In Finland, both public and private organizations are actively applying information and communication technology (ICT) in adult education. Providing ICT-supported education, e-learning, requires focus on the virtual setting, but also on physical and human factors. Studying the e-learning phenomenon from a service perspective gives new insights into how to provide better learner satisfaction.The article presents a qualitative two-case study. The cases come from Finnish organizations: one case from a polytechnic and one case from a large company. The choice of cases gives an excellent opportunity to compare practices between public and private sector. The cases have been studied using participative case simulation, an action research method. This method enables gathering of rich data, since all key players from the real-life case gather together to share knowledge on a case that was realized in the near past. The researchers get to know how the case was executed in its reality, and not an ideal version about how it should have been realized.After analyzing these cases from a service process point of view, a framework of e-learning as service provisioning is presented in this article. This framework emphasizes the fact that e-learning is a mixture of physical and virtual servicing. The most important service element is the interaction between the learner and the tutor. The technology has not removed the importance of the human face; the role of a tutor is reshaping itself.

No abstract

As a result of the corona pandemic, lives both at workplaces and universities have changed. Working "from anywhere" and studying online have come to stay. The pandemic has also caused significant changes in the demand and supply of labour, there are industries where job losses are a problem, and there are industries where there is labour shortage or there is a need to acquire new skills quickly, some people are even looking for a new profession.Before the pandemic, in Finland, about 36% of the workforce was considering a change in career and a new profession. The corona pandemic added a special boost to these needs. One reason could be the lack of digital skills. According to a recently published study [1], half of the working population is lacking in digital skills and has difficulties with digital tools. This causes stress and burnout. The so-called "digital leap" and remote work have increased the need for learning new digital skills. As a result, there is an exceptionally high need for boosting skills, digital and others, in Finland. This is the need universities of applied sciences have recognized and responded to by collaborating with businesses and labour authorities to increase the amount and variety of continuous learning offering. This paper aims to describe a development project, where recommendation systems and AI together are used to guide in the selection of open studies. We have co-created a joint artificial intelligence powered digital environment which is conceived as an ecosystem -a matching tool consisting of our study offering and the need for skills and labour in the world of work. In the system, people who would like to upgrade their own skills and knowledge have an option of taking studies matching their needs from our universities of applied sciences.During the last decades, with the rise of Facebook, Amazon, Netflix and many other web services, recommendation systems have become omni-present. From e-commerce (suggesting to buyers products that could interest them) to online advertisement (suggesting to users the right contents, matching their preferences), recommendation systems are unavoidable in our daily online journeys. For a higher education institution (HEI) to use recommendation systems in marketing their learning offering, they should pause to think whether they serve customers, students, or both. This paper discusses ways of using recommendation systems in guiding people looking for upskilling and reskilling offering, and of using artificial intelligence to identify the skills needed in the world of work and meeting those needs in higher education institutions. This all, in effect, constitutes the first building blocks of a digital learning ecosystem. In this paper, we will present some ideas and practical experience. By using a combination of recommendation system and AI, our "webstore" is fast, ecological, economical, reachable, and student or customer centred. The initial findings of the project are promising but tuning the recommendation systems and study offerings to work op...