International Journal of Continuing Engineering Education and Life-Long Learning (11 papers in press)

Special Issue on: Smart and Continuing Education and Life Long Learning

• Open Access

  Research on Interactive Audio-visual-oral Teaching in College English ( Free Full-text Access )

  by Haixia Yin, Liming Wang 
  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 today’s information age, English has become the first language of choice for data transmission between regions. To some extent, it also means that in today’s 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
   
  

• Open Access

  Multimedia-based evaluation on the intelligent distance education mode of college English ( Free Full-text Access )

  by Jia Song, Zhiguo Feng 
  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
   
  

• Open Access

  Indicators and characteristics of career visualisation ability based on cloud computing ( Free Full-text Access )

  by Zhen Zhang, Guixin Luo, Min Zhang 
  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
   
  

• Open Access

  Journalism and communication professional personnel training and precise teaching methods based on artificial intelligence ( Free Full-text Access )

  by Xuhui Zhu, Ziwen Wang 
  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
   
  

• Open Access

  The interrelationship of behavioural, emotional, and cognitive classroom engagement in higher education: understanding the mechanisms of student success ( Free Full-text Access )

  by Jin Yan, Linxi Shi, Choon Keong Tan 
  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
   
  

Regular Issues

• Based on the S-O-R model – how does interaction influence engineering students' English learning continuance on online platforms  
  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

• Personalized recommendation method for online learning resources in blended learning based on knowledge graph  
  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