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|title=Mobile Application for the Registration and Control of Student Attendance at the Universidad Católica de Santa María Based on Google Technologies and Machine Learning
|pdfUrl=https://ceur-ws.org/Vol-3693/paper16.pdf
|volume=Vol-3693
|authors=Nicolás E. Caytuiro-Silva,Eveling G. Castro-Gutierrez,Jackeline M. Peña-Alejandro,Karina Rosas-Paredes,Jose Sulla-Torres
|dblpUrl=https://dblp.org/rec/conf/jinis/Caytuiro-SilvaG23b
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==Mobile Application for the Registration and Control of Student Attendance at the Universidad Católica de Santa María Based on Google Technologies and Machine Learning==
https://ceur-ws.org/Vol-3693/paper16.pdf
Mobile application for the registration and control of
student attendance at the Universidad Católica de Santa
María based on Google technologies and Machine
Learning
Nicolás E. Caytuiro-Silva1, Eveling G. Castro-Gutierrez1, Jackeline M. Peña-Alejandro1,
Karina Rosas-Paredes1 and Jose Sulla-Torres1
1 Universidad Católica de Santa María, Urb. San José s/n Umacollo, Arequipa, Perú
Abstract
The constant evolution of emerging technologies in the midst of the digital era highlights the need to
replace traditional methods of student attendance registration in universities. Often, students record
their attendance at the beginning of classes. This method can divert students' attention during class, and
the time it takes for the teacher to record attendance increases significantly [1], considering the number
of students enrolled in certain subjects. In this context, this research proposes the development of a
mobile application for the Android operating system for attendance registration and control for
students at the Universidad Católica de Santa María (UCSM) using the XP (Extreme Programming)
project management methodology. The phases of XP detail the entire process for the development of
the application and its launch, with Firebase as the Database Manager. To conduct the respective tests
of the application, tests were carried out on fourth-year students of Systems Engineering, belonging to
the Faculty of Physical and Formal Sciences and Engineering at UCSM. The attendance system was
connected to a database that stores information about students and their attendance records.
Additionally, the user interface displays attendance records from an attractive, intuitive, and easy-to-
manage perspective for both teachers and students. The research results show that the use of the
application by UCSM teachers and students reduces and optimizes the time invested in the attendance
registration process compared to traditional methods, according to the satisfaction and acceptance
criteria of the "ASYS" application.
Keywords
Emerging technologies, Mobile application, Attendance system, Android, XP Methodology, Google
technologies, Machine Learning. 1
1. Introduction
In the January-February-March 2021 quarter, out of the total internet user population, 88.5%
accessed it through mobile phones or smartphones, 16.7% through laptops, and the rest through
other internet-connected devices [2]. When compared to the same quarter in 2020, there is a 0.6
percentage point increase in internet access via mobile phones. This figure is expected to rise
further in 2022. The usefulness of mobile phones lies in applications. There are various
advantages to using mobile applications, particularly in the educational perspective. For example,
manual attendance registration by teachers can be time-consuming and prone to errors [3]. It can
also consume teachers' time when calculating averages. The use of a mobile attendance system
eliminates the drawbacks of the manual system.
The primary motivation for this research is to optimize the time spent by teachers in taking
attendance, especially when dealing with a large number of students. Additionally, the goal is to
gain experience in developing mobile applications as part of professional growth, utilizing
JINIS 2023: XXX International Conference on Systems Engineering, October 03–05, 2023, Arequipa, Peru
nicolas.caytuiro@ucsm.edu.pe (N. Caytuiro); ecastrog@ucsm.edu.pe (E. Castro); jackeline.pena@ucsm.edu.pe (J.
Peña); kparedes@ucsm.edu.pe (K. Paredes); jsullato@ucsm.edu.pe (J. Sulla);
0000-0003-1656-396X (N. Caytuiro); 0000-0002-0203-041X (E. Castro); 0000-0002-3586-1826 (J. Peña); 0000-
0003-4650-7432 (K. Rosas); 0000-0001-5129-430X (J. Sulla)
© 2023 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
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methods and new technologies such as database management, persistence, authentication, and
storage with Firebase, and the BrainShop Machine Learning kit [4]. The aim is to create a well-
organized, robust, and consistent application capable of meeting all the basic needs for its launch,
following all stages of the XP methodology.
