International Journal of Continuing Engineering Education and Life-Long Learning (52 papers in press)
Continual Improvement Assessments Based on the ABET Accreditation Process: Overcome Challenges Implementing Management System
by Abdel-Rahman Al-Qawasmi, Abdullah Almuhaisen, Iskander Tlili
Abstract: Reducing the unemployment rate, achieving economic growth and bridging the gaps between industries needs and engineering graduate skills, are the three long-term drivers of engineering education performance which are becoming gradually competitive. To overcome the engineering education weakness issue, different approaches are being considered including programs accreditation to have the greatest potential within engineering education. Recently, decision makers and researchers reconsider assessment and improving engineering accreditation process using different management tools. In this study a new management materials based on quality standard of National Commission for Academic Accreditation and Assessment (NCAAA) and Accreditation Board for Engineering and Technology (ABET) was developed and tested. Results have shown a noteworthy improvement on the performance of faculty assessment courses and on the overall quality process. The present work demonstrates that the proposed quality management system (QMS) contributes to a substantial decrease of waste of time made by faculty member to organise and assess their course along the entire semester and an increasing percentage around 60 per cent of faculty member involved in continuous quality improvement through proposed QMS.
Keywords: Quality Management System; Assessment and improvement; SLO (Student learning outcomes),.
Geometrical Tools to Teaching Azeotropy Using Simplified Thermodynamic Models
by Gustavo Platt, F.S. Lobato, F. D. Moura Neto, G.B. Libotte, D.A. Goulart
Abstract: In this work we propose a geometric view of the azeotropy problem, using some simplified models. We demonstrate that the occurrence of azeotropes in binary mixtures can be viewed - geometrically - as the intersection of curves in the plane (for some models, these curves are parabolas). Furthermore, the idea of functions from the plane to the plane is used to understand the azeotropic phenomenon. These ideas are illustrated with two simple cases, with one and two azeotropes, allowing the analysis of a nonusual thermodynamic behavior -- such as double azeotropy -- with simple mathematical tools, by undergraduate students in Chemical Engineering courses.
Keywords: Azeotropes; Functions from the plane to the plane; Double Azeotropy.
Parametric Identification Components Maritime Systems of Automatic Control Systems with Microcontrollers
by Sergei Chernyi
Abstract: An attempt to implement an algorithm based on a microcontroller control system will either tighten the requirements for the speed of the central processor of this system, or result in a catastrophic decrease in the speed of the system and its inability to operate in real time when trying to obtain the minimum acceptable accuracy of the resource-intensive calculations The purpose of the research was to conduct a degree of parametric identification of the stability of microprocessor or computer control systems As a result of research, it has been established that control microcontrollers created computational delays into the phase-frequency characteristics of closed systems, and the converter on its own was a non-linear link with a constant transmission coefficient in a certain range, it became necessary to evaluate their effect on the stability of closed systems As a result of the analysis, it was found that to ensure sufficient stability of the internal contour of the closed system, it is necessary to increase the allowable margins both in phase and in amplitude.
Keywords: parametric identification; maritime; stability of automatic control systems; learning; microcontrollers.
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.
Outcome Based Education: A Paramount Model for Higher Educational Institutions in India
by Mallikharjuna Rao Nuka, Sasidhar Choragudi, Chinna Babu Jyothi
Abstract: In the year 2014, India was became a full member of the Washington Accord facilitates for accreditation process in engineering education system with desired policies and procedures. It signifies that our accreditation process in the engineering institutions is in filled conformity with the requirements of the Washington Accord with the Outcome Based Education. This study supports to determine the challenges in present engineering education and discusses the outcome based education implementation in engineering institutions. At the end, this study reviewed the assessment approaches.
Keywords: Engineering Education; National Board of Accreditation; Washington Accord; Outcome Based Education; Graduate Attributes.
