Forthcoming Articles
International Journal of Continuing Engineering Education and Life-Long Learning

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.
Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression "in press". For example: Smith, J. (in press). Article Title. Journal Title.
Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase.
Online First articles are also listed here. Online First articles are fully citeable, complete with a DOI. They can be cited, read, and downloaded. Online First articles are published as Open Access (OA) articles to make the latest research available as early as possible.
Register for our alerting service, which notifies you by email when new issues are published online.
International Journal of Continuing Engineering Education and Life-Long Learning (16 papers in press) Special Issue on: Smart and Continuing Education and Life Long Learning
Abstract: With the further development of information and wireless communication technology and the deepening of global economic integration, the daily communication between residents in various regions has not only been deepened but also provided a technical basis for various cross-border economic activities. In todays information age, English has become the first language of choice for data transmission between regions. To some extent, it also means that in todays society, mastering the language of English can timely obtain all kinds of latest information and data, so as to help individuals or enterprises get higher quality development. Therefore, English education has become the key teaching content that various schools in various regions should pay attention to at present. Through higher quality English teaching, it can cultivate more talents who can use English skillfully to listen, speak, read, and write to further promote social and economic development. At this time, some researchers in the field of education put forward an interactive English teaching mode (TM for short here) in the stage of college education. Keywords: English Interactive Teaching; Audiovisual Classroom; Virtual Reality; Artificial Intelligence. DOI: 10.1504/IJCEELL.2025.10072638
Abstract: As society develops, Distance Education (DE) has become increasingly important in modern education. The implementation of the DE mode provides learning opportunities for more and more people. Applying modern Information Technology (IT) to DE can effectively change the current education mode, especially applicable to the opening and growth of DE. With the help of modern IT, English distance learning can solve the serious shortage of educational resources and provide a good infrastructure for the implementation of distance learning. Therefore, this paper analysed the characteristics and functions of English DE, studied the application and existing problems of multimedia network English DE, and put forward some corresponding optimisation strategies to solve the current issues. Through comparison, the new mode teaching content design effect was 9.1% higher than the traditional ones, and the quality of teaching was 10.8% better than the conventional model. In other words, intelligent teaching and network multimedia can promote the English DE and improve its implementation quality. Keywords: college English teaching; information-based intelligent distance education; network multimedia; teaching optimisation strategy. DOI: 10.1504/IJCEELL.2025.10072600
Abstract: Professional core competitiveness is the content that all countries in the world pay attention to. Especially in the information age, with the rapid development of artificial intelligence, how to better adapt to the professional environment is an urgent problem that needs to be solved. At present, there are problems with the evaluation of occupational visualisation ability and feature construction, such as large data differences, difficulty in fusion, and difficulty in efficiently extracting and standardising various occupational data. Moreover, due to the lack of adaptability and flexibility in the adopted technical means, the ability to analyse and express data is limited. To solve this problem, this paper takes cloud computing as the main technology and constructs an index system of individual visualisation ability. It meets the requirements of modern personnel training and promotes social development base on meeting individual development needs. The index system includes five dimensions: learning development ability, work communication ability, organisational integration ability, career transformation ability, and emotional control ability. There are four reference variables under each dimension. The reliability analysis of the scale of this index system shows that the internal consistency reliability coefficient, retest reliability coefficient, and split-half reliability coefficient of other subscales and total scales are above 0.84, except for the three reliability coefficients of career transformation ability subscales ranging from 0.75 to 0.77. Keywords: cloud computing technology; professional ability improvement; visual indicators of vocational ability; professional ability characteristics. DOI: 10.1504/IJCEELL.2025.10072639
Abstract: With the rapid development of media technology, the role of journalism and communication education in higher institutions has become increasingly critical. This study investigates how artificial intelligence (AI) and big data technologies can enhance the accuracy and effectiveness of journalism and communication teaching. Focusing on four universities in Jiangsu Province, the research evaluates key factors influencing teaching quality and explores AI-driven precise teaching methods. Results show an average score of 79.55, indicating significant improvement in classroom instruction and talent training. The findings provide valuable references for optimising journalism education and offer new insights into integrating AI into teaching practices, ultimately supporting more efficient and targeted communication professional development. Keywords: big data; artificial intelligence; college journalism communication course; precise teaching method. DOI: 10.1504/IJCEELL.2025.10072601
