The use of AI for Education in Third Age: the role of EU project

Geopolitical, Social Security and Freedom Journal, Volume 7, Issue 1, 2024 49 The use of AI for Education in Third Age: the role of EU project Diana Spulber University of Genoa, Italy – e-mail: [email protected] Guido Amoretti University of Genoa, Italy – e-mail: [email protected] Anna Siri Pegaso Telematic University, Naples, Italy – e-mail: [email protected] Doi: 10.2478/gssfj-2024-0004 Abstract Society today is struggling with various challenging phenomena. This manuscript aims to analyse two phenomena, ageing and digitalisation, in the context of education. Both phenomena are an important area of research: the complexity of an ageing population and the intersection of technology and education. In this context, artificial intelligence (AI) offers the opportunity to improve the educational experiences of older adults. AI-driven tools and educational initiatives can be tailored to the different learning preferences and cognitive abilities of this population, promoting engagement and knowledge retention. The adaptability of AI systems enables personalised learning pathways that address individual challenges and promote lifelong learning and cognitive health in older learners. This research will highlight the critical role of AI in reshaping educational paradigms and its potential to facilitate knowledge acquisition and empower an often-marginalised population. Finally, focusing on the role of international projects will allow us to understand the trends in EU research and funding. Understanding the impact of AI on education in the third age and EU funding invites a broader discussion on inclusivity and innovation in the educational landscape. Keywords: third Age education, Third Age Inclusion, AI, EU projects 1. Introduction The third age is characterised by a renewed time-out from work, a phase of frailty and, in the meantime, an increase in "free time" that can be used for leisure and opportunities for personal development. Technology is increasingly finding its way into daily life. The intersection of artificial intelligence (AI) and ageing populations cannot be overstated. It is important to examine how artificial intelligence (AI) affects older populations. Studies show that older adults' past experiences with technology significantly shape their views on information and communication technology (ICT). Those who are more engaged with technology tend to have more confidence and a better attitude towards new tools (González et al., 2012). If we understand the specific problems of this age group, such as mental decline and loneliness, we can develop AI solutions that improve social interaction and mental engagement. Research shows that technical training can promote cognitive and emotional health (Shapira et al., 2007). This knowledge is key to developing user-friendly interfaces and apps that meet the specific needs of older people. It is particularly important for education, as it provides older adults with the opportunity to continue learning and adapting to new technologies. The use of technology, such as AI learning tools, Geopolitical, Social Security and Freedom Journal, Volume 7, Issue 1, 2024 50 is very important in this context as it helps to overcome the difficulties older people have in using technology. Studies show that older adults benefit from educational activities that promote social relationships and emotional health, which emphasises the value of intergenerational learning in the third age (Barroso et al., 2022). In addition, knowledge of how older people view and use AI tools can help teachers create learning experiences that work well for them and are easily accessible to enhance education for older learners (Koka, 2024). Focusing on this connection drives innovation and ensures that technological advances adequately support older adults by improving their independence and quality of life and reducing risks associated with falling behind in technology. AI technologies enhance personalised learning experiences through adaptive learning platforms that tailor educational content to individual needs, promoting an inclusive environment. These platforms utilise data analytics to assess learner progress, allowing for immediate feedback and targeted interventions, which is crucial for older adults who often face particular learning challenges (Kyung et al., 2020). In addition, AI-powered tools facilitate social interaction and engagement through virtual classrooms and discussion forums, combating the isolation that older people often experience. The integration of AI into educational practise emphasises the importance of policy frameworks that support equal access to technology, especially for marginalised groups. For example, initiatives that promote the development and funding of age-appropriate educational programmes are crucial to ensure that AI technologies are accessible and beneficial to all, including those in the third age (Alexin et al., 2021). 