Student-Parent Teams: A 10-Year Retrospective Study of an Undergraduate Research Experience
by James Giancaspro, Nam Ju Kim
Abstract: The objective of this study was to investigate the long-term (10-year) impact of a small, yet unique, outreach effort where three teams of undergraduate students were paired with their parental counterparts to conduct civil engineering research supported by the United States' National Science Foundation. Those students are compared to a control group of undergraduates who participated in a traditional research experience and were exposed to the same conditions and research project. A survey instrument was used to collect data related to the participants' actual career path trajectory, self-efficacy, scholarly productivity, and parental influence in their decisions for postgraduate education and career planning. Parental support for students' postgraduate plans either remained unchanged or increased following the research experience. While the participants in the student-parent teams produced more scholarly products than the control group in the decade following the experience, the sample size is too small to draw causal inferences.
Keywords: research experience for undergraduates; REU; engineering education; civil engineering; parent involvement; career trajectory.
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.
Introducing a Capstone Course on Social Networks
by Mohammad Fraiwan
Abstract: Cyberspace is increasingly being dominated by social networks. It is estimated that the number of users of such networks and media will reach 3.1 billion by 2021. Now even news outlets are reporting on people tweets, pictures, and online status. Social networks provide a platform for political, social, business, and leisure activities. Computer engineering students need to be well-equipped to deal with such important platforms, which will empower them to generate new business opportunities, develop useful applications, or simply prepare for the job market. In this paper, an undergraduate capstone course in social networks is described that not only exposes students to that plethora of social networks, but also makes it possible to collect and analyse data from these networks and propose useful applications. Students were required to work in teams on a project idea of their own device. The course methodology, assessment, and technical aspects will be presented.
Keywords: Data Mining; Facebook; LinkedIn; Python; Semantic Web; Social Networks; Twitter.
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.
Analysis of the learners' learning behaviours in MOOC informationisation leadership
by Mei Liu, Shusheng Shen, Changsheng Chen
Abstract: For better adapting the course to different learners' needs, this study analysed the learners' online learning behaviours. Through using data mining technology to mine the learning behaviours from five dimensions: video watching, text reading, discussion and communication, test and assignments taking, we draw the following conclusions: the demographic characteristics of learners show that the learners are mainly composed of principals, middle-level educational managers and key teachers. The learner's general learning behaviour characteristics are mainly expressed by the facts that the learners' interest in practical cases, and few participants can last more than four weeks, and the learners like videos and texts but they do not like to speak in the discussion forum. Learners can be divided into three clusters: certificate-oriented learners, practice oriented learners and browsers. The value of MOOC should not be evaluated on the basis of certification rates but on whether the learner's learning needs are met.
Keywords: online learning behaviour analysis; massive open online course; MOOC; informationisation leadership; clustering; data mining.
Research on the influence of instructor image on the learning effect of conceptual learning videos
by Xiaojin Wang, Su Mu, DongMei Tang, Huiqun Wen, Yanjie Zhou, Jing Dong
Abstract: To efficiently convey information and optimise teaching effect, it is necessary to design and develop high-quality online learning materials. To determine the different learning effect of with and without an instructor, this study selects three types of data: test data, eye movement data and questionnaire and interview data. A few primary results of this study are: 1) instructors have no significant impact on learners' conceptual learning grades of declarative knowledge; 2) there is no significant difference in learners' performance of viewing area, but there is a difference in their performance of teachers area; 3) through comprehensive questionnaire and interview data analysis, there is no significant difference in learners' learning experience of conceptual learning in declarative knowledge video with and without an instructor. This study provides a reference for designing and developing online video lectures. When designing the video lectures of conceptual learning, it can adopt instructor-free way considering saving time and cost.
Keywords: video lectures; declarative knowledge; conceptual learning; an instructor; eye movement; learning effect.
Evaluation of learners' online learning behaviour based on the analytic hierarchy process
by Xuejiao Huang, Xiaojin Wang, Fengjuan Liu
Abstract: The online learning behaviour has become an important factor in predicting the learning achievement. Evaluating online learning behaviour is one of the hot topics in the field of IT education, but does not carry out specific weights and score distribution. Therefore, the online learning behaviour data from the 'Moso Teach' cloud platform was analysed by correlation analysis, cluster analysis and analytic hierarchy process analysis. We found that problem-solving behaviour of learners is the least, which is not common in online learning behaviour, while social interaction behaviour is better than problem-solving behaviour, and resource learning behaviour is the most common in online learning. The score distribution diagram of resource learning behaviour shows an inverse s-shaped curve, while the curves of the score distribution diagram of social interaction behaviour and problem solving behaviour are close to a straight line. There are learning achievement differences in resource learning behaviour and problem-solving behaviour, and core-marginal differences in resource learning behaviour and social interaction behaviour.
