The following are the essential hardware components used in building the proposed attendance system: –

Fingerprint Sensor: The R307 fingerprint sensor (Fig. 2a) has a storage capacity of 1000 fingerprints. It operates at a voltage of 4.2-6V DC and has a 0.3 s scanning speed. It is equipped with an optical sensor that can capture high-resolution fingerprint images, recognize them, and match them accurately [26,27].

The following are the software requirements for the proposed attendance system: –

Arduino Software: It is the only platform for programming Arduino boards. It comes with different libraries for coding different types of sensors [38]. The version “2.1.0” is used for this paper.

Because fingerprints are unique, only trainee students who scan their fingerprints during attendance time are recorded as present, avoiding fake attendance. Fig. 4 shows connecting all components to the microcontroller using jumper wires. The “Adafruit Fingerprint”, “Keypad”, “Wi-Fi”, and “LiquidCrystal_ I2C” libraries are installed in the Arduino IDE. The ESP-12F Wi-Fi module connects to a Wi-Fi network, with its IP address linking the module to the proposed Android app. Fig. 5 displays the daily attendance recording of a trainee student. Below is a detailed analysis of the stages of the proposed attendance system, which consists of two stages:

Fig. 8 shows the attendance and absence of one trainee over seven training days, indicating that the trainee was present for 3 days and absent for four days.

With GPS technology increasingly being integrated into new smartphones, the location of anyone holding a GPS-enabled mobile phone can be tracked at any time [43]. In this paper, GPS technology is used to continuously monitor the location of the trainee students to ensure that they do not leave the school during field training hours. The proposed GPS monitoring system includes the following steps: –

Getting the Location of the School

This is the first step in the proposed GPS monitoring system, where the fixed location of the school is determined, which is obtained only once. Google Maps is a web mapping service developed by Google, which the user can easily use to find a certain location and reach the place [44]. It is used here to get the school’s location coordinates (latitude and longitude). –

Getting the Location of the Trainee Student

This is the second step in the proposed GPS monitoring system, where the location of the trainee student is determined, which is obtained continuously during the field training hours. First, the trainee student activates the GPS service on his mobile phone. Then, a location manager has to be created which is responsible for creating a location-based service on Android [45]. Next, the requestLocationUpdates() method is used to get the location updates [46]. Its parameters are the location provider (GPS), the minimum time interval between location updates (2000 Milliseconds), the minimum change in distance between location updates (1 m), and LocationListener, which receives callbacks for location updates. Finally, the getLatitude() and getLongitude() methods are applied to the last parameter to get the trainee’s location coordinates. Fig. 9 shows the code snippet for obtaining the trainee’s location coordinates.

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Storing the Trainee’s Location Coordinates

This is the third step in the proposed GPS monitoring system. Here, the trainee’s location coordinates are saved continuously in Firebase using the setValue() method [47,48], which writes their values to the Lat and Lng child nodes, as shown in Fig. 10.

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Calculating the Distance between the Coordinates of the School Location and the Trainee Location

This is the fourth step in the proposed GPS monitoring system. The spherical law cosines formula [49] is used to calculate the distance (d) between the coordinates of the school location and the trainee location continuously until the end of the field training day, as shown in Eq. (1): (1) d=acos(sin⁡(lat1)∗sin⁡(lat2)+cos⁡(lat1)∗cos⁡(lat2)∗cos⁡(long2−long1))∗Rwhere lat1 is the latitude of the school location, lat2 is the latitude of the trainee location, long1 is the longitude of the school location, long2 is the longitude of the trainee location, and R is 6371 km (radius of the earth). –

Determining the Daily Attendance Based on the Calculated Distance

This is the fifth step in the proposed GPS monitoring system. If the calculated distance exceeds 25 m (as per the school where the experiment was conducted) for more than 10 min, attendance will be cancelled, and supervisors, parents, and the school principal will be notified. The code snippet for determining the daily attendance based on the calculated distance is shown in Fig. 11.

