Forthcoming and Online First Articles

International Journal of Continuing Engineering Education and Life-Long Learning

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

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 Articles will not be published until the final proofs are validated by their authors.

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International Journal of Continuing Engineering Education and Life-Long Learning (3 papers in press)

Regular Issues

  • Semiotics in engineering education for enhancing communication awareness   Order a copy of this article
    by José Luis Díaz Palencia, Yanko Ordonez Ontiveros, Julian Roa Gonzalez 
    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
     
  • Based on the S-O-R model - how does interaction influence engineering students’ English learning continuance on online platform   Order a copy of this article
    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
     
  • Advanced ideological and political education strategy based on artificial intelligence: edge computing method   Order a copy of this article
    by Yue Zheng 
    Abstract: Currently advanced ideological and political education has developed rapidly. Based on transfer learning, deep neural network and edge computing, this paper analyzes 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 the identification of advanced ideological and political education, and 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