Abstract
In recent years, with the rapid development of mobile communication and the increasing popularity of smart mobile devices, the number of mobile communication services has increased sharply, and mobile terminals have become resource-constrained devices. Traditional cloud computing methods have become increasingly unable to meet the needs of many mobile communications services. In order to improve the quality of user experience, mobile edge computing has become one of the key technologies of the fifth-generation mobile communication system. It provides an effective solution that can reduce the load on the basic network and improve the user experience and has received widespread attention from all over the world. In view of the important direction of big data research, how to obtain economically valuable information from audio information is the key; first, the basic technical characteristics of big data and the technology involved are analyzed, and then the basic technical relationship of speech recognition is analyzed and the data are merged, and finally the big information in speech recognition is analyzed. The processing architecture provides a combination of speech recognition technology and big data for the application development technology architecture and application process. The effect of classroom assessment will affect whether students’ learning can be promoted and developed. For most psychology teachers, this is a topic worth exploring to determine what types of assessments can be used in the classroom to promote psychological teaching. The survey results show that in the current psychology classroom, the concept of teacher evaluation has changed, and student self-esteem and peer evaluation have appeared in the evaluation of teaching psychology. The content of the evaluation has gradually shifted to students’ emotions, attitudes, and values, and the evaluation methods have also changed. The type of evaluation can be more praised and encouraged.
1. Introduction
The algorithm for replacing computers and communication resources is based on the pricing mechanism in the MEC system. The algorithm fully considers the network status and user interaction, and provides several methods to reduce the burden on computers. The limited computer and communication resources of the MEC server are used to allocate resources [1]. In the multicell scenario, the allocation model uses QoS-based resource allocation algorithms and effective pricing strategies to provide users with dynamically adapted traffic services and select the best computer. Disabling the offloading path that provides services to users, the macro base station and each LTE bring a small load to the base station, thereby balancing and maximizing the MEC operator’s network revenue. The investigation of the MEC network solution is not thorough enough [2, 3]. For example, there are still many problems to be solved when sharing communication, computing, and storage resources. The MEC server has powerful and effective communication, storage, and computer functions, and is distributed at the edge of each access network. The MEC server is a resource-constrained device [4]. In recent years, computer offloading has become a research hotspot. In real life, different types of calculation problems have different requirements for network indicators. Therefore, in this article, the business priority will be divided according to the user’s QoS indicators. With the improvement of computer computing and network skills, traditional large-scale word processing and data mining, complex systems, speech recognition, ontology, and other academic research have begun to lay a solid foundation for practical applications [5, 6]. Big data research is gradually attracting the attention of scientists and operators. In terms of the development and application of new technologies, big data processing technologies are implemented into existing business systems. Converting academic research results into a real commercial value is a problem worthy of research [7]. Audio is one of the main ways to express information. Extracting commercial information from audio information is an important direction of big data research. In the classroom assessment, students’ self-assessment and mutual assessment are considered. The content of the assessment gradually shifts to emotions, attitudes toward student values, and different assessment methods and levels are adopted. Classroom psychological teaching evaluation will also lead to some problems, such as the lack of opportunities for students to participate in the evaluation, the repeated evaluation of language, the evaluation effect needing to be improved, and the neglect of individual differences between students. Based on the investigation and analysis of the current situation, existing problems, and causes of psychological learning, we put forward corresponding countermeasures.
