Figure
T-test for Independent Samples of the attitudes EFL teachers towards using smartphones in the classroom due to grades the teacher teaches
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... In this research, the smartphone became the most apparatus used by students to listening English through video. Based on Dweikat and Hasan (2021), the use of smartphones offers a positive attitude for teaching and learning. The majority of English department and non-English department expressed the entertainment like song and daily activities topic were suitable for improving listening skill. ...
As the usage of ICT in teaching and learning, digital literacy becomes well-liked for Indonesian English department and non-English department students from Jakarta and Central Java. This research is to investigate both the students’ listening comprehension and their insight into educational videos for improving their listening skills. The objectives are: 1) finding out the students listening comprehension through watching VOA Learning English, 2) obtaining the students' perception of listening to English?, 3) exploring students' preferences to listen through video?, 4) investigating the listening media and topic the students like to listen to?, 5) probing the students' familiarity with VOA Learning English? This research was a comparative study including descriptive statistics. The questionnaire results revealed that the students from the two campuses shared similarities and differences in their preferences to increase their listening skills through video. The students of the English department and non-English department listening comprehension were categorized as fair since most of them reached scores between seventy and eighty. The majority of both English department and non-English department students like to listening English. However, they prefer watching a video in the form of a combination between monolog and dialog. They were enjoy the song for improving their listening skill. They also commit that the VOA video was interesting since it was designed to help them in developing their English skills daily. Likewise, such videos performed native speakers as role models which are favored by English department and non-English department students. Besides, they like to receive the questions after the video ends.
... e system structure of the smart classroom system is shown in Figure 1. Pad mobile platform allows users to register and log in and realize the collection and upload of basic face information; through receiving the instructions from PC workstation, the collection and preprocessing of face attendance information are completed; the submission of face attendance information is completed, the online examination, teaching evaluation, electronic whiteboard display, and other functions are realized, and the results of teaching evaluation information and performance information can be queried in real time [17]. e equipment control system in the classroom uses PID control related technology to set the target temperature value, realize automatic temperature control, and adjust the set value of stable operation in the target area. ...
Smart classroom teaching is one of the new teaching methods. With the support of technology, teaching is carried out with the help of smart teaching tools to enhance teacher-student communication, enhance students’ learning autonomy, and provide new ideas for the realization of students’ deep learning. How to promote the overall intelligence of the teaching environment so that the teaching equipment can be used more efficiently and managed more effectively has become the main concern of schools. This article mainly studies the smart classroom system based on the Internet of Things technology and smart classroom. For temperature detection, we mainly use the DS18B20 chip to detect the temperature in the classroom. For the light intensity of the classroom, we use a photoresistor to collect the light data, and after amplification by the amplifier, the A/D sampling process of the single-chip microcomputer is used to obtain the light intensity, combined with the clock module to distinguish the influence of the classroom light. The data collection adopts the method of directly observing the source data, and the data format has not undergone secondary conversion, which ensures the accuracy of the source data. This test uses the USR-TCP232 network debugging assistant to debug the data collection. To optimize the safety and reliability of the system, dual-computer backup switching is adopted on the hardware, and process monitoring and management strategies are adopted on the software. At the same time, the amount of data interaction in the smart classroom is relatively large, so it is necessary to build a highly available cluster server, so that the system not only has a certain degree of stability, but also can quickly respond to users’ access requests. We can calculate that the average transmission time is about 10 ms, and 99.9% of the data transmission delay is less than 30 ms. The results show that the Internet of Things and smart classroom provide great convenience for future smart campus construction, daily teaching, and campus management and can also provide reference for the construction of smart classrooms in other universities.
1. Introduction
The continuous development of new media technology promotes the development of modern education technology and at the same time puts forward higher requirements for modern education technology workers. The continuous updating of educational technology, coupled with the improvement of the functionality and operability of multimedia classrooms, has created favorable conditions for the application of modern educational technology in colleges and universities. The use of multimedia equipment to develop and serve modern teaching has become a common phenomenon and then developed into a new teaching mode. Based on the concepts of smart equipment management, safety management, and energy-saving management in the classroom, this paper designs and develops an IoT cloud platform for smart classrooms and realizes real-time management of classroom environment information, combined with the development of smart campus.
With the development of information technology and the wave of intelligent technology, colleges and universities are exploring new teaching models to meet the needs and development of education. Through thinking and improving teaching, students’ subjective initiatives can be mobilized and their creativity cultivated. The Internet of Things technology is developing rapidly. The use of Internet of Things technology to build smart classrooms is helpful for information sharing and analysis and has a significant impact on the way of learning knowledge. Students majoring in the Internet of Things, computer, and other related majors can use the platform to learn wireless sensing technology and embedded development technology and can also use the provided interface to carry out the secondary development of the project.
