Application of high-performance computing in sustainable energy campus building design

Abstract

In high-performance computing (HPC) systems, energy and power considerations play an increasingly important role. This work aims to ensure the implementation of China’s green and ecological concepts, respond to China’s strategy of building an environment-friendly and resource-saving society, and actively promote the construction of sustainable development campuses. First, the theoretical basis of sustainable energy campus architecture is described. Next, the teaching feedback model under HPC is constructed. Finally, with the evaluation results of students’ task completion processes and students’ task works as measurement indexes, the corresponding data is collected and comprehensively evaluated and analyzed to verify the effectiveness of the model. The analysis results indicate that most students are able to complete tasks within two hours; however, their proficiency with multimedia technology is inadequate, and they lack initiative in the learning process. There is a correlation between the overall evaluation of task performance and the students’ level of understanding of the tasks. By implementing a teaching feedback model, students’ learning enthusiasm and the quality of their work improved, providing effective educational support for promoting sustainable development on campus. Overall, the awareness of using computers and other multimedia technologies among students is not strong, and their learning process is relatively closed, with insufficient enthusiasm and initiative. This model can achieve the acquisition, integration, and statistical analysis of teacher feedback information. The model can realize the acquisition, integration, and statistical analysis of teachers’ feedback information. This work hopes to use this learning and feedback mode in practical teaching to address specific problems in computer multimedia courses.

Keywords

Highperformance computing (HPC)sustainable energy multimedia technology teaching feedback model information gathering

1. Introduction

In recent years, multimedia technologies such as computers and networks have been widely used in school education [1]. Since the 1980s, computer multimedia technology has rapidly evolved, integrating various media forms such as text, images, audio, video, and animation. This integration has profoundly impacted fields such as education, entertainment, advertising, and communication. In the realm of education, multimedia technology enhances student interest and engagement by providing vivid and intuitive instructional content, thereby overcoming the monotony and limitations of traditional teaching methods. However, despite its immense potential, the effectiveness of multimedia technology in educational practice is still constrained by factors such as the cost of technical equipment, the skill levels of teachers, and the students’ ability for self-directed learning. The computer multimedia teaching system is a simple and efficient teaching tool from the teachers’ perspective. The open network environment and rich network resources create excellent conditions for teachers to complete teaching tasks [2].

However, there are some characteristics of “time division, space division, teacher division, and teaching management division” in the Internet online classroom. Therefore, the weakening of teachers’ main role is bound to weaken the management of classroom teaching, making it inevitable to rely too much on students’ initiative in the process of multimedia education [3]. Moreover, the quality of network information is uneven, and online courses can easily lead to students’ “information drift off course.” Yousef (2021) conducted an experimental study comparing the effects of traditional teaching methods with multimedia-assisted teaching in primary education. The results indicated that multimedia-assisted teaching significantly improved students’ learning outcomes and engagement, particularly in terms of comprehension and memory retention [4]. Holly et al. (2023) employed a mixed-method approach, combining surveys and in-depth interviews, to analyze the application of multimedia technology in higher education. Their findings revealed that multimedia technology significantly enhanced students’ interest and comprehension, but its effectiveness was limited by teachers’ technical proficiency and the quality of instructional design [5]. Al-Rahmi et al. (2023) conducted a quantitative study using extensive surveys to evaluate the application of multimedia technology in secondary education. Their results showed that multimedia technology helped improve students’ learning efficiency and initiative, although issues such as unequal distribution of technological equipment and resources were also noted [6]. In summary, how to control the whole process of computer multimedia technology education to promote the completion of educational objectives needs further study.

This problem has been deeply studied in the key areas of effective classroom teaching theory and classroom teaching feedback. Through the in-depth study of teaching feedback in computer multimedia classrooms, a teaching feedback model for computer multimedia classrooms has been constructed, which provides a new research angle for the development of the cognitive system of task-driven curriculum theory. This model focuses on the basic methods of obtaining, integrating, and statistically analyzing feedback information in computer multimedia technology teaching. In teaching practice, this work aims to use this teaching feedback model to address some practical problems in computer multimedia teaching and thereby promote the development of computer multimedia teaching. The contributions of this study can be summarized as follows:

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Scenario Application: This work leverages computer multimedia technology to implement multi-scenario applications of teaching feedback. By utilizing sensors and student terminal devices, the system can collect multidimensional data in real-time, covering aspects such as student behavior, task completion, and work evaluation. This ensures the comprehensiveness and timeliness of data, supporting diverse teaching scenarios.
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Enhancement of Teaching Quality: This work advocates the use of machine learning and natural language processing technologies to generate personalized student feedback and recommend teaching resources, significantly enhancing teaching quality. By analyzing student learning behavior patterns and key influencing factors, the system provides specific improvement suggestions and evaluations, promoting student engagement and improving teacher effectiveness.
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Management Visualization: A user-friendly interactive interface has been developed to provide real-time feedback and visual data presentations. Through clear and intuitive charts and reports, managers can comprehensively understand the teaching process and student performance, supporting decision-making analysis, optimizing resource allocation, and improving management efficiency and effectiveness, thus achieving scientific and refined management.
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End-to-End Control: The proposed model encompasses the entire process of data collection, processing and analysis, feedback generation, and interactive interface. By employing algorithms such as random forest and k-means, the system conducts precise analysis and prediction of student learning data, ensuring the accuracy and timeliness of feedback, and comprehensively enhancing the achievement of educational objectives.

2. Overview of research-related theories and models

2.1 Connotation of sustainable energy campus architecture

Green building has always been a topic eagerly discussed by Chinese researchers and has received significant attention and recognition from all walks of life. The Scientific and Technological Guidance for Green Buildings suggests that reasonably saving resources, land, water and materials, protecting the environment and reducing pollution can provide people with a good, comfortable and reassuring living environment. This means that green building materials meet people’s needs for health and comfort with their characteristics of saving resources and environmental protection. At present, there are many teachers and students in colleges, leading to higher requirements for building comfort, which in turn increases the energy consumption of school buildings. Moreover, college buildings are generally large, with many types of equipment and complex management and operation needs, which further increases the unit energy consumption of school buildings. College buildings account for a significant proportion of urban buildings. Therefore, the concept of a “green campus” was independently proposed in the subforum of the Eighth World International Conference on Green Building and Building Energy Saving Technology. The construction of a green campus has become a focal point for energy conservation and emission reduction efforts [7, 8].

To provide a healthier and more pleasant teaching environment and research conditions, colleges must comprehensively consider four aspects: appropriate ambient temperature and humidity, fresh air with minimized dryness and air pollutants, good lighting environment, and perfect acoustic facilities. Excessively high room temperature can also affect people’s temperature regulation function. Appropriate temperature and humidity can enhance the comfort of the working space [9, 10]. Fresh and high-quality air can promote blood circulation, strengthen the body and make individuals more energetic. A suitable natural light environment can enhance work and learning efficiency. The natural light and sound environment inside the school building also directly impact work efficiency and physical and mental health [11, 12, 13]. Excellent acoustic design can improve speech intelligibility, create an optimal classroom and office environment, and facilitate efficient teaching and a comfortable working and learning atmosphere.

2.2 Overview of teaching feedback

Figure 1.

Control system without feedback.

Modern systems theory also emphasizes that “feedback” is the key to system optimization. In other words, the optimization of the control system is achieved through feedback [14]. The effectiveness and stability of a control system can only be effectively realized through feedback control. Figure 1 depicts a control system without feedback.

The target signal input from the controlled end can be regarded as a form of “excitation.” This means that through physical or biological stimulation within the system’s internal processes, the internal state of the controlled system is characterized or reflected by various parameters. It can influence its input and output parameters or certain state parameters, and it can serve as the target response [15]. It can be observed that the “education goal information system” in these block diagrams is equivalent to the “education goal” set according to the outline. It plays a controlling role in the entire process of school education. The “controlled system” refers to the social activities of all teachers and students, while the “state information system” generally refers to the professional situation of all students, but it also reflects the educational outcomes of all social activities. Figure 2 depicts a feedback control system.

Figure 2.

Feedback control system.

Figure 2 illustrates the sampling points of the feedback system, the state signal output of the controlled system and the adjustment points sampled and controlled by the feedback system, known as the control points. The controlled target signal is compared with the feedback signal of the control system, and the comparison results are used to influence the controlled system. The feedback information of the control system is sampled by the feedback system [16].