This paper is organized as follows. Section II provides a general overview of various previous
studies on methods implemented for student attendance systems using mobile applications.
Section III details the application implementation process through the XP methodology. In
Sections IV and V, the results and discussion are outlined after testing the application with 100
students from the Faculty of Physical and Formal Sciences and Engineering at the Universidad
Católica de Santa María during one month in the odd academic semester 2022-I. Finally, Section
VI presents the research conclusions.
2. Related Work
In this section, we conduct a systematic review of related works in the development of mobile
applications focused on student attendance tracking, with a focus on time optimization and
resource use in this process. We also explore those that use cloud-based technologies and their
implementation through the use of the XP methodology.
In [5], an automated solution is presented, where a mobile application based on JAVA was
developed. It wirelessly connected to a central Database created using MySQL, tasked with
registering attendance information. The system was implemented in a university to record
student data, absence and presence times, and accumulated attendance per month, resulting in
effective and efficient system use. Similarly, in [6], an application was developed for Android and
iOS devices to register student attendance as an alternative to manual methods. The proposal
includes an application dedicated to teachers and students, displaying information such as the
courses taught by teachers and the courses in which students are enrolled. Attendance data is
synchronized with the Moodle platform, reflecting this information on the virtual platform. Tools
used for development include MariaDB as the database manager and Web Services for application
synchronization with the Moodle and institutional databases. The implementation is justified
through a survey where 100% of teachers would support the use of an application for attendance
and rated its use and synchronization with the virtual platform at 4.8.
Figure 1: Block diagram of the attendance system presented in [5]
On the other hand, [7] presents a study where information from 367 students was collected to
measure attendance in classes, online learning activities, and performance in online formative
assessments. This study applied learning analysis methods to measure attendance, online
learning activities, and performance in online formative assessments. The research results
contribute to understanding the impact of class attendance on course academic performance and
the interaction of participation factors in online learning in the context of technology-enhanced
courses.
In the research conducted by [8], a proposed solution to the attendance control problem is
presented, consisting of the development of a hybrid Android application prototype. This was
achieved by employing open-source technologies such as the Ionic framework and the face-api.js
library of JavaScript. The proposal is oriented towards efficient and agile monitoring of student
attendance within the classroom, utilizing facial recognition as a key element for faster and more
secure control. 92.8% of teachers show satisfaction with the application, feeling more secure with
the use of facial recognition for verifying student attendance.
Concerning the use of the Extreme Programming (XP) methodology, [9] developed a mobile
application for managing attendance and evaluation information for university students. For this,
development environments such as SQLite for database management, Android Studio, and the
Extreme Programming methodology were used, allowing acceptance and compliance with the
proposal and meeting the requirements demanded by the client. Among the obtained results is
the high availability and integrity of information regarding attendance and evaluations.
Furthermore, the use of the XP methodology allowed constant feedback with the client and,
consequently, continuous improvement of the application.
The data analysis proposed in [10] is used to analyze various skills through the collection of
unstructured data to identify trends in job positions in the oil and gas industry. Although the
context of the case study is different from that presented in this document, it can be proven that
data analysis allows a better understanding of the skills and performance of a group of
individuals, identifying them on a scale of 1 to 10 in job recurrence, which is sought to be
addressed with attendance analysis and academic performance.
In this context, [11] demonstrated that the use of the XP methodology guarantees the
development of applications from small to medium scale. Compared to processes and tools, XP
focuses on the aggressive development of mobile applications and allows an immediate response
to changes that arise during the development process. Therefore, its use to develop a mobile
application for student learning in various schools proves to be efficient and effective.
