L
Lennart E. Nacke
Researcher at University of Waterloo
Publications - 228
Citations - 16483
Lennart E. Nacke is an academic researcher from University of Waterloo. The author has contributed to research in topics: Game design & Game mechanics. The author has an hindex of 44, co-authored 207 publications receiving 13729 citations. Previous affiliations of Lennart E. Nacke include University of Saskatchewan & Information Technology University.
Papers
More filters
Proceedings ArticleDOI
Games user research: practice, methods, and applications
TL;DR: This workshop is investigating different methodologies currently used in practice in Games User Research, highlighting benefits and drawbacks in assessing game design issues hoping to gain insights into player experience.
Proceedings Article
Guided emotional state regulation: understanding and shaping players' affective experiences in digital games
TL;DR: A framework for modulating player emotions and the main components involved in regulating players' affective experience is proposed and described, which will allow game designers to focus on defining high-level rules for generating gameplay experiences instead of having to create and test different content for each player type.
Proceedings ArticleDOI
The edge of glory: the relationship between metacritic scores and player experience
TL;DR: In this article, the authors examined how measures of player experience used in videogame research relate to Metacritic Professional and User scores, and found that the professional and users appear to allocate game ratings differently.
Proceedings ArticleDOI
"The Collecting Itself Feels Good": Towards Collection Interfaces for Digital Game Objects
TL;DR: This work investigates players' collecting behaviors in digital games to determine what digital game objects players enjoyed collecting and why they valued these objects, and identifies design implications for digital game object collection interfaces.
Proceedings ArticleDOI
A Hybrid Approach at Emotional State Detection: Merging Theoretical Models of Emotion with Data-Driven Statistical Classifiers
TL;DR: In this article, a two-layer classification process was employed to detect Arousal and Valence (the emotion's hedonic component), based on four psycho physiological metrics: Skin Conductance, Heart Rate and Electromyography measured at the corrugator supercilii and zygomaticus major muscles.