Article: Career planning and pathway generation based on multimodal learning analytics Journal: International Journal of Information and Communication Technology (IJICT) 2025 Vol.26 No.29 pp.39 - 58 Abstract: Concerning the growing complexity of the business environment and career growth, conventional career planning strategies have become challenging to satisfy personal needs. This paper suggests a new career planning and path generating model based on multimodal learning technology, which integrates data from many sources (e.g., educational background, work experience, social networks, emotional data, etc.) so giving individuals more personalised and accurate advice. First, by preprocessing the data with feature fusion, the study creates tailored career path recommendations by building an adaptive model architecture combining deep learning and data mining approaches. In the experimental phase, the results reveal that the model has major benefits in terms of recommendation accuracy, personalisation and flexibility, and offers a fresh technical path for the field of career planning by means of the validation of the parameter tuning of the model and the effect of career path recommendation. Inderscience Publishers - linking academia, business and industry through research

Title: Career planning and pathway generation based on multimodal learning analytics

Authors: Wenqing Liu

Addresses: Logistics Management Office, Wuxi Institute of Technology, Wuxi 214121, China

Abstract: Concerning the growing complexity of the business environment and career growth, conventional career planning strategies have become challenging to satisfy personal needs. This paper suggests a new career planning and path generating model based on multimodal learning technology, which integrates data from many sources (e.g., educational background, work experience, social networks, emotional data, etc.) so giving individuals more personalised and accurate advice. First, by preprocessing the data with feature fusion, the study creates tailored career path recommendations by building an adaptive model architecture combining deep learning and data mining approaches. In the experimental phase, the results reveal that the model has major benefits in terms of recommendation accuracy, personalisation and flexibility, and offers a fresh technical path for the field of career planning by means of the validation of the parameter tuning of the model and the effect of career path recommendation.

Keywords: multimodal learning; career planning; path generation; personalised recommendation; data fusion.

DOI: 10.1504/IJICT.2025.147880

International Journal of Information and Communication Technology, 2025 Vol.26 No.29, pp.39 - 58

Received: 16 May 2025
Accepted: 29 May 2025
Published online: 05 Aug 2025 *

Title: Career planning and pathway generation based on multimodal learning analytics

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