International Journal of Continuing Engineering Education and Life-Long Learning (56 papers in press)
Dynamic Evaluation Method Of Distance Learning Quality Based On Mooc Theory
by Xiao-long Wen, Lin Zeng, Jun-cheng Wang
Abstract: In order to improve the accuracy of distance education quality evaluation, a dynamic evaluation method of distance education quality based on the theory of MOOC is proposed. The fuzzy correlation constraint method is used to evaluate the remote MOOC teaching quality dynamically. The big data in the process of the dynamic evaluation of the remote MOOC teaching quality is mined by association rules to obtain the binary semantic features of the remote MOOC teaching quality. The dynamic feature set of remote MOOC teaching quality evaluation is constructed, and the decision function of remote MOOC teaching quality evaluation is constructed by fuzzy c-means clustering method. Through the similarity fusion method, the dynamic evaluation of the remote MOOC teaching quality is carried out. The simulation results show that the method can evaluate the quality of MOOC teaching dynamically and has high precision.
Keywords: MOOC theory; distance learning; quality; dynamic evaluation; fuzzy correlation constraints.
Research On The Evaluation Method For English Teaching Efficiency Based On Data Mining
by Zhonghui Man
Abstract: In order to overcome the problems of large errors and long time consuming in traditional evaluation methods for English teaching efficiency, a new method based on data mining is proposed. This paper first introduces the application of DEA in the evaluation of English teaching efficiency, combines the decision-making unit of DEA with data mining, and then cleans, supplements and repairs the acquired teaching data to complete the mining of the characteristic data of English teaching efficiency evaluation. At last, the data of English teaching efficiency evaluation of college students and teachers are obtained by questionnaire survey. The experimental results show that the proposed method has a small error and a short evaluation time in the evaluation of English teaching efficiency, which has a certain practical significance.
Keywords: Data mining; English teaching; Efficiency evaluation; Excellence rate; Reliability indicator.
Research On The Teaching Mode Of Improving The Learning Efficiency Of University Students Based On Vr Technology
by Lede Niu, Ying Chen
Abstract: In order to solve the problem of low learning efficiency of students under the traditional teaching mode, this paper proposes a new teaching mode based on VR technology to improve the learning efficiency of university students. This teaching mode is based on VR theory. It constructs VR teaching data background, including teaching organization information and event system, which together constitute the current classroom VR immersion teaching environment. Relying on VRPC interface and high-performance CPU, it builds VR development platform, constructs WTK, Vega, MR and other teaching tools, enriches VR teaching methods. Finally, according to the characteristics and principles of VR teaching, it designs the basis. In VR teaching platform tools and teaching background appropriate teaching mode, to achieve the improvement of university students' learning efficiency. Experimental data show that the education model can improve students' interest in learning from multiple perspectives, thus effectively improving students' learning efficiency.
Keywords: VR Technology; VR Teaching; Teaching Background; Creativity.
An Effectiveness Model Of Vocational Education Mode Reform Based On Data Mining
by Jiaen Gu
Abstract: The existing education mode reform model is not deep enough in data mining, there are problems of poor accuracy and low credibility. This paper proposes the construction of the effectiveness model of vocational education mode reform based on data mining. Analyze the effective indicators of vocational education mode reform, obtain the indicators of vocational education mode reform; use the simhash algorithm to remove and clean the indicators of vocational education mode reform, and use the data information gain algorithm to select the characteristics of indicators. Construct the topological structure of the effectiveness model, determine the input and output parameters of the model, introduce the data mining method to mine the effectiveness index data, and complete the construction of the effectiveness model of vocational education mode reform. The experimental results show that the validity index of the model is 26.79, and the analysis accuracy of the model can reach 97.2%.
Keywords: Data mining; Vocational education; Mode reform; Effectiveness model.
The application of virtual reality technology in the efficiency optimization of students online interactive learning
by Ninghua Lv, Jingjing Gong
Abstract: In order to overcome the problems of poor interactivity and insufficient authenticity in the current research methods for students learning efficiency, this paper proposes an efficiency optimization method for online interactive learning based on virtual reality technology. The individual extremum in the learning system is tested by variation factor, and the depth zero locus information and feature space of students online learning are obtained. By using virtual reality technology, students performance interval value is divided and corresponding learning content is tracked quickly. Combined with the principle of greedy search, through the normalization processing, the online interactive learning of students is updated, to achieve the optimization of learning efficiency. The experimental results show that this method has strong performance in the aspects of fluency, interaction and virtual reality of virtual learning.
Keywords: Virtual reality technology; learning efficiency; optimization; normalization.
Interactive Sharing Of Fragmented English Learning Resources Based On Internet Of Things
by Na Wang, Xiaohong Zhang
Abstract: In order to overcome the problems of low user satisfaction in current research on English learning resources sharing, this paper proposes interactive sharing of fragmented English learning resources based on Internet of Things technology. This method mainly uses questionnaire survey to investigate students of different grades and majors in normal universities. On the basis of sharing research, this paper introduces the Internet of Things technology, divides the interactive sharing of English learning resources into perception layer, network layer and application layer, and analyzes the key technologies of communication module, resource management module, user management module and dynamic interactive sharing in the process of sharing. The experimental results show that the research results in this paper have good user satisfaction and high resource utilization rate, and are more suitable for interactive sharing of English learning resources.
Keywords: Internet of Things; Fragmentation; English learning resources; Sharing.
Study On The Evaluation Method Of Students' English Classroom Performance Based On Big Data Analysis
by Wenting Ma
Abstract: in order to overcome the problems of low rationality, low significance and low accuracy of the current evaluation methods of students' English classroom performance, this paper proposes a method based on big data analysis. It uses the method of questionnaire to obtain the evaluation indicators of experts and students, uses the method of vector normalization to deal with the original decision matrix, and uses the information entropy to calculate the corresponding weight of the evaluation indicators of students' English classroom performance. It also uses the product operator to aggregate the evaluation matrix, combines the reference point method model, the total multiplication model and the ratio system to obtain the evaluation value of students' English classroom performance, and to achieve the evaluation of students' English classroom performance. The experimental results show that the proposed method is more than 90% reasonable, more than 90% significant, and more than 93% accurate.
