# Analysis of Student Academic Performance Using Human-in-the-Loop Cyber-Physical Systems
## 5 Conclusions and Future Direction  
This work presents a study on the use of ISABELA, a specifically developed student-centric application, which analyzes student behavior and its relationship with their academic performance. This sensing system is a nonintrusive platform to obtain data, as it passively captures the data without requiring any input from the user. We have shown that there is a significant correlation between the GPA and the time spent at university. Despite this study being exploratory, the results led us to conclude that a higher percentage of attendance at classes in the Ecuadorian educational scheme can help students to improve their academic performance.  
In addition, we obtained strong correlations between the sensing data and the information collected with the questionnaire, which shows that there is a harmony between them and opens the way, in the future, to reduce the amount of questions in the questionnaire.  
The academic performance of students could be influenced by other factors such as sleep quality, physical activity, study time, amongst others. For this reason, we will continue our study to obtain more information and demonstrate these influences.  
There are other factors that could also affect the academic performance such as lighting and noise levels in the classroom, and technologies used in classes, etc. As a direction for future study, we hope to use IoT technology to obtain information about the environment where the students are studying, focusing on future communication trends related to IoT services and applications.  
An IoT box has been implemented to collect this information and to determine how these new values can help to improve the academic performance. It will be interesting to analyze the European reality in this area and compare it with the Latin America one. Nowadays, we are using ISABELA to study the reality in several educational institutions in Portugal.  
Figure 7: _StudyQ_ and Sleep Quality (SQ) reported.  
**Author Contributions:** All authors contributed to the conceptualization and discussed the paper; [PERSON] wrote the original draft, developed and performed tests and data analytic; [PERSON] contributed in the tests; [PERSON], [PERSON] and [PERSON] participated in the implementation and tests, [PERSON], [PERSON] and [PERSON] supervised this work, review and editing. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research The work presented in this paper was partially carried out in the scope of the SOCIALITE Project (PTDC/EEI-SCR/2072/2014) and the MOBIWISE Project (P2020 SAICTPAC/0011/2015), both co-financed by COMPETE 2020, Portugal 2020 - Operational Program for Competitiveness and Internationalization (POCI), European Union's ERDF (European Regional Development Fund) and the Portuguese Foundation for Science and Technology (FCT). Partial support was also given by Escuela Politecnica Nacional of Ecuador, and SENESCYT - Secretaria Nacional de Educacion Superior, Ciencia, Tecnologia e Innovacion of Ecuador.  
**Conflicts of Interest:** The authors declare no conflict of interest.