Course Description
Digital Learning Environments, EDUC W161
Digital learning environments are taking residence in the educational experience of many, from replacing components of traditional classroom instruction to providing open platforms for lifelong learning. In this class we will study the various forms and functions of a sampling of digital learning environments ranging from subject specific Intelligent Tutoring Systems in K-12 to domain neutral systems for post-secondary online learning.
Key Information
Credit: 4.5 quarter units /
3 semester units credit
UC Berkeley, Grad School of Education
Course Credit:
Upon successful completion, all online courses offered through cross-enrollment provide UC unit credit. Some courses are approved for GE, major preparation and/or, major credit or can be used as a substitute for a course at your campus.If "unit credit" is listed by your campus, consult your department, academic adviser or Student Affairs division to inquire about the petition process for more than unit credit for the course.
UC Berkeley:
Major Requirement: fulfills Education minor elective
UC Davis:
Unit Credit
UC Irvine:
Major Requirement: Elective for Education Science Major
UC Los Angeles:
Unit Credit
UC Merced:
Unit Credit (see your Academic Advisor)
UC Riverside:
General Education: BA Education/Society/Human Development Elective Units
UC San Diego:
General Education: Warren - May be counted depending on major/PofC/AS, Transfer students may use for UD noncontiguous GE depending on major; TMC 1 course toward upper division disciplinary breadth if noncontiguous to major; Revelle - one course towards Social Science (no major overlap); Seventh - 1 course towards Alternatives - Social Science
UC San Francisco:
Unit Credit
UC Santa Barbara:
Unit Credit
UC Santa Cruz:
Major Requirement: Elective for Education minor
Course Fees
No fees
More About The Course
This Course Qualifies for Credit Towards a Certificate in Education from UC Berkeley.
Learn more about the Education Minor program at UC Berkeley.
Course Creator
Zachary Pardos
Dr. Pardos is an associate professor of education at UC Berkeley studying adaptive learning and AI. His current research focuses on knowledge representation and recommender systems approaches to increasing upward mobility in postsecondary education using behavioral and semantic data.
He earned his PhD in Computer Science at Worcester Polytechnic Institute with a dissertation on computational models of cognitive mastery. Funded by a National Science Foundation Fellowship (GK-12), he spent extensive time with K-12 educators and students working to integrate educational technology into the curriculum as a formative assessment tool. After completing his PhD in 2012, he spent one year as a Postdoctoral Associate at the Massachusetts Institute of Technology applying adaptive learning paradigms to Massive Open Online Courses. At Cal, he directs the Computational Approaches to Human Learning research lab, teaches in the Data Science undergraduate program, and is an affiliated faculty in Cognitive Science.
Dr. Pardos is an associate professor of education at UC Berkeley studying adaptive learning and AI. His current research focuses on knowledge representation and recommender systems approaches to increasing upward mobility in postsecondary education using behavioral and semantic data. He earned his PhD in Computer Science at Worcester Polytechnic Institute with a dissertation on ...Dr. Pardos is an associate professor of education at UC Berkeley studying adaptive learning and AI. His current research focuses on knowledge representation and recommender systems approaches to increasing upward mobility in postsecondary education using behavioral and semantic data.
He earned his PhD in Computer Science at Worcester Polytechnic Institute with a dissertation on computational models of cognitive mastery. Funded by a National Science Foundation Fellowship (GK-12), he spent extensive time with K-12 educators and students working to integrate educational technology into the curriculum as a formative assessment tool. After completing his PhD in 2012, he spent one year as a Postdoctoral Associate at the Massachusetts Institute of Technology applying adaptive learning paradigms to Massive Open Online Courses. At Cal, he directs the Computational Approaches to Human Learning research lab, teaches in the Data Science undergraduate program, and is an affiliated faculty in Cognitive Science.