For predictions and data analysis to be accurate, sensors or tools that collect real-time data
are necessary. An example of this is presented in the research [12], where Google tools (Firebase)
are used for the immediate collection and ordering of data for the detection of cardiovascular
diseases. This demonstrates great effectiveness in recognition and ease of handling a large
amount of data. In this context, in the research conducted by [13] on the use of frameworks in the
development of mobile applications, a comprehensive investigation is presented on the needs
and characteristics that a mobile application must meet. To discover these characteristics, a
systematic study mapping, consultation with experts, implementation in projects with agile
methodologies, and testing in a university environment were used. The results showed
improvement in development and a useful guide to cover all needs or aspects of the mobile
application, improve development times, and can also be used as teaching material.
Finally, in the research proposed by [14], an application was developed to monitor the health
status of patients with heart problems. Considering that data must be updated in real-time, the
researchers concluded that Firebase was the most suitable platform for handling data in the
cloud. As mentioned earlier, this tool provides various services such as Analytics that provide
data and charts of user interactions. As a final point, the authors highlight the accuracy of the
application in offering advice and predictions in sensitive health areas.
In this regard, in relation to the use of NoSQL databases (non-relational databases), [15]
presents a method based on computer vision to automate the process of reading water and
electricity meters through a mobile application, storing photos and data of readings in a NoSQL
database. Through Firebase Storage, it allows a dealer to store and process these readings with
the aim of conducting predictive analysis in the future for water or electricity resource
management. This method was patented, generating viable results in the meter reading market
in Brazil. On the other hand, in [16], they propose a personal and decentralized cloud-based data
model to manage health data in schoolchildren using the real-time NoSQL database provided by
the Firebase platform. Through this service, a school's health information system can have total
control over the administration of sensitive data such as the student's school number, name,
temperature test time, temperature data, and the test machine number. This model was tested
and applied, fulfilling its objective, and provides schoolchildren with more active control over the
health information data of their personal status.
Considering the research conducted, for the development of the proposal, Firebase will be
used as the Database manager, as it is a fast and efficient technology for handling a large amount
of unstructured data [17], Android as the development platform, and the XP methodology to
manage the development of the proposal.
3. Materials and Methods
In order to evaluate the satisfaction of teachers and students regarding the use of an
application for attendance marking, data will be collected from students of the Professional
School of Systems Engineering at the Universidad Católica de Santa María, whose ages range from
19 to 25 years.
The XP methodology consists of the following phases [18]: Planning, Design, Coding, Testing,
and Release. As shown in Figure 2.
Figure 2: Phases of the XP methodology. [19] cited by [18]
3.1. Phase 1: Planning
According to [20], it is important to select the priority functions that will be developed first so
that the application can be implemented gradually and meet the main needs of users. In the
operation of the application developed in [20], two types of data (Primary and Secondary data)
are collected. In this research, primary and secondary data are related to student attendance (see
Table 1).
Table 1
Student attendance data, adapted from [20]
Primary Data Secondary Data
Student identification code, and name. University profile
Student enrollment data Location data
Calendar data (Day, Month, Year) Student's academic performance data
Global time data Attendance recap report format
Internet quota Application development time
Development difficulty level
Application design difficulty level
Feature development rate
In this context, the first thing defined in this phase was the user stories, which in other
development methodologies are known as requirements, to later prioritize them. Some of the
identified user stories are shown below [21].
Table 2
User Story 01. Own elaboration
User Story 01
Number: 1 Name: Access to the application
User: Teacher, Student Assigned Iteration: 1
Business Priority: High Estimated Points: 2
Development Risk: Medium Actual Points: 2
Description: Users will have a unique username and password with which they can log in.
Observations: Only registered users will have access to its functionalities.
Table 3
User Story 02. Own elaboration
User Story 01
Number: 2 Name: Attendance registration
User: Student Assigned Iteration: 1
Business Priority: High Estimated Points: 2
Development Risk: Medium Actual Points: 2
Description: The application will allow students to register attendance by selecting the subject they
need to mark attendance for through a card on the main screen of the application.
Observations: Only courses that correspond to marking attendance will be enabled. That is, if the
allowed time for attendance registration is met (±5 minutes) at entry and exit times.