Keywords: Big Data Analysis; Evaluation Indicators; Classroom Performance; Evaluation Methods.
A New Evaluation Method For English Mooc Teaching Quality Based On Ahp
by Xin Li
Abstract: In order to overcome the problems of traditional English MOOC teaching quality evaluation methods, such as accuracy and low evaluation efficiency, this paper proposes a new method of English MOOC teaching quality evaluation based on AHP. This method selects evaluation indexes through factor analysis, establishes evaluation index sets, and performs normalization processing. Set up a comment set, use AHP to calculate the index weight, calculate the membership degree according to the weight calculation result, construct the membership degree matrix, and finally conduct a comprehensive evaluation of the English MOOC teaching quality. The experimental results show that compared with traditional evaluation methods, the proposed method has higher accuracy of teaching quality evaluation, the highest evaluation accuracy is 97.8%, and the detection efficiency of the proposed method is higher, the shortest evaluation time is only 0.9min, It shows that the proposed method has higher practical application performance.
Keywords: AHP; MOOC; English teaching quality; Membership matrix.
Quasi-experimental study on the classroom flipping degree in the course of Information Technology and Application
by Ke Hong, Lu Jia
Abstract: Abstract: In recent years, the flipped classroom teaching mode is increasingly widely applied. We adopted the flipped classroom teaching mode in the course of Information Technology and Application in Nanchang University and achieved the good teaching effect. In order to deeply explore the relationship between flipped classroom and teaching effect, three groups of flipped classroom experiments were performed under three flipping degrees (25%, 50% and 75%) and the statistical data analysis was performed with the final experimental results. The analysis results indicated that the teaching effect was the best under a flipping degree of 50%.
Keywords: flipped classroom; classroom flipping degree; experimental comparison; data analysis.
Design and application of educational information management system based on SOA
by Liping Han
Abstract: Due to low throughput, long average response time and low operating efficiency of current educational information regulatory system, it is because of SOA framework designed. The hardware part includes system access port module, computer-aided instruction module and security management module. The software part uses the service bus of the SOA framework to complete the collection of educational information, realise the management of educational information through the service interface, calculate the average value of the time series of the teaching resource management data through the moving average method, filter the redundant data, and realise the collection and sharing of educational information To complete the design of service function of educational information. The experimental results show that the designed system has the characteristics of fast response, high efficiency and high throughput.
Keywords: SOA framework; Teaching resources; Management system design; Application research.
The Evaluation Method Of Distance Learning Engagement Based On The Multi-Level Linear Model
by Humin Yang
Abstract: The traditional evaluation process of distance learning engagement cannot solve the problem of hierarchical confusion of the data to be processed, which leads to low recovery rate of distance learning engagement data and large evaluation error. A distance learning engagement evaluation method based on multi-layer linear model is proposed. Establish the level index of distance learning curriculum, compile the questionnaire of students and teachers, and determine the influencing factors of distance teaching involvement. By constructing a multi-layer linear model of distance learning, this paper analyzes the curriculum effectiveness that affects students' engagement ability in distance learning, and evaluates the engagement degree of distance learning.The simulation results verify that the recovery rate of the proposed method is above 97%, and the error rate of the evaluation of distance learning engagement is below 0.002%.
Keywords: Multi-leveled linear model; Distance learning engagement; Evaluation.
Study on the Design of Interactive Distance Multimedia Teaching System based on VR Technology
by Tian Ge, Otto Darcy
Abstract: In order to improve the intelligence and human-computer interaction of interactive distance multimedia teaching, an interactive distance multimedia teaching system based on virtual reality (VR) technology is proposed. Firstly, the overall structure of the interactive distance multimedia teaching system is designed under B/S framework. Secondly, the VR information of the distance multimedia teaching system is reconstructed by means of fuzzy control parameters and fast image region segmentation. Thirdly, information fusion and regional scheduling of VR scene images of interactive distance multimedia teaching are implemented using a deformation model. Finally, the background server construction and interface design of the interactive distance multimedia teaching system are carried out under the B/S framework. The simulation results show that the interactive distance multimedia teaching system designed by this method has a stability of over 99% and a strong response ability of human-computer interaction, which improves the control ability of distance multimedia teaching.
Keywords: VR technology; interactive; distance multimedia teaching; system design.
Research On Evaluation Of Mooc Distance Learning Effect Based On Bp Neural Network
by Jiefeng Wang, Henry Loghej
Abstract: At present, MOOC learning effect evaluation method has the problems of large evaluation error and low evaluation efficiency. Therefore, this paper proposes a MOOC distance learning effect evaluation method based on BP neural network. Select the evaluation index, and the gray correlation analysis method is used to optimize the evaluation index, and the entropy weight method is used to calculate the index weight. The BP neural network model is constructed, which is used as the evaluator of MOOC distance learning effect. The sample data to be identified is input to minimize the accumulated evaluation residual and output the evaluation result of MOOC distance learning effect. After testing, the error rate of the design method is only 0.9259%, the evaluation time is always less than 1.0s, the evaluation error is small and the evaluation efficiency is high.
Keywords: MOOC; Distance learning effect; Gray correlation analysis; BP neural network.
A New Hybrid Teaching Platform for College English Based on Iot
by Fangqiong Liu
Abstract: In order to improve the practice ability of new hybrid teaching of college English, it is necessary to integrate hybrid English teaching resources, so a new hybrid teaching platform for college English based on the Internet of Things is proposed. In this paper, a new hybrid teaching resource information fusion model for college English is constructed, and hybrid teaching resource information about college English is scheduled using the big data statistical analysis method, and network modularization design is carried out for the new hybrid teaching platform for college English under the Internet of things. The simulation results demonstrate that the new hybrid teaching resource scheduling method for college English can provide good information fusion and contribute to high output stability and reliability of the teaching platform.
Keywords: Internet of things technology ; college English; new hybrid teaching; practice; resource fusion; big data.
