Grad courses!
Last night we sent in our TA applications (results of which will be posted July 4th), and this morning the course outlines for the graduate level courses in Fall 2006 and Spring 2007 were posted. Reading them makes me exceedingly happy. They simultaneously sound fascinating and within my capabilities. I'm so excited.
Here's what I'll probably be taking in the Fall:
IAT 801: Foundations of Computational Art and Design
The goal of this course is to learn Java programming in the context of an art and design practice, that is, to understand computation as an expressive medium. We will juxtapose reading and discussion of seminal articles in computational media (from the New Media Reader) with Java programming projects designed to exercise specific technical skills as well as encourage conceptual explorations in computational art and design. Anyone working in new media will eventually be involved on interdisciplinary projects in which the ability to program will be a strong asset, if not a necessity. Even if in your future career as an artist or designer programming is not a large part of your practice, this course will empower you to communicate confidently with programmers, and thus deepen your interdisciplinary collaborations. And perhaps a few of you will become fascinated with the expressive possibilities opened up by programming, and will choose to make computation one of your primary media.
There are six projects. Each of the projects will explore an expressive possibility of computational systems and exercise specific Java programming skills. With each project we will read and discuss a number of seminal readings in new media where the conceptual explorations in the readings intersect with the project.
Bonus coolness: the New Media Reader textbook for this course was edited by a Johnston Alum that we know!
IAT 810: Cognition, Learning and Collaboration
The aim of this course is to address what it means to know something, how people gain and use knowledge and complex skills, how to determine what an individual knows, how humans learn, how knowledge is created within a social and group context, and how to model human capabilities and performance. We will select and study theoretical perspectives that inform the design of computer-based mediated environments, products, and experiences.
The course will consider theories that inform our understanding of the development of knowledge for individuals and for collaborative groups. Students will be encouraged to consider the contributions, limitations and integration of a variety of theoretical perspectives in order to create computer-based tools and applications that are useful, learnable, and transferable.
This course will provide foundational knowledge for students of the graduate program and prepare them for specialized elective courses particularly in the areas of learning design and media, and networked practice.
Possible research project areas students may pursue include:
• Learning Design
• Knowledge sharing environments
• Human computer interface design
• Cognitive tools to support performance
• Strategic Game Design
Bonus coolness: I studied several of the papers being presented in this course in my graduate level cognitive science courses at UCSD.
And in the Spring:
IAT 813: Artificial Intelligence in Computational Art and Design
This core course is fundamental for anyone interested in applying artificial intelligence methods in creating new technologies for learning and creative professional work. Working through a set of motivating examples from domains such as generative design, dance simulation, social interaction, adaptive user interface design and knowledge sharing in e-learning the course provides insights on how AI techniques can be used to address important problems in art and design. The topics are presented in a comparative manner to clearly highlight advantages and disadvantages of each method providing students with ability to weight benefits of a particular approach when facing a concrete problem in their research area.
The purpose of the course is to enable students to understand AI in the context of particular problems. The course will engage students with AI topics through the use of motivating problems and demonstrate how the AI techniques can help to solve these problems. The course will require students to apply selected AI techniques to their research. The starting set of domain problems would be from current faculty research in applied AI. The course will comprise lectures and a significant project component in which students will choose the project from their research area. Example projects would include building a design generator, a specialized constraint language, a user modelling system, or a robotic soccer team using an advanced multi-agent framework. It is recommended that students enrolling in this course have completed prior coursework in artificial intelligence.
Bonus coolness: I already own and have read parts of the textbook for this course
IAT 814: Knowledge Visualization and Communication
Visualization and Communication are two sides of the same coin. When information and knowledge are perceived we must form our own mental models before we can effectively communicate it. Thus this course will explore how we perceive information from different visualization approaches and how we can best communicate the information and the concepts represented. There is a particular emphasis on material related to 3D data visualization, 3D interactive interfaces and the challenges of mining knowledge from these standard visualization approaches. The approach of this course is human centered rather than machine centred. Understanding visualization and communication requires a knowledge of human perception and cognition.