2. Related Work
If a user submits a computing task to the MEC server for execution, there are two transmission paths. The first is to let users outsource computing tasks to the SeNB, and then use the feedback between the SeNB and MeNB to transfer the tasks to the MEC server for execution [8]. If a load of a specific cell is too high, then the long delay required for users to upload tasks through the SeNB will cause a large delay. However, the current load of small base stations is too large, and the entire network is not conducive to the load of the base station. At this time, the second path can be used for load balancing, and delay-sensitive services can directly use the MeNB to offload computing tasks to the MEC server for execution [9, 10]. In the literature, computer offloading is an important feature and application of the MEC system. Since MEC was proposed, computer offloading research has always been a hot topic in MEC systems. Some computing tasks have been outsourced to MEC. If the computing tasks running locally consume computing resources for server execution, and reducing the burden of MEC execution requires additional communication overhead, MEC’s powerful computing capabilities can be used to save equipment power and reduce access delays [11, 12]. In the traditional classroom assessment, the teacher’s assessment is usually the standard, and the students are only the objects of the assessment and are not qualified for the assessment. In personal interviews with teachers in specific schools, it was found that the interviewed teachers had different levels of understanding and ideas about teaching assessment, but the understanding and application of teaching assessment concepts advocated by the new curriculum reform were not thorough enough, and the traditional classroom assessment concepts still have a certain impact [13]. The literature suggests that at the academic and social level, schools should create a favorable practice and research environment to evaluate psychology teachers in the classroom so that teachers can appropriately develop and improve their assessment skills while creating an environment that provides them with professional support [14]. To provide teachers with guidance, we conduct standardized assessment practices and research, and train teachers to improve classroom assessment methods and strategies [15]. However, it should be noted that when teaching psychology teachers in classroom assessment, in addition to teaching theoretical knowledge for teacher assessment, it is necessary to strengthen the training of teachers’ practical ability to assess teachers. In addition, the survey results show that in the current psychology classroom, the concept of teacher assessment has changed [16, 17]. This article is suitable for the MEC system solution. Next, we mainly discuss the process and basic principles of uninstalling the computer, and the strategy of updating the latest content of the cache system. In the process of uninstalling the computer, various resources in the MEC system are virtualized and abstracted from computing and communication resources, and a price concept is proposed, an outsourcing strategy based on maximizing network revenue and improving traditional mobile resource allocation algorithms [18].
3. Mobile Edge Computing Resource Allocation and Voice Big Data
3.1. Mobile Edge Computing Resource Allocation
As shown in Figure 1, a scenario with multiple units and many users is considered. Each cell has a small base station. Each small base station is connected to the macro base station, and the user role can be a local role. Tasks can also be submitted to the MEC server for execution. In the future 5G system, these small base stations will form their own small base stations, which can each provide services to users.
In the system model, the MeNB is connected to the MEC server, and each SeNB is connected to the MeNB. Corresponding to Shannon’s theorem: between the user and SeNB or between the user and SeNB, as in the following formula:
Use this option to show that is the percentage of the radio spectrum allocated by the small base station n to the user by so that the data rate does not exceed the SeNB backhaul, as in the following formula:
indicates that the total data rate of a user shall not exceed the throughput of the MeNB backhaul, as in the following formula:
In the case of backhaul between MeNB and SeNB, it is assumed that they are only connected by wired fiber, the bandwidth is limited, and the backhaul delay is proportional to the data length. According to the theorem, the uplink data rate at which users can access the MeNB can be expressed as in the following formula:
represents the power spectral density of the additive white Gaussian noise. Similarly, if the user accesses the SeNB through channel h, we can get the uplink data rate as in the following formula:
Different devices have different computing capabilities, and the local execution time can be expressed as in the following formula:
This time includes the wireless uplink transmission time from the UE to the MeNB and the time spent performing tasks on the MEC server, that is, the total elapsed time as in the following formula:
is the processing capacity of the MEC server. In order to pay attention to the impact of different computer offloading methods on the total system revenue, assuming the constants of various computer tasks , represents the total uplink transmission rate from user to MeNB, that is, the following formula:
The total energy consumption is as in the following formula:
indicates that the MEC server has reached a certain power consumption per CPU cycle. Generally, the MEC server is more energy efficient than mobile devices. Therefore, indicates the number of channels used by the device to transmit data to MeBS, as in the following formula:
The total time required for outsourcing tasks through the SeNB includes the uplink transmission time from the user to the SeNB, the delay of the return flight, and the execution time of the MEC server. In other words, the total time spent is as in the following formula :
represents the single data backhaul delay rate and the uplink transmission rate, as in the following formula :
The total energy consumption is as in the following formula :
This article discusses the problem of computer unloading. The main problem is to replace computer communication resources, fully consider the processing power and communication overhead of mobile devices and MEC servers, and use constraints based on meeting user QoS requirements to determine how many computer communication resources to allocate. Figure 2 shows a specific schematic diagram of the parameters used to replace communication and computing resources.