Such continuous circulation allows the controlled system to further develop or ultimately reach a balance point. Clearly, in a system with feedback, monitoring the controlled system is related to the selection of control objectives and the feedback of system output. The combined effect of these two aspects drives the control system to develop or stabilize, which is the principle of the feedback control system [17, 18]. The feedback control system enables the information system to achieve efficient and rapid development and relative stability in implementing work objective management, which cannot be achieved without the feedback control system. The actual feedback control system includes many branch business processes and multiple controlled objects, thus the block diagram reflecting the business process becomes more abundant and complex [19].

Figure 3.

Positive transmission of teaching information in the traditional classroom.

All kinds of educational media used in classroom teaching and the primary energy of teachers essentially serve for positive feedback. Classroom teaching staff need to master the entire information transmission process and fully leverage their leading role in traditional classroom teaching. Figure 3 illustrates the forward propagation of information in traditional classroom teaching.

In the classroom, teachers often transmit a significant amount of teaching information. Based on the concept of information transmission and processing, classroom teaching forms a complex information network system. Vast teaching information originates from the podium and is conveyed to the receiving end through various educational media. The receiving terminal is the school, and ultimately, the information is fed back to students, which is the fundamental purpose of educational communication [20]. The signal propagation direction can be from the podium to the student, and such a signal propagation step can be termed as the “forward propagation business process.” It constitutes the primary channel for the dissemination of educational information in the classroom.

The main difference between Figs 2 and 3 lies in the types of systems they describe, as well as the modes and purposes of information transmission. Figure 2 illustrates a feedback control system, where sampling points, status signal outputs, and control points form a closed-loop system. This system adjusts the controlled system by comparing the control target signal and the feedback signal, aiming for stability or further development through continuous feedback loops. This system emphasizes the bidirectional interaction of monitoring and adjustment to achieve effective management of objectives and stable development. In contrast, Figure 3 emphasizes the forward transmission mode of teaching information in traditional classrooms. In this mode, the teacher is the primary source of information, transmitting it to students through various educational media, forming a unidirectional forward propagation business process. The core of this mode lies in the transmission and reception of information, rather than real-time feedback and adjustment. Therefore, the feedback system in Fig. 2 exhibits characteristics of dynamic adjustment and stability, while Fig. 3 emphasizes the unidirectionality and transmission efficiency of information transmission, lacking the complexity and interactivity of real-time feedback mechanisms. A comparison of the two reveals that communication and information transmission in modern education are bidirectional and dynamically coordinated processes, rather than unidirectional, static teaching processes.

Figure 4.

Classroom teaching transmission feedback.

Another way to transmit teaching information is by taking students as the information source. Students utilize various methods to convey corresponding information to teachers and report their learning status. This method of information transmission can also be referred to as the “feedback transmission process” or simply “teaching feedback.” The communication task accomplished by the feedback channel differs from that of the main channel. Its primary purpose is to demonstrate the result and situation of message transmission to the main channel. Therefore, it serves as an effective method for detecting the effects of information transmission. Classroom feedback denotes the process in which the information content transmitted by teachers and students in the classroom is relayed again through the effects formed after being mutually processed to impact the retransmission of teaching information. Classroom teaching feedback is a crucial link in the effective development of the teaching system. It provides teachers with an effective means to understand issues such as quality and efficiency, evaluate and adjust teaching plans during the classroom teaching process, offer a reasonable and scientific basis for curriculum development, and enable the curriculum to achieve its expected objectives more efficiently and effectively. Figure 4 illustrates the transmission process of classroom feedback.

2.3 Teaching feedback under computer multimedia technology

In the classroom employing computer multimedia technology, teachers have shifted from their previous roles as knowledge authorities and dominant figures to becoming creators of knowledge situations, providers, and promoters of knowledge information. Similarly, students have transitioned from passive recipients of knowledge to engaging in independent inquiry-based learning. The teaching purpose has shifted from emphasizing the mastery of basic knowledge to cultivating students’ comprehensive skills. Additionally, the once limited and insufficient teaching resources have now become rich and diverse [21]. Based on the concept of system theory, for a teaching system to develop stably, it must fully utilize its maximum potential, with the major factors within the system closely cooperating. Achieving such a coordinated relationship requires the relevant parties of various system factors to accept each other’s feedback information and establish a mutually balanced system structure by adjusting the collaboration between different factors. In this mutually balanced system, the feedback signal is adjusted to reach a certain equilibrium point by modifying the increase or decrease of different dependent variables.

