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Jeff Schiel – ACT Education Corp., 2024
Disparities in technology access currently exist for adults, but do they also exist for high school students? If so, might the disparities have lessened since ACT first investigated this matter? This study examined high school students' access at home and school to four types of technological devices (desktop computers, laptop computers, tablets,…
Descriptors: High School Students, Student Attitudes, Access to Internet, Access to Computers
Edwards, John; Hart, Kaden; Shrestha, Raj – Journal of Educational Data Mining, 2023
Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…
Descriptors: Data Analysis, Computer Science Education, Learning Analytics, Research Methodology
Payne, J. Scott; San Pedro, Sweet Z.; Moore, Raeal; Sanchez, Edgar I. – ACT, Inc., 2020
High-stakes, standardized testing plays an important role in the lives of many students as they apply to college and compete for scholarships. In states where college readiness measures, like the ACT® test, are used for school and district accountability, the ACT scores of all students, whether college-bound or not, are a top priority for school…
Descriptors: Test Preparation, Testing Programs, State Programs, School Districts
Phillips, Andrea; Pane, John F.; Bogart, Andy – RAND Corporation, 2018
The Kentucky Valley Educational Cooperative and Green River Regional Educational Cooperative received an Investing in Innovation (i3) development grant from the U.S. Department of Education to implement the Creating College and Career Readiness (C3R) initiative. The initiative offered a suite of software developed by WIN Learning (WIN) to support…
Descriptors: Career Readiness, College Readiness, Program Effectiveness, Program Evaluation
Corwin, Z.; Maruco, T.; Bernstein, S.; Galan, C.; Rocha, C. – Pullias Center for Higher Education, 2018
High schools today have a unique challenge: to equip students with the knowledge and tools they need to prepare for, apply to and enroll in college--all while proving them with digital resources and skills essential for the 21st century. This guide by the Pullias Center's Digital Equity in Education team provides a general overview of what a…
Descriptors: High School Students, Information Sources, College Applicants, College Attendance
McArdle, John J.; Paskus, Thomas S.; Boker, Steven M. – Multivariate Behavioral Research, 2013
This is an application of contemporary multilevel regression modeling to the prediction of academic performances of 1st-year college students. At a first level of analysis, the data come from N greater than 16,000 students who were college freshman in 1994-1995 and who were also participants in high-level college athletics. At a second level of…
Descriptors: Multivariate Analysis, Multiple Regression Analysis, Hierarchical Linear Modeling, College Athletics
Reisel, John R.; Jablonski, Marissa; Hosseini, Hossein; Munson, Ethan – International Journal of Mathematical Education in Science and Technology, 2012
A summer bridge program for incoming engineering and computer science freshmen has been used at the University of Wisconsin-Milwaukee from 2007 to 2010. The primary purpose of this program has been to improve the mathematics course placement for incoming students who initially place into a course below Calculus I on the math placement examination.…
Descriptors: Academic Achievement, Engineering, Computer Science, Calculus