Forthcoming articles

International Journal of Continuing Engineering Education and Life-Long Learning

International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL)

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International Journal of Continuing Engineering Education and Life-Long Learning (28 papers in press)

Regular Issues

  • An exploratory study of discrimination toward contract faculty teaching in engineering colleges of the border area of Gurdaspur, India   Order a copy of this article
    by Vishal Mahajan, Darshan Kumar 
    Abstract: The tradition and practice of hiring contract labour have been common in many parts of India for the long time back. Although believed to be a monetary necessity, but it has been condemned on the ground that it creates employee exploitation. Though system cannot be abolished exploitation absolutely. In spite, the many harm linked to it, but the structure offers much essential employment to a considerable number of employees. This paper aimed to explore the feelings of contractual faculty towards administrative discrimination in engineering institutions in the border area of Gurdaspur district. In this article helps in finding the relationship between parameters like stress level of work, welfare services, pay satisfaction, provident fund facility, gratuity facility, professional with the satisfaction level of the contract faculty. The diagnosis of this study is that the technical institutions and private university in border area Gurdaspur need to understand the importance of feelings of contract faculty.
    Keywords: Contractual Government Engineering Faculty; Private Faculty Job Satisfaction; Administrative discrimination; Gurdaspur District.
    DOI: 10.1504/IJCEELL.2020.10022186
     
  • Satisfaction ranking of employers towards graduates from higher education institutions: An application of hybrid multiple criteria decision-making approach   Order a copy of this article
    by Mongkol Kittiyankajon 
    Abstract: Proper curriculum development is very important to higher education institutions (HEIs), and input from graduate users should be clearly identified. Thus, this study proposed hybrid multiple criteria decision-making (MCDM) to identify and rank employer satisfaction towards graduates from HEIs based on different weights of each graduate quality aspect. A case study of employer satisfaction ranking towards graduates from Industrial Management Department of Udonthani Rajabhat University (UDRU), Thailand was used to validate the effectiveness of the proposed method against the existing method. The results showed that the proposed method gave more reasonable ranking than the existing methods. Consequently, we recommend curriculum development utilise satisfaction levels and ranking results.
    Keywords: Graduate employer satisfaction; MCDM; AHP; TOPSIS; Satisfaction ranking.
    DOI: 10.1504/IJCEELL.2020.10022187
     
  • Automatic Generation of Questions from DBpedia   Order a copy of this article
    by Oscar Rodríguez Rocha, Catehrine FARON-ZUCKER, Alain Giboin, Aurélie Lagarrigue 
    Abstract: The production of educational quizzes is a time-consuming task that can be automated by taking advantage of existing knowledge bases available on the web of linked open data (LOD) such as DBpedia. For these quizzes to be useful to learners, their questions must be generated in compliance with the knowledge and skills necessary to master for each subject and school year according to the official educational standards. We present an approach that exploits structured knowledge bases that contain the knowledge and skills, from which it selects a set of DBpedia resources relevant to a specific school subject and year. This set of resources is enriched with additional related resources, through the NEFCE heuristic. Finally, question generation strategies are applied to the graph generated with this set of resulting resources. Likewise, we provide an evaluation of two knowledge bases and of the proposed NEFCE heuristics.
    Keywords: eEducation; Semantic Web; Linked Data.
    DOI: 10.1504/IJCEELL.2020.10024221
     
  • Multi-agent approach for collaborative authoring and indexing of pedagogical materials   Order a copy of this article
    by Samir Bourekkache, ABIK Mounia, Okba Kazar 
    Abstract: In e-learning environment, the learner may feel that he is isolated and disoriented because of the absence of the teacher and the huge number of materials. Moreover, the pedagogical documents have several characteristics so that we must offer the appropriate documents for each learner according to his level, characteristics, and preferences, etc. Consequently, the adaption of the learning content is an important technique. Creating materials, without additional information, makes the delivering of relevant material an impossible task. Consequently, one has to pay attention to the stage of creating of learning content using new technics. In addition, it may not be convenient if we havent additional information about the learner and the learning material (learning objective, prerequisites, and learner background, etc.). Therefore, we develop a multi-agent system that supports a set of authors who create and index educational materials. The indexes are used to manipulate the learning content efficiently by the machine when choosing the appropriate content to satisfy the needs of heterogeneous learners.
    Keywords: E-learning; Shared editor; Metadata; Educational Content; indexing of documents; Computer Supported Collaborative Work; XML; adaptive hypermedia.
    DOI: 10.1504/IJCEELL.2020.10024222
     
