Dataset of adaptive Children-Robot Interaction for Education based on Autonomous Multimodal Users' Readings

# Dataset of adaptive Children-Robot Interaction for Education based on Autonomous Multimodal Users’ Readings 

## Background

This dataset is generated from multiple interactions between a Social Robot (NAO) and 5th grade students from a private school in São Paulo, Brazil. 

In the interaction, the robot approached the content that teachers were approaching at the time with the participants students about the wasting system in Brazil.

The measures here are the readings that the R-CASTLE system did for each answer the students gave to the questions the robot asked. 

For more information about how these measures were collected, please refer to this thesis at:  https://doi.org/10.11606/T.55.2020.tde-31082020-093935

Since the goal of the R-CASTLE is to provide autonomous adaptation, we built a ground-truth dataset based on human feedback of an expert in education operating the robot in loco. The person was teleoperating the robot to change its behaviour (or not) according to observed values of the participants as Face Gaze, Facial emotion displayed, Number of spoken words, the correctness of the answer (based on pre-defined answers), and the time students took to answer. These measures are the 5th columns of this csv file. The evaluator could decide to increase (1), maintain (0), or decrease (-1) the level of difficulties of the following questions depending on the mentioned observed measures. This is the human true label, stored in the 6th column.   

## Description:
Each row of this file is a tuple of the autonomous reading the robot made in the 5 first columns, plus the true label in the 6th row (True Value) and the Final Crisp Value using fuzzy classification in the 7th row (Final Crisp Value).

Deviations (integer): number of face deviations of the participant during the question answering identified by the system.

EmotionCount (integer): a balance between "good" and "bad" emotions (good - bad) identified by the system.

NumberWord (integer): number of words comprised in the sentence the participant gave.

SucRate/Ans/RWa: (between 0 and 1, where 0 is completely wrong and 1 is completely right): The success rate of the participant’s answer to that question, based on the expected answer programmed by their teachers.

Time2ans (float): The time spent to answer the question since the robot has finished the question until the end of the participant’s speech in seconds.

True Value (-1, 0, 1): Ground-truth value. Value of adaptation chosen by the human observing the interaction if the system needed to decrease, maintain, or increase the level of difficulty of asked questions.    

Final Crisp Value (float): value of calculated fuzzy output based on the implementations in the paper: https://doi.org/10.1145/3395035.3425201

## Creators 
Daniel Tozadore: dtozadore@gmail.com
Roseli Romero: rafrance@icmc.usp.br

## License: 
[Creative Commons Licenses](https://creativecommons.org/share-your-work/cclicenses/)