Abstract: This study delves into the correlation between undergraduate student engagement and their academic achievements within the context of Chinese culture. It systematically explores the interrelationship of various aspects of student engagement, including teacher-student relationships, student-student relationships, as well as cognitive and behavioural dimensions. Additionally, it investigates the moderating role of gender in the relationship between student engagement and student academic achievement. The results provide the following insights: 1) overall student engagement, teacher-student relationship, cognitive engagement, and behavioural engagement exhibit significant direct effects on student academic achievement, while student-student relationships do not significantly impact student academic achievement; 2) among the various components of student engagement, behavioural engagement has the most substantial influence on student academic achievement, followed by the teacher-student relationship. Cognitive engagement has the least pronounced effect on student academic achievement; 3) the four main components of student engagement affect student academic achievement in a serial pattern: teacher-student/student-student relationship → behavioural engagement → cognitive engagement → student academic achievement; 4) the influence of teacher-student relationship/behavioural engagement on student academic achievement is more prominent in male students than in female students. Keywords: behavioural engagement; BE; cognitive engagement; CE; student-student relationship; SSR; teacher-student relationship; TSR; student engagement; SE; student academic achievement; SAA. DOI: 10.1504/IJCEELL.2025.10072789
Abstract: With the advancement of information technology, intelligent multimedia has become essential in online physical education. This study explores human-computer interaction design in sports online teaching platforms, focusing on how intelligent multimedia technology enhances teaching effectiveness. Through experiments assessing student motivation, academic performance, and satisfaction of both students and teachers, results show that intelligent multimedia significantly boosts student engagement and learning outcomes. The design improves interaction, overcomes limitations of traditional teaching, and increases student satisfaction by 7.9%. It also enhances teacher satisfaction, demonstrating that intelligent multimedia integration promotes effective online physical education and supports digital education development. Keywords: sports online teaching; intelligent multimedia; human-computer interaction; HCI; digital teaching. DOI: 10.1504/IJCEELL.2025.10072925
Abstract: China's education is undergoing a new transformation. The development of the times requires that the teaching method of English translation change from 'teacher-led' to 'student-led', and intuitive classroom teaching is particularly important. Based on 'mobile learning', this article proposes a new model of English translation teaching that is different from the traditional teaching method. By introducing 'mobile learning' to compare the traditional teaching model, this article proposes a new model of English translation classroom teaching that meets the requirements of the times to solve objective problems such as the single translation method in the English classroom teaching system. The comparison results show that compared with the traditional English translation teaching model, the new model based on mobile learning has increased student satisfaction by 25%, and in terms of student freedom, English scores have increased by 23%. The learning effect index has increased from 0.43 to 0.7, and the student time freedom score has increased from 2.0 to 3.6 (5-level scale). It also shows that the English translation teaching model based on mobile learning is more in line with the times and is of great significance to students in English translation teaching classrooms. Keywords: classroom teaching system; English translation; classroom teaching; mobile learning. DOI: 10.1504/IJCEELL.2025.10073008
Abstract: To address the limitations of traditional university physical education in time and space and its inability to meet individual student needs, this study proposes an intelligent sensing + digital teaching model. Centred on a smart sensor network, it collects real-time motion data via wearable devices, uses Kalman filtering for noise reduction, and applies CNNs for accurate movement recognition. K-means clustering analyses student profiles to generate personalised training programs. An interactive digital environment built on Moodle enables data visualisation, real-time feedback, and online guidance, forming a perception-analysis-feedback closed-loop system. Experiments show improved data quality and recognition accuracy, with a 28.6% fitness improvement among low-level students, demonstrating the models effectiveness in promoting scientific, precise physical education teaching. Keywords: digital teaching; college physical education; personalised training; Kalman filter algorithm; convolutional neural networks. DOI: 10.1504/IJCEELL.2025.10073046
Abstract: An intelligent music teaching system based on human-computer interaction is proposed to address limitations in traditional music education. The system includes three modules: video-supervised teaching, instrument selection, and course selection. These form a complete intelligent teaching framework. Experimental comparisons were made between traditional and intelligent methods across three key issues in music education. Feedback from six students showed improvements in learning efficiency, engagement, and personalized instruction when using the intelligent system. Data analysis confirms the systems potential to enhance music education by offering more interactive and tailored experiences. This study demonstrates the effectiveness of integrating interactive technology into music pedagogy. Keywords: intelligent music teaching; human-centred computing; precision rate; cost of economy.