2. AI in Third Age Education The integration of Artificial Intelligence (AI) into educational initiatives for older adults can enhance learning experiences by creating individualised and engaging environments that meet their needs. AI technologies can enable personalised learning pathways that adapt to the cognitive abilities, learning pace and interests of each participant, creating inclusive educational opportunities. In addition, immersive technologies such as augmented and virtual reality can stimulate cognitive engagement and sensory experiences, counteracting the cognitive decline that often accompanies ageing (Lee et al., 2019; Schlomann et la, 2024). As demonstrated in interprofessional simulation courses, improved collaboration through AI-driven platforms also promotes effective communication and empathy among learners, reflecting a shift towards integrated models of care (Baillie et al., 2017). Through the use of AI, educational programmes can enrich the learning landscape for older adults and bridge the gap between traditional educational practises and modern, interactive methods. Education and training are crucial for older adults' attitudes towards artificial intelligence (AI) and influence their perception of its relevance and usability in everyday life. Programmes to improve digital literacy are crucial. They provide practical skills and promote confidence in the use of new technologies, as shown by Geopolitical, Social Security and Freedom Journal, Volume 7, Issue 1, 2024 51 studies in which improved ICT education led to higher life satisfaction among participants (Shapira et al., 2007). By addressing educational deficits, older adults can better understand the benefits of AI and thus reduce fears based on ignorance or misconceptions about technology. As the results of a course on tele-services for older people show, previous experience with technology correlates positively with openness to AI applications, emphasising the need for targeted training that addresses the specific motivations of older learners. Fostering a supportive learning environment that emphasises the accessibility of AI can mitigate resistance and promote an adaptive mindset in older adults. 3. AI in Third Age and Inclusivity The integration of artificial intelligence (AI) technologies into the lives of older people has a significant impact on improving their quality of life and general wellbeing. By facilitating social contact and providing personalised health information, AI can alleviate loneliness and promote a sense of belonging among seniors. Research has shown that the use of ICT can promote independence. Older adults use technology for practical communication, health monitoring and social engagement, as shown by (Kerryellen et al. et al., 2014). In addition, AI-driven applications can tailor content and services to individual needs, improve usability and reduce barriers to technology use. For example, users who participate in technology training report increased self-confidence and social activity, which emphasises the role of AI in empowering seniors, as mentioned in (Xu et al. 2024, Peral, 2021). The ability of AI technologies to adapt to the specific preferences and abilities of older adults will be critical to bridging the digital divide and ensuring their continued engagement in a technology-driven society. Recent advances in artificial intelligence (AI) technology have the potential to significantly improve social connectivity for older adults and address the pervasive problem of isolation in this population. AI-driven platforms can provide userfriendly communication tools that enable seniors to engage more actively with their family and friends, which is crucial for their mental health and well-being, as emphasised in (Shapira et al., 2007). In addition, AI applications, such as smart health monitoring systems, have been shown to help older people maintain vital relationships by facilitating the exchange of health information and coordination of care between family members, alleviating feelings of dependency and loneliness (Kerryellen et al. et al., 2014). By tailoring content to individual preferences and learning abilities, these technologies can engage seniors more effectively, making technology feel less like a luxury and more like a necessity in daily life. Consequently, fostering meaningful interactions through AI promotes social engagement and empowers older adults to better navigate the digital world (Selwyn, 2004). In the wake of technological change, the use of artificial intelligence (AI) in communication tools offers good opportunities to improve the engagement of older people. Many seniors struggle with traditional communication tools because they are difficult to use, leaving them feeling isolated and disconnected. AI can help solve Geopolitical, Social Security and Freedom Journal, Volume 7, Issue 1, 2024 52 these problems by creating more user-friendly interfaces and more personalised experiences. For example, AI technologies such as speech recognition and natural language processing can help older users interact with smart devices and reduce the anxiety often associated with using technology (Kerryellen et al., 2014). Furthermore, studies show that improving digital skills through organised training can significantly change older people's attitudes and behaviour when using technology (Chattaraman et al. 2019). Therefore, if we focus on developing AI applications that meet the needs and preferences of older adults, we can promote more social engagement and a better quality of life through technology-enabled communication. The potential of artificial intelligence (AI) to combat social isolation and loneliness in older adults is becoming increasingly clear in current research. By facilitating social interactions and improving communication, AI applications, such as virtual assistants and social robots, provide valuable companionship and engagement for seniors who often struggle with mobility limitations or limited access to social networks. The findings of (Shapira et al., 2007) show that structured computer training increases older people's confidence in using technology and leads to greater social connectedness via online platforms. Furthermore, the integration of AI into telemedicine solutions enables timely access to healthcare services, allowing older adults to maintain their independence while reducing feelings of loneliness associated with health-related anxiety. As (Kerryellen et al., 2014) has shown, ongoing support and the establishment of user-friendly interfaces can ensure sustained engagement with technology and ultimately create a vital ecosystem that fosters social connections and improves seniors' quality of life. This multi-faceted approach highlights the transformative ability of AI to alleviate loneliness. It suggests that customised technological solutions can significantly enrich the social experiences of older adults, addressing a major public health issue. 