Motivation behind parameterized exercises

Abstract

We have already discovered that “The authoring of parameterized exercises has been an useful activity both for teachers, who could take advantage of databases of parameterized exercises for preparing study materials, but also for master students that learn by producing new problems.” We’ve considered two aspects of motivation: (a) motivation inspired by the effective use of the final product by teachers and students, i.e., several online versions of exercises to be practiced by students and materials for textbooks, evaluation or diagnosis, and (b) motivation of the creative process itself to build parameterized exercises in an online environment. It’s clear that these are motivations from a “connected learning world”. The first one, (a), already presented in [2], approaches motivation on the perspective of the use of parameterized exercises making an analogy with the R´s from the environmental studies (reuse, recycle, reduce,...). The second form of motivation, (b), can be seen as the personal motivation in the process of “playing” with a small computer Domain Specific Language (DSL) for creating parameterized exercises. Producing these exercises requires a computer coding language and we have chosen Python because of its simplicity and relatedness to mathematics. Our study focus on improving the DSL to conceive parameterized exercises with mechanisms that promote motivation on the creative process. We found out that not all mathematics teachers, who are not regular programmers, are very fond of programming, so we are developing a challenging mechanism to be included in the DSL, in order to keep authors (as teachers) motivated on the process of creating new exercises. This method of deploying parameterized exercises uses LaTeX behind the scenes and, when needed, HTML for web publishing, as the main vehicle. Our exercises are mainly for STEM math courses. This success inspired us to produce a fine tuning of this DSL that will be used from now on. The new DSL contains more robust features: error control, specification of coding language and the obligation to specify decision variables that will conduct the “factory” in the process of building a new exercise. This work is embedded in a project called MEGUA where the focus is a package to build parameterized exercises.