## 6 Discussion  
As illustrated in Section 4, both skill and course recommendations as well as recommended curriculum updates are very meaningful for users. Specifically, course and skill recommendations help learners ensure that the skills they are being taught are both valuable for the labor market and compatible with their current profile. Without using this service, they would spend several days to draw valuable inferences regarding the labor market requirements, while their analysis would not be built on a sufficiently large data sample, and therefore, it might not be as accurate as the results of the Skill and Course Recommendation service. Of course, in case users need more information about specific specializations in the job market, they can conduct their own analyses, since the objective of the Skill and Course Recommendation service is to provide a generic overview of the labor market and be used as an advisor. These objectives are greatly achieved, according to the opinions of the early users of the service. Concerning comparison with other course recommendation services from the literature, the results of this study are not directly comparable. This is because this study is based on real-life data from the Greek labor market, and at the time of authoring this publication, only a limited number of users were using the platform, and their reactions to the recommendations were not tracked. For instance, in [39], [PERSON] et al. developed a personalized course recommender system based on a hybrid approach, which performs well in comparison with other similar services. The performance value they use is accuracy of recommendations as the ratio between the number of relevant courses proposed and the total number of courses proposed. For this publication, information on the relevance of a specific recommendation to a user's preferences is not available. However, according to the questionnaire in Figure 15, the recommended courses are very relevant with the users' preferences, as well as compatible with the requirements of the job market. On the other hand, [PERSON] et al. [40] evaluated their course recommender system in terms of precision (the ratio between the number of recommended course taken by students and the number of recommended courses) and recall (the ratio between the number of recommended course taken by students and the number of courses taken by students), with satisfactory results. However, such information requires either a big user base, or monitoring users for a long period, in order to draw significant conclusions about the courses taken by the students. For similar reasons the results of our study are not comparable with the results in [41]. Specifically, the authors evaluate their system in terms of hit ratio (HR) and normalized discounted cumulative gain (NDCG). Similarly, due  
Figure 17: MCDSS service evaluation. to lack of information of specific user reactions to the provided recommendations, we cannot calculate these evaluation metrics. Hence, the evaluation of the presented services using precision, recall, NDCG, and HR is intended to be performed in future extensions of this work. Regarding the Curriculum Designer service, it helps educational institutions be aware in a few seconds whether there are skills in high demand by the job market that are not taught in the context of their curriculum. Moreover, educational institutions that use the Curriculum Designer are aware of new skills that are compatible with a course and can be introduced in its syllabus. The use of this service can also save a lot of time for education institutions' decision makers, as updating a school's curriculum is a crucial decision and, therefore, much more time-consuming than selecting a course. Furthermore, it helps higher education advance in parallel with the labor market. This is very important, since the labor market, especially in technology-related fields, is evolving more rapidly than ever, while educational institutions tend to advance at a very slow pace.