Context. We present the second Gaia data release, Gaia DR2, consisting of astrometry, photometry, radial velocities, and information on astrophysical parameters and variability, for sources brighter than magnitude 21. In addition epoch astrometry and photometry are provided for a modest sample of minor planets in the solar system. Aims. A summary of the contents of Gaia DR2 is presented, accompanied by a discussion on the differences with respect to Gaia DR1 and an overview of the main limitations which are still present in the survey. Recommendations are made on the responsible use of Gaia DR2 results. Methods. The raw data collected with the Gaia instruments during the first 22 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into this second data release, which represents a major advance with respect to Gaia DR1 in terms of completeness, performance, and richness of the data products. Results. Gaia DR2 contains celestial positions and the apparent brightness in G for approximately 1.7 billion sources. For 1.3 billion of those sources, parallaxes and proper motions are in addition available. The sample of sources for which variability information is provided is expanded to 0.5 million stars. This data release contains four new elements: broad-band colour information in the form of the apparent brightness in the GBP (330–680 nm) and GRP (630–1050 nm) bands is available for 1.4 billion sources; median radial velocities for some 7 million sources are presented; for between 77 and 161 million sources estimates are provided of the stellar effective temperature, extinction, reddening, and radius and luminosity; and for a pre-selected list of 14 000 minor planets in the solar system epoch astrometry and photometry are presented. Finally, Gaia DR2 also represents a new materialisation of the celestial reference frame in the optical, the Gaia-CRF2, which is the first optical reference frame based solely on extragalactic sources. There are notable changes in the photometric system and the catalogue source list with respect to Gaia DR1, and we stress the need to consider the two data releases as independent. Conclusions. Gaia DR2 represents a major achievement for the Gaia mission, delivering on the long standing promise to provide parallaxes and proper motions for over 1 billion stars, and representing a first step in the availability of complementary radial velocity and source astrophysical information for a sample of stars in the Gaia survey which covers a very substantial fraction of the volume of our galaxy.

Charles is a PhD student in Environmental Sciences at Louisiana State University. In 2012, he earned his master's degree in Medical and Health Physics and has since been working towards a PhD. During his studies, he has worked actively with the LSU STEM Talent and Expansion Program and LSU Center for Academic Success helping with different methods that aim to improve how STEM college students learn including tutorial centers, PLTL, SI, and recitation programs. Dr. Wang's research interests focus on the development of feasible solutions to practical radiation protection and radiation detection issues. The majority of his work has emphasized operational radiation safety, radiation detection instrumentation, air monitoring methodology, and radioactive waste management. He has authored or co-authored more than 30 peer-reviewed publications, conference proceedings and abstracts, and book chapters. He has also chaired five graduate committees and served on another 16 graduate committees. In addition, he has served as a manuscript reviewer for four referred journals (i.e.,

Background: Louisiana State University's (LSU) STEM Talent Expansion Program (STEP) was established to increase students' persistence in first-year, declared engineering majors (a project priority), in science, technology, engineering, and math (STEM) majors (an NSF goal), and in all majors at LSU (an institutional goal). Over 8 years, 3,097 (27%) engineering students participated in one or more STEP activities including a residential college, a student mentoring program, an introductory engineering design course, and a summer bridge camp for first-year students. Purpose: This paper describes the influence of the STEP activities on persistence, while accounting for demographic and academic preparation variables. Design/Method: Data collected over 8 years from first-year engineering students include demographics, academic preparation, participation in STEP activities, and yearly status regarding major and graduation. Descriptive statistics, correlation analysis, and multiple logistic regression determine which factors significantly impact persistence in engineering majors, in STEM majors, and in all majors at LSU. Results: STEP participants have higher persistence levels than nonparticipants by at least 11% in engineering, 9% in STEM, and 5% in all majors at LSU. Gender, ACT math scores, and, in some cases, ethnicity significantly impact persistence. Participation in the residential college, introductory course, and mentoring programs significantly increased persistence in engineering majors, in STEM majors, and at the university, while the summer bridge camp did not show as much influence on persistence overall. Conclusion: STEP was successful at increasing persistence in engineering and STEM majors. Specific STEP activities continue to evolve in the College of Engineering and should continue to reap positive results in the persistence of engineering students. K E Y W O R D S attrition, persistence, quantitative analysis, regression, retention

Charles is a PhD student in Environmental Sciences at Louisiana State University. In 2012, he earned his master's degree in Medical and Health Physics and has since been working towards a PhD. During his studies, he has worked actively with the LSU STEM Talent and Expansion Program and LSU Center for Academic Success helping with different methods that aim to improve how STEM college students learn including tutorial centers, PLTL, SI, and recitation programs. Ms. Adrienne Steele, Louisiana State UniversityAdrienne Steele has over 15 years experience in STEM education. Currently, Adrienne works at Louisiana State University in the College of Engineering, managing all aspects of the STEP project that consists of a large-scale peer mentoring program. Previously, she coordinated the Scope-On-A-Rope Outreach Program (SOAR) in the Department of Biological Sciences for 10 years with funding from the Howard Hughes Medical Institute. In this position, she led over 175 professional development workshops for K-12 teachers. Prior to her positions at LSU, Adrienne was the Science Education Curator at the Louisiana Art and Science Museum in Baton Rouge. Adrienne has a Master of Science degree in zoology from LSU, where she studied in the Museum of Natural Science, and an Education Specialist Certification in science education. Mr. James Blake GegenheimerJames Gegenheimer is an MSME Candidate in Mechanical Engineering at LSU. When graduated, James will commission as a Second Lieutenant in the United States Air Force. He will be stationed at Hill Air Force Base in Salt Lake City, Utah. He plans to pursue a Ph.D. through the Air Force and work with the Air Force Weapons Research Laboratory. James is currently a Supplemental Instructor at LSU for Thermodynamics where he has served since 2013. He has worked to improve how STEM college students learn through the use of active learning.c American Society for Engineering Education, 2016 The Unsubstantiated Cutoff: Deeper Analysis of Supplemental Instruction Sessions in Engineering CoursesAbstract Active learning sessions such as those in the Supplemental Instruction model are often reported as successful when incorporated into high DFW (Drop, Fail, Withdraw), high enrollment courses (1) . Research conducted by The U.S. Department of Education, Redish, Longfellow, and many others have reported significant benefits to students enrolled in courses that incorporate active learning strategies (1,2,3) . The initial analysis of the impact of Supplemental Instruction on students in the College of Engineering at Louisiana State University (LSU) was consistent with these previous findings (4) . However, researchers like Dawson and McCarthy recognized some sobering truths-many analyses regarding Supplemental Instruction were incomplete and made weak conclusions (5,6) . The research presented herein investigated two different modes of analysis to better determine the effectiveness of Supplemental Instruction (or similar models), taking advantage of the large dataset at LSU and attempting to r...