ProMe: A Mentoring Platform for Older Adults Using Machine Learning Techniques for Supporting the “Live and Learn” Concept

Kostopoulos, Giorgos; Neureiter, Katja; Papatoiu, Dragos; Tscheligi, Manfred; Chrysoulas, Christos

Abstract

It is well known what an important role employment plays in our lives and how it influences our everyday life. With the help of employment, all of us as individuals manage to create our personal and social net that not only gives meaning and financial security but also heavily affects our social status, contributes to self-esteem, and plays a vital role on the way our social relationships at work and (not only) are formed. Being work active even after the retirement time has been found to have mostly useful and positive effects. Age groups that are in the after retirement age group (65 and more) and keep working can significantly improve their mental health since they feel that there are still things to offer to others. ProMe aims to provide a unique framework for the people being in this transitional phase of their life, from work to retirement, thus playing a vital role in supporting their mental health and well-being. ProMe provides a platform for the younger generation to benefit from the accumulated professional and formal knowledge and experience of the older. In this way, ProMe supports professional intergenerational cooperation and mentoring, bringing together older adults with younger generations.

Citation

Kostopoulos, G., Neureiter, K., Papatoiu, D., Tscheligi, M., & Chrysoulas, C. (2018). ProMe: A Mentoring Platform for Older Adults Using Machine Learning Techniques for Supporting the “Live and Learn” Concept. Mobile Information Systems, 2018, 1-8. https://doi.org/10.1155/2018/9723268

• Journal Article Type: Article
• Acceptance Date: Nov 11, 2018
• Publication Date: Dec 2, 2018
• Deposit Date: Feb 7, 2020
• Publicly Available Date: Feb 17, 2020
• Journal: Mobile Information Systems
• Print ISSN: 1574-017X
• Publisher: Hindawi
• Peer Reviewed: Peer Reviewed
• Volume: 2018
• Pages: 1-8
• DOI: https://doi.org/10.1155/2018/9723268
• Keywords: Computer Networks and Communications; Computer Science Applications
• Public URL: http://researchrepository.napier.ac.uk/Output/2543052