Table 4
User Story 03. Own elaboration
User Story 01
Number: 3 Name: Attendance control
User: Teacher Assigned Iteration: 1
Business Priority: High Estimated Points: 2
Development Risk: Medium Actual Points: 2
Description: The application will allow downloading a spreadsheet-format file that will contain
student attendance (in CSV format) when selecting a specific subject.
Observations: Only the attendance of those students who marked their attendance within the
specified time frame (±5 minutes) of entry and exit will be counted.
3.2. Phase 2: Design
In this phase, all the mockups of the application were developed with which end-users would
be interacting. While other methodologies usually develop deliverables such as sequence
diagrams, in this case, the client-server model was chosen [21]. Below are the main interfaces of
the mobile application.
• Students
Ø Screen for user login.
Ø Screen to view the list of student courses and the attendances they need to mark at
the scheduled time.
Ø Screen to mark the entry and exit attendance of students.
• Teachers
Ø Screen for user login.
Ø Screen to view the list of courses they teach.
Ø Screen to download the attendance list of a specific course.
Figure 3: Mobile Application Interfaces
3.3. Phase 3: Coding
3.3.1. Implementation of the Model View ViewModel Design Pattern
In this phase, the application's functionalities were coded using the Model View ViewModel
(MVVM) design pattern. MVVM allows the implementation of more robust Android applications
and aligns well with the chosen development methodology [22]. The structure can be observed
as follows.
Figure 4: MVVM Pattern of the application
Where the model layer translates all the data and delivers it to the model, the ViewModel layer
connects to the database or external APIs, and the view layer presents the data, which can be
invoked using commands.
3.3.2. Use of Firebase as a Database Manager
As mentioned earlier, Firebase was used as the database manager due to its advantages, such
as cloud storage and rapid scaling, as well as its data analytics addon for generating reports on
application demand by users.
Figure 5: Firebase as a Database Manager
In Figure 5, the implemented Firebase database can be visualized. It shows the code of the
courses and their corresponding fields, such as classroom, day, entry time, exit time, course name,
and teacher. In Cloud Firestore, the storage unit is the document, which is a record using few
resources and contains fields with assigned values [23], such as the "email" field. Collections store
documents, and in Illustration 5, there is a collection called "attendance," which contains a set of
documents that can, in turn, store collections, such as the "courses" collection storing the courses
each student is enrolled in.
Figure 6: "Courses" Collection in Cloud Firestore
Figure 6 shows the collection of courses, which stores the courses in which the student is
enrolled. Each subject has a unique identifier, the subject code.
The following details the data model represented in the student and their corresponding
courses' data dictionary.
1. Data Model
The attributes handling the main functionalities of the mobile application were collected from
students and their corresponding courses in the 4th year of the Systems Engineering professional
career (odd semester 2022-I) at the Faculty of Physical and Formal Sciences and Engineering of
UCSM, and are shown in Table 5 and 6, respectively.
Table 5
Data Dictionary – Student
Attribute Description Encoded Domain Data Type
Student Code Student code codigo String
Email Student's institutional email email String
Professional School Professional school of the student eprofesional String
Name Full name of the student nombre String
Table 6
Data Dictionary – Courses
Attribute Description Encoded Domain Data Type
Classroom Classroom where the student attends aula String
classes
Day Day on which the student has classes dia String
Entry Time Time of entry to classes horaingreso String
Exit Time Time of exit from classes horasalida String
Course Name Name of the course nombrecurso String
Teacher Name Name of the teacher who teaches the nombredocente String
course
3.3.3. Implementation of Automatic Responses in the Application
To generate automatic responses to user questions, such as obtaining instructions on how to
use the application or how to mark attendance [24], the BrainShop.ai Machine Learning kit was
used. It can respond to user questions based on a knowledge base (a set of previously entered
responses in the model) and generate automatic responses for users [25]. The knowledge base
and its training are shown below.
Figure 7: BrainShop.ai Knowledge Base
Figure 8: Training of the Machine Learning Model Knowledge Base
Additionally, Figure 9 shows the implementation of the ChatBot in the application.