I can't wait!
Here's what I'll probably be taking in the Fall:
IAT 801: Foundations of Computational Art and Design
The goal of this course is to learn Java programming in the context of an art and design practice, that is, to understand computation as an expressive medium. We will juxtapose reading and discussion of seminal articles in computational media (from the New Media Reader) with Java programming projects designed to exercise specific technical skills as well as encourage conceptual explorations in computational art and design. Anyone working in new media will eventually be involved on interdisciplinary projects in which the ability to program will be a strong asset, if not a necessity. Even if in your future career as an artist or designer programming is not a large part of your practice, this course will empower you to communicate confidently with programmers, and thus deepen your interdisciplinary collaborations. And perhaps a few of you will become fascinated with the expressive possibilities opened up by programming, and will choose to make computation one of your primary media.
There are six projects. Each of the projects will explore an expressive possibility of computational systems and exercise specific Java programming skills. With each project we will read and discuss a number of seminal readings in new media where the conceptual explorations in the readings intersect with the project.
Bonus coolness: the New Media Reader textbook for this course was edited by a Johnston Alum that we know!
IAT 810: Cognition, Learning and Collaboration
The aim of this course is to address what it means to know something, how people gain and use knowledge and complex skills, how to determine what an individual knows, how humans learn, how knowledge is created within a social and group context, and how to model human capabilities and performance. We will select and study theoretical perspectives that inform the design of computer-based mediated environments, products, and experiences.
The course will consider theories that inform our understanding of the development of knowledge for individuals and for collaborative groups. Students will be encouraged to consider the contributions, limitations and integration of a variety of theoretical perspectives in order to create computer-based tools and applications that are useful, learnable, and transferable.
This course will provide foundational knowledge for students of the graduate program and prepare them for specialized elective courses particularly in the areas of learning design and media, and networked practice.
Possible research project areas students may pursue include:
• Learning Design
• Knowledge sharing environments
• Human computer interface design
• Cognitive tools to support performance
• Strategic Game Design
Bonus coolness: I studied several of the papers being presented in this course in my graduate level cognitive science courses at UCSD.
And in the Spring:
IAT 813: Artificial Intelligence in Computational Art and Design
This core course is fundamental for anyone interested in applying artificial intelligence methods in creating new technologies for learning and creative professional work. Working through a set of motivating examples from domains such as generative design, dance simulation, social interaction, adaptive user interface design and knowledge sharing in e-learning the course provides insights on how AI techniques can be used to address important problems in art and design. The topics are presented in a comparative manner to clearly highlight advantages and disadvantages of each method providing students with ability to weight benefits of a particular approach when facing a concrete problem in their research area.
The purpose of the course is to enable students to understand AI in the context of particular problems. The course will engage students with AI topics through the use of motivating problems and demonstrate how the AI techniques can help to solve these problems. The course will require students to apply selected AI techniques to their research. The starting set of domain problems would be from current faculty research in applied AI. The course will comprise lectures and a significant project component in which students will choose the project from their research area. Example projects would include building a design generator, a specialized constraint language, a user modelling system, or a robotic soccer team using an advanced multi-agent framework. It is recommended that students enrolling in this course have completed prior coursework in artificial intelligence.
Bonus coolness: I already own and have read parts of the textbook for this course
IAT 814: Knowledge Visualization and Communication
Visualization and Communication are two sides of the same coin. When information and knowledge are perceived we must form our own mental models before we can effectively communicate it. Thus this course will explore how we perceive information from different visualization approaches and how we can best communicate the information and the concepts represented. There is a particular emphasis on material related to 3D data visualization, 3D interactive interfaces and the challenges of mining knowledge from these standard visualization approaches. The approach of this course is human centered rather than machine centred. Understanding visualization and communication requires a knowledge of human perception and cognition.
I can't wait!