FARMA-ALG-REBORN it is an app for teaching algorithms, focused in error mediaton between teachers and students. We belive that the error is part of the learning process and should not be ignored. However, it is not unusual to see classes with a lot of students and only one teacher to handle with them. Specially when it envolves programming, thinking in the quantity of output errors generated in a class: it is impracticable for a teacher analise all these outputs.
So FARMA-ALG-REBORN it is a tool to automatically save and analise these outputs, calculating the error similarity, exposing to the teacher the error cases pedagogically more relevant to the class.
Originally, FARMA-ALG was developed by Alex Kutzke in the Federal University of Paraná. FARMA-ALG-REBORN is a new implementation of the tool. This implementation intend to bring back the original features of the tool with upgrades, plus a module of gamification.
The implementation is in course and constantly updated in this repository.
Please note:
Deadlines issues allied to project scope changes made me ignore some good practices in code to have a finished version of the tool to be tested. This is a result of a search project, and should be evaluated for its purpose and functionality. A lot of code refactor can be done, and future steps of this work (after evaluate its practical result) include this.
This app is docker based. To avoid extra configurations, you should have docker and docker-compose installed in your machine.
If you don't want to install these softwares, you will be able to use this app installing:
- Free Pascal Compiler;
- ElasticSearch (>= 2.4.5);
- PhantomJS (>= 1.9) - Used to run tests in development;
- Postgres (>= 9.5);
- Ruby (>= 2.3).
Clone the repository: git clone https://github.com/rwehresmann/farma_alg_reborn.git.
In the repository folder, run:
docker-compose build;docker-compose run --rm app rake db:create;docker-compose run --rm app rake db:migrate;docker-compose run --rm app rake db:seed(only if you want to populate the db with sample data);docker-compose run --rm app rspec
If rspec finish without errors, you're ready to start. Run docker-compose up and access http://localhost:3000.
Fork the project, create a branch and send a pull request!