  • Research on Evaluation Model of Oral English Teaching Quality based on Cloud Computing   Order a copy of this article
    by Shixin Sun, Haiyan Li 
    Abstract: Aiming at the problem of low evaluation accuracy of the existing evaluation model of oral English teaching quality, this paper proposes an evaluation model of oral English teaching quality based on cloud computing. The evaluation indicator is divided into expert's evaluation indicator, student's evaluation indicator and teacher's self-evaluation indicator and a comprehensive evaluation indicator set is obtained. The cloud weight in cloud computing model is described by three digital eigenvalues: weight value, entropy value and hyper-entropy value, and the corresponding evaluation cloud model is set up. Based on the cloud computing principle, the cloud evaluation model of oral English teaching quality is constructed. The experimental results show that the model can effectively evaluate the quality of oral English teaching. The selected evaluation indicators are highly representative and the evaluation results are accurate.
    Keywords: Cloud computing; Oral English; Teaching quality; Evaluation.
    DOI: 10.1504/IJCEELL.2021.10025593
     
  • Design Of Virtual Education Experiment Platform Based On Artificial Intelligence   Order a copy of this article
    by Minglei Song, Binghua Wu, Lihua Liu 
    Abstract: In order to solve the problem that the digital image processing of traditional virtual education experiment platform is time-consuming and the evaluation result of the platform does not match the actual result, the design method of virtual education experiment platform based on artificial intelligence is proposed. This paper introduces the general framework of virtual education experiment platform based on artificial intelligence, including remote registration, intelligent push of learning courses, establishment of teaching centre website by using artificial intelligence technology, etc. Based on the framework and heap code, the virtual education experiment platform is built by server and client calling service objects. The experimental results show that the accuracy of the proposed method is between 80% and 95%, the time-consuming is less than 0.02 ?s, and the fitting range is between 80% and 100%. Compared with the methods based on 3D MAX, the proposed method has obvious advantages.
    Keywords: Artificial intelligence; Virtual education; Remote registration; Digital image;.
    DOI: 10.1504/IJCEELL.2021.10025602
     
  • The Evaluation Method of English Teaching Efficiency based on Language Recognition Technology   Order a copy of this article
    by Bing Hu 
    Abstract: At present, there are some problems in the evaluation methods of English teaching efficiency, such as poor significance of indicators, low evaluation efficiency and low evaluation accuracy. This paper proposes an evaluation method of English teaching efficiency based on language recognition technology. Language recognition technology is used to identify English sentences through error detection, eigenvalue extraction, pronunciation evaluation, phoneme association and phoneme recognition. The overall structure of English teaching efficiency evaluation is constructed by B/S structure, and the weight of evaluation indicator is calculated by AHP combined with hierarchical relevance theory. The degree of relevance is obtained, and the evaluation of English teaching efficiency is completed by ranking the degree of relevance. The experimental results show that the proposed method has high significance, high evaluation efficiency and high evaluation accuracy.
    Keywords: Language recognition technology; English teaching efficiency; Evaluation indicators; Evaluation methods;.
    DOI: 10.1504/IJCEELL.2021.10026402
     