Specifically, the evaluation and analysis of students’ task performance can be elaborated in detail from three perspectives: information acquisition ability, learning attitudes and awareness, and ability to overcome difficulties. Firstly, the ability to acquire information includes students’ capacity to gather and integrate information during task completion, which is crucial for problem-solving and task accomplishment. Secondly, learning attitudes and awareness involve students’ cognition of tasks and the positivity of their learning attitudes, including whether they maintain sustained learning motivation and possess awareness of autonomous learning. Lastly, the ability to overcome difficulties refers to students’ capability to systematically address challenges encountered during tasks, demonstrating resilience and problem-solving skills. These aspects collectively assess students’ comprehensive performance in task completion.

The evaluation of students’ quality should be based on the scientific and comprehensive assessment of their completed tasks or “works.” This entails objective evaluation of correctness, simple assessment of task completion, as well as evaluation of students’ understanding, consciousness, attitude, and processing ability regarding learning tasks [22].

Specifically, the evaluation of student qualities can be divided into three aspects: task completion time, problem-solving methods, and emotional expression. Firstly, task completion time reflects the efficiency and time management skills of students during task completion. Completing tasks quickly may indicate strong work efficiency and self-management skills. Secondly, problem-solving methods involve the strategies and approaches students choose when faced with problems during tasks, including problem analysis, creative thinking, and problem-solving skills. Lastly, emotional expression assesses students’ ability to regulate emotions and communicate effectively during task completion, which is crucial for teamwork and work efficiency [23]. These three aspects collectively evaluate students’ comprehensive qualities during task completion.

The evaluation of students’ task completion process involves monitoring their learning process and comprehensively assessing their learning ability. It broadly encompasses the following three aspects: the efficiency of task completion, the technical approach to task completion, and the emotional state of students during the task completion process.

Learners’ evaluation of a computer multimedia course pertains to the assessment of the course itself from the learners’ perspective following completion of a multimedia course.

Specifically, the evaluation of students’ perceptions of computer multimedia technology teaching can be detailed from two perspectives: computer multimedia technology teaching and achieving teaching objectives [24]. Firstly, in terms of computer multimedia technology teaching, the assessment involves the richness of teaching content, the practicality and interactivity of technical applications, and whether it can stimulate students’ learning interests and enhance learning experiences. Secondly, in terms of achieving teaching objectives, the evaluation assesses whether students can achieve the expected learning objectives through this technological means, including the mastery of knowledge, improvement of skills, and cultivation of thinking abilities [25]. These two perspectives collectively evaluate the practical effects and educational significance of computer multimedia technology in teaching.

In this evaluation method, students serve as the subjects of evaluation, and the task-driven curriculum itself are the main object of evaluation. This assessment serves as a crucial feedback signal for multimedia teaching. Because it originates directly from learners’ perceptions and feelings, it holds significant reference value for the adjustment and decision-making in computer multimedia teaching.

2.4 Construction of teaching feedback model under computer multimedia technology

2.4.1 Collection and processing of teaching feedback information

Teachers should fully utilize the advantages of computer technology and the rich resources of the educational network to collect various feedback information reflecting the entire task-driven teaching process. Moreover, they need to adhere to the standard requirements of educational database records and document all types of feedback information in the teaching information database. Subsequently, the feedback information is analyzed and integrated to evaluate the entire task-driven teaching process. The evaluation of students’ tasks and works should incorporate both qualitative and quantitative evaluations based on the specific learning content. The method to be adopted should be determined according to the specific requirements of task design. Generally, it is challenging to define the evaluation of “understanding” and “conscious attitude” with data, so quantitative analysis is typically used for evaluation. The school’s evaluation of task-driven curriculum includes the assessment of tasks designed by teachers and the evaluation of curriculum situation design. After collecting such information, the teacher can send set questions to the students via email by distributing questionnaires. Students will respond to the teacher after completing the questions. Teachers can also publish the set questions on the teaching website through the online teaching platform and conduct online questionnaire surveys and statistics. After the students complete the questionnaire, the teaching results can be promptly counted and analyzed.