The environment created by the smart classroom stimulates students’ interest in learning, thereby improving the quality of education and teaching. Li believes that as the Ministry of Education vigorously promotes the construction of smart campuses, the development concept of smart campuses will have broad application prospects. However, colleges and universities are still at the stage of digital campuses, and there are still many problems. He designed and realized a complete intelligent campus management system by analyzing the design principles and design goals of the system. His system is mainly divided into face recognition terminal hardware based on the Internet of Things and smart campus software system. Although the user satisfaction of the system he studied is relatively high, there are still certain shortcomings [1]. Kim believes that the degree of student participation refers to the degree to which students are immersed in learning when receiving education in the classroom. He proposed an environmental intelligence algorithm for smart classrooms. The algorithm provided information to teachers by measuring student participation in real time. He proposed an algorithm for evaluating student participation by measuring thermal infrared images to evaluate students’ mental state. He proposed a measurement model that uses thermal infrared imaging to characterize student participation. The color of the teacher’s mobile application will change in real time according to the immersion level of the students in the classroom. Although the algorithm he proposed is innovative, it lacks algorithm simulation [2]. Tissenbaum and Slotta believe that although K-12 media has had a significant impact on many other aspects of life, people’s classroom environment has not yet incorporated ubiquitous computing, augmented reality, and other emerging technologies, even touch screens. He has carried out a series of design-based research projects to investigate the smart classroom infrastructure, which provides support for students and teachers in a new form of collaboration and inquiry, including the substantial role of large projection displays and small touch surfaces, as well as the dependence of the student’s physical location in the room. His design includes (1) the role of a large-screen display to transmit aggregate information and environmental information, (2) real-time communication between students, (3) application of intelligent software agents to formulate real-time teaching logic, (4) support cross-context learning, and (5) investigate the coordination of roles, materials, and environment. Although his research has a certain role in promoting the development of smart classrooms, it lacks specific experimental data [3]. Lin believes that, in recent years, many organizations have announced the importance of software development to the country, society, and individuals. In the process of software development, various unpredictable problems are often encountered, especially when developing large and complex software. To reduce the possibility of these problems, it is essential for students to apply software engineering techniques to scientifically define the standards, models, and processes required in the software development process. His goal is to apply an innovative teaching method, called flipped classroom, to implement a learner-centered learning environment in software engineering courses. In addition, he also developed an intelligent learning diagnosis system to support the teaching of this course. He conducted experiments on a software engineering course at a university in Taiwan to explore the effectiveness of the proposed method. The experimental group adopts the flipped classroom teaching method, and the control group adopts the traditional classroom teaching method. Although his research is more accurate, it is not innovative enough [4].
Through the Internet of Things application platform for teachers and students to build a learning experience platform with strong credibility, teachers and student users can integrate into all aspects of the Internet of Things application platform through actual operation and management, which facilitates the high-speed flow and sharing of information resources. To make full use of the Internet of Things application technology to enhance the information management of the university classrooms, based on the professional characteristics to promote the integration of theory and application practice of diversified universities, through the Internet of Things application platform to provide teachers and students with a strong credibility of learning experience, teachers and students can integrate into all aspects of the Internet of Things application platform through the actual operation and management.
2. Smart Classroom System Design
2.1. Internet of Things
With the rapid development of the Internet of Things, a large amount of unstructured data will be generated. These data are growing exponentially. The data are complex and polymorphic, and there is no obvious correlation between them. However, the traditional data acquisition, analysis, storage, and processing technologies can not meet the needs of the rapid development of society [5, 6]. Therefore, if we can focus on the following key technologies in data processing of the Internet of Things according to the characteristics of data, massive data storage, data fusion, data query, search and mining, intelligent decision making, etc., it will play a technical support and promotion role in information construction, smart city, industrial manufacturing, smart agriculture, commerce, finance, transportation, and other fields [7, 8].
Assuming that, in the regression of the function curve, the weight coefficient A, the standard deviation S, the mobile application behavior variable x, and the linear change variable y ensure a high degree of fit between the function curve and the sample point data, it is necessary to establish an alternative relationship expression between x and y based on the regression equation formula. The calculated residual SS can be used to determine whether the fitting is a composite data mining analysis requirement, and the expression is as follows [9]:
The relationship between the conversion delay of the curve regression sampling point and the perception accuracy is as follows:
Among them, represents the conversion delay and d represents the perception accuracy [10].
The errors of linear data mining are as follows:
Among them, i represents the user scale, j represents the number of data mining polls, and the function P is used for curve fitting [11].