  • Design of Step-by-step teaching System for English Writing based on Cloud Network Technology   Order a copy of this article
    by Mian Wang 
    Abstract: Aiming at the problems of low user satisfaction, low user interaction accuracy and high user help-seeking rate in the step-by-step teaching system for English writing designed by the current methods, a step-by-step teaching system for English writing based on cloud network technology is proposed. On the functional module design part of the system, the foreground and background display modules of the system are designed. On the design part of the step-by-step teaching website for English writing, the online learning system and the teaching management system are separated. The experimental results show that the system designed by the proposed method has higher user satisfaction, higher user interaction accuracy, and lower user help-seeking rate. The design of the system meets the needs of users and verifies the good performance of the system.
    Keywords: Cloud network technology; English writing; Step-by-step teaching; System design.
    DOI: 10.1504/IJCEELL.2021.10026403
     
  • Conceptual Clustering of University Graduate Students’ Trajectories Using Formal Concept Analysis: a Case Study in Lebanon   Order a copy of this article
    by Charbel Obeid, Christine Lahoud, Hicham El Khoury, Pierre-Antoine Champin 
    Abstract: Due to the weak academic advising systems in most schools, students need assistance to explore universities/colleges and study fields that match their interests and future careers. Unfortunately, the orientation programs in most schools are not well designed to cater to students' varied needs. While career orientation programs are much needed at schools, a large number of Lebanese schools have not integrated such programs in their educational systems yet. Thus, this research focuses on developing a hybrid recommender system based on machine learning techniques. Our research focuses on the implementation of the formal concept analysis (FCA) to study university graduates' trajectories. This data mining technique is applied in knowledge presentation and data processing. FCA enables the discovery of hidden knowledge by using association rule mining and machine learning. The objective of this study is to discover the university graduates' trajectories and demonstrate the effectiveness of the FCA technique in data clustering.
    Keywords: Formal Concept Analysis (FCA); Concept Lattice; Students’ Trajectories; Recommender System.
    DOI: 10.1504/IJCEELL.2020.10027147
     
  • A Model of Foreign Language Listening Ability Assessment Assisted by Mobile Devices based on Neural Network   Order a copy of this article
    by Jing Qiu 
    Abstract: In order to overcome the inaccuracy of foreign language listening assessment and the limitations of the assessment process, a model of foreign language listening ability assessment assisted by mobile devices based on neural network is proposed. Aiming at the characteristics of mobile devices, this paper applies artificial intelligence technology to foreign language listening ability assessment, and mining relevant data. BP network learning ability, nonlinear processing ability and fault tolerance ability are set as the assessment indicators of foreign language listening ability. A model of foreign language listening ability assessment assisted by mobile devices based on neural network is established, and the intelligent assessment of foreign language listening ability is realised through the model. The simulation results show that the proposed method can quickly and accurately evaluate the user's foreign language listening ability.
    Keywords: Neural network; Mobile device assistance; Foreign language listening ability; Intelligent assessment; Fault tolerance ability.
    DOI: 10.1504/IJCEELL.2022.10027335
     
  • Modeling And Analysis Of The Impact Of Smart Mobile Devices On Learning Effect Based On Partial Least Square Regression   Order a copy of this article
    by Meng Qu 
    Abstract: Aiming at the problems of long running time, high learning cost and low accuracy of the current learning effect model of intelligent mobile devices, a learning effect model of intelligent mobile devices based on partial least squares regression is designed. Use E-R diagram to analyse the relationship between courses and other resources, and build a learning database. Partial least-squares regression method is adopted to establish the influence model of intelligent mobile devices on learning effect, and partial regression coefficients are used to modify the partial least-squares regression model, so as to realise the modelling and analysis of the influence of intelligent mobile devices on learning effect. The experimental results show that the running time of this method is less than 30s, the average learning cost is only 6.25, and the fitting degree is higher than 80%, which proves that the comprehensive performance of the model in this paper is better.
    Keywords: Partial least square regression; Smart mobile device; Learning effect; Impact modeling; E-R diagram.
    DOI: 10.1504/IJCEELL.2022.10027336
     
