In October 2011, WestEd and University of California Berkeley’s Career Academy Support Network (CASN) received a three-year collaborative ITEST Strategies grant to improve learning and workforce development in science, technology, engineering, and math (STEM), and in information and communication technology (ICT)—especially for underserved students. The proposed strategy integrates the hands-on science pedagogy of the Global Learning and Observations to Benefit the Environment (GLOBE) program [1] into the multi-year curriculum of the California green high school academies [2]. The GLOBE

Engaging young science learners today requires a plethora of tools that oftentimes leverages technology in novel ways. This paper describes the use of several 21st century technologies to engage science learners in locally relevant climate science research projects and the presentation of these projects in an entirely online virtual student conference. Case studies demonstrating the use of and effectiveness of 21st century technologies and GLOBE protocols are also included. Through technology, students were able to find out more about distant locations and their own environments, talk to

One of the most important challenges facing the citizens of the 21st century will undoubtedly be climate change. Yet, understanding about climate change remains problematic for students and teachers, particularly in the United States. Understanding the small fluctuations associated with long term changes in temperature and precipitation is a daunting task for the general public let alone for the middle-aged adolescent. Unfortunately, students may only receive instruction on this general environmental science topic in middle-school and in a general science course during their freshman year of

Using consensual qualitative research, the study examines urban high school students’ reactions to a science, technology, engineering, and math (STEM) enrichment/career development program, their resources and barriers, their perspectives on the impact of race and gender on their career development, and their overall views of work and their futures. The sample included nine students who participated in a semistructured interview at the end of the 2-week summer program and again 12–18 months later. The results indicate that the students continued to explore STEM fields after the summer program

Given that many urban students exclude Science, Technology, Engineering, and Mathematics careers from their career choices, the present study focuses on urban high school students and adopts the social-cultural approach to understand the following questions: how do students envision their careers? What are the experiences that shape students’ self-reflections? And how do students’ self-reflections influence the way they envision their future careers? Five students were interviewed and data were coded in two ways: by topic domains and confidence levels. The research findings indicate that

Research shows that middle school is an important juncture for a student where he or she starts to be conscious about academic achievement and thinks about college attendance. It is already known that access to financial resources, family background, career aspirations and academic ability are indicative of a student’s choice to attend college; though these variables are interesting, they do not necessarily give sufficient actionable information to instructors or guidance counselors to intervene for individual students. However, increasing numbers of students are using educational software at

In this paper, we investigate the correspondence between student affect in a web-based tutoring platform throughout the school year and learning outcomes at the end of the year, on a high-stakes mathematics exam.

Csikszentmihalyi’s Flow theory states that a balance between challenge and skill leads to high engagement, overwhelming challenge leads to anxiety or frustration, and insufficient challenge leads to boredom. In this paper, we test this theory within the context of student interaction with an intelligent tutoring system. Automated detectors of student affect and knowledge were developed, validated, and applied to a large data set. The results did not match Flow theory: boredom was more common for poorly -known material, and frustration was common both for very difficult material and very easy