The similarity between the user demand conclusion of linear data mining and the actual demand is as follows:
The characteristics of the Internet of Things technology are to give objects to perceive the environment and to communicate with each other and have simple intelligence, so for the architecture design, the Internet of Things needs to support the above three main features. Generally speaking, the technical architecture of the intelligent Internet of Things can be divided into three levels. We can call it the control layer or perception layer, the transmission layer or network layer, and the application layer or service layer [12, 13]. After the IoT terminal device perceives the surrounding environment data, these data need to be transmitted. Therefore, the support of the network layer is required. Through the connection of the network layer, objects can be connected in series to form a mesh structure. In addition to transmission, the confidentiality and correctness of data transmission must be ensured, while stability and continuity are required. The higher-level requirement is to occupy less bandwidth and the transmission process needs to occupy less energy consumption [14, 15].
Zigbee wireless network channel distribution is shown in Table 1. Different types of network can be used to transmit different types of data to achieve the optimal allocation of network resources and the perfect integration of sensor network and current network and to realize fast, stable, accurate, safe, and reliable transmission of data. On the terminal, various functional requirements can be realized according to data characteristics and user needs, which can be realized through application design and development [16].
Number of frequency bands
Channel frequency spacing
Transfer speed (kbps)
Modulation mode
Maximum frequency
Minimum frequency
1
0
20
B0SK
868.2 MHz
868 MHz
10
2
40
HPSK
928 MHz
902 MHz
16
5
250
QPSK
2483.5 MHz
2400 MHz
The integration of mobile technology in learning process has become a challenge for education. In this study authors aimed to identify teachers' perceptions of stu-dents' mobile devices use in school environment, based on the subject they teach. Another aim of the study was to reveal the impact of teachers' experience in inter-acting with mobile devices and their attitudes toward mobile technologies on the perception of students’ mobile devices use in school. Based on the conceptual framework of the technology acceptance model, a questionnaire was developed that identifies attitudes toward mobile technologies, perceived usefulness and per-ceived ease of their use, as well as ideas about the patterns of mobile devices use by schoolchildren. The study involved 358 teachers aged 21 to 75, 91.6% wom-en. Results show that teachers generally see students’ mobile devices use as a distraction, but some acknowledge its constructive use in certain subjects. Teach-ers' attitudes and experiences greatly affected their perception of students' mobile devices use, with positive attitudes leading to more favorable views. The study highlights the significance of understanding teachers' attitudes and experiences with mobile technology for its successful integration in education, suggesting that fostering positive attitudes among teachers may promote better integration of technology in the learning process.
W rozdziale podjęto rozważania dotyczące perspektyw badawczych dla szkoły postpandemicznej. W związku z tym zdefiniowano pojęcie szkoły postapandemicznej oraz dokonano przeglądu badań prowadzonych w Polsce i zagranicą w okresie trwania epidemii COVID-19. Na tej podstawie wyprowadzono wnioski i określono kierunek dalszych badań, analizujących zróżnicowane aspekty funkcjonowania szkoły postapandemicznej, jak i wszystkich jej podmiotów. Zaprezentowano założenia badań osadzonych w metodologii jakościowej, które są prowadzone w ramach Programu wsparcia psychologiczno-pedagogicznego dla uczniów i nauczycieli (PWPP), realizowanego przez Uniwersytet Kardynała Stefana Wyszyńskiego w Warszawie. W ostatniej części rozdziału przedstawiono rekomendacje pedagogiczno-metodologiczne.
Since the New Education Policy 2020 was published, important facets of the educational technology landscape have changed quickly across the nation. The number of educational institutions with access to broadband in their classrooms, the kinds and costs of technology available to educational institutions, an evolution in the way leaders approach the purchase of ed tech solutions as well as a greater emphasis on data security and digital citizenship, the arrival of new research on the use of technology by young learners, and a greater emphasis on training teachers to lead with technology are some of these changes. We also need to alter how frequently the National Education Policy was modified in order to stay up with the changes that are occurring in schools, colleges, and institutions on a nearly daily basis. According to feedback from our stakeholders, the prior education policy did not occur frequently enough. To better reflect the rate of innovation in the industry, we start a pattern of regular, smaller-scale modifications to the NEP 2020 with this 2020 update. In light of this, it is clearer than ever that educators' daring attempts to adopt the role of thinking, reflective innovators who engage together with one another and their students to investigate novel learning models are paying off, new digital learning environments, and new approaches to working, learning, and sharing is essential if we want technology to be an effective tool to transform learning.
The present study employs the Technology Acceptance Model to explore secondary school teachers’ perceptions towards acceptance of tablet devices in their teaching practice in the classroom. A questionnaire was completed by (N=80) secondary school teachers from South Africa, and the constructs related to technology acceptance were measured along with demographic variables. Results revealed that there were no statistically significant differences in teachers’ perceptions towards acceptance of tablets in their teaching practice across gender, age and teaching experience. The findings also showed that the perceived usefulness construct has a high negative response towards the acceptance of tablets in their teaching practice. However, the findings also revealed that the perceived ease of use, attitude towards use, and behavioural intention are directly significant factors in teachers’ perceptions towards accepting tablet devices in their teaching practice.
