Connective massive open online courses (MOOC) for teachers from Ukraine and Russia were conducted in 2011-2013. They were: Strategy of Distance Learning in the Organization, Social Services in Distance Learning, Distance Learning from A to Z, Designing Online Courses. The accumulated experience allowed to develop recommendations for each ADDIE step of MOOC designing for the Russian-speaking aud...

Massive open online courses (MOOC) describe platforms where users with completely different backgrounds subscribe to various courses on offer. MOOC forums and discussion boards offer learners a medium to communicate with each other and maximize their learning outcomes. However, oftentimes learners are hesitant to approach each other for different reasons (being shy, don’t know the right match, ...

cold start is one of the main challenges in recommender systems. solving sparsechallenge of cold start users is hard. more cold start users and items are new. sine many general methods for recommender systems has over fittingon cold start users and items, so recommendation to new users and items is important and hard duty. in this work to overcome sparse problem, we present a new method for rec...

Article history: Received March 29, 2011 Received in Revised form June, 18, 2011 Accepted 19 June 2011 Available online 20 June 2011 Recommender systems are tools for realization one to one marketing. Recommender systems are systems, which attract, retain, and develop customers. Recommender systems use several ways to make recommendations. Two ways are using more than the others: collaborative ...

Recently, the worldwide COVID-19 pandemic has led to an increasing demand for online education platforms. However, it is challenging correctly choose course content from among many resources due differences in users’ knowledge structures. Therefore, a recommender system essential role of improving learning efficiency users. At present, platforms have built diverse systems that utilize tradition...

Recommender System is a process or model that can be applied to identify the user choice based on some statistical observations. In this work, A movie recommender system is defined using cluster cluster adaptive genetic approach. In first phase of this model, the clustering is applied on user dataset to identify the most similar users. Later on, the statistical analysis is applied to generate t...

Recommender systems provide personalized suggestions by processing user and item information interactions. Personalized product recommendations make it easier for users to access products that interest them. Course recommendation systems, on the other hand, aim guide students fields of in which they can succeed. On e-learning sites, there are many courses from different fields. Also, select tha...