The STELAR ITEST PI & Evaluator Summit is an annual opportunity for ITEST Principal Investigators (PIs) and evaluators to come together and share successes, challenges, and lessons learned from the ITEST program.
This pdf contains the following 2015 survey instruments: - Student - Instructor - Judge/Volunteer - Parent
This report presents important takeaways from a one-day National Science Foundation (NSF)-supported Forum, “ Next Generation STEM Learning for All,” organized by Education Development Center (EDC) and SRI International through the STEM Learning and Research Center (STELAR) at EDC, the Community for Advancing Discovery Research in Education (CADRE) at EDC, and the Center for Innovative Research in Cyberlearning (CIRCL), working in close collaboration with NSF and the White House Office of Science and Technology Policy. The Forum engaged prominent scientists in STEM learning research and school
SHOW, DON’T TELL . That’s the general idea of infographics, which use visuals to make numbers/stats/processes easier to understand. While it’s easy to enjoy a well crafted infographic, creating one can be challenging. What type of visual fits your data? How should you style your graphic? What tools can you use to create infographics without starting from scratch? Making an infographic is a multistep process, so we’ll break this tutorial into two parts. In this lesson, we’ll walk you through the basics of making your own infographic, depending on the data at hand. - See more at: https:/
The Dimensions of Success observation tool, or DoS, defines twelve indicators of STEM program quality in out-of-school time (e.g., afterschool, summer camps, etc.). It was developed and studied with funding from the National Science Foundation (NSF) by the Program in Education, Afterschool and Resiliency (PEAR), along with partners at Educational Testing Services (ETS) and Project Liftoff. The DoS tool allows researchers, practitioners, funders, and other stakeholders to track the quality of STEM learning opportunities and to pinpoint strengths and weaknesses.
Missing data are a common and significant problem that researchers and data analysts encounter in applied research. Because most statistical procedures require complete data, missing data can substantially affect the analysis and the interpretation of results if left untreated. Methods to treat missing data have been developed so that missing values are imputed and analyses can be conducted using standard statistical procedures. Among these missing data methods, Multiple Imputation has received considerable attention and its effectiveness has been explored, for example, in the context of
The Computing Attitudes Survey (CAS) is an extension of the Colorado Learning Attitudes about Science Survey and measures novice-to-expert attitude shifts about the nature of knowledge and problem solving in computer science. It has five subscales related to different facets of attitudes measured on the survey (transfer, personal interest, problem solving strategies, real world connections, and fixed mindset). Validity and reliability of the CAS has been evaluated with first-year undergraduate students in a variety of classes for both majors and non-majors in computing fields at multiple institutions.
Computer Attitude Questionnaire (CAQ) is a 65-item Likert instrument for measuring middle school students' attitudes on all Young Children's Computer Inventory subscales plus computer anxiety. The paired-comparisons portion of the Young Children's Computer Inventory is also included on the instrument. CAQ v5.14 4-point scale is recommended for grades 4-8. CAQ v5.22 5-point version is available for high school use; includes all other areas on the CAQ plus a classroom E-mail subscale. Authors provide reliability information.
The Climate Change Attitude Survey is composed of 15 Likert-type attitudinal items selected to measure students’ beliefs and intentions toward the environment with a focus on climate change.
This study reports the development and evaluation of the Vocational Identity Status Assessment (VISA), which is derived from established conceptual models and includes career exploration, commitment, and reconsideration dimensions.