The simulation results are shown below. From the simulation result curve in Figure 3, it can be seen that when the number of users is less than 10, the calculation will be performed. The network profitability of this method is slightly lower than that of traditional algorithms. If the number of users exceeds 10, the network revenue of the algorithm proposed in this article will greatly exceed the usual revenue.
This paper effectively expands the MEC server by overlapping MBS and SBS and configuring each cache server. This hierarchical cache architecture can make full use of the advantages of MEC, improve the service functions of the MEC system, and improve user experience.
In the cache area of the MEC server, each data block stores an attribute representing the CRF weight. Since the cache exchange algorithm uses trade-off CRF to balance access time and access, calculations need to be performed. The formula for the CRF value of the resource file can be defined as in the following formula :
In the above formula, such as in the following formula :
and display the number of accesses to file a in the last time unit, and the value and of file a indicate the current number of times per unit of time.
The defined variable indicates that the video has been cached on server j, and the cache capacity of each server is limited, as in the following formula :
In order to express the possibility of passing the video request to the server j, the vector is defined as in the following formula :
As you can see from the above, one of the above situations occurred when the request was initiated, so constraints can be specified, as in formula :
Therefore, the cost of receiving the video from the j cache server on the return flight can be expressed by the following formula :
The cost of the return flight reflects the business volume and the consumption of network resources in the return journey. Given the available resources, formulate the best objective function to minimize the return cost, as in the following formula :
As can be seen from the above formula, the number of videos that can be fully cached is as in the following formula :
The number of videos in which only the initial segment of the video is cached is in the following formula :
The total number of videos that each MEC server can cache is the following formula :
Assuming that video popularity is evenly distributed, the cache hit rate can be expressed as the following formula :
The access delay of the cache error and the access delay of the cache hit are the average access delay, as shown in the following formula :
3.2. Voice Big Data
In the 1960s, dynamic programming and linear predictive analysis techniques implemented speech recognition for individual words of a specific person. In the 1970s, research on speech recognition was further developed. In the 1980s, HMM and artificial nerves have been successfully used in speech recognition. Since the 1990s, speech recognition has reached important milestones in the development of improved models, parameter extraction and optimization, and system adjustment. Speech recognition technology has begun to develop into real business applications.
This article has fully explored the technical architecture used to process large amounts of data in the industry, and there are many practical examples. The application system of this article uses data to perform business-oriented low-level operations, storage, combination, cleaning, and transformation of large data sets. At the same time, advanced technologies are used to determine the characteristic values of big data, which can be limited to the first level, or the data set generated from the first level can be processed. The business system can easily call, request, and display the processing results, or the analysis system can more effectively extract data features and perform appropriate analysis.
4. Psychological Teaching Classroom Evaluation
4.1. Status Quo of Classroom Evaluation of Psychological Teaching
Most of the content of classroom assessment includes three implementation forms: teacher assessment, student review, and student self-assessment. Table 1 shows the author’s observations on teacher assessment.
It can be seen from the above table that in the teaching process of psychology class, teacher’s assessment is the main factor, accounting for about 90% of the total assessment time. The forms of student mutual assessment and student self-assessment also appear in the education process. It accounts for approximately 10% of the total number of reviews, which shows that in the evaluation process of psychology classrooms, teachers try to get students to participate in the evaluation.
The new curriculum standards indicate that the content of student psychological learning assessment mainly includes the attention of students in the classroom, their learning attitude, the level of active participation, and the ability to use language. Table 2 shows the content of psychological education teaching assessment obtained from classroom observations case.
It can be seen from the results in the table that teachers’ assessment of students’ language skills accounts for approximately 86% of the total assessment time and approximately 14% of all other aspects. This shows that in addition to the knowledge of the students, the teacher’s attention and evaluation of other aspects are the attitude, interest, and enthusiasm of some students to actively participate in the classroom.
Table 3 shows how primary school teachers use the classroom assessment methods discovered by the author through classroom observations and student questionnaires.
It has been observed that psychology teachers usually require students to answer questions individually or collectively in the classroom throughout the class or group, and the teacher provides timely feedback on the evaluation. From the results in the table, this type of teacher oral assessment accounts for about 80% of the total assessment of psychology classes. Sometimes teachers often use body language, written grades, or grade rewards, such as smiling faces, red flags, postcards, and candy.