Abstract: With the advancement of curriculum reform, the teaching objectives of Chinese language and literature courses have gradually shifted to cultivating students practical application abilities and personalised learning. Interactive teaching provides students with more opportunities for self-expression, which is conducive to their development. This paper studies the evaluation and scoring of live teaching and recorded teaching by students majoring in Chinese language and literature through questionnaire survey, and sets up a simple group and a live teaching model group under the interactive intelligent teaching mode. The questionnaire data were analysed using big data decision tree technology. The results showed that about 58.5% of the students were delighted with the live teaching and believed it was effective. Their learning attitude and results had been significantly improved. However, more students disagreed with the recorded teaching mode. Keywords: interactive intelligent teaching mode; hash algorithm; decision tree; SHA256 algorithm. DOI: 10.1504/IJCEELL.2026.10073055 Regular Issues
![]() by Wei Yin, Jiayi Li, Kehan Ji Abstract: Students' satisfaction and continuance intention are critical for the success of online courses. Extensive research has been conducted to explore the contributors of continuance intention, focusing on the student-related and technological elements. However, few attempts have been made to comprehensively explore the influence of online learning interaction on students' continuance intention. Based on the stimulus-organism-response (S-O-R) model, this study proposed a model taking online interactions as the stimulus variable, learners' satisfaction as the organism variable, and learners' continuance intention as the response variable. Data on student engagement, satisfaction, and persistence in online learning were collected from a sample of 771 engineering students, ranging from freshmen to postgraduates. The data were analysed using structural equation modelling (SEM) to validate the proposed theoretical model. The results indicate that student-content interaction exerts the most significant influence on students' continuance intention among the four types of online learning interactions, highlighting the importance of learning materials' content quality. Meanwhile, the other three types of online interaction also have considerable influence coefficient. The findings provide some advice on improving e-learning interactions to promote engineering students' online English learning satisfaction and continuance intention. Keywords: online interaction; engineering students; online English learning; satisfaction; learning continuance; S-O-R model. DOI: 10.1504/IJCEELL.2025.10070136 Construction and implementation of exploratory teaching model based on social network analysis ![]() by Qiushi Wu, Lei Bo, Chunhang Qu Abstract: In order to solve the problems existing in traditional methods, such as the achievement rate of teaching objectives, learning participation rate and low academic performance, this paper puts forward a research method for the construction and implementation of exploratory teaching model based on social network analysis. Through questionnaire, online interactive platform monitoring and direct observation, the interaction data of students are collected, and the collected data are cleaned, and the social network analysis is carried out by using the cleaned data to determine the key nodes and groups among students. The inquiry teaching mode is constructed from the determination of learning objectives, the allocation of learning resources, the organisation of learning activities and the evaluation of learning effects. The maximum achievement rate of the proposed method of implementation is 93.1%, the maximum participation rate is 97.2%, and the maximum student academic performance is 90.2%. Keywords: social network analysis; exploratory; teaching model; determination of learning objectives; allocation of learning resources; organisation of learning activities; evaluation of learning effects. DOI: 10.1504/IJCEELL.2025.10071208 Semiotics in engineering education for enhancing communication awareness ![]() by José Luis Díaz Palencia, Yanko Ordóñez Ontiveros, Julián Roa González Abstract: The aim of this work is to explore the potential benefits of considering semiotics in engineering education to promote communication skills and cultural awareness among engineering students. We introduce semiotic-based activities in various engineering courses at the university level. The intention is to promote students' awareness concerning