# Analysis of Student Academic Performance Using Human-in-the-Loop Cyber-Physical Systems
## 3 Methodology
### Measures  
The ISABELA study had three stages: orientation, data collection, and test finalization.  
During the orientation phase, the students accepted the terms of consent for the use of their data, collected anonymously, and gave the necessary permission. In addition, they were given a tutorial on  
Figure 2: ISABELA cloud.  
the installation and use of the ISABELA application; a major concern was to ensure they understood the importance of answering and submitting the questionnaire daily. This questionnaire was part of the ISABELLA application and easily accessible in the main menu. All the students enrolled in the study had a mobile phone with the Android operating system on which the application was installed.  
The collection stage lasted 30 days between May 14 and June 12, within the first academic period of the semester (April-August 2018). The test days included the evaluation period of the first bimester.  
It should be noted that the data stored through the ISABELA application comes from two types of sources: mobile phone sensors and the questionnaire answered daily by each student.  
The data collected through the sensors available on the mobile phone were (Figure 3):  
* Location: university, house, and other;
* Physical activity: exercise, still, walking, in vehicle, and unknown;
* Sociability: number of SMSs sent and received; number of calls made, received, and lost; duration of the calls; number of different destinations for calls and SMSs.  
The data obtained through the questionnaire were measured with a scale between 0 and 4 as follows:  
* Sociability state: (4) very high, (3) high, (2) medium, (1) low, and (0) very low;
* Sleep quality: (4) very good, (3) good, (2) normal, (1) bad, and (0) very bad;
* Amount of study: (4) a lot, (3) fairly, (2) moderate, (1) little, and (0) nothing.  
Sensor data were collected and stored automatically, while the explicit participation of the students was necessary to obtain the data from the questionnaires. The average number of times the information of questionnaires was sent during the testing period was approximately 19 times per student. In case the student did not have an Internet connection, the data were stored on the mobile phone, and when there was a connection, either via WiFi or cellular network, data were sent to the ISABELA platform. During the data collection period, a web-based monitoring solution based on freeboard.io was used to observe the information received in real time.  
To ensure the students' privacy, all the data sent to the ISABELA cloud was saved with a student ID obtained by applying a secure hash function to the real student ID. This way it was not possible to associate the data saved on the cloud with any student.  
After analyzing the collected data, we sent the information to the student through the chatbot; this involved the system sending some recommendations related to the time spent in the university, as well as changes to their activity in cases where the student had been inactive for a long period of time (Figure 4).  
Figure 3: ISABELA application interface of Localization.