties, a student can initiate his or her degree project. However, due to the excessively time-consuming process of completing the form, an alternative solution was proposed: a survey in the Canvas Learning Management System (LMS) that replace s the UT-EXAR form. Although the survey reduces the time required by students to provide information and find examiners, it is by no means the most efficient solution. The survey suffers from multiple flaws, such as asking students to answer unnecessary questions, and for certain questions, presenting students with more alternatives than necessary. The survey also fails to automatically organize the data collected from the students’ answers; hence administrators must manually enter the data into a spreadsheet or other record. This thesis proposes an optimized solution to the problem by introducing a dynamic survey. Moreover, this dynamic survey uses the Canvas Representational State Transfer (REST) API to access students’ program-specific data. Additionally, this survey can use data provided by students when answering the survey questions to dynamically construct questions for each individual student as well as using information from other KTH systems to dynamically construct customized alternatives for each individual student. This solution effectively prevents the survey from presenting students with questions and choices that are irrelevant to their individual case. Furthermore, the proposed solution directly inserts the data collected from the students into a Canvas Gradebook. In order to implement and test the proposed solution, a version of the Canvas LMS was created by virtualizing each Canvas-based microservice inside of a Docker container and allowing the containers to communicate over a network. Furthermore, the survey itself used the Learning Tools Interoperability (LTI) standard. When testing the solution, it was seen that the survey has not only successfully managed to filter the questions and alternative answers based on the user’s data, but also showed great potential to be more efficient than a survey with statically-presented data. The survey effectively automates the insertion of the data into the gradebook.