4. AI for inclusive education in the third age The integration of AI-driven personalised learning pathways can significantly improve the educational experiences of the third age and promote lifelong learning and personal growth. Inclusive education for the elderly is receiving a lot of attention as societies struggle with a growing ageing population. A closer look shows that old education systems often fail to meet the diverse needs of older students. There is a need to turn to new methods, including the use of artificial intelligence (AI). Knox, Wang and Gallagher's (Knox et al., 2019) review of the role of AI in promoting inclusive practises highlights its ability to customise learning. However, they also warn that over-reliance on personalised help can lead to exclusion. Furthermore, programmes such as the Newcastle University Ageing Generations Education (NUAGE) demonstrate successful ways to engage different generations and enhance the learning experience for older adults and younger learners (Forster et al., 2021). Geopolitical, Social Security and Freedom Journal, Volume 7, Issue 1, 2024 53 As mentioned in (Forster et al., 2021), programmes that mix generations, such as Newcastle University’s Ageing Generations Education initiative, show how effective personalised methods can be. They show that older participants can improve course development while increasing younger learners' confidence in their interactions. Furthermore, the issues highlighted in (Jeremy Knox et al., 2019) in finding a balance between AI-driven personalised learning and social aspects of education highlight the need for a comprehensive approach. By focusing on understanding and group learning, AI can help to bridge the generation gap and ensure that educational programmes effectively engage older adults and create a sense of belonging and community for all learners (Du et al 2024; Cacico et al 2023). Researchers point out that while AI can improve the outcomes of personalised learning, it should work with community engagement and collaborative efforts to ensure that these technologies fit into the everyday lives of older students (Knox et al., 2019). The use of AI technologies to educate older adults highlights important systemic issues and ethical questions that need to be explored to ensure fairness and access. One major issue is the digital divide, where many older learners struggle with technological skills, exacerbated by differences in income levels. This divide raises the question of how AI resources are distributed equitably and whether they are able to support inclusive education, as Ferguson's research on inclusive practises shows (Forster et al., 2021). Furthermore, as Knox, Wang and Gallagher mention, the use of AI for personalisation often ignores the importance of group participation, which is central to building community and ensuring that older adults feel valued and included in educational discussions (Knox et al., 2019). The conversations about AIEd show that there is often a mismatch between technology-based methods and the community goals stated in (Knox et al., 2019). This mismatch raises important questions about inclusivity and the need for genuine social connections between learners. The application of adaptive learning technologies is fundamentally changing the educational landscape for older adults, placing an emphasis on personalised engagement. Through the use of artificial intelligence, these technologies can tailor learning experiences to individual needs, enabling deeper interaction with learning content. Research shows that adaptive systems significantly increase motivation and retention rates, leading to more meaningful learning experiences. For example, technologies used in the creative arts have improved the cognitive abilities and behaviours of people with dementia through tailored interventions (Harwood et al., 2019). This adaptive approach promotes intellectual engagement and social relationships between learners and enables collaborative experiences that enrich understanding. In addition, immersive environments, such as those being developed for museums, are an example of how interactive storytelling and digital avatars can engage older learners and make knowledge acquisition an engaging and empowering process. Adaptive learning technologies offer profound opportunities to revitalise education for the ageing population and promote lifelong learning and engagement. Geopolitical, Social Security and Freedom Journal, Volume 7, Issue 1, 2024 54 It is important to pursue a balanced strategy that combines technological advancement with community and ethical engagement. This will help ensure that education systems are truly inclusive, especially for older adults. To move forward, targeted efforts are needed to promote empathy, trust and active participation in creating educational structures that meet the diverse needs of learners. The use of artificial intelligence (AI) in inclusive education for older adults has both useful benefits and serious difficulties. On the one hand, AI can enable personalised learning experiences that help learners to engage and adapt learning materials, which is crucial for older students with different learning styles. This is supported by the findings of (Knox et al., 2019) highlighting the role of AI in enhancing personalised education. However, over-reliance on technology could compromise the important human bonds that create effective learning spaces. As (Forster et al., 2021) highlights, building relationships and trust is key to intergenerational teaching; therefore, it is important to embrace the social aspects of learning. 