printer friendly pageEDUC 391: Engineering Education and Online Learning (ENGR 391)
A project based introduction to web-based learning design. In this course we will explore the evidence and theory behind principles of learning design and game design thinking. In addition to gaining a broad understanding of the emerging field of the science and engineering of learning, students will experiment with a variety of educational technologies, pedagogical techniques, game design principles, and assessment methods. Over the course of the quarter, interdisciplinary teams will create a prototype or a functioning piece of educational technology.
Terms: Spr
| Units: 3
Instructors:
Bowen, K. (PI)
;
Reynante, B. (TA)
EDUC 398: Core Mechanics for Learning
In game play, core mechanics refers to the rules of interaction that drive the game forward. This class will consider whether there are core mechanics that can drive learning forward, and if so, how to build them into learning environments. The course mixes basic theory, research methods, and application of learning principles.
Terms: Win
| Units: 3
Instructors:
Blair, K. (PI)
EDUC 399A: Designing Surveys
This workshop/course is designed for students who are designing a survey for use in a research project. The workshop content draws on relevant cognitive processing theories and research (on comprehension, retrieval, judgment, and reporting). In addition to some readings and a few lectures, this workshop is designed to be highly interactive and practical. By the end of the course students will have designed and pilot tested their survey instrument. Course may be repeated for credit.
Terms: Win
| Units: 1-2
| Repeatable
20 times
(up to 40 units total)
Instructors:
Porteus, A. (PI)
EDUC 401A: Mini Courses in Methodology: Statistical Packages for the Social Sciences (SPSS)
Statistical analysis using SPSS, including generating descriptive statistics, drawing graphs, calculating correlation coefficients, conducting t-tests, analysis of variance, and linear regression. Building up datasets, preparing datasets for analysis, conducting statistical analysis, and interpreting results.
Terms: Aut
| Units: 1
Instructors:
Lang, D. (PI)
EDUC 401B: Mini Courses in Methodology: Stata
The goal of this course is to familiarize students with the Stata statistical software package for use in quantitative research. By the end of the course, students should be able to import and export data, clean and manage data, conduct standard statistical tests (e.g., correlation, t-test, regression), and produce a graph.
Terms: Aut, Win
| Units: 1
Instructors:
Stenhaug, B. (PI)
EDUC 401D: Multilevel Modeling Using R (STATS 196A)
See
http://rogosateaching.com/stat196/ . Multilevel data analysis examples using R. Topics include: two-level nested data, growth curve modeling, generalized linear models for counts and categorical data, nonlinear models, three-level analyses. Class meets April 8, April 15, April 22, April 29, May 13.
Terms: Spr
| Units: 1
Instructors:
Rogosa, D. (PI)
EDUC 421: Powerful Ideas for Learning Sciences and Technology Design: Sociocultural Practices of the Blues
This course is intended as a graduate level seminar that provides in-depth readings and discussions, Professor Roy Pea's professional reflections, and student essay-writing on topics examined in Dr. Pea's select publications and associated influential writings.
Terms: Aut
| Units: 3
| Repeatable
6 times
(up to 18 units total)
Instructors:
Pea, R. (PI)
EDUC 423: Introduction to Data Science (EDUC 143, SOC 302)
Social scientists can benefit greatly from utilizing new data sources like electronic administration records or digital communications, but they require tools and techniques to make sense of their scope and complexity. This course offers the opportunity to understand and apply popular data science techniques regarding data visualization, data reduction and data analysis.
Terms: Win
| Units: 3-5
Instructors:
McFarland, D. (PI)
;
Smith, S. (PI)
EDUC 426: Unleashing Personal Potential: Behavioral Science and Design Thinking Applied to Self (PSYCH 264)
This course facilitates the application of the methods, theories, and findings of behavioral science to students own lives and improvement projects. It does so by combining behavioral science with a design thinking approach. You will learn to identify your potential, navigate to achieve it, and stay resilient during the journey. Students will design their own action plans, define goals and prototype strategies to test them, in an iterative feedback cycle. Our course thus blends two intellectual streams that seldom intersect: behavioral science and design thinking.
Terms: Aut
| Units: 2-4
EDUC 430C: Using Data to Describe the World: Descriptive Social Science Research Techniques (SOC 258C)
This course focuses on the skills needed to conduct theoretically-informed and policy-relevant descriptive social science. Students read recent examples of rigorous descriptive quantitative research that exemplifies the use of data to describe important phenomena related to educational and social inequality. The course will help develop skills necessary to conceptualize, operationalize, and communicate descriptive research, including techniques related to measurement and measurement error, data harmonization, data reduction, and visualization. Students develop a descriptive project during the course. Prerequisite: satisfactory completion of a course in multivariate regression.
Terms: Spr
| Units: 3-5
| Repeatable
2 times
(up to 10 units total)
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