Algorithmic affordances are defined as user interaction mechanisms that allow users tangible control over AI algorithms, such as recommender systems. Designing such algorithmic affordances, including assessing their impact, is not straightforward and practitioners state that they lack resources to design …

This exploratory study investigates the rationale behind categorizing algorithmic controls, or algorithmic affordances, in the graphical user interfaces (GUIs) of recommender systems. Seven professionals from industry and academia took part in an open card sorting activity to analyze 45 cards with examples …

In flexible education, recommender systems that support course selection, are considered a viable means to help students in making informed course selections, especially where curricula offer greater flexibility. However, these recommender systems present both potential benefits and looming risks, such …

Recommender systems are widely used in today’s society, but many of them do not meet users’ needs and therefore fail to reach their full potential. Without careful consideration, such systems can interfere with the natural decision-making process, resulting in the disregard for recommendations provided. …

Recommenders play a significant role in our daily lives, making decisions for users on a regular basis. Their widespread adoption necessitates a thorough examination of how users interact with recommenders and the algorithms that drive them. An important form of interaction in these systems are algorithmic …

Social networks and news outlets use recommender systems to distribute information and suggest news to their users. These algorithms are an attractive solution to deal with the massive amount of content on the web [6]. However, some organisations prioritise retention and maximisation of the number of …

We extend a standard for doing agile scrum teamwork in education that permits individual assessment within teams (IAFOR ECE2020). Since the teacher's bandwidth in education is limited and increasingly under pressure, we focus on course design options that can be used to leverage the bandwidth. One economizing …

Social networks and news outlets entrust content curation to specialised algorithms from the broad family of recommender systems. Companies attempt to increase engagement by connecting users with ideas they are more likely to agree with. Eli Pariser, the author of the term filter bubble, suggested that …

Recommendation systems, recommenders in short, selecting and filtering content are widely used by companies in order to provide suggestions for items to users. These ‘items’ range from songs (e.g., Spotify), series (e.g., Netflix), and movies (e.g., YouTube) to messages (e.g., Facebook), job vacancies …

FD Mediagroep (FDMG1 ) is the leading information provider in the financial economic domain in the Netherlands. FDMG operates “Het Financieele Dagblad” (FD) a daily finan- cial newspaper, similar to the Financial Times. In addition, FDMG operates the daily all-news radio station “Business News Radio” …