Learning and Games

Part of the Volume on the Ecology of Games: Connecting Youth, Games, and Learning In this chapter, I argue that good video games recruit good learning and that a game's design is inherently connected to designing good learning for players. I start with a perspective on learning now common in the Learning Sciences that argues that people primarily think and learn through experiences they have had, not through abstract calculations and generalizations. People store these experiences in memory -- and human long-term memory is now viewed as nearly limitless -- and use them to run simulations in their minds to prepare for problem solving in new situations. These simulations help them to form hypotheses about how to proceed in the new situation based on past experiences. The chapter also discusses the conditions experience must meet if it is to be optimal for learning and shows how good video games can deliver such optimal learning experiences. Some of the issues covered include: identity and learning; models and model-based thinking; the control of avatars and "empathy for a complex system"; distributed intelligence and cross-functional teams for learning; motivation, and ownership; emotion in learning; and situated meaning, that is, the ways in which games represent verbal meaning through images, actions, and dialogue, not just other words and definitions

Self-Directed Learning in Teacher-Lead Minecraft Classrooms

Minecraft, an online multi-player sandbox video game, is now being used as a teaching tool for course subjects ranging from digital literature to computer science. To understand how Minecraft was being adopted as a classroom tool, we interviewed 16 teachers and 10 students who had used Minecraft inside a classroom setting. Analysis revealed three key ways in which Minecraft enables and motivates students to work towards their own learning goals: the ability to customize context, live through stories, and assume roles in the virtual world. Drawing from these themes we propose a set of design recommendations for online informal learning spaces

Designing for deep learning in the context of digital and social media

There is today a great deal of controversy over digital and social media. Even leaders in the tech industry are beginning to decry the time young people spend on smartphones and social networks. Recently, the World Health Organization proposed adding “gaming disorder” to its official list of diseases, defining it as a pattern of gaming behavior so severe that it takes “precedence over other life interests”. At the same time, many others have celebrated the positive properties of video games, social media, and social networks. This paper argues that a deeper understanding of human beings is needed to design for deep learning. For the purposes of this study “design for deep learning” means helping people matter and find meaning in ways that make them and others healthy in mind and body, while improving the state of the world for all living things, with due respect for truth, sensation, happiness, imagination, individuality, diversity, and the future. In particular, fifteen features related to human nature are suggested based on recent scientific developments to answer the question: What is a human being? Consequently, proposals that are linked to learning and transformation, as well as social improvement, should fit with the ways in which humans, as specific sorts of biological and social creatures, learn best (or can learn at all) and can change for the better

Designing for deep learning in the context of digital and social media

There is today a great deal of controversy over digital and social media. Even leaders in the tech industry are beginning to decry the time young people spend on smartphones and social networks. Recently, the World Health Organization proposed adding “gaming disorder” to its official list of diseases, defining it as a pattern of gaming behavior so severe that it takes “precedence over other life interests”. At the same time, many others have celebrated the positive properties of video games, social media, and social networks. This paper argues that a deeper understanding of human beings is needed to design for deep learning. For the purposes of this study “design for deep learning” means helping people matter and find meaning in ways that make them and others healthy in mind and body, while improving the state of the world for all living things, with due respect for truth, sensation, happiness, imagination, individuality, diversity, and the future. In particular, fifteen features related to human nature are suggested based on recent scientific developments to answer the question: What is a human being? Consequently, proposals that are linked to learning and transformation, as well as social improvement, should fit with the ways in which humans, as specific sorts of biological and social creatures, learn best (or can learn at all) and can change for the better

Semantic Perspicuity and the Locative Hypothesis

Proceedings of the Eighth Annual Meeting of the Berkeley Linguistics Society (1982

Efficient Generation of Shape-Based Reference Frames for the Corpus Callosum for DTI-based Connectivity Analysis

Yushkevich et.al. [17, 18] established a PDE-based deformable modeling approach called continuous medial representation (cm-rep), in which the geometric relationship between the medial axis of a 3D object and its boundary is captured. Continuous medial description of an object not only provides useful shape features for object characterization and comparison; it also imposes a shape-based reference frame on the interior of that object. Such a reference frame provides a useful means of representing different instances of an anatomical structure using a common canonical parametrization domain. This paper presents an efficient method to construct continuous medial shape models for 2D objects. A closed form solution for the ordinary differential equation (ODE) is derived via Pythagorean hodograph (PH) curves. That closed form solution reduces the computation complexity from solving an ODE system to pure algebraic manipulation. Using this method, we generate shape-based reference frames, and demonstrate how they can be applied to the analysis of anatomical connectivity of corpora callosa, obtained by fiber tracking in diffusion tensor magnetic resonance imaging (DTI) in a chromosome 22q11.2 deletion syndrome study