International Journal of Continuing Engineering Education and Life-Long Learning (13 papers in press)
Statistical Analysis for Assessing Sample/Practice Exams in Undergraduate Engineering Education
by Mohammad Khasawneh
Abstract: The inclusion of practice exams in undergraduate engineering courses was assessed utilising survey results and the analysis of variance (ANOVA) tools. Data collected was from the survey completed by students and students grades spanning over two semesters one with implementing practice exams and the other without. Results based on survey indicated that there was a very strong consensus among students about the usefulness and validity of such course improvement. Furthermore, the statistical analysis results using the ANOVA and the independent samples t-test tools also showed a significant increase, on the 0.05 significance level (or 95% confidence level), in students academic procurement when utilising the practice exams technique. Therefore, it is recommended that sample exams be implemented in undergraduate engineering education to enhance students earnings and their learning experience.
Keywords: Highway Design; Geotechnical Engineering; Sample Exams; Practice Exams; Undergraduate; Engineering; Assessment; Survey; Statistics; ANOVA.
Multidisciplinary Collaboration: an Integrated and Practical Approach to the Teaching of Project Management
by Silvia Mazzetto
Abstract: This paper presents a practical approach to the teaching of applied project management in the form of a collaborative, multidisciplinary project involving the Departments of Architecture and Urban Planning (AUP) and Industrial and Systems Engineering (ISE) at Qatar University. The two courses, Construction and Project Management (ARCT 530 AUP) and Project Engineering (IENG 481 ISE), were running in the same semester, which made it possible to assemble multidisciplinary project teams that included students from both courses, and to share out the management and development roles between them. The primary objective was to simulate a real-world scenario that gave students the opportunity to address the problems arising out from typical situations of professional projects, such as collaboration and leadership within a team, organisation and tasks allocation, and the ability to manage the time pressure and meet deadlines. This approach brought the theoretical teaching of project management to be closer to its practical application and made it easier for the students to learn the techniques and tools commonly used in the professional setting.
Keywords: Practice Experience; Theoretical Approach; Collaborative Project; Management Process; Leadership Skills.
An exploratory study of discrimination toward contract faculty teaching in engineering colleges of the border area of Gurdaspur, India
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.
Satisfaction ranking of employers towards graduates from higher education institutions: An application of hybrid multiple criteria decision-making approach
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.
Comprehensive Evaluation System of Teaching Quality Based on Big Data Architecture
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.
Special Issue on: Big Data and Data Science in Educational Research
Design of multimedia engineering teaching system based on internet of things technology
by Huikai Zheng, Zachary Perez
Abstract: In order to improve the multimedia control performance of teaching, a multimedia engineering teaching system design model based on internet of things technology is proposed. The overall structure model of the real estate engineering multimedia teaching system design is constructed based on the embedded ARM core. The system integration control is implemented through the decentralised control method, and the overall design framework of the real estate engineering teaching system is carried out. The internet of things networking technology is used for system network design, the VIX bus technology is used to carry out real estate engineering teaching data communication and information processing, and the software design of the multimedia engineering teaching system is realised in embedded environment. The test results show that adopting this method to design the multimedia engineering teaching system can provide better robustness, stronger human-computer interaction, and can realise multimedia integrated control of teaching system.
Keywords: internet of things technology; multimedia; engineering teaching; system design.
Modelling and analysis of innovative path of English teaching mode under the background of big data
by Kanmanli Maimaiti
Abstract: In order to improve the efficiency of the best way to choose innovative English teaching mode, this paper proposes an innovative path model of English teaching mode based on ant colony algorithm. The innovation strategy of English teaching mode is analysed, then the influence index of English teaching mode is analysed, the weight of index is calculated, and the objective function is constructed according to the influence index of English teaching mode. On this basis, the ant colony algorithm is used to find the best path of English teaching mode innovation and the modelling and analysis of English teaching mode innovation path is completed under the background of big data. The experimental results show that the proposed method has higher efficiency in selecting the best path, and the time for searching for the optimal path is shorter, which has a good convergence speed.
Keywords: big data background; English teaching; model innovation; path; modelling.
Analysis of optimisation method for online education data mining based on big data assessment technology
by Guixian Su
Abstract: The existing online education data mining method has the problems of low coverage, low accuracy and high error rate. An optimisation method for online education data mining based on big data assessment technology is proposed. Combining with big data assessment technology, the number of online education is determined according to the target to be evaluated. According to the collected content, the abnormal data, missing data and noisy data of online education are preprocessed. According to the preprocessed results, a model of online education information flow is constructed, and the spectrum characteristics of discrete samples of educational data are extracted. PSO algorithm is used to cluster and optimise the features of online education data to realise the optimisation of online education data mining. The experimental results show that the proposed method can improve the mining accuracy, reduce the mining error rate and ensure the stability of data mining.