The advantage resources mining of practical English with internet of things technology
by Chunzi Zhang
Abstract: In order to overcome the problems of low efficiency and accuracy of traditional methods for the advantage resources mining of practical English, this paper proposes a new method for the advantage resource mining of practical English which integrates Internet of things technology. Using the Internet of things technology to guide the focused crawler, the search strategy ACO-FC to collect practical English resources can be gotten, the features of practical English resources are extracted, the weight corresponding to the features of English resources by TF-IDF weight calculation method is calculated, and the practical English resources are classified by the nearest distance discrimination algorithm of class center vector, so as to complete the advantage resources mining of practical English. The experimental results show that compared with the traditional mining methods, the mining efficiency and mining accuracy of the proposed method are higher, and the highest mining accuracy can reach 98%.
Keywords: Internet of things technology; Advantage resources of practical English; Resource classification; Resource mining.
Research on Modeling and analysis of factors influencing students classroom communication ability based on support vector machine
by Jue Wang, Xi Chen, Yang Zhang
Abstract: In order to improve students classroom learning effect, the influencing factors of communication ability were analysed. The traditional method of analysing students classroom ability neglects the ordering of classroom communication ability factors, which results in poor fitting effect and high CPU consumption. This paper proposes an analysis model of influencing factors of students classroom communication ability based on support vector machine. The sample data were converted and cleaned to establish a SVM model for influencing factors and students classroom communication ability. The trained SVM model was used to analyse the degree of influence of each factor on students classroom communication ability, and the factors were ranked in importance, so as to clarify the influencing factors of students classroom communication ability. The simulation results show that the prediction results obtained by the research method are close to the fitting curve of the actual results. The CPU consumption of system operation is 15.88 Hz, which is lower than the traditional method.
Keywords: Support vector machine; Students classroom communication ability; modeling analysis of influencing factors.
Expectations for cooperative instruction supported by the Internet+Employment platform in work placement practice
by Xifeng Liao
Abstract: Close high-quality cooperation between a workplace employer and the college is a prerequisite for effective training of students in vocational education. Therefore, the researcher adopted the internet+employment platform as a typical case to analyse its main supportive functions for work placement instruction. Descriptive data analysis was employed to study the expectations of both vocational students and workplace supervisors for the cooperative teaching supported by the platform. The case study showed that the platform was weak in several areas such as in sharing teaching resources to facilitate employer-college cooperation. The results of the data analysis suggested that most students and workplace supervisors have a thorough understanding of the importance of closer cooperation and cooperative assessment by both the employer and the college. However, the expectations of the students and workplace supervisors were different in seven aspects. Among them, the students did not expect much cooperation that would lead to a closer monitoring of their work positions, and the willingness of the workplace supervisors to cooperate with college advisors in the use of cloud technology was quite limited. Suggestions for future development of the internet+employment platform were proposed. Combining the functions of this platform with those of other cloud platforms might support better employer-college cooperative instruction.
Keywords: student and employers expectation; cooperative instruction; work placement; workplace supervisor; cloud platform technology.
Multi-Interaction English Teaching Platform Based On Internet Of Things
by Xianglang Hou, Zongning Zhang
Abstract: There are some problems in college English teaching, such as poor level, which increase the interactive function of the classroom. An interactive foreign language teaching software is proposed. The platform consists of platform management layer, multiple interactive English teaching module, test paper assignment module and database module. The task of management analysing administrators, and setting instruction program, the multiple interactive English teaching module constructs the multiple interactive English teaching model, the paper exercise allocation module constructs the test paper quantitative model, and the database module specifies the information storage rules. The experimental results show that: the u-value of oral English and listening of the experimental group is less than 0.05, and the P-value of reading score is 0.059.
Keywords: internet of things technology; multi-interaction; teaching platform; platform management module; multi-interaction English teaching module; test paper quantitative model.
Analysis And Research On The Integrated English Teaching Effectiveness Of Internet Of Things Based On Stochastic Forest Algorithm
by Xiaoying Hu
Abstract: In order to overcome the problem of low accuracy in the analysis of teaching effect, this paper proposes a new method for English teaching effect analysis. The decision tree model is constructed through data training, and the stochastic forest algorithm framework is built on this basis. Based on the binary data classification project, relying on data parallel units provided by the internet of things, and relying on integrated data, the sample division of current education data is completed and an open source platform to complete the internet of things docking is designed. The random algorithm is combined with the data indicators of the internet of things to obtain data clusters. According to the classification points of stochastic forest algorithm, datasets are merged to complete sub-aggregation, and the effect evaluation is achieved. The experimental results show that the aggregation rate of the evaluation data of the stochastic forest algorithm is 50% less than or equal to 80%, which is effective.
Keywords: stochastic forest; internet of things; teaching effect; framework of the algorithm.
Research On The Teaching Mode Of University Virtual Laboratory Based On Component Technology
by Shuling He, Dejiang Kong, Jingjun Yang, Lingfa Ma, Yuwei Chang
Abstract: In order to overcome the problems of low flexibility, low efficiency and non-reusability of laboratory teaching mode, a research method of university virtual laboratory teaching mode based on component technology is proposed. This method is composed of platform architecture module, platform operation module, routine project detection module and platform component module. Through the platform operation module scheduling module components to complete the experimental process; the components needed in the experimental process are detected, so that students can get more accurate experimental process and experimental results. By extracting the internal information of bean component, controlling and managing the dynamic results of the component after execution; using the component technology in swing graphics toolkit to realise the experiment process and result visualisation. The experimental results show that it can improve the utilisation rate of students' spare time, and the experimental practice ability can be improved by more than 15 points.
Keywords: Component Technology; Virtual Laboratory; Teaching Mode; Software Development; Visualization.
Research on Knowledge Tree Growth Model for Intelligent English Teaching System based on Hypertext Structure
by Shixin Sun, Haiyan Li
Abstract: At present, the knowledge management model of intelligent English teaching system has some problems, such as weak relevance of knowledge points and poor judgment accuracy of precursor knowledge points. This paper proposes a new knowledge tree growth model for intelligent English teaching system based on hypertext structure. Using hypertext structure resources for English teaching content model to build, packaging, the content of the metadata and completed the organisation of English teaching resources, through the tree of knowledge map, knowledge circulation knowledge teaching, the precursor of judgment, determine the level of knowledge mastery, and knowledge extraction process, realise the building of knowledge tree growth model. The experimental results show that the proposed knowledge tree growth model greatly improves the relevance of knowledge points and the accuracy of judgment of precursor knowledge points, improves the knowledge base of intelligent English, and improves the efficiency and quality of English teaching.
