This article discusses Spotify’s approach to music recommendation as dataficationof listening. It discusses the hybrid types of music recommendation that Spotifypresents to users. The article explores how datafication is connected to Spotify’spush for the personalization and contextualization of music recommendationsbased on a combination of the cultural knowledge found in editorial curation andthe potential for large-scale personalization found in algorithmic curation. Thearticle draws on the concept of ubiquitous music and other understandings ofthe affective and functional aspects of music listening as an everyday practice toreflect upon how Spotify’s approach to datafication of listening potentially leads itto prioritize music recommendations that entice users to engage in inattentive andcontinuous listening. In extension to this, the article seeks to contribute with knowledgeabout how the datafication of listening potentially shapes listening practicesand conceptions of relevance and quality in music recommendation.
I denne artikel diskuterer vi, hvordan kvaliteten kan fremmes i studerendes arbejde med kommunikationsprodukter på universitetet. Først redegør vi for den universitetspædagogiske litteratur om kvalitets- og bedømmelseskriterier og peger på, hvordan denne primært beskæftiger sig med undervisning i og bedømmelse af akademiske opgaver. Vi argumenterer for, at kommunikationsprodukter ikke i samme grad som de akademiske opgaver har faste kvalitetskriterier, og at de studerende derfor først må lære at diskutere kvalitet og kvalitetskriterier i en konkret kommunikationssituation for derefter at kunne udarbejde et godt kommunikationsprodukt til denne. Med afsæt i de undervisnings- og bedømmelsespraksisser for kommunikationsprodukter, som vi selv har været en del af, foreslår vi et læringsdesign, der dels kan bruges til at stilladsere udviklingen og ekspliciteringen af kvalitetskriterier for kommunikationsprodukter i undervisningen, dels kan bruges til eksamen for at sikre en faglig og fair bedømmelse.
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