Wodel-Edu

Wodel-Edu: an MDE solution for the generation and evaluation of exercises

Wodel-Edu is an extension to Wodel for the automated generation of exercises. It generates seven kinds of exercises:

• Alternative response: the student has to tell if the diagram or the textual representation is correct or not.
• Multiple diagram choice: the student has to tell which of the shown diagrams is correct.
• Multiple text choice: the student has to tell which of the shown textual representations is correct.
• Multiple emendation choice: the student has to tell which text options fix the shown diagram.
• Match pairs choice: the student has to match the statement on the left with the correct option of the drop-down list.
• Missing words choice: the student has to complete the gaps of the text shown with the correct options in the drop-down lists to match the statement.
• Text drag and drop: the student has to complete the gaps of the text shown with the correct options of the set of texts presented as labels in categories to match the statement.

With this purpose, Wodel-Edu provides 4 DSLs along with Wodel:

eduTest: DSL for the configuration of the questionnaire, and the exercises' definition:

navigation=free
MultiChoiceDiagram simple {
    retry=no
    description for 'exercise4.model' = 'Select which of these automata
                                         accepts only "a*bab*"'
}
MultiChoiceEmendation complex {
    retry=no, weighted=no, penalty=0.0,
    order=options-descending, mode=checkbox
    description for 'exercise5.model' = 'Select the required changes so that
                                         the automaton accepts only "a+b+"'
}
MatchPairs rfs1, mts2, rfs2 {
    retry=no
    description for 'exercise6.model' = 'Select which of these options modifies
                                         the above automaton to accept only
                                         the language defined by ' %text('reg-exp')
}
MissingWords mtsrfs1 {
    retry=no
    description for 'exercise7.model' = 'Complete the following text with the
                                         options for each gap that modify this automaton
                                         to accept only the language defined by "ab(ba)*"'
}

modelDraw: DSL for the models' graphical visualization. It uses alternatively Graphviz and Circuit Macros for model renderization:

metamodel "http://dfaAutomaton/1.0"

Automaton: diagram {
    State(isInitial): markednode
    State(not isFinal): node shape=circle
    State(isFinal): node shape=doublecircle
    Transition(src, tar): edge label=symbol.symbol
}

modelText: DSL for the configuration of models elements text identification (optional):

metamodel "http://dfaAutomaton/1.0"

>State: State %name
>State(isFinal): final
>State(isInitial): initial
>Transition: Transition %symbol.symbol
>Transition.tar: target
>Transition.src: source

mutaText: DSL for the configuration of text options shown in the multiple emendation choice, match pairs, missing words, and text drag and drop test exercise kinds (optional):

metamodel "http://dfaAutomaton/1.0"

>TargetReferenceChanged: Change %object from %fromObject
                         to %toObject with new %refName %oldToObject /
                         Change %object from %fromObject to %oldToObject
                         with new %refName %toObject
>AttributeChanged: Change %object to %oldValue /
                   Change %object to %value

You can view an example of a test exercises web application generated with Wodel-Edu at www.wodel.eu.

We are currently working on the generation of exercises for the Moodle platform. You can access our private Moodle here and see: moodle.wodel.eu (user: demo; password: Wodel-Edu4Moodle).

This is a short video demo of Wodel and Wodel-Edu:

New: Automated generation and correction of diagram-based exercises for Moodle with Wodel-Edu:

Here you can download an example of Wodel-Edu.
Wodel-Edu samples .zip
Wodel-Edu samples .tar.gz

Acknowledgements

This work has been funded by the Spanish Ministry of Science (RTI2018-095255-B-I00, project "MASSIVE") and the R&D programme of Madrid (P2018/TCS-4314, project "FORTE").