  • Research on Centralized Matching Method of Teaching Knowledge Categories Based on Intelligent Language Recognition   Order a copy of this article
    by Lei Liu 
    Abstract: In order to improve the accuracy and efficiency of teaching knowledge classification matching, a method of teaching knowledge classification matching based on intelligent language recognition is proposed. The deep learning network was constructed, the language files were preprocessed, and the extracted language feature vectors were used to train the network and optimise the deep learning network. The intelligent language recognition network model is established and the k-means clustering algorithm is used to acquire the model. Classification of teaching knowledge is processed centrally and the classification system of teaching knowledge is obtained. Matching problem of teaching knowledge classification system is modelled, and the corresponding undirected graph is constructed, which is converted into the matching problem with the greatest weight, and the optimal matching scheme under the category of teaching knowledge concentration is obtained. Experimental results show that the matching results based on intelligent language recognition are more accurate and more efficient.
    Keywords: Intelligent Language Recognition; Knowledge Category; Category Set; Category Matching.
    DOI: 10.1504/IJCEELL.2022.10027338
     
  • Design of Interactive English Reading Teaching System Based on Hybrid Communication Network   Order a copy of this article
    by Le Yang 
    Abstract: In order to overcome the problem of long response time and poor interaction in traditional English reading teaching system, an interactive English reading teaching system based on hybrid communication network is proposed. The hardware part of the system is composed of seven modules, among which the course management module mainly adopts the combination of file system and multimedia attribute database to manage the uploaded data of teachers. Students use the hyperlink location field to mark the connection location of the media, can see more colourful learning pages, to achieve the interactive design of the teaching system. In the software part, the learning evaluation model is constructed by covering method or error method to realise the comprehensive evaluation of students' learning state. Simulation results show that this method can comprehensively understand and evaluate students' learning status and knowledge points, shorten the response time of the system, and has great advantages.
    Keywords: Hybrid Communication Network; Interactive; English Reading; Teaching System.
    DOI: 10.1504/IJCEELL.2021.10027340
     
  • Research on Classification Method of Answering Questions in Network Classroom Based on Natural Language Processing Technology   Order a copy of this article
    by Lanlan Liu, QIANG Yu 
    Abstract: In order to overcome the inaccuracy of the current research results of online classroom question-answering classification, a method of online classroom question-answering classification based on natural language processing technology is proposed. The entity relationship model of the network classroom question answering system is constructed, and the model is transformed into the relational data model, the network classroom question answering database is constructed. TF-IDF technology is used to extract curriculum keywords, construct attribute word set, use natural language processing technology to segment students' questions reasonably in the network classroom, convert the words into vectors, calculate the question similarity according to cosine theorem, and then return the answers with the highest degree of similarity to students in the same type of questions. Experimental results show that the classification accuracy of the proposed method is always above 96%, and the user satisfaction is above 94%, with high classification accuracy and user satisfaction.
    Keywords: Natural Language Processing; Online Classroom; Question Answering Classification; Rules; Support Vector Machine.
    DOI: 10.1504/IJCEELL.2022.10027342
     
  • Data Acquisition Model for Online Learning Activity in Distance English Teaching based on xAPI   Order a copy of this article
    by Mingqi Wang, Yuanyuan Wang 
    Abstract: In order to overcome the problems of low accuracy and low recall rate of online learning activity data acquisition, an online learning activity data acquisition model of distance English teaching platform based on xAPI is proposed. According to the visual attribute data of elements, this model divides and judges the online learning activity web page and preliminarily determines the location of noise data. According to the context content rules, the segmentation results of online learning activity web pages are processed in detail, the subblocks are evaluated comprehensively, and the noise data are locked and filtered. The data acquisition model is built by using the modules of user login verification, user mouse track replication, and English online learning activity data acquisition report display. Experimental results show that the model has high recall and precision.
    Keywords: Distance English teaching; Online learning; Data acquisition; Noise data; User information.
    DOI: 10.1504/IJCEELL.2021.10027343
     
