The Business Japanese Curriculum Education and Teaching Classroom and Mode Based on IoT Technology in the Age of Big Data

Taking the Japanese major of a college as an example, the training feature is "international business direction", and the talent training mode is divided into two stages: 1~2 years of junior students are learning basic language knowledge, and the goal is to express their views accurately and fluently in their own language at the end of sophomore year; The second stage is from grade 3 to grade 4. In addition to the training and improvement of "language + culture" intercultural communication ability, the main training goal is to learn business knowledge "interdisciplinarily" in Japanese. Each course supports the achievement of the overall goal of talent training, and the teaching materials used in each course must strongly support each knowledge point to achieve the corresponding course teaching goals. See Figure 1 for details

Figure 1.

Distribution of Business Japanese Course of Commercial Specialty

Based on the advantages of the new generation of information technology and various intelligent terminal products, intelligent learning design in commercial Japan is not only a classroom design activity for teachers and students. The smart classroom transcends the limitations of time, region and space, and changes from classroom based application to the whole process. The scene is full of teaching applications, forming an open intelligent classroom interaction. In combination with in class and out of class, online and offline, as well as virtual and realistic business Japanese intelligent teaching design of the whole scene, a complete business Japanese intelligent teaching process will be naturally integrated before, during and after class, and high-quality information resources will be presented to students to the maximum capacity. The characteristics of business Japanese intelligent teaching enabled by IoT technology are summarized in Figure 2.

Figure 2.

Characteristics of Smart Teaching

The intelligent business Japanese learning system can reduce the workload of classroom teachers and administrators, and improve the efficiency of classroom management. Developing an intelligent business Japanese intelligence learning system is crucial to the development of modern classrooms. This chapter first analyzes the functional requirements of the system, and then proposes the terminal and platform control program draft.

Smart sensor measurements are as follows: 6 I=K.R \[I=K.R\]

where R is the measured value, I is the light intensity, and K is the sensor calibration factor.

Smart Curtain Test Formula.

where the present light intensity is denoted by L_s , the target light intensity by L_t , and the curtain adjustment amplitude by A.

The Air Quality Index calculation 8 AQI=∑​i=1nCi⋅Wi∑​i=1nWi \[AQI=\frac{\underset{n}{\overset{i=1}{\mathop{{{\mathop{\sum }^{}}^{}}}}}\,{{C}_{i}}\cdot {{W}_{i}}}{\underset{n}{\overset{i=1}{\mathop{{{\mathop{\sum }^{}}^{}}}}}\,{{W}_{i}}}\]

where W_i is the equivalent weight and C_i is the pollutant type I concentration.

2.2.1

Analysis of system functional requirements

The business Japanese teaching model with IoT technology is in Figure 6, which is divided into preparation module, learning module and evaluation module. Each part is supported by four key technologies and constitutes the core system of business Japanese education. The preparation module is the evaluation stage before students formally start learning, and it is a crucial link to build the business Japanese education system. Learning module is the core of realizing intelligent teaching and is a process of intelligent cycle optimization. The evaluation module is a link to effectively evaluate the teaching effect. It can intelligently adjust the teaching plan and optimize the teaching effect according to the assessment of students.

Formula for Classroom Energy Optimization 9 Es=Et−Eu \[{{E}_{s}}={{E}_{t}}-{{E}_{u}}\]

Where E_s is the saved energy consumption, E_t is the theoretical energy consumption and E_u is the actual energy consumption.

The Attendance Efficiency Formula: 10 E=tttm \[E=\frac{{{t}_{t}}}{{{t}_{m}}}\]

where t_m, is the smart attendance elapsed time, t_t is the traditional attendance elapsed time, and E represents efficiency.

Figure 3.

Intelligent education model

2.2.2

Overall system design

The design of business Japanese intelligent teaching system based on IoT communication technology mainly consists of two parts: smart classroom and monitoring system. The overall architecture of the smart classroom system using IoT technology mainly includes: sensing layer, control layer, data layer and network layer, as shown in Figure 4.

Figure 4.

The smart classroom system using IoT

A correspondingly sized digital sensing collection device is installed on both the inside and outside sides of the smart classroom system to simultaneously sense the surrounding environment and automatically collect all practical application data within the smart classroom. Among the light sensor system devices installed in the smart classroom system, the light sensor module can be specifically used to detect the light level of the entire classroom in real time, so as to achieve real-time, reasonable and accurate dynamic control of the ambient lighting in each classroom area; the RF sensor module installed at the same time can be used to verify the personal identity information of each classroom manager and each student and teacher in real time.