Keywords: online learning; learning behaviour; learning analysis.
A study of ISEC students' online learning behaviour in ethnic universities and colleges
by Jinan Jia
Abstract: Studies on e-learning behaviours of undergraduates are of great significance to improve the quality of e-learning. With e-learning behaviours in the course cross-cultural communications offered for students majoring in International Economy and Trade of the International Scholarly Exchange Curriculum (ISEC) program launched by an ethic university in China as the object, this paper collects students' e-learning behaviour data during the learning process and concludes that there is strong utilitarian element and weak interactivity with e-learning. Students lack the awareness of reflective learning. There is significant difference in learning hours among students, with a considerable portion of the hours being allocated to homework. Content of courses on the e-teaching platform is not pertinent. This study provides suggestions to improve e-learning behaviours of undergraduates in terms of course resources, external and internal monitoring of e-leaning, teacher-student interaction and assessment system optimisation. E-learning environments should be improved and more online courses should be provided. External and internal monitoring over e-learning should be enhanced to foster independent learning capabilities. Communications between students and teachers should be encouraged to better the e-learning quality.
Keywords: improvement strategy; learning behaviour analysis; blended teaching.
Research on curriculum construction and application in colleges under blended learning
by Hongtao Yu
Abstract: This study collects and analyses data on the development and application of 281 blended teaching reform courses of a college. The results show that all teachers and students highly recognise blended teaching model and believe the reform of blended teaching has improved students' motivation and ability to learn, and students' cognition is growing as the reform is advanced. However, the development of these courses has some problems, such as insufficient teaching video resources and monotonous teaching methods, and for these problems this study proposes two recommendations on the development and application of school-based college courses in the context of blended learning, namely strengthening the development of video resources for these blended teaching courses and enhancing teachers' capability of blended teaching.
Keywords: colleges; blended learning; course development.
Design for blended synchronous learning: the instructor's perspective
by Qiyun Wang
Abstract: Blended synchronous learning (BSL) has the potential to combine the advantages of classroom instruction and online learning. In this study, BSL was designed and implemented from the pedagogical, social, technical, and managerial aspects. This paper presents how BSL was prepared and designed before a lesson, implemented during the lesson, and improved after the lesson from the instructor's perspective. The results showed that the instructor needed to adjust certain learning activities before a lesson. He was often cognitively overloaded and having difficulties in monitoring the participation and engagement of the online students during the lesson. The design and implementation of BSL was gradually improved through reflections after the lesson. Implications for teachers who intend to apply this approach are discussed.
Keywords: blended synchronous learning; BSL; pedagogical design; social design; technical design; managerial design; video conferencing.
Bayesian network algorithms used in the assessment of learners' learning behaviour
by Suzhen Li
Abstract: In order to solve the problem that teachers cannot monitor learners' learning behaviour or evaluate learners' learning objectively and scientifically because of the relative separation of time and space between teachers and students, covering Bayesian network learning evaluation model based on knowledge relationship is proposed. The information related to students can be divided into two parts: domain-related information and domain-independent information. Firstly, the modelling of domain-related information is mainly discussed. The process of domain-related information modelling is the Bayesian networking process of the courses that students have learned. Secondly, the time and space complexity of the algorithm is reduced by simplifying the network structure and optimising the order of node deletion in the triangulation process. The results show that the model can accurately judge the degree of students' mastery of knowledge, and can provide students with personalised guidance strategy.
Keywords: network learning; learning evaluation; Bayesian network; student model.