Keywords: big data assessment; education data; accuracy; coverage; mining optimisation.
Educational resource information sharing algorithm based on big data association mining and quasi-linear regression analysis
by Yanjun Gao
Abstract: In order to solve the problem that the information sharing level of educational resources is not high in the cloud computing environment, it is required to improve the design of educational resource information sharing algorithm in cloud computing environment. Therefore, an educational resource information sharing algorithm based on big data association mining and quasi-linear regression analysis is proposed. In this algorithm, information fusion and comprehensive measurement index system reconstruction are performed to resource distribution information of the educational resource database based on attribute type and semantic ontology characteristics. The simulation results show that the algorithm performs well in convergence during resource scheduling in educational resource information sharing and can provide average sharing level up to 0.9247, so this algorithm can be adopted to allocate resources in a balance way.
Keywords: educational resource information management system; resources; information sharing; big data; scheduling.
Online course learning outcome evaluation method based on big data analysis
by Hai-jie Li, Min Peng
Abstract: In order to solve the low credibility and poor timeliness of the online course learning effect evaluation, a method based on big data for online course learning results evaluation is proposed, which can better solve the problems existing in traditional methods. A statistical average analysis model for big data of online course learning outcomes is constructed for learning outcome big data analysis based on the sample regression analysis method; a decision objective function of online course learning outcome evaluation is established. The experimental results show that when the method proposed in this paper is adopted to evaluate online course learning outcomes, the method has relatively high confidence and overall timeliness, and the time taken to evaluate the effectiveness of online courses is 28 s and 29 s less than that of the other two methods, so it can provide accurate and reliable evaluation results.
Keywords: big data analysis; online course learning; outcome evaluation; feature extraction; pattern recognition.
Modelling and analysis of the influence of affective factors on students' learning efficiency improvement based on big data
by Humin Yang, Henry Loghej
Abstract: In order to improve learning efficiency and quantify the quality of teaching, a method of modelling the influence of emotional factors on students' learning efficiency is proposed. The statistical feature analysis object model is constructed. The quantitative regression analysis method is used to construct the big data model of emotional factors and learning efficiency. The association rule decomposition method is used to decompose and model the big data samples, and analyse the influence factors of emotion on learning efficiency. The fuzzy constraint control method clusters and mines big data association rules, and analyses the promotion factors of emotional factors to students' learning efficiency, calculates the level of promotion contribution, and adopts adaptive evolutionary game method to realise emotional factors under big data. Modelling the impact of student learning efficiency, experiments show that the proposed method has high confidence level and small error in analysing subject problems.
Keywords: big data; affective factor; students' learning efficiency; information fusion; data mining.
Extended query model for MOOC education resource metadata based on big data
by Yu Cao, Shu-Wen Chen
Abstract: In traditional education resource metadata extended query methods, data recall is poor. In order to solve this problem, an extended query model for MOOC education resource metadata based on big data information fusion clustering scheduling is proposed. The semantic ontology model is adopted to analyse the storage structure of MOOC education resource metadata and extract binary semantic feature quantity of MOOC education resource metadata to construct a binary semantic decision model for extended query of MOOC education resource metadata; the integrated information processing technology of big data is adopted for extended query and adaptive scheduling of MOOC education resource metadata to improve the ability to retrieve and identify metadata. The simulation results show that the proposed method can provide an average precision ratio of 0.976 in extended query of MOOC education resource metadata and good data recall performance.
Keywords: big data technology; MOOC education resource; metadata; extended query; scheduling.
Research on optimisation of MOOC education model based on participatory visual teaching technology
by Zhi-yong He, Yun-qiang Wu, Xiao-ping You
Abstract: The current MOOC education model has the problems of weak interactivity, low participation and poor learning atmosphere. To this end, an optimisation method for the MOOC education model based on participatory visual teaching technology is proposed. The original, dynamic and regenerated resources in the MOOC education model are mapped to the conceptual interactions, information interactions and operational interactions in the hierarchy theory, and hierarchically divided to optimise the resource construction model; the technology change, concept change and application change is used to coordinate, integrate and optimise resources at different levels; the normal distribution statistical analysis is integrated to improve the accuracy of mutual evaluation and optimise the mutual evaluation strategy; The introduction of participatory visual teaching technology optimises the MOOC education model. The experimental results show that the proposed MOOC education model optimisation method is feasible.
Keywords: participatory teaching; visual technology; teaching technology; MOOC education model; model optimisation.