  • Design of Key Data Integration System for Interactive English Teaching based on the Internet of Things   Order a copy of this article
    by Zhihong Yang, Baiyang Feng 
    Abstract: In the traditional key data integration system for interactive English education based on the Internet of Things (IOT), there are many problems, such as long integration time and low accuracy. To this end, a new key data integration system for interactive English teaching based on Internet of Things is designed. According to the construction of the design framework of key data integration for interactive teaching based on the Internet of Things, the integration of teaching objectives, teaching content, teaching process and teaching evaluation are realized. The configuration and system integration operation are carried out according to the actual requirements of key data integration for teaching. The test results show that the system has a short time and high accuracy to integrate the key data of interactive English teaching based on the Internet of Things.
    Keywords: Internet of Things; Interactive English teaching; Key data; Integrated system.
    DOI: 10.1504/IJCEELL.2021.10027600
     
  • Research on the Evaluation Method of Students' Classroom Performance Based on Artificial Intelligence   Order a copy of this article
    by Huaxi Chen, Yang Liu, Anjahol Thoff 
    Abstract: In order to overcome the problem that the traditional evaluation method of students’ classroom performance has long time and low reliability, the evaluation method of student's classroom performance based on artificial intelligence is proposed. This method builds the assessment criteria for students’ classroom performance and quantifies the assessment of classroom performance. Assessment indicators such as attendance, participation, attention, and abnormal behavior in the student’s classroom performance are analyzed, and the final output is used as the results of the staff’ classroom performance. The experimental results show that compared with the traditional evaluation method, the evaluation method of students’ classroom performance based on artificial intelligence saves an average of 69 seconds in time and the 6.25% increase in reliability.
    Keywords: artificial intelligence?classroom performance?evaluation method?students’ performance?monitoring image.

  • Construction Of Case-Based Oral English Mobile Teaching Platform Based On Mobile Virtual Technology   Order a copy of this article
    by Huaxi Chen, Ji Li 
    Abstract: In order to overcome the problems of long response time and low user satisfaction of current spoken English teaching platform, this paper proposes a case-based mobile spoken English teaching platform based on mobile virtual technology. The platform framework is selected as B/S data framework. In order to match the framework structure, all the subordinate design patterns choose MVC mode. According to user roles, the platform framed the core design content into three parts: student user module, teacher user module and administrator user module. The experimental results show that, compared with the traditional platform, the designed mobile teaching platform has the advantages of short response, high user satisfaction rate and application advantages.
    Keywords: Mobile Virtual; Case-Based; Spoken English; Mobile Teaching Platform; Background Data.
    DOI: 10.1504/IJCEELL.2021.10027601
     
  • Research on remote control method of assisted instruction based on machine learning   Order a copy of this article
    by Hualin Sun 
    Abstract: Aiming at the problems of poor stability and low efficiency in the traditional remote control system of assisted instruction, a remote control system for assisted instruction based on machine learning is proposed. The hardware part of the system is composed of authentication module, student learning module, teaching management module, forum management module and system management module. The basic functions of the remote control system for assisted instruction, such as course learning, self-test evaluation, homework submission and online question answering, are determined and analyzed in detail to improve teaching efficiency. Machine learning is introduced into the teaching control process. The remote learning signal of LSML-SVM is controlled. The machine learning function is defined and the linear equations of machine learning are solved. Finally, the software flow chart is given. The test results show that the proposed design method has good stability and high efficiency.
    Keywords: Machine learning; Assisted instruction; Remote control; System design.
    DOI: 10.1504/IJCEELL.2021.10027602
     

Special Issue on: Computer Based Learning In Higher Education

  • Construction of a learning behaviour tracking analysis model for a MOOC online education platform   Order a copy of this article
    by Peng Zhang, Wei Wang, Chui-Zhen Zeng 
    Abstract: Aiming at the problems of low extraction accuracy, high missed detection rate and low learning efficiency of existing learning behaviour tracking analysis models, a learning behaviour tracking analysis model of MOOC online education platform based on XAPI and Bayesian fuzzy rough set is established. Firstly, the learning behaviour is stratified, then the learning behaviour of online education platform and its correlation with learning effect are analysed, and the learning behaviour indicators are determined. Finally, the learning behaviour tracking analysis model based on Bayesian fuzzy rough set is established. The experimental results show that the accuracy of learning behaviour extraction of the model is always above 93%, and the accuracy is high; the rate of missing detection is between 1% and 4%, and the rate of missing detection is low; the maximum improvement of learning efficiency is 14.8%, and the students' learning efficiency is high, which verifies the validity of the model.
    Keywords: education platform; learning behaviour; behaviour tracking analysis model.
    DOI: 10.1504/IJCEELL.2020.10024631
     