Video call uses audio and video communications to bring people from different places together. It is an internet-based technology that provides the ability to see and hear the person at the end of the line, allowing interviews to be conducted effectively face-to-face [50,51]. It is used in the proposed Android application to allow the supervisor, in case of his absence from the school, to remotely monitor the trainee’s completion of the tasks assigned to him. The trainee also uses it to inquire about something from the supervisor, and to communicate with other trainees in the group. Below are the steps to add and use this technology in the proposed Android application. –

Creating a New Project on the Agora Platform

Agora provides audio, video, and interactive broadcast SDKs that allow to integrate interactive communications right from within mobile, desktop and web applications [52]. After registering for a free account on the Agora website, a new project is created. Agora then assigns an App ID to the new project as a unique identification and an App certificate, which is required for authentication to establish a channel for real-time data transmission as shown in Fig. 12. Finally, the App ID and App certificate are added to the proposed Android app to integrate the Agora Video SDK into it. –

Designing the User Interface for the Video Call

The user interface for the video call contains three controls. These controls are a “SurfaceView” where Agora usually renders its streams on Android, with one for the caller and one for the callee, a “Button” to end the call, and a “FrameLayout” which contains the two SurfaceViews and the Button. Fig. 13 shows the user interface for the video call.

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Selecting the Callee from the Training Group

A video call icon is displayed next to each training group member (trainee student or supervisor). The member (the caller) clicks on the video call icon next to the other member of the group he wants to communicate with (the callee). –

Establishing a Communication Channel

The caller ID is used as the name of the communication channel that connects the caller to the callee. It is stored in the “ch” child node of the callee’s Firebase. Also, the status of the communication channel becomes “on” in the “stat” child node as shown in Fig. 14.

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Starting the Video Call

Once the “stat” becomes “on”, the callee is notified that there is a video call. The setupRemoteVideo() method [53] is used to initialize remote user’s video view on the local device. It is called on an rtcEngine instance, which is the Agora SDK core interface that implements the main real-time communication functions [54]. It generates a VideoCanvas object that parameters are: SurfaceView to display the remote user’s video, Fit Mode, which ensures that the video is adjusted to fit the display window, and the remote user’s ID [55]. Similarly, the setupLocalVideo() method [53] is used to initialize the local video view on the local device. Fig. 15 shows the code snippet for displaying the remote user’s video on the local device.

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Ending the Video Call

To end the video call, the “Close” button is clicked. As a result, the “stat” child node is set to “off”, and the video call is terminated.

Chat app allows users to send and receive real-time messages with people from anywhere. When face-to-face connection is unavailable, it is used to provide alternatives for learning [56,57]. In this paper, the proposed chat complements the video call by providing a text channel for communication. The data storage medium for chat history, etc. is Firebase, which stores and syncs real-time data between users and devices [58,59]. The user interface for the proposed chat (as shown in Fig. 16) contains a “ListView” to display a set of vertically scrollable views, where each view is placed directly below the previous view in the list, an “EditText” to type a new message, and an “ImageButton” to send the message.

There are two cases of chat between two training group members, whether they are supervisors, trainees, or a supervisor with a trainee: First-time chat and non-first-time chat. –

First-time Chat between Two Training Group Members

The following are first-time chat steps to be followed between two training group members:

1. Selecting the Recipient from the Training Group

A chat icon appears next to each member in the training group, whether he is a supervisor or a trainee. The member (the sender) clicks on the chat icon next to the other member in the group whom he wishes to message (the recipient). Consequently, a blank chat screen opens up.

2. Sending a New Message

The sender types the new message in the “EditText” and presses the “ImageButton” to send it. The time and date of the message in milliseconds are saved in Firebase. The message text, sender ID, and recipient ID are also saved in the “msg”, “sender”, and “to” child nodes. Additionally, the “New Messages” text is saved in the “msgs” child node, as shown in Fig. 17.

