Many students who enter community colleges are underprepared in reading, writing, and/or mathematics and designated as not being college-ready. Colleges typically require students who are not college-ready in one or more subjects to enroll in developmental education (DE), which has traditionally consisted of a series of subject-based courses for students to complete prior to entering college-level classes. Data from 2010 suggest that 68 percent of community college students enrolled in at least one DE course, at a cost of approximately $7 billion (Community College Research Center, 2014a; Scott-Clayton, Crosta, and Belfield, 2012). However, evidence indicates that traditional approaches to DE were not working for many students. One study found that only 20 percent of students assigned to traditional course-based math DE and 37 percent of students assigned to course-based reading DE completed a first college-level course within three years of entering school (Bailey, Jeong, and Cho, 2010). Faced with troubling evidence on the success of students who take traditional DE courses, states and higher education institutions across the United States are rethinking the way they address college readiness. C O R P O R A T I O N Designing and Implementing Corequisite Models of Developmental Education Findings from Texas Community CollegesLindsay Daugherty, Celia J. Gomez, Diana Gehlhaus Carew, Alexandra Mendoza-Graf, Trey Miller• Five common types of corequisite models were identified as being implemented in the participating Texas community colleges: paired-course models, extended instructional time models, Accelerated Learning Program models, academic support service models, and technology-mediated support models.• Challenges to implementation included lack of stakeholder buy-in, issues with scheduling and advising, limited instructional preparation and support, and uncertainty around state policy.• Efforts to build buy-in and address challenges were essential to successful implementation.• Some strategies, such as dedicated time for design, professional development, and small class sizes, could be more costly.• Unique features, such as use of a single instructor for the corequisites and mixed-ability peer groups, could be important to the effectiveness of their models but often faced more challenges with scheduling, advising, and buy-in across the institution.

As the United States seeks to maintain a competitive edge in artificial intelligence, the strength of its AI workforce will be of paramount importance. In order to understand the current state of the domestic AI workforce, Diana Gehlhaus and Santiago Mutis define the AI workforce and offer a preliminary assessment of its size, composition, and key characteristics. Among their findings: The domestic supply of AI talent consisted of an estimated 14 million workers (or about 9% of total U.S. employment) as of 2018.

mall businesses are important to the U.S. economy. 1 In 2017 (the latest year for which data are available), enterprises with fewer than 20 employees accounted for 16.4 percent of U.S. total employment and 12.2 percent of total payrolls. 2 Enterprises with fewer than 500 employees accounted for 47.0 percent of employment and 40.3 percent of payrolls.Less easily quantified but equally important is the role that small businesses play in creating and sustaining the character and vitality of local communities. Both physically and socially, small businesses constitute an essential part of the "streetscape" of their communities.Our principal aim in this Perspective is to provide a preliminary understanding of the challenges that these businesses are facing as a result of the global coronavirus disease 2019 (COVID-19) pandemic. Using this understanding, we provide a preliminary description of what kinds of policies will help them to survive. 3 Existence can be precarious for small businesses, even in the best of times. For example, in 2016 (the latest year for which these data are available) the "exit

Since the mid-2000s, China has consistently graduated more STEM PhDs than the United States, a key indicator of a country’s future competitiveness in STEM fields. This paper explores the data on STEM PhD graduation rates and projects their growth over the next five years, during which the gap between China and the United States is expected to increase significantly.

A globally competitive AI workforce hinges on the education, development, and sustainment of the best and brightest AI talent. This issue brief compares efforts to integrate AI education in China and the United States, and what advantages and disadvantages this entails. The authors consider key differences in system design and oversight, as well as strategic planning. They then explore implications for the U.S. national security community.