We present initial results from our work towards developing a concept inventory for algorithm analysis (AACI) at the post-CS2 level. We used a Delphi process to identify a list of algorithm analysis topics that were considered both important and hard by surveying a panel of experienced instructors. Through a similar survey process, we identified a list of student misconceptions related to the identified topics. Based on this, a set of pilot AACI items were developed. We validated the misconceptions list by analyzing student responses to four administrations of the pilot AACI in two different universities during Fall 2015 and Spring 2016. Results revealed that a sufficient number of students held most of the misconceptions identified in the list.

and add 15.6 million jobs to the 2012 employment level of 145.4 million. Of the 818 occupations for which the Bureau of Labor Statistics (BLS) produces and publishes projections data, 667 are projected to add jobs and 151 are expected to decline in employment during the 2012-2022 period. Some of the fastest projected growth will occur in the healthcare, healthcare support, construction, and personal care fields. Together, these four occupational groups are expected to account for more than 5.3 million new jobs by 2022, about one-third of the total employment growth. Occupational projections provide information on how changes in demographics, technology, consumer preferences, and other factors are expected to affect the future labor force. Job seekers and career counselors use this information to see where the strongest or weakest growth is expected to be over the coming decade. Policymakers use the projections for long-term policy planning, and states use the data to prepare state and area projections. In addition to projecting growth, BLS projects the number of job openings that will stem from the need to replace workers who change occupations or leave the labor force and tracks the typical level of education that is needed for entry-level positions in each occupation. Together, projected growth, replacement needs, and education category assigned by BLS provide data users with a more complete picture of trends in the labor market. December 2013 U.S. BUREAU OF LABOR STATISTICS 2 MONTHLY LABOR REVIEW This article provides a broad overview of the 2012-2022 occupational projections. The first section summarizes the data and how the projections are made. Subsequent sections provide more detail of the projections, including information about drivers of occupational growth and decline, employment by education, and growth or decline within each of 22 major occupational groups. The article also discusses the occupations that are projected to grow the fastest, add the most new jobs, decline most rapidly, and lose the most jobs. Additional information about occupations may be found in the Occupational Outlook Handbook. 1 The Handbook contains 334 occupational profiles with information on typical job duties, work environment, education, training, licensure requirements, median pay, and the job outlook. Projections process and data sources Occupational projections are the final step in the BLS projections process. The projections process begins with high-level labor force and macroeconomic projections, makes use of an input-output framework to convert final demand into industry output, and ends with detailed projections that are released for 818 detailed occupations in 329 detailed industries. 2 The Employment Projections program's methodology page includes a detailed recounting of the entire process, including the final occupational-projections step. 3 Current projections data cover the decade from 2012 to 2022. The 2012 data are derived from BLS surveys. Industry employment comes from the Current Employment Statistics surv...

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According to professionals in education, change is an ever-present and evolving process. With transformation in education at both state and national levels, technology education must determine a position in this climate of change.This paper reflects the views on the future of technology education based on an ongoing research project. The purpose of the project is to show a contemporary view of one direction that technology education can take for providing 21st century skills and learning to students.

Students identified as at-risk of non-academic continuation have a propensity toward lower academic self-efficacy than their peers (Lent, 2005). Within engineering, self-efficacy and confidence are major markers of university continuation and success (Lourens, 2014 Raelin, et al., 2014).  This study explored academic learning self-efficacy specific to first-year engineering students with at-risk indicators.  The at-risk determination was made through trajectory to matriculate, classified by cumulative grade point average of academic studies. An adapted version of the Self-efficacy for Learning (SEL) scale, modified by Klobas, Renzi and Nigrelli (2007), was administered to freshman engineering students identified at-risk and not at-risk of matriculation. Internal consistency of the SEL was analyzed and once deemed satisfactory (Cronbach alpha = .94), item-level outcome comparisons between student subgroups were made for each of the 22 instrument items.

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Nanotechnology is a multidisciplinary field of research and development identified as a major priority in the United States. Progress in science and engineering at the nanoscale is critical for national security, prosperity of the economy, and enhancement of the quality of life. It is anticipated that nanotechnology will be a major transitional force that possesses the potential to change society. Rapid and continued advancement in the field of nanotechnology is accelerating the demand for specific professional knowledge and skill. These lines of technological discovery and improvement continue to unlock new content for classroom incorporation. Contemporary approaches and practices to further engage learners and enhance their abilities to apply nanoscale-related content knowledge must be continually developed in order for the United States to solidify itself as the primary builder of nanotechnology research and development. Steadfast development of new technologies leading to continual transformation of society serves as a strong indicator that current educational practices should be altered in order to prepare knowledgeable and engaged citizens. The use of three-dimensional graphics, virtual reality, virtual modeling, visualizations, and other information and communication technologies can assist in reinforcing nano-associated scientific and technological concepts.