Figure 9: Result of ChatBot Implementation in the Application
3.3.4. Results of the Coding Phase
The following are the main screens of the resulting application based on the user stories from
the planning phase (Phase 01 of the XP methodology). It is important to note that these results
are after the testing phase (Phase 04 of the XP methodology).
1. User Story 01: Access to the Application
The following interfaces illustrate how access to the application is achieved, featuring a
welcome screen and another where entry is made based on roles (Student – Teacher).
Figure 10: Access to the Application Interfaces
2. User Story 02: Attendance Registration
Figure 11 displays the list of courses in which the student is enrolled, along with various alerts
depending on whether it is their turn to register attendance or not.
Figure 11: Attendance Registration Interfaces
3. User Story 03: Attendance Control
The following screens demonstrate how attendance control is carried out by teachers,
following these steps:
• Log in to the application with the role of "Teacher" (only accesses identified with this
role are recognized).
• Navigate to the corresponding course and click on "DOWNLOAD ATTENDANCE
CONTROL," which will generate and download a CSV spreadsheet for teachers.
Illustration 13 shows an example of attendance control performed by a teacher.
Figure 12: Screen to download student attendance control
Figure 13: "Mobile Technologies - Practice Group 1" Attendance Control File
The record indicates the date, entry time, and exit time registered by the student. The record
corresponds to the "Mobile Technologies – Practice Group 1" course, scheduled for "Tuesday
15:00 – 17:00."
3.4. Phase 4: Testing
When using the XP methodology, it is recommended to use unit tests and acceptance tests [26].
Unit tests verify the code developed by the programming team, while acceptance tests verify if
the final product meets the expectations proposed in the planning phase. In our project, each
module was tested to ensure that appropriate values were entered, it led the client to correct
activities, and maintained integrity and security of the data provided by students and teachers.
Finally, customer satisfaction was verified through surveys and scheduled presentations of the
final product to determine if all user requirements and expectations were met.
Table 7
Functional Tests
Identifier Functional Requirement Errors or Failures Detected Improved (YES/NO)
CU01 Student registration in the No access errors detected No
application
CU02 Student attendance marking Incomplete interface YES
CU03 Attendance saving Inconsistency in Firebase YES
date format
CU04 Teacher login to the Incomplete interface YES
application
CU05 Attendance list download Incomplete downloads YES
CU06 Attendance view Disordered visualization YES
CU07 Attendance marking Attendance could not be YES
recorded
CU08 Login with email and Lack of email recognition YES
password
For the application launch, a survey was developed. The survey includes various questions to
validate and verify user satisfaction with the use of the application. The criteria considered for
the survey development are shown in Table 8.
Table 8
Evaluation Criteria
No. Criteria to Evaluate Description
1 Satisfaction and Ease Evaluation of attendance marking through communication with
of Attendance Marking students and the ease with which they perceive the marking.
2 Organization of ASYS A form is provided where users rate the organization of application
Application Elements elements, divided into different views of the application.
3 Application Colors A list of colors, including the current application color, is provided,
and users are asked to vote for the most comfortable color for
them.
4 Application Navigation Communication with application users about their comfort level
Style with application navigation.
5 Application Ease of Communication with application users about their initial
Use experiences using the application.
6 Application Learning Communication with application users about the time it takes to
Ease adapt to it.
7 Intuitive Application Users are asked to rate the application based on the ease it provides
for performing all actions within it.
8 Recommendation of Communication with users about the likelihood of recommending
Application Use the application.
9 Satisfaction Level with A form with different areas of the application is provided for users
Application Use to measure the satisfaction level for each view and a general rating.
3.5. Phase 05: Launch
For the application launch, the following steps were followed:
• Generate the APK of the application.
• Publish the APK on the website: https://coachup.site/
• Evaluate the results obtained through the survey.
This launch method was chosen for its flexibility and ease, as the application is still in its
validation stage.
4. Results
Information was collected from 100 students and teachers in the 4th year of the Systems
Engineering professional career at the Universidad Católica de Santa María for 1 month in the
odd academic semester of 2022-I. The results of the conducted surveys are presented below.