Keywords: hypertext structure; intelligence; English; teaching; knowledge tree; model.
Application of fuzzy ahp in the evaluation of students cognitive ability
by Zhaohui Wei, Ziyan Luo, Peng Sang, Juan Du
Abstract: Cognitive theory holds that each individuals cognitive ability is different. If teachers can adopt appropriate evaluation method, they will be able to accurately know each students cognitive ability and characteristics, which is conducive to personalised teaching implementation. Therefore, based on the revised Bloom cognitive theory, this paper establishes the evaluation index system of students cognitive ability by adopting the analytic hierarchy process (AHP) method, carries out fuzzy evaluation of students test scores with the fuzzy theory, works out the weight of each indicator of cognitive ability by expert scoring method, and finally obtains the comprehensive evaluation of students cognitive ability. It is proved that this method can be more objective and comprehensive in evaluation of the students cognitive ability, and it can reflect their achievement degree of each goal, show their strengths and weaknesses, offering some valuable information for students later study.
Keywords: Blooms cognitive theory; fuzzy logic; analytic hierarchy process; AHP.
The Method Of Interest Text Recommendation In English Education Based On Data Mining
by Linlin Fan
Abstract: In order to solve the problem of low accuracy and long time consuming of traditional English educational interest recommendation methods, a text recommendation method based on data mining was proposed. Build English education text classification system, according to the classification results determine user interest areas, based on the setting behaviour data information domain, recommended target clearly, get user browse English data matrix, standardising the user data, get the user interest degree apriori algorithm combining with data association rules with English education text, finally completed in English education text using association rule mining algorithm is recommended. The experimental results show that the proposed method has a high-precision of recommendation, and the precision and recall rate are significantly better than the traditional method, which provides effective theoretical support for the research in related fields.
Keywords: data mining; English education; text recommendation; interest text; association rules.
Research on Effectiveness Model of Online Learning for College Students in Big Data Era
by Xiaojun Zhang, Xiaoji Yang
Abstract: In order to enhance the effectiveness of online learning of college students in the era of big data, this paper puts forward the research on the effectiveness model of online learning of college students. This paper establishes a fusion clustering model for the evaluation of online learning effect, and uses fuzzy fusion grouping method to analyse the panel data of online learning effect evaluation of college students combined with big data mining method, analyses the characteristics of online learning behaviour of college students and mining association rules. Linear programming model is used to optimise the scheduling of online learning resources for college students. The experimental results show that the design method has high accuracy and reliability in predicting the online learning effect of college students in the era of big data, and improves the convergence and optimisation ability of learning process.
Keywords: learning analysis; big data era; online learning; effectiveness assessment.
Formative assessment method of English language application ability based on consistency assessment
by Guanguan Zeng
Abstract: Due to the fact that learners mastery of English language is not taken into account in the current methods, resulting in higher error and lower credibility of the assessment results, a formative assessment method of English language application ability based on consistency assessment is proposed. According to the principles of formative assessment, the implementation conditions of formative assessment include clear assessment objectives, diversified assessment means, determination of assessment criteria and timely feedback of information. Specific assessment tasks are defined and theoretical model of autonomous learning is constructed to realise the assessment of English language application ability. Taking the students of two classes of automobile maintenance major in college was the test objects; the final assessment scheme is set. Experimental results show that the proposed method can effectively reduce the assessment error and improve the credibility of the assessment results.
Keywords: consistency assessment; English language; application ability; formative; assessment.
Research on the integration and optimization of MOOC teaching resources based on deep reinforcement learning
by Kun Jiao, Xin Han, Li Xu, Terry Gao
Abstract: There are some problems in the merging of English MOOC learning information, such as high packet loss rate and high repetition rate. This paper designs a new method of resource data merging with the help of deep reinforcement learning. Analyse the operation mode of English MOOC platform, and collect teaching resources for the initial application of MOOC under this platform. The pre-processing of the initial collection of resources is completed through translation, Chinese word segmentation, semantic annotation of word segmentation results and other steps. The features of English MOOC teaching resources are extracted, and the deep enhancement learning algorithm is adopted to optimise. Through comparative experiments, it is found that the packet loss rate of the combined learning information is only 0.28% and the integrated resource repetition rate is only 0.89%.
Keywords: deep reinforcement learning; English teaching; MOOC teaching; integration of teaching resources; resource characteristics; feature weight value.
Analysis Of Mixed Learning Mode Of Distance Education Based On Mooc
by Zhikai Li
Abstract: In order to improve the evaluation ability of mixed learning in distance education, a mixed learning mode of distance education based on massive open online course (MOOC) is proposed. By building the distance education based on MOOC mixed study effect evaluation of heterogeneous storage structure of data model, remote education characteristics of distribution of blended learning model, remote education multi-parameter fusion model of blended learning and remote education blended learning process and effect evaluation of multi-parameter fusion model, multidimensional characteristics evaluation method is applied to the remote education blended learning model optimisation. The simulation results show that this method has better process control ability and higher reliability in learning effect evaluation, which effectively improves the mixed learning effect of MOOC-based distance education.
Keywords: massive open online course; MOOC; distance education; mixed learning mode; parameter fusion; big data mining.
New Technologies in Personalisation of STEM and STEAM Education - International Context
by Todorka Glushkova, Krzysztof Gurba, Theo Hug, Nataliia Morze, Tatiana Noskova, Eugenia Smyrnova-Trybulska
Abstract: This article focuses on new technologies in personalisation of STEM and STEAM education in contemporary education, as viewed by experts from different countries: Austria, Bulgaria, Poland, Russia and Ukraine. The article aims to review research literature, and provide opinions, views and reflections presented by scientists and experts from several European universities. The research review includes the theoretical background of the discussed topic, a review of national and international research and literature, identification and definition of key concepts, examples of practical achievements, and a description of contemporary trends of STEM and STEAM Education and adaptive learning as well as microlearning- effective methods of e-learning. At the end a number of conclusions are drawn.
Keywords: STEM; STEAM; personalised learning; individual learning; experts; adaptive learning; microlearning; international context.