5. Method The aim of the study is to find out whether there is a funding project on the topics of AI and education in the third age. The sample was selected using the CORDIS portal for Horizon project results. This platform allows us to search for funded projects, including those with the prospect of funding. The platform makes it possible to clean up the results by inserting various philtres, as shown in Figure 1. The philtres on the CORDIS platform are different and offer the possibility to filter the project by content: Collection: here you can select different options: Projects, Results Packages, Project Info Packages, Results in Brief, News, Podcasts. Area of application: You can select various options here: Industrial technologies, basic research, transport and mobility, health, society, security, climate change and environment. Language: here you can select different languages for the selected results: Deutsch, English, Español, Français, Italiano, and Polski. Programme: here you can select the different funded programmes: Horizon Europe Framework Programme, Horizon 2020 Framework Programme, FP7 Framework Programme, FP6 Framework Programme, FP5 Framework Programme, FP4 Framework Programme, and FP3 Framework Programme. This step is important because with this filter it is possible to divide a project by year, as each programme applies to a different period: FP4 for the period 1994-1998, FP5 for the period 19982002, FP6 for the period 2002-2006, FP7 for the period 2007-2013, FP8/Horizon 2020 for the period 2014-2020, FP9/Horizon Europe for the period 2021-2027 Last update: This filter allows you to select the period from which you want to make the result more accurate. Project ID acronym: This filter is used if the name of the project to be searched for is known Geopolitical, Social Security and Freedom Journal, Volume 7, Issue 1, 2024 55 Scientific field: You can select various options here: Agricultural Sciences, Engineering and Technology, Humanities, Medicine and Health Sciences, Natural Sciences, Social Sciences. Start/end date Here you can select a period in which the project started or in which the project ended. Total cost: This filter allows you to select a project according to the total cost of the project (EU funding + co-financing) EU contribution: with this filter it is possible to select a project according to the funding received from the EU by specifying the sum from Euro to Euro. Cal ID: this filter allows you to select a project that has been selected as part of a specific call. Topic ID: this filter allows you to select a project selected under a specific topic. Organisation characteristics: 3 Filter Organisation name, Organisation country, Organisation region. Figure 1: CORDISS search platform The selection of the sample was carried out in various steps: 1. Keywords ‘AI and Ageing’ - 1315 results were obtained by using the Boolean operator AND 2. Adding the keyword ‘education’, ‘AI and Ageing and Education’ - 864 results were obtained. Considering the purpose of the research, the filter collection was used by selecting Projects, Results Packs, Projects Info Packs, and Results in Brief - 773 cases were obtained. Another filter was the domain of the application. The project domains Transport and Mobility, Climate Change and Environment and Industrial Technologies were excluded. This reduced the sample to 123 projects. By using the science domain filter, the projects on natural sciences and agricultural sciences were excluded - the sample was reduced to 18 cases. As the CORDISS search platform does not offer the option of using the Boolean term “or” for search accuracy, a new level of keywords was implemented. Keywords “AI and older*” - 197 results were obtained Geopolitical, Social Security and Freedom Journal, Volume 7, Issue 1, 2024 56 By adding the keyword education, the sample was reduced to 87 results. By using the same philtres as for the application area and research area, the sample was reduced to 5 results. Once the projects are selected, each one is analysed. Fourteen projects were excluded as they did not match the characteristics of the sample. The research results of the European project proposal were analysed using the qualitative approach. Text analysis is the process of examining textual material to capture key concepts and themes and uncover hidden relationships and trends without needing to know the exact words and terms used by the authors to formulate these concepts. Voyant tool was developed by two professors Stefan Sinclair and Geoffrey Rockwell. Voyant tool is for the analysis of digitally recorded texts and it is an s open -source online platform the analysis of digitally recorded text that can be used for free As can be seen in Figure 2, the most frequently used words in the project objectives are "care" and "health". Figure 2 Cloud with the most frequently used words (Voyant tool image) Geopolitical, Social Security and Freedom Journal, Volume 7, Issue 1, 2024 57 Figure 3 Trends on words use Figure 4 Links with other words The placement diagram shows a network diagram of the words that occur most frequently in the vicinity of a particular word. Keywords are shown in blue and nearby words in orange. Figure 4 shows the links between the words. “Care” is mostly linked to service, support, professionals, digital and people. The word health is mainly linked to care, social solution services and professionals. The word data is linked to fusion, interoperability, extensive use and data protection. The peripheral Geopolitical, Social Security and Freedom Journal, Volume 7, Issue 1, 2024 64 pp. 3923:1–3923:19https://doi.org/10.3390/ijerph18083923 Maarup, M., Dohan, M., Zhao, W., Wu, S. (2019). "Radical Technological Innovation and Perception: A Non-Physician Practitioners’ Perspective" (2019). 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