Exploration of data mining algorithms of an online learning behaviour log based on cloud computing
by Rongguo Wang
Abstract: In this research, the learning patterns and behavioural data of learners' online learning in a cloud computing environment are analysed, and the learners' learning progress, learning rules, and learning effects through data mining algorithms are studied to promote learners' self-learning consciousness and self-learning ability and achieve the learner-centred application goal. This study is aimed at an online learning course, randomly selected eight learners as research subjects, and analysed their online learning behaviour through data mining algorithms, including establishing learning behaviour models, behavioural data feature analysis and behaviour evaluation, and finally realise personalised recommendation of learning content based on data mining results. It finds that through the data mining algorithm to analyse the learning behaviour of online learners, the learner's learning state and learning effect can be intuitively understood, and the individual's learning behaviour characteristics can be roughly defined, then guiding suggestions can be given to help them complete learning goals and improve learning efficiency. Due to the small sample size of the survey, the results obtained are relatively one-sided. In future research, attention should be paid to the data collection and collation work.
Keywords: cloud computing; online learning; data mining; behaviour analysis.
Design of an online learning early warning system based on learning behaviour analysis
by Xin Li, Tong Zhou
Abstract: The objective of this study is to design an academic warning system to identify students with abnormal learning behaviours, to give early warning of students' learning status, and to help students successfully complete their studies. In this study, the comprehensive academic performance of university students is taken as the research object, and the basic information data, academic performance data, and online data are collected. After analysing the students' learning behaviour, an online learning warning system is constructed based on grid based on clustering by fast search and find of density peaks (GBCFSFDP) algorithm, and the system is divided into dynamic warning and static warning. It found that the clustering of students' learning behaviour completed by GBCFSFDP algorithm can be divided into six specific categories, and the attributes that influence the learning performance can be differentiated by weighted naive Bayes classification algorithm based on fruit fly optimisation algorithm (WNBC-FOA). The results show that the time spent online have the greatest impact on students' performance. Therefore, this online learning early warning system can make it easier for students and teachers to understand the reasons for learning abnormalities and the correlation between different behaviours and academic performance, so as to make corresponding improvements.
Keywords: learning behaviour analysis; learning early warning system; GBCFSFDP algorithm; WNBC-FOA algorithm.
K-means clustering algorithms used in the evaluation of online learners' behaviour
by Xiaoming Chen, Wenge Li, Yubo Jiang
Abstract: K-means clustering algorithm is used to analyse plenty of learners' behaviour data stored on the online learning platform. The learning behaviour data, basic information, and user types and factors affecting performance of online learning learners are firstly analysed and explored. Secondly, based on feature selection and optimisation algorithm of initial clustering centre, a K-means feature selection algorithm is proposed, and an equilibrium discriminant function is presented to balance the difference between the clusters and within the clusters. Finally, the clustering centre obtained by K-means feature selection algorithm is used as the centre of the neural network. The parameters, input and output variables of the prediction model are set. Based on the radical basis function (RBF) neural network structure, the performance prediction model is constructed, which dynamically updates to enable accurate performance predictions. The results show that the performance prediction model proposed has high prediction accuracy for online learners' performance.
Keywords: online learning; behaviour evaluation; K-means algorithm; prediction model.
Adaptive optimisation algorithm for online teaching behaviour
by Jinhua Zhu
Abstract: It is believed that there are two mechanisms, namely, the mechanism of mutual learning among multiple teachers and the mechanism of adaptive step size improvement, to optimise teaching learning-based optimisation (TLBO) algorithm. Firstly, by setting up multiple teachers to teach in the TLBO algorithm, the diverse nature of the population can be preserved. The algorithm is improved in the precision of optimisation, and the algorithm is improved on the weakness of local optimisation. The student's learning step size is a random value in the standard algorithm, which neglects the fact that the student's progress speed changes continuously with own state. Adjusting the student's own state is an improved learning step, which can improve the accuracy of the algorithm. The results show that the improved algorithm has faster convergence speed and higher solution precision, so the improved algorithm is superior to TLBO in solution accuracy, stability and convergence speed.
Keywords: teaching learning-based optimisation algorithm; adaptive step size; global optimisation; multi-teacher.