Titlebook: User Modeling, Adaptation and Personalization; 23rd International C Francesco Ricci,Kalina Bontcheva,Séamus Lawless Conference proceedings

人類的發(fā)源

使困惑

Diagrammatic Student Models: Modeling Student Drawing Performance with Deep Learninghitecture, to reason about sequences of student drawing actions encoded with temporal and topological features. An evaluation of the deep-learning-based diagrammatic student models suggests that it can predict student performance more accurately and earlier than competitive baseline approaches.

Mawkish

Exploring the Potential of User Modeling Based on Mind Mapsld be valuable for user-modeling and recommender systems. In this paper, we explored the effectiveness of standard user-modeling approaches applied to mind maps. Additionally, we develop novel user modeling approaches that consider the unique characteristics of mind maps. The approaches are applied

glans-penis

Modeling Motivation in a Social Network Game Using Player-Centric Traits and Personality Traitsor persona allows game designers to personalize game content; however, there are many ways to characterize players and little guidance on which approaches best model player behavior and preference. To provide knowledge about how player characteristics contribute to game experience, we investigate ho

Between

溫和女孩

The Value of Social: Comparing Open Student Modeling and Open Social Student Modelingnown for its ability to increase student engagement, motivation, and knowledge reflection. A recent extension of OSM known as Open Social Student Modeling (OSSM) attempts to enhance cognitive aspects of OSM with social aspects by allowing students to explore models of peer students or the whole clas

Myelin

integral

Context-Aware User Modeling Strategies for Journey Plan Recommendationext-aware recommendation technologies in an existing journey planning mobile application to provide personalized and context-dependent recommendations to users. We describe two different strategies for context-aware user modeling in the journey planning domain. We present an extensive performance co

同位素

quiet-sleep

Dynamic Approaches to Modeling Student Affect and its Changing Role in Learning and Performancey-moment estimates of students’ affective states derived from a series of affect detectors accompany each student response within the tutoring system. By applying a series modified factorial hidden Markov models that account for students’ affective state at the time of the given response and compari