Research on online evaluation method of MOOC teaching quality based on decision tree-based big data classification
by Jiefeng Wang, Humin Yang
Abstract: In order to improve the online evaluation ability to massive open online course (MOOC) teaching quality, an online evaluation method of MOOC teaching quality based on decision tree-based big data classification is proposed. First, a big data statistical analysis model is built to identify fuzzy degree parameters. Then, the quality index system is obtained to realise big data fusion and cluster analysis. It is concluded that this method has high accuracy in online evaluation. In this paper, the method shows that the accuracy as high as 0.996 when the number of iterations reaches 500. Its innovation lies in the analysis of the global optimal solution of online evaluation of distance MOOC teaching quality by using the big data decision tree model, which improves the information management of MOOC online evaluation.
Keywords: big data statistical analysis; decision tree-based classification; MOOC teaching quality; online evaluation method; information fusion and clustering.
Advanced And Effective Teaching Design Based On BOPPPS Model
by Changdong Wu, Xiangzhen He, Hua Jiang
Abstract: To meet the requirement of teaching reform, effective teaching design is an important way to improve teachers teaching ability and students learning ability. How to design a high quality teaching content is a critical problem which should be considered. BOPPPS model is an advanced and effective teaching design method, which includes six parts such as bridge-in, outcome, pre-assessment, participatory learning, post-assessment and summary. In this process, it takes teacher as the instructor, problem-oriented, student-centred and participatory learning as the core. In order to apply the advanced teaching concept in teaching design, this paper takes series feedback voltage stabilising circuit as an example to build a teaching design based on BOPPPS model. In this process, many improved circuits based on the real teaching situation are analysed and discussed. It has been proved that the proposed method is an effective teaching model for promoting the teachers teaching quality and students learning ability.
Keywords: teaching design; teaching reform; BOPPPS model; circuit design; improved circuit.
The Role of Critical Thinking Development Technology in the Development of Students Intellectual Ability
by Bakhytkul Kaskatayeva, Maral Andassova
Abstract: This article discusses the role of critical thinking development technology in the formation of students' intellectual abilities. Purposeful formation of intellectual abilities of students allows to establish cause-and-effect relations between phenomena and laws of development of events that is necessary for the student for mastering scientific knowledge and foreign languages. The aim of the study is to reveal the essence of critical thinking of students in the learning process and to develop and test the technology of critical thinking as a tool for intellectual development of students. The study applied methods such as analysis of psychological, pedagogical, scientific, methodological and educational literature on the topic of research; monitoring the progress of the educational process; questioning; rating control; testing; conversations with teachers and students. The article proposes a solution to the problem of formation of intellectual qualities of students on the basis of technology of critical thinking.
Keywords: critical thinking; intellectual qualities; technology; higher education institution.
Research on teaching quality evaluation model of distance education in colleges based on analytic hierarchy process
by Xiao-long Wen
Abstract: There are some problems in the existing teaching quality evaluation methods, such as low evaluation accuracy, puts forward a model of distance education teaching quality evaluation in colleges and universities by means of analytic hierarchy process. From this perspective in students, peers and supervisors, obtain the evaluation index of teaching quality and calculate its weight value, analysing the hierarchical process is introduced. In this model, the evaluation indexes in the hierarchy are sorted and the consistency is verified, and the teaching quality evaluation model of distance education in colleges based on AHP. Through the research of the proposed method, the conclusion is drawn that the error of distance education effect of imparting knowledge evaluation by using the proposed model is relatively low, and it is feasible to some extent.
Keywords: distance education; effect of education; evaluation model; consistency verification.
Student as researchers: towards redefining undergraduate projects
by Suki Honey, Asiya Khan, Richard Pemberton, Priska Schoenborn, Andrew Edward-Jones
Abstract: The aim of this paper is to collect evidence of success and identify areas of good practice that can enable the process of re-defining undergraduate projects and lead to peer-review publications through student-staff collaborations. A pilot study was conducted with ten participants from STEM and non-STEM backgrounds. Based on the response and feedback, the questionnaire was revised and sent to a number of internal and external peers mainly in STEM. Twenty eight responses were received. Finally, four focus groups were hosted two with five internal members of staff and two with nine undergraduate students studying civil and mechanical engineering at the University of Plymouth. The findings show that the majority of undergraduate student projects resulting in publications were jointly chosen by tutors and student and positively impacted on student learning. The emphasis was on good quality data collection by the students. The biggest barrier identified was the time commitment required by staff to convert student reports to publishable papers.
Keywords: student projects; engineering; undergraduate research; peer-reviewed publications.
Research On The Method Of Educational Text Classification Based On Deep Learning
by Yuqin Wang
Abstract: To improve the efficiency of traditional text classification methods of education and the recall rate of research objectives, we proposed an educational text classification method based on the depth of learning. The English web pages covering the economics, politics, sports, entertainment, and life, etc., which involves carriers containing explanatory texts and discussion papers, etc., will be used as the source of English education texts for corresponding collection and processing. Upload the collected English educational texts, introduce deep learning algorithms, perform preprocessing and feature learning, and input the learning features into the deep learning Softmax classifier based on the learning results. The output of the classifier is the classification result of the educational text To complete the classification of educational texts. Experimental results show that the experimental results show that the proposed method of classification accuracy, higher recall rate, and time-consuming short, the average distribution time-consuming to 3.992 s. It shows that the proposed method can effectively improve the classification efficiency of educational texts.
Keywords: deep learning; educational text; text classification; learning characteristics; English education.
Detection Method Of Students Classroom Learning Behavior Based On Parallel Classification Algorithm
by Degang Lai, Ke Wang
Abstract: In order to overcome the problem that students learning behaviour process is easy to form misclassification in the process of serial classification, this paper proposes a method to detect students learning behaviour in class based on parallel classification algorithm. The parallel classification model is constructed. By measuring Kinect coverage and adjusting Kinect top view angle, the coordinates of each students position are transformed. The auxiliary feature vector is applied in behaviour recognition to realise the parallel combination and processing of multiple data sources, accurately extract the feature vector to form different relevance, and realise the detection of students classroom learning behaviour. The experimental results show that students can grasp the degree of interest in the course and the degree of seriousness in the whole teaching process. The detection rate is more than 90%, which is practical.
