Course Description

Digital Learning Environments, EDUC W161

Syllabus(opens in a new tab)
Enrollment closed

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

Fall Semester 2017
Instruction start date: August 23, 2017
Instruction end date: December 2, 2017
Credit: 4.5 quarter units / 3 semester units credit
UC Berkeley, 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:
Units toward Degree (see your adviser)

UC Riverside:
Unit Credit

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

UC San Francisco:
Unit Credit

UC Santa Barbara:
Unit Credit

UC Santa Cruz:
Unit Credit

Course Meeting Requirements

The two online meeting periods will be on the Zoom video conferencing platform. Many weeks will feature a guest speaker from one of the featured digital learning environments of study. They are invited mostly to field critical questions but may also provide a brief introduction of themselves and their role at the platform.

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.

Additional Course Information

Exam Info

Grading: - Participation: 15% - Midterm: 20% - Homework: 40% - Final Project: 25%

Proctoring Info

There will be a Midterm proctored online during one of the class sessions

Relevant Website

Course Creator

Zachary Pardos
Dr. Pardos is an Assistant Professor at UC Berkeley in a joint position between the Graduate School of Education and School of Information. His focal areas of study are educational data mining and learning analytics concentrating on measurement of learning phenomena in digital environments. He earned his PhD in Computer Science at Worcester Polytechnic Institute in the Tutor Research Group in 2012. Funded by a National Science Foundation Fellowship (GK-12) he spent extensive time on the front lines of K-12 education working with teachers and students to integrate educational technology into the curriculum as a formative assessment tool. He was program co-chair of the 2014 conference on Educational Data Mining, on the organizing committee for the 2014 Learning Analytics and Knowledge conference, and serves on the executive committee for the Artificial Intelligence in Education Society. He has received numerous academic awards and honors for work on predictive models of learning including a top prize applying his educational analytics in the 2010 KDD Cup, an international big data competition on predicting student performance within an intelligent tutoring system. Pardos comes to UC Berkeley after a post-doc at MIT studying Massive Open Online Courses. At UC Berkeley he directs the Computational Approaches to Human Learning (CAHL) research lab and teaches courses on Data Mining and Analytics, Digital Learning Environments, and Machine Learning in Education. Dr. Pardos is an Assistant Professor at UC Berkeley in a joint position between the Graduate School of Education and School of Information. His focal areas of study are educational data mining and learning analytics concentrating on measurement of learning phenomena in digital environments. He earned his PhD in Computer Science at Worcester Polytechnic Institute in the Tutor Research Group in ...

Dr. Pardos is an Assistant Professor at UC Berkeley in a joint position between the Graduate School of Education and School of Information. His focal areas of study are educational data mining and learning analytics concentrating on measurement of learning phenomena in digital environments. He earned his PhD in Computer Science at Worcester Polytechnic Institute in the Tutor Research Group in 2012. Funded by a National Science Foundation Fellowship (GK-12) he spent extensive time on the front lines of K-12 education working with teachers and students to integrate educational technology into the curriculum as a formative assessment tool. He was program co-chair of the 2014 conference on Educational Data Mining, on the organizing committee for the 2014 Learning Analytics and Knowledge conference, and serves on the executive committee for the Artificial Intelligence in Education Society. He has received numerous academic awards and honors for work on predictive models of learning including a top prize applying his educational analytics in the 2010 KDD Cup, an international big data competition on predicting student performance within an intelligent tutoring system. Pardos comes to UC Berkeley after a post-doc at MIT studying Massive Open Online Courses. At UC Berkeley he directs the Computational Approaches to Human Learning (CAHL) research lab and teaches courses on Data Mining and Analytics, Digital Learning Environments, and Machine Learning in Education.

Instructor of Term

Zachary Pardos
pardos@berkeley.edu

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