3. Displaying the New Message Data on the Sender’s Device

Once the sender presses the “ImageButton”, a custom view is created to display the new message data on the sender’s device. The custom view components are defined in a static layout file called “mymsg” which includes two “TextView” for the message text, and the time and date of the message. After that, the inflate() method [60] is used to call the layout file dynamically. The message text is obtained from the “EditText”, and the time and date of the message are obtained using the Calendar class methods. Finally, the custom view is added to the “ListView” using the addView() method [61], which is used to add additional views to the root view. Fig. 18 shows the code snippet for displaying the new message data on the sender’s device.

4. Displaying the New Message Data on the Recipient’s Device

Once the text “New Messages” is present in the “msgs” child node in Firebase, the recipient receives an alert notification of the new message. Next, a custom view is created to display the sender’s message data on the recipient’s device. Here, the name of the layout file is “othersmsg” which contains three “TextView” for sender name, message text, and the time and date of the message. After that, the inflate() method is used to call the layout file dynamically. The sender name, message text, and the time and date of the message are all obtained from Firebase. Finally, the addView() method is used to add the custom view to the “ListView”. The recipient can reply with a new message and become the sender, and the previous steps are repeated. –

Non-First-Time Chat between Two Training Group Members

If the chat is not the first time between the sender and the recipient, their chat history will be retrieved from Firebase and then displayed on each other’s device. After that, the previous steps are repeated to send a new message. Figs. 19–21 illustrate the flowcharts of the proposed monitoring system using GPS, video call, and chat technologies.

This is the first item in the proposed evaluation system. Online exam is a technology that simplifies exam activities such as defining exam patterns with question banks, assigning exam scores, and taking exams using computers or mobile devices. The proposed Android app allows trainees to access the exam from anywhere and at any time, saving them time and effort in traveling to the exam site. Also, it saves supervisors’ time and effort, which is especially important as the number of trainees grows. Below is a detailed analysis of the steps for preparing the exam, displaying it, correcting it, and recording its score. –

Preparing the Exam Questions

Each of the three supervisors has a 10-point exam. Through the proposed Android app, each supervisor enters a set of multiple-choice questions, their answers, and their model answers, all of which are then kept in Firebase. The supervisor also has the ability to delete or modify any of the questions or add additional questions. Fig. 22 displays a question from an external supervisor, along with its answers and its model answer, all recorded in Firebase.

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Displaying the Exam Questions

During the exam, all questions, answers, and model answers are imported from Firebase and then stored in an array list in the proposed Android app. The system randomly displays 10 questions to the trainee, and the trainee’s answers to these questions are also added to the array list. The trainee can review or change his answers using the “Back” and “Next” buttons. Fig. 23 displays a sample of the exam questions presented to the trainee student via the proposed Android app.

The system compares the trainee’s answer to each question with the question model answer. If the two answers are the same, the trainee’s answer is correct, and vice versa. The exam grade is calculated based on the number of correct answers. It is then saved in Firebase as shown in Fig. 24. After calculating the exam grade for each supervisor, the total exam score is 30 points.

This is the second item in the proposed evaluation system. Since manual calculation of attendance grades is prone to errors and time-consuming, the grades are calculated automatically here. This is achieved by dividing the number of days the trainee attends training by the total number of training days, multiplying the result by ten, and rounding it to the nearest integer. This grade is then saved in Firebase as shown in Fig. 24. It is considered as the trainee’s attendance grade by each of the three supervisors and the school principal. As a result, the total attendance score is 40 points.

This is the third item in the proposed evaluation system. Each supervisor assigns 10 points for the trainee’s implementation of the required activities and tasks during the field training period. This grade is called the trainee’s monitoring grade and it is saved in Firebase as shown in Fig. 24. Therefore, the total monitoring score is 30 points. Finally, the total score for the trainee in the field training course is saved in Firebase, as shown in Fig. 24, and then sent to the college’s student affairs. Fig. 25 shows the use case diagram for the proposed management system.