Keywords: classroom learning behaviour; parallel classification algorithm; Kinect; skeleton feature vector.
The problem-based learning mode for Teaching English to college students
by Lijuan Song
Abstract: This paper firstly introduced the traditional English teaching mode and then briefly introduced the problem-based learning (PBL) English teaching mode. Then, in order to test the effect of the PBL teaching mode, 200 college students were selected for relevant teaching tests. The final results demonstrated that the performance distribution of students who were taught by the traditional mode almost had no change after English teaching, and the performance distribution of students who were taught by the PBL mode in the experimental class had improvement. The questionnaire survey of students in the experimental class showed that most students agreed with the PBL mode.
Keywords: English; problem-based learning; PBL; teaching mode; listening; speaking; reading.
Evaluation model of College Students' online learning level difference based on support vector machine
by Kunzhe Liu, Xiqiang Ge, Jiefeng Wang
Abstract: There are some problems in the evaluation of online learning level differences among college students, such as low accuracy and long evaluation time, to propose a new research method. By extracting online learning behaviour characteristics, to determine behaviour evaluation indexes and evaluation standards, and by the depth of the residual neural network method to remove interference index, using the Lagrange multiplier method, the evaluation problem is transformed into the dual problem, and the nonlinear transformation, thus seeking the optimal classification plane, to obtain the optimal classification function, difference evaluation data accessed by the big data technology, through the normalised processing the data, obtain the final evaluation results, complete online learning evaluation level differences. Through comparison, the accuracy of this method is 97%, and the time cost of assessment is always less than 9.5 ms.
Keywords: support vector machine; online learning; difference evaluation; behaviour characteristics.
An online teaching process monitoring method of MOOC platform based on video recognition
by Humin Yang, Jiefeng Wang
Abstract: In order to overcome the problem of low monitoring accuracy of traditional methods, a new online teaching process monitoring method based on video recognition for MOOC platform is proposed. The weight coefficient of online teaching process monitoring information of MOOC platform is calculated, and the monitoring information is reconstructed. On this basis, video recognition method is used to mine the online teaching process monitoring information of MOOC platform. Through the construction of monitoring model, the online teaching process monitoring of MOOC platform is realised. The experimental results show that the mean square error analysis results of the monitoring method based on video recognition verify that the effect of different gender students is different. The method has high correction coefficient, high monitoring accuracy and good application effect, which can effectively improve the effect of students online learning.
Keywords: video recognition; MOOC platform; online teaching; process monitoring.
The Evaluation Method For English Mooc Quality Based On Grounded Theory
by Sujuan Ren, Bin Yu
Abstract: In order to overcome the poor rationality of the weight distribution of the existing English MOOC quality evaluation indicators, a grounded theory-based method of English MOOC quality evaluation is proposed. This method constructs the evaluation framework of English MOOC quality and determines the overall goal of teaching. Based on the selected MOOC quality evaluation indexes, the weight value of each evaluation index is determined by AHP, and the comprehensive evaluation indexes of each level are evaluated by fuzzy algorithm. The evaluation results of English MOOC quality are obtained by integration and calculation. The evaluation of English MOOC quality based on grounded theory is realised price. The experimental results show that the maximum value of the weight distribution of the proposed MOOC quality evaluation method can reach 29.45, and the quality evaluation result U >= 90, which shows that the quality effect is excellent and has better evaluation effect.
Keywords: grounded theory; English; MOOC; quality; evaluation.
Design of reservation model of teaching equipment in NC laboratory based on BS mode
by Haibo Liu, Xinbo Zhang, Qingzhong Gong
Abstract: In order to solve the job scheduling problem of CNC laboratory equipment concurrent reservation, the design method of CNC laboratory teaching equipment reservation model based on BS mode is proposed. By using BS mode, the equipment management structure of numerical control laboratory is designed hierarchically. Build the reservation time series model to realise the load transmission and information estimation in the process of reservation. According to the statistical results, the reservation fitness function is designed, and the reservation scheduling and reservation algorithm are designed. Based on this, the database security storage function and SMS processing function of the model are designed to realise the construction of teaching equipment reservation model in CNC laboratory. Experimental results show that: compared with the traditional equipment design model, the model designed in this paper has higher reservation success rate and better application performance.
Keywords: BS mode; numerical control laboratory; teaching equipment reservation; statistical characteristic quantity; fitness function.
A balanced allocation method of English MOOC teaching resources based on QoS constraints
by Xiaodong Yuan
Abstract: In order to overcome the problems of long allocation time and high bandwidth consumption in traditional resource allocation methods, this paper proposes a new balanced allocation method of English MOOC teaching resources based on QoS constraints. With the support of big data and cloud computing technology, MOOC English teaching resources are mined and collected, and the resource balanced allocation model is constructed by using MMPs algorithm. The resource balanced allocation of virtual machine is realised through the selection of QoS constraint parameters, physical resource mapping and QESA resource allocation system. On the basis of experiments, the proposed method has the advantages of balanced resource allocation and execution time.
Keywords: QoS constraints; MOOC resources; MMPS algorithm; QESA system.
Developing a computer-assisted writing system to solve phraseological problems for Chinese graduate students academic writing
by Tong Zhao, Xiuhai Zhang, Zhongliang Zhan
Abstract: This study develops a computer-assisted writing system, consisting of the searching module and the text editing module. The searching module is characterised by part-of-speech (POS) collocation search which retrieves technical and general collocations from a customised corpus of research articles in a specialised field. The text editing module is characterised by next-word prediction which works on lexical bundle lists from COCA. Through the development of these modules and functions, the POS and position of collocations are specified, the word likely to follow a given sequence is predicted, English for technical use and general use are concerned, and the display of the retrieved information is optimised. At present, this system works well in the research field of tubulin. It could be applied to academic writing of other research areas if the customised corpus of that area is built and uploaded.
Keywords: phraseological learning; computer-assisted writing system; academic writing; Chinese graduate students; corpus.