  • Application of mobile education in assisted autonomous learning platforms in intelligent campus   Order a copy of this article
    by Yanyan Song 
    Abstract: In order to solve the problems of low teaching effect and poor student performance in traditional methods of building intelligent campus, an application method of mobile education in intelligent campus assisted autonomous learning platform is proposed. This method analyses the connotation and characteristics of mobile learning, and studies the influence of mobile education on assisted autonomous learning in intelligent campus. By means of questionnaires, the teachers who have carried out mobile education and those who have not carried out mobile education are investigated. And compare the examination results of mobile education classes with those of non-mobile education classes. The results of the survey show that the application of mobile education in intelligent autonomous learning platform can diversify teaching methods, improve teachers' teaching effect, and improve students' learning performance on the premise of improving students' enthusiasm in class, thereby improving the teaching level of intelligent campus.
    Keywords: mobile education; intelligent campus; autonomous learning platform; mobile learning.
    DOI: 10.1504/IJCEELL.2020.10024630
     
  • Research on the innovation of modern network distance education models based on the web   Order a copy of this article
    by Youkun Tan, Chankyu Lee 
    Abstract: In view of the low degree of visualisation of the current network distance education model, this paper proposes an innovative research on the modern network distance education model based on web. Firstly, the physical structure of the network distance education model is elaborated and the architecture of the network distance education model is constructed. Taking the examination of network question bank under the mode of distance education as an example, this paper designs the implementation process of the examination of network question bank, in order to realise the innovative research on the mode of network distance education. The experimental data show that the CPU time of this method is about 0.1 hours shorter than that of the traditional method and the flexibility coefficient is close to 1 when the number of users is increased by 200 at a time. This shows that the method is more flexible and intelligent.
    Keywords: web; modern network; distance education model; innovative research.
    DOI: 10.1504/IJCEELL.2020.10024627
     
  • Online mobile teaching methods based on Android in the 5G environment   Order a copy of this article
    by Yanhua Wang, Jeroma Talim 
    Abstract: Aiming at the problem of long delay response of online mobile teaching platform, a design method of online mobile teaching platform based on Android 5G environment is proposed. Firstly, the hardware of the online learning platform is designed, and the Android mobile terminal is taken as the hardware core. In the software part of the system, AIMD algorithm is used to reduce the transmission volume. By controlling the speed of multimedia data flow on the platform, the network congestion of the platform is alleviated. DB-KAD algorithm is used to select the optimised network delay parameters to meet the requirements of multimedia data transmission. The performance test results show that the maximum response delay of this method is 0.07 s, the maximum buffer delay of video is 1.4 s, the number of video pauses varies in the range of 0-1.0, and the response delay requirement of online mobile teaching platform.
    Keywords: 5G environment; Android system; online mobile teaching.
    DOI: 10.1504/IJCEELL.2020.10024629
     
  • An intelligent evaluation model of bilingual teaching quality based on network resource sharing   Order a copy of this article
    by Li Qian, Zachary Perez 
    Abstract: Aiming at the poor application performance of traditional model for bilingual teaching quality evaluation, this paper proposes a model construction method of bilingual teaching quality evaluation based on network resource sharing. The evaluation indicators are selected reasonably, and an intelligent evaluation model of bilingual teaching quality based on network resource sharing is constructed. The evaluation indicators in the model are compared and weighted by analytic hierarchy process (AHP), and a fuzzy comprehensive evaluation matrix is established. The bilingual teaching quality evaluation has been realised. The experimental results show that the fluctuation range of evaluation error is between 1.6 and 1.7, and the evaluation error is small. Through the questionnaire survey, it is found that the time for teachers to compile teaching plans is shortened by 0.4 hours, the students' scores are improved by 1.5 points, the quality of bilingual teaching is improved, and the satisfaction of teachers and students is improved.
    Keywords: resource sharing; bilingual teaching; teaching quality evaluation; indicators; hierarchical analysis.
    DOI: 10.1504/IJCEELL.2020.10024628
     