At the same time, each main school building should set up a sub-center control platform to monitor the use of each smart classroom in the school building and the class situation as a whole, and the management personnel of the control platform can access and use the use of each smart classroom, class schedule information and teachers' and students' personal information at any time to facilitate the daily inspection of the smart classroom situation. The school should set up a central control platform to achieve real-time monitoring of the whole school. Management and users are required to verify and validate their identities and complete authorization for use of the control platform.

Formula for Adjusting Instructional Feedback

Lesson plans are modified in light of evaluation findings.

When the assessment objective is C_e, the original plan target is C_o, and the adjustment range is A_c.

Rate of increase in students' linguistic skills 12 G=Lt+1−LtLt×100% \[G=\frac{{{L}_{t+1}}-{{L}_{t}}}{{{L}_{t}}}\times 100%\]

where L_t+1 is the subsequent level of competence, L_t is the starting language competency, and G is the growth rate.

The semantic data layer in the smart classroom system is to transform the standardized data information collected from the intelligent voice sensing devices into semantic, and the standardized voice information should be scientifically screened and stored in the voice data server in real time after processing is completed. The real-time data server in the smart classroom is usually directly connected to the real-time data server system in the school, so that the school management professionals can view and retrieve the real-time data of the smart classroom system in each area of the school through this platform system at any time and anywhere, and get timely information on the use of the smart classroom, the information of the users and the teaching schedule and other data.

The network layer architecture of the smart classroom is mainly built by network transmission equipment, mainly using three kinds of heterogeneous networks, namely Ethernet, star network and wireless network.

The new Academic Attendance Management System effectively solves the previous problem of slow efficiency of paper sign-in or roll-call. Teachers and students can sign-in and sign-out on the corresponding punch card system before class. The classrooms are equipped with a full range of safety monitoring equipment, such as smoke sensors, door sensors, wireless body sensors, etc. When the safety index of the classroom fails to reach the safety standard, the safety monitoring system will send out alarm information independently, which effectively solves the safety problem of the smart classroom and establishes a technical guarantee for the safety of teachers and students. Lighting is also an important part of the smart classroom design. Through the lighting management system, the lighting situation and brightness of each smart classroom can be easily viewed to reduce the waste of electricity. The curtain control system of the smart classroom makes use of traditional curtains and uses IoT technology and sensor technology to intelligently control and adjust the classroom curtains. The remote control mode is to use wireless network remote control system and use mobile devices to connect with the curtains to achieve the purpose of remote control by users. The intelligent air conditioner control system is a combination of intelligent sockets and full-angle infrared transmitters to achieve remote control of the air conditioner. Installing these two devices in the classroom allows the air conditioner to receive remote settings and achieve remote control of the air conditioner.

Noise threshold detection 13 An={ 1,N>Nth0,other \[{{A}_{n}}=\left\{ \begin{matrix} 1, & N>{{N}_{th}} \\ 0, & other \\ \end{matrix} \right.\]

where N_th is the noise threshold and N is the noise value.

Facial recognition matching probability: 14 Pm=NmNt×100% \[{{P}_{m}}=\frac{{{N}_{m}}}{{{N}_{t}}}\times 100%\]

where N_t is the total number of feature points, N_m is the number of matching feature points, and P_mis the matching probability.

The project adopts temperature sensor, light sensor, carbon dioxide sensor and rain sensor to regulate the temperature, detect light, carbon dioxide, noise, detect outdoor environment and automatically open and close windows and adjust to the environment. The project also implements the functions of face recognition, attendance statistics, status detection, and the development of the corresponding app to obtain the data and visualize the operation. In this project, the space and environment of the intelligent classroom are controlled in a holistic and intelligent way, each sensor records and uploads data in real time according to the environmental changes, and the mobile app on the user side receives the data at the same time to obtain effective information and make corresponding planning.

The environmental monitoring module consists of a central processor, a temperature and humidity sensor, a light sensor, an infrared sensor, a raindrop sensor, a high-sensitivity microphone sound sensor, a co₂ gas sensor, and a Sharp optical dust sensor. The micro central processor controls the light bulbs, the air vents, and the infrared light emission. The processed information is sent to the OneNET cloud and APP, so that users can see the classroom environment information directly on their cell phones.