The proposed attendance system was tested on the study sample 15 times to calculate its accuracy using Eq. (2), and the results are presented in Table 3. (2) Accuracy=number of successful fingerprint matching total number of fingerprinttest data∗100

According to the data in Table 3, six fingerprints were not identified, as indicated by “×”. These cases resulted from various issues, such as incorrect finger placement, fingers being wet or oily, or a thin finger surface. Successful identifications are marked with “✓”. Consequently, the accuracy of the proposed attendance system is 98.67%.

To evaluate the accuracy of the proposed monitoring system using GPS, it was used to measure the distance between each trainee student in the study sample and the center of the school on a training day. The measured distances were then compared to the actual distances, as detailed in Table 4.

Table 4 reveals that the proposed monitoring system using GPS provides accurate results, with an average distance error of 1.08 m. To further evaluate the accuracy of the proposed monitoring system, the video call functionality was tested on the study sample on a training day. This test measured video latency, which referring to the duration it took for a video signal to travel from the supervisors to the study sample, with the results displayed in Table 5.

As illustrated in Table 5, the average video latency was less than a second. This result indicates that the proposed monitoring system using video call effectively reduces data transmission delays and supports high-quality video streaming.

To evaluate the performance of the proposed monitoring system using chat, a questionnaire was developed and initially reviewed by a group of ten arbitrators from the Department of Educational and Psychological Sciences at the college. This was to verify its validity and reliability. Some statements were modified, and others were removed to finalize the questionnaire. This version underwent arbitrator validation, and its reliability was confirmed with a Cronbach’s alpha coefficient of 0.96. Subsequently, it was presented to the study sample to gather their opinions. Their responses were recorded using a five-point Likert scale (Strongly agree = 5, Agree = 4, Neutral/Uncertain = 3, Disagree = 2, Strongly disagree = 1). Table 6 shows the response rates of the study sample to the field training students’ satisfaction questionnaire regarding the proposed monitoring system using chat.

As shown in Table 6, the study sample’s response rates to the questionnaire statements ranged between 94% and 98%. While the overall response rate to the questionnaire was 96.05%. This indicates that the proposed monitoring system using chat has significantly enhanced effective and convenient communication between supervisors and trainee students during the field training day.

To measure the effectiveness of the proposed evaluation system, an online exam was conducted for the study sample. Then, the same exam was conducted on paper to an equivalent group of the study sample, comprising 30 trainee students. Table 7 displays the exam results for two groups: the first group took the exam online, while the second took it on paper.

As depicted in Table 7, the average grades of trainees in the online exam are higher than those in the paper-based exam. This suggests that trainees may perform better in online assessments.

To assess the effectiveness of the proposed management system in attendance, monitoring, and evaluation, a questionnaire was developed and presented to a group of fifteen arbitrators from the departments of Computer Science, Educational Technology, and Educational and Psychological Sciences at the college to survey their opinions. Their responses were recorded on a five-point Likert scale (Strongly agree = 5, Agree = 4, Neutral/Uncertain = 3, Disagree = 2, Strongly disagree = 1). Table 8 displays the results of the questionnaire evaluating the effectiveness of the proposed management system.

As shown in Table 8, the arbitrators’ response rate to the questionnaire was 96.61 %, which demonstrates the effectiveness of the proposed management system in managing attendance, monitoring, and evaluation in field training. Numerous tests were conducted also on the proposed management system, explained as follows: –

Functional testing: The proposed management system was used by several users (trainee students, supervisors, etc.) to verify that the system meets their requirements, performs the tasks for which it was designed, and that the actual outputs matched the expected outputs. The results were completely satisfactory.

Based on the results of previous tests, it is clear that the proposed management system has many characteristics, including ease of use, accuracy, confidentiality, efficiency, reliability, etc. Therefore, it is considered a valuable addition to the colleges concerned with field training in Egyptian universities.