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Articles 1 - 6 of 6
Full-Text Articles in Statistics and Probability
The Gaise College Report: The American Statistical Association Meets Sound Pedagogy In Central Virginia, Beverly Wood
The Gaise College Report: The American Statistical Association Meets Sound Pedagogy In Central Virginia, Beverly Wood
Beverly Wood
Research in undergraduate statistics education often centers on the introductory course required for a large percentage of college students. While acknowledging the diverse setting, audience, and purpose of introductory courses, existing research assumes that courses offered by different disciplines share the same goals and teaching practices. The purpose of this study is to examine the objectives for student outcomes and pedagogical delivery of introductory statistics courses in various academic departments to provide explicit evidence for this assumption. The American Statistical Association’s Guidelines for Assessment and Instruction in Statistics Education (GAISE) are meant to apply to all introductory courses. The College …
Guidelines For Assessment And Instruction In Statistics Education (Gaise) College Report 2016, Robert Carver, Michelle Everson, John Gabrosek, Nicholas Horton, Robin Lock, Megan Mocko, Allan Rossman, Ginger Holmes Roswell, Paul Velleman, Jeffrey Witmer, Beverly Wood
Guidelines For Assessment And Instruction In Statistics Education (Gaise) College Report 2016, Robert Carver, Michelle Everson, John Gabrosek, Nicholas Horton, Robin Lock, Megan Mocko, Allan Rossman, Ginger Holmes Roswell, Paul Velleman, Jeffrey Witmer, Beverly Wood
Beverly Wood
In 2005 the American Statistical Association (ASA) endorsed the Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report. This report has had a profound impact on the teaching of introductory statistics in two- and four-year institutions, and the six recommendations put forward in the report have stood the test of time. Much has happened within the statistics education community and beyond in the intervening 10 years, making it critical to re-evaluate and update this important report. For readers who are unfamiliar with the original GAISE College Report or who are new to the statistics education community, the full …
Updated Guidelines, Updated Curriculum: The Gaise College Report And Introductory Statistics For The Modern Student, Beverly Wood, Megan Mocko, Michelle Everson, Nicholas J. Horton, Paul Velleman
Updated Guidelines, Updated Curriculum: The Gaise College Report And Introductory Statistics For The Modern Student, Beverly Wood, Megan Mocko, Michelle Everson, Nicholas J. Horton, Paul Velleman
Beverly Wood
Since the 2005 American Statistical Association's (ASA) endorsement of the Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report, changes in the statistics field and statistics education have had a major impact on the teaching and learning of statistics. We now live in a world where "Statistics - the science of learning from data - is the fastest-growing science, technology, engineering, and math (STEM) undergraduate degree in the United States," according to the ASA, and where many jobs demand an understanding of how to explore and make sense of data. In light of these new reports and other …
Determining Graduation Rates In Engineering For Community College Transfer Students Using Data Mining, Marcia Laugerman, Diane T. Rover, Mack C. Shelley, Steven K. Mickelson
Determining Graduation Rates In Engineering For Community College Transfer Students Using Data Mining, Marcia Laugerman, Diane T. Rover, Mack C. Shelley, Steven K. Mickelson
Diane Rover
This study presents a unique synthesized set of data for community college students entering the university with the intention of earning a degree in engineering. Several cohorts of longitudinal data were combined with transcript-level data from both the community college and the university to measure graduation rates in engineering. The emphasis of the study is to determine academic variables that had significant correlations with graduation in engineering, and levels of these academic variables. The article also examines the utility of data mining methods for understanding the academic variables related to achievement in science, technology, engineering, and mathematics. The practical purpose …
The Engineering Admissions Partnership Program: A Navigation Strategy For Community College Students Seeking A Pathway Into Engineering, Marcia R. Laugerman, Mack C. Shelley, Steven K. Mickelson, Diane T. Rover
The Engineering Admissions Partnership Program: A Navigation Strategy For Community College Students Seeking A Pathway Into Engineering, Marcia R. Laugerman, Mack C. Shelley, Steven K. Mickelson, Diane T. Rover
Diane Rover
This paper presents the evaluation of a program designed to improve transfer outcomes for community college students pursuing an engineering degree. The program, the Engineering Admissions Partnership Program (E-APP), was designed to improve the navigational success of community college transfer students through connections to the university. These connections include coordinated academic advising, peer-mentoring, campus visits, and online social and professional networks. The objective of the study is to determine the efficacy of the E-APP and its interventions, which will be measured by increased participation rates and increased university retention rates for E-APP participants. Outcome data for the students are analyzed …
Statistical Models For Predicting College Success, Yelen Nunez
Statistical Models For Predicting College Success, Yelen Nunez
Yelen Nunez
Colleges base their admission decisions on a number of factors to determine which applicants have the potential to succeed. This study utilized data for students that graduated from Florida International University between 2006 and 2012. Two models were developed (one using SAT as the principal explanatory variable and the other using ACT as the principal explanatory variable) to predict college success, measured using the student’s college grade point average at graduation. Some of the other factors that were used to make these predictions were high school performance, socioeconomic status, major, gender, and ethnicity. The model using ACT had a higher …