Mobile learning determinants that influence Indian university students learning satisfaction during COVID-19
by Md Qamar, Mohd Ajmal, Abdullah Malik, Mohd. Ahmad, Juhi Yasmeen
Abstract: Due to the COVID-19 pandemic whole world went under strict lockdown, including educational institutes. This led to the quick reshaping of educational systems to provide uninterrupted education to the students. Preferably, both teachers and students switched from physical classrooms to online classrooms. This overnight change brought numerous challenges for a country like India. But the authors of this study see it as an opportunity and aim to explore mobile learning (m-learning) determinants that influence Indian university students learning needs during the COVID-19. For this, the data were gathered using a web-based questionnaire from 557 students of seven different universities (both public and private) in India. Next, the data were quantitatively analysed using reliability analysis, confirmatory factor analysis, and multiple regression analysis. The results show that out of three first-order m-learning variables, only two (system and service quality items) have a positive impact on students learning satisfaction in the Indian context. In the end, the implications of the study in the adoption of m-learning at different Indian universities have been discussed.
Keywords: COVID-19 and online learning; m-learning determinants; students learning satisfaction; India.
Automatic quantitative assessment of English writing proficiency based on multi feature fusion
by Fengtian Xu
Abstract: In the existing quantitative evaluation methods of English writing level, the accuracy of feature extraction is low and the error is high. An automatic quantitative evaluation method of English writing level based on multi-feature fusion is put forward. By using vector space model and Jekard similarity coefficient to determine the cosine similarity of English text, the features of English text are extracted by Manhattan distance. Through kernel function, the multi-feature fusion of English writing text is realised. The multivariate linear regression model is used to determine the feature weight of English text and to quantitatively process the feature data. The automatic quantitative evaluation model of English writing level is constructed to complete the automatic quantitative evaluation of English writing level. The experimental results show that the accuracy of the proposed automatic quantitative evaluation method is always higher than 90 and the minimum error of text feature extraction is about 2%.
Keywords: multi-feature fusion; English writing; automatic assessment; corpus.
Authentic learning environment for in-service trainings of cyber security: a qualitative study
by Mika Karjalainen, Anna-Liisa Ojala
Abstract: Todays rapidly digitalising world has led to business processes becoming digitalised, which necessitates paying attention to the cybersecurity issues inherent in those digital processes. The multi-disciplinary nature of working life and the complexity of cybersecurity issues place demands on learning environments. The present study examined the requirements for optimal in-service training to ensure individual and organisational learning of the competencies that are crucial for dealing with cybersecurity incidents. Building on theories of authentic learning and qualitative research methods, the study identified three fundamental components and four elements of optimal in-service cybersecurity training. The research found that practicing organisational actions increased readiness and competence to act in the face of a real cybersecurity incident. A comprehensive cyber arena supports the implementation of optimal training and thus the efficiency of in-service training.
Keywords: cyber security; cyber arena; cyber range; authentic learning environment; training; exercises; peadagogy; in-service training.
Teaching Practice-oriented Computer Vision Courses in COVID-19 Pandemic
by Jing Tian
Abstract: This paper aims to present an online teaching pedagogic experience for the practice-oriented computer vision course during the COVID-19 pandemic. COVID-19 has been disruptive to the education system worldwide, particularly to the computer vision course that usually requires face-to-face lectures and project collaboration during the study. This paper addresses three fundamental questions in teaching computer vision courses: 1) how to design the course topic and adapt to the online teaching format?; 2) how to conduct hybrid project collaboration in a hybrid mode?; 3) how to conduct the course assessment efficiently online? More specifically, this paper presents the pedagogic experience, including learning objectives, course curriculum structure, teaching methodologies, as well as final holistic assessments. The presented approach is an effective way of teaching practical computer vision courses, as verified by feedback from students. These experiences can be insightful to other lecturers who need to design, develop and deliver similar courses in the post pandemic era.
Keywords: engineering education; computer vision teaching; active learning.
The Recommendation Method For Distance Learning Resources Of College English Under The Mooc Education Mode
by Hongxin Yin
Abstract: In view of the low efficiency and low accuracy of the traditional recommendation method for college English distance learning resources, a new recommendation method for college English distance learning resources under the MOOC education model is proposed. The metadata set of distance learning resources was extracted, and the metadata set was used as the data support of the learning recommendation model. The review matrix method was used to establish the interest evaluation matrix and the user interest feedback model, and the interest feedback model was used to optimise the recommendation algorithm, so as to realise the recommendation of distance learning resources in the MOOC education model. The experimental results verify that the proposed method is more efficient than the traditional method and has higher recommendation accuracy, which provides a scientific basis for the recommendation method of distance learning resources.
Keywords: college English; MOOC education mode; distance learning; resource recommendation.
Allocation of multi-dimensional distance learning resource based on MOOC data
by Yan Liang
Abstract: In order to overcome the problems of allocation balance and low allocation efficiency in traditional distance teaching resource allocation methods, the paper proposes a multi-dimensional distance learning resource allocation method based on MOOC data. This method establishes a network model of MOOC resources, analyses the structure of the MOOC remote teaching platform, and collects MOOC data and learning resource information in layers on the basis of the model. Based on the data collection results, clustering of data resources can be achieved from multiple dimensions. Finally, by calculating the allocation of learning resources, a balanced allocation of multi-dimensional distance learning resources is achieved. Experimental results show that, compared with the traditional learning resource allocation method, the proposed method has a maximum allocation balance of 93% and a resource allocation efficiency of 96.2%.
Keywords: MOOC data; Multi-dimensional; Distance learning; Resource allocation.
The Evaluation Method For Distance Learning Engagement Of College English Under The Mixed Teaching Mode
by Yansong Zhang, Yanbin Yang
Abstract: In order to overcome the problems of low input and poor effectiveness of evaluation, this paper puts forward the evaluation method of distance learning input. This method constructs a learning behaviour input model under the mixed teaching mode of College English. Determine the evaluation standard of learning engagement as the comparison standard of evaluation indicators. Collect the learning information of students in the process of distance English learning, and determine the specific indicators of learning input evaluation. Combined with the weight of the index, the specific value of the comprehensive evaluation index of learning input is calculated, and the final evaluation result of learning input is obtained by comparing with the evaluation standard. The experimental results show that the evaluation results are all over 85%, the evaluation effectiveness is 90%, and the average English score is improved by 7.8 points.
Keywords: Mixed teaching model; College English; Distance learning; Engagement evaluation.