2.4.2 Establishment of teaching feedback model

Figure 5.

Teaching feedback model under computer multimedia technology. (a: collection of teaching feedback information; b: processing of teaching feedback information).

In sustainable energy campus building design, the teaching feedback model based on computer multimedia technology optimizes the teaching process through four modules: data collection, processing and analysis, feedback generation, and interactive interface. The system utilizes sensors and learning management systems to collect multidimensional data, employs machine learning algorithms for analysis, generates personalized feedback, and provides teaching resource recommendations for teachers through natural language processing and recommendation algorithms. Random forest and K-means algorithms are used for classification and behavioral pattern analysis, enabling the automated processing and personalized generation of teaching feedback, enhancing student engagement and teacher effectiveness, and facilitating the achievement of educational objectives. Figure 5 depicts two modules of the teaching feedback model under computer multimedia technology: the collection of teaching feedback information and the processing of teaching feedback information.

The transmission and information collection module focus on what kind of transmission message is accepted and how to obtain the transmission message. The collection of educational feedback data should pay special attention to the standardization of recording the data results into the information base, as it directly affects the later management of statistical analysis. The software module of the management system of teaching feedback information mainly includes the division and statistics of the data results of teaching feedback information and the formation of a teaching analysis report.

2.5 Case analysis of teaching feedback model under computer multimedia technology

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Teaching content: Sustainable campus architectural design.
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Teaching method: Teaching method under the application of computer multimedia.
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Teaching situation: All learning materials are stored on the teacher’s server, and students can log in, browse, and download materials. Schools need to maintain students’ electronic teaching files and ensure smooth communication between teachers and students on the Internet. Teachers should ensure that the teaching arrangement for this part has been explained to the students in advance.
•
Teaching objective: The objective is to enable learners to master the teaching content through multimedia teaching technology such as computers and to emphasize the education of students’ active cognitive consciousness to enhance their learning ability, active thinking, and exploration of new problems. The specific goal is for students to complete tasks within the specified time limit, proficiently utilize computer technology to solve problems, and accurately comprehend learning tasks. The task completion rate should ideally reach 70% or more. Students should be adept at using electronic technology tools to maintain communication with teachers.
•
Teaching process: students log in to the teacher’s server as usual and download teaching tasks and relevant materials. The teacher activates instant messaging tools on the special classroom host and sends emails to the students. Students can access resources online and engage in discussions with their classmates. The teacher dedicates one-third of the class time to face-to-face communication with the students in the online classroom.

2.6 Data analysis

SPSS software version 25.0 is utilized for data statistical analysis. The primary analysis methods include independent sample T-test and linear regression. Equation (1) demonstrates the specific calculation:

$\displaystyle t=\frac{\bar{x}_{1}-\bar{x}_{2}}{\frac{(n_{1}-1)S_{1}^{2}+(n_{2}% -1)S_{2}^{2}}{n_{1}+n_{2}-2}\left(\frac{1}{n_{1}}+\frac{1}{n_{2}}\right)}$ (1)

Equation (1) describes the comparison of means between two independent samples. Here, $\bar{x}_{1}$ represents the mean of the first sample; $\bar{x}_{2}$ represents the mean of the second sample; $n_{1}$ represents the sample size of the first sample; ${n}_{2}$ represents the sample size of the second sample; ${S}_{1}$ represents the standard deviation of the first sample; ${S}_{2}$ represents the standard deviation of the second sample.

3. Analysis of teaching feedback results

3.1 Evaluation results of the task completion process

Figure 6.

Data statistics of task completion process evaluation.

During the students’ learning process, their progress is understood through synchronous and asynchronous tracking. The tracking record data of students’ task completion process evaluation is statistically analyzed, as depicted in Fig. 6.

Figure 6 illustrates that most students can complete the task within 2 hours, with more than 80% spending 100–120 minutes, and 5 students taking more than 2 hours. This indicates that students’ proficiency in using computer multimedia technology is inadequate, their learning process is time-consuming, and their learning autonomy is lacking. The statistical analysis results of the tracked and recorded evaluation data of students’ task completion process reveal that the students’ awareness of using computers and other multimedia technologies at school is weak. Their learning process is relatively closed, and their enthusiasm and initiative in learning are insufficient.