In the teacher’s classroom, there are three types of evaluation: positive evaluation, negative evaluation, and nonevaluation. Positive evaluation refers to positive evaluation or praise, that is, motivational evaluation. Negative evaluation refers to the recommendation or ridicule of students or the incorrect handling of wrong answers given by students, usually refers to willingness to give correct answers, and etc. Insufficient grading means that the teacher did not evaluate the students’ answers. Table 4 is an overview of the types of classroom assessment.
According to the results of classroom observations, psychology teachers can promote and reward students for most of the timetable in the classroom, accounting for about 82% of the total grades. The reactions of criticizing students, opposing students, or not evaluating students are few, accounting for about 18% of the total. From the analysis of the two charts above, it can be seen that after answering correctly or performing well, the teacher often asks, what will happen to the teacher if the answer is incorrect or poor consciousness; 72.8% and 85.3% of students tend to encourage and praise often. This shows that teachers can usually praise and reward students regardless of whether the student’s answer is correct or not. Only when students do not observe discipline, such as talking to other students without being attentive, sitting casually, and waiting, will the teacher criticize and correct their assessments. Psychology courses are divided into two dimensions: language richness and observation of language ease of use, as shown in Table 5.
4.2. Strategies to Improve the Evaluation Effect of Psychological Teaching
The main function of all learning is to improve people’s quality and to regard teaching as an integral part of overall learning. The main purpose of the evaluation should also be to promote the development of all aspects of the quality of the subject. Classroom teacher evaluation should promote continuous and effective student learning and promote the healthy development of students in all aspects. This is the concept of transforming and supporting our teachers. Teachers should design an assessment framework to promote student development in three ways.
4.2.1. Fully Pay Attention to Student Development
Elementary school is the initial stage of psychological teaching. During this time, students’ interest and enthusiasm for learning increase, which has a great impact on the future of psychological teaching. However, traditional assessment only considers the results of students’ psychological learning and ignores the development of students in the process of psychological learning, such as learning style, learning attitude, learning strategy, interest, as well as screening and learning. Choosing the function of evaluation that is too prominent: the scores are different. Only a few students have passed the evaluation, established their confidence in learning, and gained the joy of success, while other students were ignored or even gave up, resulting in some students losing interest and confidence in learning. In order to avoid this situation, teachers need to follow the concept of the new curriculum reform. Combined with the new curriculum standards, we pointed out in the evaluation suggestions that when evaluating students, we should praise, encourage, and guide students’ behavior and actual situation, attention, learning strategies, etc. according to each student’s psychological level, protect students’ confidence in learning psychology, and promote students’ learning and self-development in all aspects.
4.2.2. Pay Attention to the Individual Differences between the Evaluation Objects
The implementation of classroom assessment concepts that help students develop is inseparable from understanding the individual differences of students. Traditional classroom assessment always uses the same external standards to evaluate students (e.g., tests) and classifies students based on test scores. This level was canceled, and the development opportunities of some students were destroyed. The constructivist theory believes that people have different views and interpretations of the outside world due to different experiences and backgrounds. When evaluating teachers in the classroom, differences in student knowledge and experience should also be considered. When evaluating different students, different evaluation standards and methods should be used. Under normal circumstances, teachers’ choices of classroom assessment topics are very subjective, and they will discriminate against class teachers or students with good performance. These students usually provide more verification, as well as complete freedom of expression and thought. Because of the differences between them and the poor academic performance of other students, teachers often feel that this part of the students cannot learn and will not do well in other fields. Students become addicted and easily rely on the teacher, and the teacher’s assessment directly affects their psychological learning. Therefore, psychology teachers must avoid subjective prejudice, respect differences in students’ personalities and educational experiences, evaluate different content, and develop different standards for students of different levels and personalities. For some students with a high dropout rate or poor performance in school, teachers may evaluate their own characteristics or qualities beyond their knowledge level. For example, we may dare to speak, express opinions, and actively participate in classroom situational work as a standard for evaluation. Teachers should create opportunities and situations for these students so that they can practice the language as much as possible and encourage them to express themselves and communicate in appropriate statements. Teachers should praise and reward their small achievements, help them build confidence, and encourage their further development. We must encourage the best-performing students to maintain their standards, and at the same time, we must strongly encourage them to encourage their continuous improvement.