Research On The Scheduling Method Of Distance Learning Process Education Resource Based On Augmented Reality
by Yan Li
Abstract: Aiming at the problem of large scheduling error in traditional education resource scheduling methods, a distance education process education resource scheduling method based on augmented reality is proposed. This paper constructs the big data mining model of educational resources in the process of distance education, and selects the rule vector set of educational resources scheduling in the process of distance education by using the method of decision attribute recognition. Using augmented reality technology to judge the independence of educational resources in the process of distance education, and based on clustering processing method to classify the characteristics of resources. According to the results of classification and recognition, the educational resources in the process of distance education are scheduled. Simulation results show that the method has good adaptability and strong feature recognition ability in the process of distance education resource scheduling, and improves the adaptive learning ability of scheduling.
Keywords: Augmented reality; distance learning; process education; resource scheduling; feature classification.
The Improvement Of Interactive Learning Efficiency Based On Virtual Simulation Technology
by Lu Bai
Abstract: In order to overcome the problems of learning efficiency and low learning interest in the existing English teaching methods, this paper proposes a new method for constructing an English interactive learning efficiency improvement platform based on virtual simulation technology. Design the XLua execution framework as the core component of the virtual simulation technology framework. Select Unity3D as the interactive platform for the structural components of the virtual reality development platform, and use the 3DsMAX analysis tool to construct the interactive learning courseware module as the courseware information collection. The coordinate system and graphics system are background rendering is performed on the basis to build a complete interactive English learning efficiency improvement platform and complete the overall construction of the interactive learning efficiency improvement platform. The experimental results show that compared with the traditional learning platform, the application of the learning platform can effectively improve the learning interest of students, thereby improving the learning efficiency of students.
Keywords: Virtual simulation technology; English teaching; Interactive learning; Efficiency improvement.
Evaluation Model Of Distance Learning Effect Based On Mooc Theory
by Na Liu
Abstract: In order to overcome the problem of fuzzy data in distance learning effect evaluation, a distance learning effect evaluation model based on MOOC theory is proposed. The vector of original time series and multi bit space analysis is constructed. The minimum embedding dimension of phase space reconstruction is extracted by using the false nearest neighbour algorithm, and the chaotic correlation dimension characteristics of data related to learners' learning are obtained. The input-output MOOC model is used to evaluate the effectiveness of decision-making units, and all decision-making units are arranged in a comprehensive way to realise the effect evaluation of distance learning. The experimental results show that the learning effect score of the designed model is basically consistent with the learning effect score given by the experts in the sample, the approximate error is less than 0.5, the training error is about 0.02, and the accuracy of the model reaches 90%.
Keywords: MOOC theory; Distance learning; Learner; Learning effect; Evaluation model.
Research on Students' Classroom Performance Evaluation Algorithm Based on the Machine Learning
by Enwei Cao
Abstract: In order to overcome the poor accuracy of traditional classroom performance evaluation algorithm, a machine learning-based classroom performance evaluation algorithm was designed. This paper makes an empirical analysis of the statistical data and constructs a statistical information analysis model for students' classroom performance evaluation. According to the mining results of students' classroom performance evaluation information, the adaptive mining and feature clustering of students' classroom performance evaluation data are carried out. This paper USES quantitative game method to evaluate students' classroom performance, constructs the explanatory variable and control variable model of students' classroom performance evaluation, and then USES machine learning method to optimise the evaluation of students' classroom performance. The simulation results show that the evaluation accuracy of the proposed method is always above 0.77, which has high reliability and adaptability, and improves the quantitative evaluation ability of students' classroom performance.
Keywords: Machine learning; students' classroom performance; evaluation; test statistics; intelligent teaching.
Recommended methods for teaching resources in public English MOOC based on data chunking
by Zhenhua Wei
Abstract: In order to overcome the problems of time-consuming and high recommendation error in traditional public English MOOC teaching resource recommendation methods, this paper proposes a new public English MOOC teaching resource recommendation method based on data partition. The data of public English MOOC teaching resources are collected, and hierarchical clustering algorithm is used to preprocess public English MOOC teaching resources to support the recommendation demand of mobile MOOC teaching resources. According to the preprocessing results, the data block algorithm is used to divide the resource data iteratively. Finally, we calculate the similarity of users resource use and preference, and construct the public English MOOC teaching resource recommendation model based on the index weight results. Comparative validation results show, in the conventional method, the proposed method recommended consuming less and less precision compared to the recommended.
Keywords: data partition; public English; MOOC teaching resources; block partition.
An Evaluation Method of English Online Learning Behavior Based on Feature Mining
by Chao Han
Abstract: In order to overcome the problems of low precision of feature retrieval and poor clustering effect of traditional online learning behaviour evaluation methods, this paper designed an English online learning behaviour evaluation method based on feature mining. Firstly, the unbiased estimation theory is used to quantitatively sample English online learning behaviour. After data preprocessing, the clustering centre is divided, and the data is allocated to different clusters through clustering processing, and the feature mining results are obtained through iteration. Then the evaluation index system is constructed, and the final evaluation results are obtained on the basis of the grey interval clustering treatment of the evaluation index. According to the test results, the retrieval accuracy of behaviour features of method of this paper is closer to one, and its clustering effect on different online learning behaviour features is good, which proves that it has achieved the design expectation.
Keywords: online learning behaviour; data clustering; characteristics of the mining; evaluation indicators.
Personalized recommendation method of college English online teaching resources based on hidden Markov model
by Qing Tian
Abstract: Aiming at the problem of the high comprehensive evaluation index of recall and precision in the traditional personalised recommendation methods of college English online teaching resources, a personalised recommendation method of college English online teaching resources based on hidden Markov model is proposed. Extract label features, student learning behaviour features, and time weight features, and pre-process the extracted college English online teaching resource data, build a recommendation model based on the pre-processing results, and use a hidden Markov model to process the hidden data to obtain the maximum likelihood estimates the parameter, and inputs the parameter into the recommendation model to obtain the optimal parameter, that is, the optimal recommendation result. The simulation results show that the comprehensive evaluation index values of precision and recall of the recommended results of the proposed method are within 0.9 and 0.5, which has a good recommendation effect and meets the needs of the development of network teaching.
Keywords: hidden Markov model; university English; online teaching resources; personalised recommendation method.