The detection control system is divided into 3 parts: sensing part, information transmission part, and control part. The sensing part consists of various sensors that collect data about the current environment; the information transmission part is responsible for uploading data and issuing commands through Wi-Fi and MQTT communication protocols; the control part, Arduino, judges the light intensity and adjusts the light intensity to achieve energy saving; judges whether the noise exceeds the threshold, and gives the necessary prompt to the noise maker; the raindrop sensor judges whether it is raining or not, and the haze sensor judges the air quality to achieve The raindrop sensor determines whether it is raining or not, and the haze sensor determines whether the air quality is good or bad, so as to automatically close the windows when it is raining or haze. Figure 5 shows the overall hardware block diagram of the environment monitoring module.

Figure 5.

The overall hardware of the intelligent classroom system

Setting student course demands in order of importance: 15 R=wi⋅di∑​i=1nwi \[R=\frac{{{w}_{i}}\cdot {{d}_{i}}}{\underset{n}{\overset{i=1}{\mathop{{{\mathop{\sum }^{}}^{}}}}}\,{{w}_{i}}}\]

If the course importance weight is w_i, the student demand data is d_i, and the priority is R.

The BH1750FVI light sensor is used for light sensing and data acquisition. The sensor SDA pin is used to output the light intensity data, and 1SCL is connected to the clock signal. Figure 6 shows the connection between the light sensor and the chip.

Figure 6.

Connection Diagram of Light Sensor and Chip

A high-sensitivity microphone sensor module is used to collect sound data from the classroom. The A0 port is used to simulate the data output, and the Arduino sets the noise threshold, which is indicated by a light once the sound exceeds the threshold. Figure 7 shows the connection between the sound sensor and the Arduino.

Figure 7.

Sound sensor and Arduino connection diagram

The raindrop module sensor, D0 port TTL signal output to detect whether it is raining or not. The GP2Y1010AU0F dust concentration sensor is used to detect the outside air quality. The sensor is equipped with infrared emitters and phototransistors distributed in pairs of legs, which work on the principle of photosensitivity. If the dust concentration in the outside air exceeds the threshold, the Arduino drives the stepper motor to close the window. Figure 8 shows the smart window circuit connection diagram.

Figure 8.

Circuit connection diagram of intelligent window

Most of the traditional classroom attendance records are taken by teachers before class to sign in, which takes up more class time. The system uses a Raspberry Pi and an 8 megapixel camera to implement face recognition. Firstly, we collect photos to create a database of face photos to be recognized, and then use the deep learning API of Baidu cloud platform to obtain face photos on site and perform live detection, identify 150 face feature points, compare them with the photos in the face database uploaded in the cloud, and output the face recognition results to help teachers sign in. Figure 9 shows the workflow of the artificial intelligence module.

Figure 9.

Artificial intelligence module workflow

After actively transforming the intelligent teaching platform of the IoT into traditional courses, this paper takes students majoring in Japanese and Business Japanese (undergraduate) of the College in 2019 as the survey objects and issues questionnaires. Among the 74 questionnaires collected, "Do you still want to keep the intelligent teaching of the IoT after returning to traditional classroom teaching?" The results of this problem are as follows. See Table 4.

In the question of "learning links to be completed by intelligent teaching of the IoT", this paper adopts the form of multiple topics, and the results are as follows. See Table 5.

According to the answers of the respondents, it is not difficult to see that as a new generation of Internet college students, they accept the intelligent teaching form of the IoT quickly and highly. However, after returning to the traditional classroom, how to set the proportion of online and offline learning time, how to divide the online and offline teaching content, and how to use a more scientific and efficient way to help students understand and master the teaching content are issues worth thinking about by every front-line teacher.

The concept of "golden curriculum" was first proposed by the Ministry of Education at the National New Era Student Education Conference in June 2018, and then "golden curriculum" was included in the documents of the Ministry of Education. At the 11th "China University Education Forum" held on November 24, 2018, the Department of Higher Education of the Ministry of Education released the report "China's Golden Curriculum Design". As an introductory course for zero grade primary school students, the second foreign language and language course should focus on the priorities of online mixed education reform and how to achieve the standard of "gender homogeneity". We can find out what the following questions are. See Table 6.

The survey results show that students are not satisfied with learning new knowledge through traditional lectures, and they are also full of expectations for improving the application ability of business Japanese. Therefore, in the future classroom teaching, we should strive to create a training camp to help students solve problems, improve their ability and face the future, rather than a lecture hall where I tell you what to listen to and accept passively.