4.2.3. Encourage Students to Take Class Exams
Students’ development cannot be separated from their own initiative. When studying psychology, they cannot give up the initiative to establish their own mental structure of knowledge. Students can participate in the assessment so that students can more clearly identify each other’s shortcomings and areas for improvement while assessing each other. The new psychology curriculum standard stipulates in the evaluation recommendations that it should focus on combining teacher evaluation and student self-evaluation with student peer evaluation. Students are required to fully evaluate their own answers to questions, own weaknesses and strengths, other students’ answers to questions, find out the reasons for their success or failure in learning, as well as nonintellectual aspects, such as language ability and student proficiency. Emotional attitudes play an important role in the development of education. It is an indispensable link in the process of scientific and meaningful learning for students. Teachers encourage students to participate in the evaluation of psychology classes. This is what should be done: First, to make students interested in the assessment, various situations related to the course content should be created. When some teachers talk about the situation when they go to a restaurant to eat based on the content of the text, the students need to reproduce the content of the text after they are familiar with the text and understand the meaning of the text. Or let students practice this role and then let the students evaluate it after the performance to reproduce a problem that reveals the differences between Chinese and Western food cultures. Motivate learners to evaluate and mobilize their enthusiasm by setting up the context. Second, teachers should take time to give students the opportunity to participate in classroom assessments. Teachers should take time to participate in classroom assessments so that students can express themselves, prove themselves, and actively participate in the classroom. Finally, teachers must allow students to learn how to evaluate. When guiding students to participate in the evaluation, teachers should help students understand the content of the evaluation, take the evaluation methods and standards as the guide, and learn how to conduct the evaluation. For example, when students perform assessments, they must learn to “listen” and “see.” This is the only way to find out what other students are saying and doing and what they have achieved. Finally, considering how they should evaluate and organize the evaluation language, and how they should be evaluated, students should also humbly listen to the feedback and opinions of others. Due to differences in students’ language proficiency, vocabulary, sentence expression, etc., teachers need to understand and record students’ differences in these aspects in psychology teaching, so that different students can participate in the assessment and give them opportunities to appear. It should be pointed out that when instructing students to conduct assessments, teachers should encourage students to cherish and learn from each other instead of focusing on each other’s shortcomings, otherwise it can easily lead to student dissatisfaction, accusations, ridicule, and advice. Students will know how to cherish others, tolerate learning, create an atmosphere of solidarity and mutual assistance, and improve and develop together.
Advanced evaluation theory should be established. Combined with the evaluation concept of psychological courses and educational and teaching purposes, people should establish a reasonable and scientific psychological classroom evaluation system, carefully define the evaluation objectives of psychological classroom, clarify the evaluation contents and standards, and select appropriate evaluation methods and tools. The purpose of classroom psychological evaluation is to determine the premise of the content, standards, and methods of the evaluation. The evaluation goal should be based on the appropriate evaluation education theory, psychological education goals, and the concepts and evaluation requirements put forward in the new curriculum. As educational evaluation theory provides a theoretical foundation and support for classroom evaluation goals, the new curriculum proposes psychological education goals in order to provide specific evaluation content and evaluation standards for classroom evaluation to select specific evaluation methods and evaluations. The concepts and requirements of guidance should be provided for assessing classroom objectives. In order to scientifically and reasonably determine the purpose of assessment of psychology teaching, these two elements must be combined.
