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Showing 1 to 15 of 18 results Save | Export
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Martin Abt; Katharina Loibl; Timo Leuders; Wim Van Dooren; Frank Reinhold – Educational Studies in Mathematics, 2025
In the boxplot, the box always represents -- regardless of its area -- the middle half of the data and thus a measure of variability (interquartile range). However, when students first learn about boxplots, they are usual already familiar with other forms of statistical representations (e.g., bar or circle graphs) in which a larger area represents…
Descriptors: College Students, Data Analysis, Graphs, Error Patterns
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Ge Bai – International Journal of Web-Based Learning and Teaching Technologies, 2025
This study focuses on the construction of the learner-centered teaching college English teaching mode under big data technology. Traditional college English teaching has issues, such as standardized teaching ignoring individual differences and lagging feedback. However, the development of big data technology offers opportunities for teaching…
Descriptors: Student Centered Learning, English Instruction, College Instruction, College Students
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Turcotte, Nate; Hollett, Ty – Information and Learning Sciences, 2023
Purpose: The datafication of teaching and learning settings continues to be of broad interest to the learning sciences. In response, this study aims to explore a non-traditional learning setting, specifically two Golf Teaching and Research Programs, to investigate how athletes and coaches capture, analyze and use performance data to improve their…
Descriptors: Athletic Coaches, Student Athletes, Athletics, Data Use
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Ana Stojanov; Ben Kei Daniel – Education and Information Technologies, 2024
The need for data-driven decision-making primarily motivates interest in analysing Big Data in higher education. Although there has been considerable research on the value of Big Data in higher education, its application to address critical issues within the sector is still limited. This systematic review, conducted in December 2021 and…
Descriptors: Higher Education, Learning Analytics, Well Being, Decision Making
Cheng, Diane – Postsecondary Value Commission, 2021
There are a number of ways that student investment can be measured, including full cost of attendance (COA, also known as sticker price), net price (COA minus grant aid), and opportunity costs in the form of forgone earnings. This paper explores those options and makes recommendations for how student investment should be measured with ideal data…
Descriptors: Measurement Techniques, Student Costs, Investment, College Students
Marcia Jean Ham – ProQuest LLC, 2021
Leveraging big data for student data analytics is increasingly integrated throughout university operations from admissions to advising to teaching and learning. Though the possibilities are exciting to consider, they are not without risks to student autonomy, privacy, equity, and educational value. There has been little research showing how…
Descriptors: Educational Policy, Personal Autonomy, Privacy, Equal Education
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Kai Li – International Association for Development of the Information Society, 2023
Assessing students' performance in online learning could be executed not only by the traditional forms of summative assessments such as using essays, assignments, and a final exam, etc. but also by more formative assessment approaches such as interaction activities, forum posts, etc. However, it is difficult for teachers to monitor and assess…
Descriptors: Student Evaluation, Online Courses, Electronic Learning, Computer Literacy
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Travis, Tiffini A.; Ramirez, Christian – portal: Libraries and the Academy, 2020
Libraries remain one of the last places on campus where the purging of usage data is encouraged and "tracking" is a dirty word. While some libraries have demonstrated the usefulness of analytics, opponents bring up issues of privacy and debate the feasibility of student-generated library data for planning and assessment. Using a study…
Descriptors: Academic Libraries, Data Collection, Learning Analytics, Ethics
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Odiri, Amatari Veronica – Education Quarterly Reviews, 2019
The primary objective of the study is to examine the level of awareness and usage of data triangulation among under and post graduates in the tertiary institution. A descriptive survey was adopted and data collected from a sample of 114 selected randomly. A self-developed and validated instrument was used to collect data. Data collected were…
Descriptors: Foreign Countries, College Students, Data Use, Data Analysis
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De Silva, Liyanachchi Mahesha Harshani; Chounta, Irene-Angelica; Rodríguez-Triana, María Jesús; Roa, Eric Roldan; Gramberg, Anna; Valk, Aune – Journal of Learning Analytics, 2022
Although the number of students in higher education institutions (HEIs) has increased over the past two decades, it is far from assured that all students will gain an academic degree. To that end, institutional analytics (IA) can offer insights to support strategic planning with the aim of reducing dropout and therefore of minimizing its negative…
Descriptors: College Students, Dropouts, Dropout Prevention, Data Analysis
Isaac, James; Velez, Erin; Roberson, Amanda Janice – Institute for Higher Education Policy, 2023
Students, families, colleges, and lawmakers need clearer information on postsecondary outcomes to make informed decisions. By leveraging data available at institutions and federal agencies, a nationwide student-level data network (SLDN) would close information gaps that persist in our higher education landscape to answer critical questions about…
Descriptors: College Students, Data, Information Networks, Program Design
Singer-Freeman, Karen; Robinson, Christine – National Institute for Learning Outcomes Assessment, 2020
A number of national and international organizations have compiled lists of grand challenges to unify the efforts of scholars and practitioners in a field. Unified efforts increase the possibility of creating meaningful and lasting progress. In this paper we share ten grand challenges that were identified through an examination of the assessment…
Descriptors: Higher Education, College Outcomes Assessment, Innovation, Budgeting
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Van Wart, Sarah; Lanouette, Kathryn; Parikh, Tapan S. – Journal of the Learning Sciences, 2020
Data increasingly mediates how we understand the world. As such, there is growing interest in designing initiatives to help young people learn about data--not only the techno-mathematical skills necessary to work with data, but also the dispositions needed to participate in data-centric ways of knowing and doing. In this article, we argue that as…
Descriptors: Data, Social Problems, Data Collection, Data Use
Maldonado, Monica; Mugglestone, Konrad; Roberson, Amanda Janice – Institute for Higher Education Policy, 2021
Data-informed decision-making has always been -- and always will be -- a smart approach to policy, including at institutions of higher education. Just over one year since the COVID-19 pandemic radically and abruptly shifted every aspect of higher education, states and institutions are tackling the same student success goals as before, but with…
Descriptors: Data Analysis, Learning Analytics, Decision Making, Higher Education
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Zilvinskis, John – Journal of Postsecondary Education and Disability, 2020
Each year hundreds of institutions will administer national surveys to measure the engagement of their students. However, stakeholders on college campuses, such as educators (faculty, instructors, student affairs educators, and disability services administrators) and institutional research staff who work with this information are often unaware of…
Descriptors: Students with Disabilities, Data Collection, Data Use, Student Needs
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