1. Population
Figure 14: Total Population
The chart shows that 80% of respondents are students, and 20% are teachers. Likewise, a scale
was made to assess the satisfaction level of users with the mobile application. Table 9 shows the
scales, and the chart below shows the responses obtained by students.
Table 9
Satisfaction Levels with the Mobile Application
Satisfaction Level Description
1 Poor
2 Regular
3 Good
4 Very Good
5 Excellent
2. Satisfaction Level with the Application Use
Figure 15: Users' Satisfaction Level with the Mobile Application
Among the total respondents, 18 (18%) consider their interaction with the application to be
good, 51 (51%) consider it very good, 28 (28%) consider it excellent, and 2 (2%) consider it
regular. The latter cases may be due to a lack of internet connection or inappropriate use of the
application by users.
3. Application Acceptance Level
Additionally, given that one of the long-term objectives of this research is for the application
to be used in all schools of the Universidad Católica de Santa María, a question was asked about
whether users would recommend the use of the application to others. The responses to this
question are shown below.
Figure 16: Would users recommend the use of the application?
The chart shows that 92.9% of users would highly recommend the use of the application, while
the remaining 7.1% would not recommend it. These cases were evaluated in the testing phase, as
many of these users may not have constant internet access or may not use the application
appropriately.
5. Discussion
The results demonstrate that users (teachers and students at UCSM) feel comfortable using the
application to register their attendance, indicating ease of use.
Additionally, acceptance criteria were developed to verify the acceptance levels of the "ASYS"
mobile application [8], achieving the following compliance levels for each criterion:
Table 10
App Acceptance Criteria. Adapted from [8]
Criteria Results Compliance Level (%)
Functionality The system meets the necessary functionalities for the 100%
correct process in attendance registration and control.
Operability The system works in an integrated manner with the 100%
database manager for subsequent functionalities
implemented in the application.
Satisfaction The results obtained in section IV indicate the degree of 98%
satisfaction that both teachers and students have with
the use of the application.
Acceptance The "ASYS" application meets the registration and 92.9%
attendance control of students.
The table indicates that based on the acceptance criteria, 100% compliance was achieved in
the functionality and operability criteria, indicating complete fulfillment. In contrast, in the
satisfaction and acceptance criteria, 98% and 92.9% were obtained, respectively, which,
according to [8], represents a significant percentage compared to the resulting percentage of the
difference (2% and 7.1%, respectively).
6. Conclusions
• It is concluded that the XP methodology, after executing its first three phases, ensures
the quality of the mobile application. It has the advantage of being more customer-
oriented than development process-oriented, unlike other traditional methodologies
that impose a disciplined development plan.
• The use of tools and techniques oriented in the XP methodology contributed to the
identification of functional and non-functional requirements, which helped in
developing an application oriented to compliance with specified guidelines and
requirements.
• The use of the XP methodology contributes to the development of a mobile application
for attendance control by enabling constant communication and feedback with the
client/user. It also provides quick responses to changes suggested by the client, thanks
to the flexibility of the tools and techniques found in this methodology.
• The execution of the mobile application demonstrated positive results in the correct
implementation of Firebase services (Cloud Firestore and Firebase Authentication) in
the access and attendance marking modules.
• The use of the application facilitated attendance registration for students and teachers,
allowing the generation of a record with the attendance of each student.
• Machine Learning techniques were employed to generate automatic responses to user
questions. This functionality of the application proved to be useful when users do not
know how to mark their attendance or have other questions related to the use of the
application.
Future Work
As future work, the use of other ML techniques such as image recognition and geolocation for
student attendance registration is proposed.
Improvement in control is also suggested. This includes the ability for teachers to download
files that allow them to select which types of data they want to retrieve from the database, such
as dates or student information. Additionally, enhancing the visualization of control data is
proposed, as currently, it is only downloaded in a date and time format when the student
registered their attendance (Entry/Exit).
Furthermore, scaling the database to a relational database schema is considered, which can
work hand in hand with the UCSM database.
Improving the security of the application is suggested, considering that data is an important
asset for an organization. Enhancing application security to a much higher level is part of the
future plans.
Implementing the application for iOS operating systems is also planned.
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