Students should appropriately develop knowledge skills, emotional attitudes, teaching strategies, and cultural awareness through some psychological teaching. Therefore, the selection of the evaluation content and the evaluation system definition criteria of the psychological office should also be multidimensional and adaptable.(1)Extensive language knowledge and skills The most basic assessment content of the psychological assessment is basic language ability. In the process of working in the classroom, in addition to questions, vocabulary dictation, classwork, reading texts, and exercises to obtain simple answers, teachers can also learn how students master language psychology. Create specific problem situations, for example, divide students into groups to perform, go shopping, to the doctor, and play, so that they can participate in actual problem-solving. In the process of problem-solving, students can be tested with language. The ability of expression, such as whether oral expression is clear, whether the pronunciation and intonation are standardized, whether they understand others, whether they can express their own thoughts, and the ability to act and innovate psychologically, are all reflected in the language. People should focus on the process of solving problems rather than copying the dialogue in the book.(2)Emotions, relationships, and values The evaluation system should assess learners’ emotions, attitudes, and values, including learners’ interest in learning when to participate in various classroom activities and encourage students to develop language skills. In addition to evaluating students’ language proficiency, teachers should also evaluate whether students are listening carefully in the classroom, whether they are actively speaking, whether they can create new situations and use academic performance and learning ability to judge, whether they actively participate in group activities and perform joint tasks, etc.
The processing of psychological evaluation results in the classroom is mainly carried out after teachers quickly collect students' information, especially reasonable ranking, evaluation, and analysis. Teachers use language and methods that students can understand to explain so that psychological evaluation can be conducted in the classroom and students can understand. In this way, learners can immediately and directly understand their own progress or decline and make adjustments in time to better learn. The teacher’s ability to provide timely feedback affects students’ performance in the classroom. For example, a teacher reported that for a student or group, the best grade is the worst, and the teacher will reward individuals or groups. When the teacher with the worst academic performance is punished, the teacher must keep his promise in time to make the students feel that the teacher is trustworthy. The trust in the teacher will help the students become positive in the future. At the same time, teachers should analyze the students’ absorption of new knowledge so that they can adapt to their own activities.
In order to improve the knowledge framework of psychology teachers’ self-assessment courses, they must continue to expand their knowledge of education and teaching assessment, pay attention to recent research on assessment teaching, and finally, assess the teaching of psychology. Teachers summarize these experiences, share assessment experience with colleagues and experts in schools and other places, gradually improve the knowledge structure of classroom psychological assessment, and constantly improve their assessment skills. This means that learning needs to reflect more than these practices. All aspects of assessment knowledge should also emphasize the background of the assessment, so that if teachers use different assessment standards, assessment methods, assessment language, etc., they should clearly understand the specific teaching environment of the assessment. Steadkins and Conklin said that teacher assessment training aims not only to teach teachers knowledge and survey techniques but also to teach teachers how to use practical tools and methods, and design and develop data collection procedures. Let teachers understand the common misunderstandings in assessment, such as assessment bias and abuse of assessment methods, so that teachers can avoid these misunderstandings by using correct attitudes and methods. At the same time, teaching knowledge should be closely related to the teacher’s teaching experience: learning necessary and useful skills for assessment in the classroom.
5. Conclusion
This article summarizes the full text of the research and focuses on the resource allocation of mobile edge networks and optimization of computer, communication, and storage caching strategies. It focuses on offloading computers, pricing algorithms, and various cache refresh strategies. As a starting point for research, it is optimized together with communication resource allocation and cache allocation, and memory resource refresh algorithms. Finally, this article discusses the future application of general problems in the optimization of communication, memory, and computing resources in MEC systems. Combined with the current application direction, the focus is on the architecture of the key technology system voice big data, and provide the processing flow and direction of the big data voice application program. The future direction of research lies in algorithmic methods through which the variables and features at the end of language big data can be identified and analyzed, standardized, and semantic processing technology can be further integrated. It can help better understand and discover content to discover big data at the enterprise level. At the same time, the efficiency of the processing technology of the big data function for extracting and analyzing large amounts of data is being studied. Can a processing architecture be created for distributed computing? Large amount of data can be processed in parallel, and data attributes of business systems can be retrieved quickly. In enterprises, the rules for analyzing and invoking business systems need to be improved, and the design of reporting systems for business requirements and data mining also needs to be improved so that the value of big data can be fully reflected. Classroom assessment focuses on the learning process of the learner, not the learning outcome. It not only focuses on assessing learners’ knowledge and skills but also on their participation in the classroom, learners’ attitudes, emotions, and values, and the significance of promoting and improving the psychological evaluation of learners’ learning environment. Therefore, classroom assessment research has important practical and theoretical functions.
Data Availability
The data used to support the findings of this study are available from the corresponding author upon request.
Conflicts of Interest
The author declares that there are no conflicts of interest.