  • Association analysis of online learning behaviour in interactive education based on an intelligent concept machine   Order a copy of this article
    by Yuenan Chen 
    Abstract: Aiming at the problem that the existing association analysis of online learning behaviour in interactive education has poor practical application effect, this paper proposes an association analysis method of online learning behaviour in interactive education based on intelligent concept machine. Association rules are used to obtain association information between data. Based on the characteristics of online learning, a data classification index system was constructed by RFM analysis method. K-means method is adopted to cluster user behaviours. PageRank algorithm was used to obtain the most representative learning users, recommend the best courses for users, and analyse the learning behaviour and effect through association rules. Finally, through simulation experiment, it is found that the average learning score of learners increases by 15 points after using this method, and the application effect is good, which verifies the effectiveness of this method.
    Keywords: intelligent concept machine; interactive education; online learning; behaviour association analysis.
    DOI: 10.1504/IJCEELL.2020.10024625
     
  • A comprehensive evaluation system of teaching quality based on big data architecture   Order a copy of this article
    by Yanan Wang 
    Abstract: Aiming at the problems of long response time and high error rate in traditional teaching quality comprehensive evaluation system, a teaching quality comprehensive evaluation system based on big data structure is proposed. Firstly, different evaluation indicators are designed, the principle of teaching quality comprehensive evaluation is designed by using data dictionary, the requirement analysis of teaching quality comprehensive evaluation system is realised by using UML use case model, then the overall framework of the system is designed, and the comprehensive evaluation system of teaching quality is developed and studied by using Asp.net related technology. The experimental results show that the response time of the designed system is shorter than that of the traditional teaching quality comprehensive evaluation system, and the fitting degree between the evaluation results and the actual situation is higher, which fully proves the superiority of the designed system.
    Keywords: big data architecture; teaching quality; comprehensive evaluation; system design.
    DOI: 10.1504/IJCEELL.2020.10023768
     
  • Construction of a sharing model for network digital teaching resources oriented to big data   Order a copy of this article
    by Lin Chen, Tianming Feng, Dahang Fan 
    Abstract: Aiming at the problems of low resource utilisation rate, low model reliability and poor feasibility of current network resource sharing model, this paper proposes and constructs a sharing model for network digital teaching resource based on semantic web. The game model is used to analyse the behaviour evolution of teaching resource sharing model. Based on ontology relationship, a general framework of metadata for teaching resources is constructed to realise interoperability between metadata. Taking XML as the basic grammar, according to the details of the application of teaching resources, the related application based on XML is created, and the sharing of network digital teaching resources is realised by defining the pattern layer by layer. The experimental results show that the utilisation rate of teaching resources under this model is high, and the fitting degree between the model and the actual situation is high.
    Keywords: big data; digital teaching; resource sharing.
    DOI: 10.1504/IJCEELL.2020.10024626
     
  • Prediction of university students' academic level based on linear regression model   Order a copy of this article
    by Chao Dong, Yan Guo 
    Abstract: Aiming at the problems of the prediction results by using the existing methods for university students' academic level prediction, such as large error and long time-consuming prediction, this paper proposes a method based on linear regression model to predict the academic level of university students. In order to improve the accuracy and real-time of prediction, Firstly, the students' academic related information is denoised, and then the denoised academic level information is classified. Finally, the linear regression model is used to predict the academic level of university students. The experimental results show that compared with other methods, the prediction error rate of the proposed method varies from 1% to 8%, and the prediction accuracy rate is higher. The predicted duration of the students academic level is in the range of 1 minute to 5 minutes, and the prediction speed is faster.
    Keywords: academic level; prediction; linear regression.
    DOI: 10.1504/IJCEELL.2020.10024624