Course Descriptions and Syllabi

 

FALL 2004

 

Catalog Description: (Also listed as Electrical Engineering 355) Theories and concepts from computer science, artificial intelligence, cognitive science, and education that are important to designing, building, and evaluating computer-based instructional systems. Development and substantiation of the concept, architecture, and implementation of Intelligent Learning Environments. Multimedia and Web-based technology in teaching, learning, collaboration, and assessment. Prerequisite: 260, 360, or equivalent.

 

Prerequisite: CS 260 (CS 360), or equivalent, or permission of instructor.

 

Focus for Fall 2004 class: Design, implementation, and evaluation of Intelligent Learning Environments that promote learning with understanding and transfer. To do this, we will first look at Cognitive Science and Education research on ôHow People Learn.ö We will study educational theories of constructivist, active, and anchored learning, then look at the role of transfer in deep learning, assessment and feedback, and the role of metacognition or metacognitive strategies that promote learning with understanding.

 

In the second phase of the course, we will look study a variety of computer-based instructional systems. Traditional systems can be categorized as intelligent tutors and cognitive tools. We will study a number of approaches to tutoring û tutorial dialogs, simulation-based systems, cognitive tutors, coaches, student model-based systems with bug repair models, and systems that promote self-explanation and reflective feedback. We will also look at Cognitive tools, where the locus of control is mainly with the system user or the student. These systems focus more on constructivist theories, situated cognition, and cognitive apprenticeship.

 

A third phase of this study will focus on new approaches to instruction and learning, such as animated and pedagogical agents, teachable agents, other multi-agent approaches that provide a mix of teaching and learning approaches, and last game environments.

 

There is no text book for the course. We will be reading and discussing a number of book chapters, journal and conference papers, and even recent technical reports. A lot of the material can be accessed on the web. Otherwise hard copies of papers will be made available in the CS office (Sandy Winters), and students can make a Xerox copy of the paper for their own use.

 

Topics:

 

Aug-26-04		Introduction & Review of Course Contents
Aug-31-04		Self-study: Role of computers in the learning process
Sep-02-04		Self-study: Introduction to traditional learning environments
Sep-07-04		Learning Theories -- A Historical Perspective
Sep-09-04		Learning Theories -- Part 2
Sep-14-04		Learning Theories -- Part 3
Sep-16-04		Constructivism
Sep-21-04		Constructivist Approaches to Science and Math education
Sep-23-04		Metacognition and Learning
Sep-28-04		Characteristics of Expertise and Transfer of Learning
Sep-30-04		Learning and Transfer
Oct-05-04		The Design of Learning Environments
Oct-07-04		Back to Transfer
Oct-12-04		Overview of Computer-based Learning Environments
Oct-14-04		Part 2: Computer-based Learning Environments
Oct-19-04		Fall Break: No class
Oct-21-04		Exploratory Environments versus AI-based Tutors
Oct-26-04		Cognitive Neuroscience and Learning: David Noelle
Oct-28-04		Tutoring Dialog Structures (Collins, et al.) and Overlay Modeling (Goldstein, et al.)
Nov-02-04		Student Modeling: Bug Catalogs
Nov-04-04		Repair Theory (van Lehn), Self Explanations (Chi)
Nov-09-04		Apprentice Learning, Cognitive Tutors (CMU)
Nov-11-04		Cognitive Tutors -- Lessons learned, Computer Coaching
Nov-16-04		Anchored Instruction, Macrocontexts plus Microworlds, Animated Pedagogical Agents
Nov-18-04		Pedagogical Agents, Teachable Agents, Metacognitive Strategies
Nov-23-04		Thanksgiving Holiday
Nov-25-04		Thanksgiving Holiday
Nov-30-04		Participatory Environments and Computer Support for Metacognition
Dec-02-04		Video Games and Education
Dec-07-04		Video Games and Education, contd.
Dec-09-04		Last class: Review

 

Grading:

Grading for the course will be based on the following:

1.      Weekly summaries of the papers that are discussed in class.á û 20%

2.      Presentation of at least two topics in the classroom.á û 20%

3.      Participation in classroom discussions. û 10%

4.      Class Project û 50%