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Australian Government Tertiary Education Quality and Standards Agency, 2024
The Australian Government Tertiary Education Quality and Standards Agency's (TEQSA's) guidance notes are concise documents designed to provide high-level, principles-based guidance on interpretation and application of specific standards of the Higher Education Standards Framework (Threshold Standards) 2021. They also draw attention to other…
Descriptors: Foreign Countries, Instructional Improvement, Quality Assurance, Data Collection
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Natasha Arthars; Kate Thompson; Henk Huijser; Steven Kickbusch; Samuel Cunningham; Gavin Winter; Roger Cook; Lori Lockyer – Australasian Journal of Educational Technology, 2024
Assessing group work formatively in higher education poses a significant challenge. The complexity of evaluating individual contributions is compounded by the lack of efficient and effective methods for tracking, analysing and assessing individual engagement and contributions, which can impede timely feedback and the development of group work…
Descriptors: Formative Evaluation, Cooperative Learning, College Students, Student Evaluation
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Gray, Cameron C.; Perkins, Dave; Ritsos, Panagiotis D. – Assessment & Evaluation in Higher Education, 2020
The field of learning analytics is progressing at a rapid rate. New tools, with ever-increasing number of features and a plethora of datasets that are increasingly utilized demonstrate the evolution and multifaceted nature of the field. In particular, the depth and scope of insight that can be gleaned from analysing related datasets can have a…
Descriptors: Educational Research, Data Collection, Data Analysis, Visual Aids
Moore, Colleen; Bracco, Kathy Reeves; Nodine, Thad; Esch, Camille; Grubb, Brock – Education Insights Center, 2019
California does not have a statewide data system that tracks student progress through K-12 and higher education and into the workforce. As a result, educators and policymakers cannot answer critical questions about student progress, which limits their ability to make evidence-based changes to support better and more equitable opportunities for…
Descriptors: Progress Monitoring, Data Collection, Elementary Secondary Education, Higher Education
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Thiry, Heather; Zahner, Dana Holland; Weston, Timothy; Harper, Raquel; Loshbaugh, Heidi – Change: The Magazine of Higher Learning, 2023
Vertical transfer from community college to a university offers a promising, although unrealized, pathway to diversify STEM disciplines. Studying how successful transfer-­receiving universities support STEM transfer students can offer insights into the institutional practices that promote transfer student retention and success. Using institutional…
Descriptors: College Transfer Students, STEM Education, College Role, Student Needs
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Cano, Alberto; Leonard, John D. – IEEE Transactions on Learning Technologies, 2019
Early warning systems have been progressively implemented in higher education institutions to predict student performance. However, they usually fail at effectively integrating the many information sources available at universities to make more accurate and timely predictions, they often lack decision-making reasoning to motivate the reasons…
Descriptors: Progress Monitoring, At Risk Students, Disproportionate Representation, Underachievement
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Knight, Rupert; Sullivan, Stefanie – Journal of Education for Teaching: International Research and Pedagogy, 2022
Initial Teacher Education (ITE) is inherently complex. Challenges include the uncertain nature of teacher knowledge, the need to learn in both practical and theoretical contexts and the developmental journey of the beginning teacher. While one response to this complexity is greater standardisation, another is to foster thinking, autonomous…
Descriptors: Preservice Teacher Education, Teacher Education Programs, Elementary Secondary Education, Preservice Teachers
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Love, Hailey R.; Horn, Eva; An, Zhe – Teacher Education and Special Education, 2019
Making data-based decisions is a pervasive expectation for educators and is linked to improved outcomes for students. Observational data collection for progress monitoring, in particular, can help educators track and support students' progress toward individualized educational goals in inclusive settings. Yet, many educators struggle with data…
Descriptors: Teaching Methods, Data Collection, Observation, Early Childhood Teachers
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Ahn, Jeong Yong; Mun, Gil Seong; Han, Kyung Soo; Choi, Sook Hee – Education and Information Technologies, 2017
As higher education increasingly relies on e-learning, the need for tools that will allow teachers themselves to develop effective e-learning objects as simply and quickly as possible has also been increasingly recognized. This article discusses the design and development of a novel tool, Enook (Evolutionary note book), for creating activity-based…
Descriptors: Higher Education, Programming, Electronic Learning, Educational Technology
Parnell, Amelia; Jones, Darlena; Wesaw, Alexis; Brooks, D. Christopher – EDUCAUSE, 2018
As higher education institutions in the United States strive to maximize their use of resources to better support students, it is critical for professionals to make data-informed decisions. Most institutions are currently gathering an abundance of data from multiple sources, which provides a good opportunity for functional units, divisions, and…
Descriptors: College Students, Colleges, Data Analysis, Data Collection
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Barret, Mandy; Branson, Lisa; Carter, Sheryl; DeLeon, Frank; Ellis, Justin; Gundlach, Cirrus; Lee, Dale – Inquiry, 2019
Artificial intelligence (AI) technology is becoming the basis for business. Most businesses use it to improve the customer experience. The education community is just beginning to find ways to successfully implement AI for staff and students. Artificial Intelligence should be leveraged to create a better student experience. For example, Elon…
Descriptors: Artificial Intelligence, Technology Uses in Education, Higher Education, Educational Opportunities
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Wagner, Dana L.; Hammerschmidt-Snidarich, Stephanie M.; Espin, Christine A.; Seifert, Kathleen; McMaster, Kristen L. – Learning Disabilities Research & Practice, 2017
Teachers must be proficient at using data to evaluate the effects of instructional strategies and interventions, and must be able to make, describe, justify, and validate their data-based instructional decisions to parents, students, and educational colleagues. An important related skill is the ability to accurately read and interpret…
Descriptors: Preservice Teachers, Progress Monitoring, Curriculum Based Assessment, Teacher Competencies
Moore, Colleen; Bracco, Kathy Reeves; Nodine, Thad – Education Insights Center, 2017
California collects expansive sets of data about students in its public K-12 and higher education systems--data that, collectively, have great potential to meet the information needs of state policymakers, local educators, and other stakeholders. But the data are collected and maintained in systems that are not connected, were designed for…
Descriptors: Student Records, Data Collection, Progress Monitoring, College Students
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Santoso, Harry B.; Batuparan, Alivia Khaira; Isal, R. Yugo K.; Goodridge, Wade H. – Journal of Educators Online, 2018
Student Centered e-Learning Environment (SCELE) is a Moodle-based learning management system (LMS) that has been modified to enhance learning within a computer science department curriculum offered by the Faculty of Computer Science of large public university in Indonesia. This Moodle provided a mechanism to record students' activities when…
Descriptors: Case Studies, Educational Environment, Student Centered Learning, Electronic Learning
Miller, Cynthia; Cohen, Benjamin; Yang, Edith; Pellegrino, Lauren – MDRC, 2020
College students have a better chance of succeeding in school when they receive high-quality advising. High-quality advising, when characterized by frequent communications between advisers and students, early outreach to students showing signs of academic or nonacademic struggles, and personalized guidance that addresses individual student needs,…
Descriptors: College Students, Academic Advising, Technology Uses in Education, Faculty Advisers
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