The Exercise Class

In PyRope, every exercise is modelled by a separate subclass of the pyrope.Exercise class. This subclass serves as a container to put together variables that contain metadata and functions that implement the different elements of an exercise.

If you are not familiar with classes: Don’t worry! You do not need to know about object oriented programming to write exercises in PyRope. You only need to keep a couple of things in mind:

In simplified terms, a class is nothing but a way to bundle variables and functions together.
The variables in a class are commonly called attributes and its functions methods.
Methods have an additional first parameter, called self by convention.

Unless you want to use particular exercise types such as single or multiple choice, the pyrope.Exercise class is the only class you will come across when writing basic exercises.

If you are familiar with classes: The methods of the pyrope.Exercise class are not meant to be called directly, as there is a lot of magic behind the scenes. If you intend to access the data derived in the course of an exercise, have a look at the pyrope.core.ParametrizedExercise class.

Exercise Methods

The different actions that have to be performed when running an exercise interactively are modeled by particular methods of the pyrope.Exercise class and will be explained in more detail below.

Method	Short description
`preamble()`	give some context information
`parameters()`	generate randomised parameters
`problem()`	construct a template with the statement of the problem
`the_solution()`	give a unique solution
`a_solution()`	give a solution that is not necessarily unique
`hints()`	provide hints on how to solve the exercise
`scores()`	score the learner’s answers
`feedback()`	provide feedback based on the learners answers

Exercise Attributes

Exercise metadata is stored in attributes of the pyrope.Exercise class. The use of metadata is not mandatory, but strongly suggested. The following is a list of recommended metadata attributes which will be recognised by PyRope. A more verbose description of exercise metadata attributes can be found in the example template pyrope.templates.QuadraticEquation.

Attribute	Meaning
title	short description of the exercise
subtitle	additional information
author	author with email in the form `John Doe <john.doe@infinity.org>`
license	software license
URL	URL, where the exercise can be found
pyrope_versions	PyRope version(s) the exercise has been tested with
origin	origin from which the exercise is derived, inspired or translated
discipline	main discipline of the exercise, such as “mathematics” or “physics”
area	area of the exercise, such as “linear algebra” or “mechanics”
topics	topics the exercise covers
keywords	keywords characterising the exercise
language	natural language in which the exercise is presented
taxonomy	taxonomy according to Bloom

Commentѕ

There is no explicit convention for metadata names either, but if you stick to the naming in the table above, you facilitate easy filtering of exercise pools based on keywords or search patterns.
Avoid metadata depending on context, such as a course name or the difficulty of the exercise.
If used, the above attributes must be strings.
The attributes author, discipline, area, topics, keywords and taxonomy each can also be a tuple of strings, ordered by relevance.
An exercise can easily be translated into other languages by replacing only the language specific methods, i.e. the preamble(), problem(), hints() and feedback() methods. Metadata, documentation and comments should therefore be written in English.
Exercise definitions are actually source code. So one should give a software license, preferably a liberal one to make the exercise an Open Educational Resource.