https://github.com/brains-on-code/tapping-into-the-natural-language-system-using-artificial-languages-when-learning-programming

Replication package and supplementary materials for our Brocanto paper.

https://github.com/brains-on-code/tapping-into-the-natural-language-system-using-artificial-languages-when-learning-programming

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Replication package and supplementary materials for our Brocanto paper.

https://github.com/brains-on-code/Tapping-into-the-Natural-Language-System-Using-Artificial-Languages-when-Learning-Programming/blob/master/

# Tapping into the Natural Language System with Artificial Languages when Learning Programming

This repository contains additional information to our paper: "Tapping into the Natural Language System with Artificial Languages when Learning Programming".


## Appendix
In this appendix, we show more details about the experiments and the results.

### Structure of the repository
The repository is divided into the following folders: 

1. material: script and tasks of the programming pre-course. questionnaire, pretest, posttest, the programming task of the posttest and interview transcripts.
2. data: data of our course.
3. data_analysis: script to evaluate or data. 
4. figures: plots created by our data analysis.


### Additional Data: Group division according to pretest (maximum: 8 points)
| Group       | Age | Gender | Pretest Score | Group | Age | Gender | Pretest Score |
|-------------|-----|--------|---------------|-------|-----|--------|---------------|
| Brocanto    | 19  | m      | 2             | Git   | 22  | m      | 0             |
| Brocanto    | 25  | m      | 0             | Git   | 18  | m      | 0             |
| Brocanto    | 28  | m      | 5             | Git   | 18  | m      | 5             |
| Brocanto    | 18  | m      | 7.5           | Git   | 18  | m      | 8             |
| Brocanto    | 32  | f      | 5.5           | Git   | 24  | m      | 5             |
| Brocanto    | 21  | m      | 6             | Git   | 29  | m      | 7             |
| Brocanto    | 18  | f      | 7.5           | Git   | 18  | m      | 8             |
| Brocanto    | 18  | m      | 6             | Git   | 18  | m      | 6             |
| Brocanto    | 19  | m      | 8             | Git   | 20  | f      | 8             |
| Brocanto    | 19  | m      | 3             |
| Brocanto    | 22  | f      | 2.5           |


### Additional Data: Mean scores and standard deviation of pretest, posttest, and posttest programming task
| test                 | Brocanto Group | Git Group  |
|----------------------|----------------|------------|
| pretest              | 4.56  3.05    | 5.00  3.08 |
| posttest             | 7.19  0.92    | 7.30  1.10 |
| posttest programming | 7.50  1.07    | 7.30  1.56 |


### Post-Programming Tasks: 
In their first semester, students attend the course Algorithms and Programming, in which they submit 7 assignments on various programming constructs throughout the semester. Students can achieve a total of 50 points. The course instructor provided us with an overview of points that students of our study achieved. This allows us to evaluate whether learning Brocanto has a long-term effect on programming learning.

# Replication

If you want to replicate the experiment, you will find all the necessary materials in the materials folder. 

Use the questionnaire at the beginning and the pretest afterwards. 

Next/the next day you will use the Brocanto tasks or the Git tasks. For Brocanto you need the software PsychoPy. You will find an instruction in the folder material - Brocanto. For the introduction to Git, GitHub Desktop was used. 

This is followed by the actual programming pre-course. Its order is chronological. In our study, we did not manage to cover all the content. The last chapter was for loops. 

Finally, use the posttest and posttest programming assignment to catch both reading and writing programs. If you have taught all the content of the programming course, then Rainfall would be more appropriate as a programming task. 

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