Title: Personalised recommendation model for senior learning: a case study of Thai seniors to enhance social network skills

Authors: Kanchana Boontasri; Punnarumol Temdee

Addresses: School of Information Technology, Mae Fah Luang University, Chiang Rai, Thailand ' Computer and Communication Engineering for Capacity Building Research Center, School of Information Technology, Mae Fah Luang University, Chiang Rai, Thailand

Abstract: To promote senior learning, this study proposes a personalised recommendation model using the combination of performance, preference, and physical condition factors of the learners, namely the 3P personalised recommendation model. Presented in the set of pre-defined rules, it consists of learning object selection and content presentation. A total of 68 Thai seniors aged between 60 and 83 years old from senior school participated in the case study for enhancing social media skills, how to use LINE application, on electronic learning platform. The learners were required to complete all learning objects with flexible learning paces. The recommendation was given to everyone individually after having each test in a learning object. The proposed model was evaluated in learning enhancement ability and learner satisfaction. The result revealed that the recommendation provided by the proposed model could effectively enhance learning efficiency of seniors. Also, the proposed model obtained satisfaction at the 'very satisfied' level.

Keywords: senior learning; recommendation; personalised learning; social network skill.

DOI: 10.1504/IJIL.2022.126637

International Journal of Innovation and Learning, 2022 Vol.32 No.4, pp.435 - 455

Received: 26 Jun 2021
Accepted: 27 Nov 2021
Published online: 31 Oct 2022 *

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