the role of symbols in engineering, which lead to a better understanding of their cultural and communicative significance. The classroom activities introduced within this work highlight the need for clear, consistent, and universally understandable symbols in engineering practice to promote a universal community approach in the engineering profession. This paper is rooted in the dynamic nature of signs (as noted by Peirce, 1931) and the necessity for pre-service engineers to adapt to evolving symbols as they may appear in their future professions. Keywords: semiotics; engineering education; symbolic communication; cultural context; technical communication. DOI: 10.1504/IJCEELL.2025.10070058 Advanced ideological and political education strategy based on artificial intelligence: edge computing method ![]() by Yue Zheng Abstract: Currently, advanced ideological and political education has developed rapidly. Based on transfer learning, deep neural networks (DNN) and edge computing, this paper analyses and studies an advanced recognition system of ideological and political education. We compare the precision and other indicators obtained from the training of AlexNet and ResNet deep learning models. It compares the suitability of the two models for identifying advanced ideological and political education. It deploys the ResNet model to the edge server, which can execute feature extraction and real-time detection. Finally, this paper carries out the simulation experiments on the above models and algorithms respectively. The ResNet deep learning model based on edge computing has a superior task completion rate compared to traditional deep learning algorithms and it has better practicability for advanced ideological and political education strategies. Keywords: artificial intelligence; deep learning; edge computing; advanced ideological and political education strategy. DOI: 10.1504/IJCEELL.2025.10070778 Learners' eye movement behaviour in a conceptual knowledge video lecture: a Chinese case study ![]() by Xiaojin Wang, Jinyou Zou, Dongmei Tang Abstract: In MOOCs, video lectures are widely used, yet how to design them effectively based on knowledge type remains underexplored. This study investigates learners' eye movement behaviours and conceptual knowledge acquisition while watching a six-minute video lecture. Twenty-six university students participated by viewing the video and completing a conceptual knowledge test. Eye-tracking technology was used to collect data on pupil position, fixation time, and gaze paths, generating indices such as heat maps and viewing durations for areas of interest. Results indicate: 1) learners' attention was evenly distributed across the four concept elements – name, definition, attribute, and example; 2) highlighted content (e.g., in red) drew more attention; 3) no significant differences were found in eye movement behaviours between high- and low-performing students; 4) no gender-based differences were observed in fixation times. These findings provide empirical insights into video lecture design, suggesting that emphasising key content visually may enhance learners' attention without necessarily affecting performance outcomes. Keywords: video lecture; conceptual knowledge learning; eye movement behaviour; cognitive processing; influencing factor. DOI: 10.1504/IJCEELL.2025.10071949 Special Issue on: Smart Education in the Digital Society
![]() by Quanzhong Yang, Yu Zhang, Xiaoli Li, Feifei Shen, Xiaoyin Wang, Ruili Zhang, Yongwei Chen Abstract: To improve the hit rate of personalised learning resource recommendations, this paper proposes a knowledge graph-based personalised recommendation method for online learning resources in blended learning. First, user browsing data on online learning resources is collected through web crawlers to construct a knowledge graph. Then, the self-organising map network and K-means clustering algorithm are used to cluster the learning resource content, while graph neural networks calculate the similarity between users and resources. Finally, the users rating for recommended resources is predicted, and a time-weighted strategy is introduced to dynamically adjust the ratings, completing the recommendation based on the rating results. Experimental results show that this method consistently maintains a hit rate above 95%, achieves a minimum normalised discounted cumulative gain of 0.92, and reaches a maximum entropy value of 0.75. Keywords: blended learning; online learning resources; resource recommendation; knowledge graph; self-organising mapping network; K-clustering algorithm. DOI: 10.1504/IJCEELL.2025.10072393 |