3.2 Evaluation results of task works

Figure 7.

Data statistics of task work evaluation information. (A: excellent; B: good; C: qualified; D: unqualified).

Figure 7 presents the data statistics of task work evaluation information.

Figure 7 illustrates that five task works are comprehensively evaluated as excellent, six are good, and the excellent rate is close to 80%. From the perspective of students’ comprehension, four students are evaluated as excellent, three are evaluated as good, and the excellent rate is close to 40%. This indicates that the quality of students’ work is directly proportional to their understanding of the task to a certain extent.

3.2.1 Student teaching evaluation results

Table 1
Statistics of students’ feedback information in computer multimedia technology teaching

Contents	Accept		Do not accept
	Evaluation	Number	Evaluation	Number
Multimedia technology	Rich content, increased interest in learning	20	Not vivid enough to arouse enthusiasm	3
Teaching methods	Novel form and meets the needs of students	15	Unable to meet class conditions	2
Statistic	35		5

Following the course, students provide feedback on the computer multimedia technology teaching method. The specific results are presented in Table 1.

Table 1 suggests that most students accept the designed computer multimedia technology teaching method. Twenty students believe that the use of multimedia technology enriches the teaching content and increases their interest in learning, while fifteen students find this teaching method novel and meeting their actual needs. Only five students believe that the teaching method is not vivid enough to mobilize enthusiasm and cannot meet class conditions. Therefore, the designed computer multimedia technology teaching method has achieved positive results.

4. Discussion

The analysis of the experimental results regarding student task completion processes, task performance evaluations, and student teaching feedback yields several important conclusions. Firstly, although the majority of students are able to complete the tasks within 2 hours, over 80% of students take between 100–120 minutes. This indicates insufficient proficiency with computer multimedia technology among students, resulting in lengthy learning processes and limited autonomy. This finding is consistent with related research. Tohara (2021) noted that students often lacked confidence and practical experience when facing new multimedia technologies, leading to low learning efficiency. Furthermore, the task performance evaluation results indicate an excellence rate close to 80%, suggesting that despite students’ limited technical proficiency, their learning outcomes to some extent reflect their understanding of the tasks [26]. This aligns with the findings of Kousloglou et al. (2023), who observed a significant improvement in students’ understanding and mastery of learning content through multimedia-assisted teaching. Student teaching feedback results indicate that the majority of students accept and appreciate the teaching methods involving computer multimedia technology, considering it enriches teaching content and enhances learning interest [27]. Compared to previous research, this work provides more detailed data analysis through specific task evaluations and teaching feedback, further validating the special value and advancement of multimedia technology in education.

5. Conclusion

In the actual teaching process, the utilization of computer multimedia technology leverages the abundance of educational resources and the open classroom teaching environment on the Internet to create a modern classroom teaching scene, enabling learners to enhance their initiative. This work discusses how to address the challenges of classroom teaching in the context of computer multimedia technology application through the lens of classroom teaching feedback. Building upon this foundation, a multimedia teaching feedback mode based on computer technology is developed, serving as an effective approach to resolving students’ learning challenges in computer multimedia technology. In classroom teaching practice, this approach is applied to address various practical issues in computer multimedia teaching. However, challenges arise with the network infrastructure of teaching activity spaces, such as user control, managing the process of educational work and teaching activities, and aligning with educational objectives. Additionally, overseeing the overall development of computer multimedia technology education to facilitate the achievement of educational objectives remains an important area for further study.

While this work has unveiled the potential of computer multimedia technology in teaching, it also presents limitations. For instance, students demonstrate lower proficiency and autonomy with the technology, and teaching methods lack adequate interactivity and vividness. Future research will concentrate on refining multimedia teaching designs to augment interactivity and bolster students’ technical skills training. Furthermore, additional investigation is needed on user control and educational goal management in online teaching activities to ascertain the efficacy of the teaching process and the attainment of educational objectives.

Footnotes

Conflict of interest

The authors have no relevant financial or non-financial interests to disclose.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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