Traditionally, machine learning algorithms relied on reliable labels from experts to build
predictions. More recently however, algorithms have been receiving data from the general …

This study defines and analyses adaptive gamification design principles for online courses.
It was conducted as a holistic single case study framed by two theoretical approaches …

From e-commerce to e-learning, recommendation systems have given birth to an important
and thriving research niche and have been deployed in a variety of application areas over …

The information on the web is ever increasing and it is becoming difficult for students to find
appropriate information or relevant learning material to satisfy their needs. Technology …

Educational Data Mining (EDM) is a research field that focuses on extracting valuable
insights and knowledge from data in the education sector. EDM exploits Data Mining (DM) …

In this paper, we propose a framework for building automatic recommendations of answers
in MOOCs' Discussion Forums. The general aim of this research is to contribute to …

Recommender systems (RSs) use information filtering to recommend information of interest
(to a user). Similarly, personalisation can be adopted for recommendations in e-market. We …

Early supervised machine learning algorithms have relied on reliable expert labels to build
predictive models. However, the gates of data generation have recently been opened to a …

Bu araştırma, çevrimiçi dersler için uyarlanabilirliğe dayalı oyunlaştırma tasarımı ilkelerinin
belirlenmesini amaçlamaktadır. Bu amaç doğrultusunda araştırmaya oyunlaştırma ve …

To address the diversity of user preferences and dynamic changes of interests in the
personalized recommendation scenario, a personalized recommendation model based on …