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Lottridge, Sue; Burkhardt, Amy; Boyer, Michelle – Educational Measurement: Issues and Practice, 2020
In this digital ITEMS module, Dr. Sue Lottridge, Amy Burkhardt, and Dr. Michelle Boyer provide an overview of automated scoring. Automated scoring is the use of computer algorithms to score unconstrained open-ended test items by mimicking human scoring. The use of automated scoring is increasing in educational assessment programs because it allows…
Descriptors: Computer Assisted Testing, Scoring, Automation, Educational Assessment
Senter, Mary Scheuer – Honors in Practice, 2020
Engaging students in assessment practice benefits honors students, faculty, and administrators. Students gain meaningful research experience while honors programs receive data to help assess student learning and prepare for program review. A one-semester course, Program Evaluation Experiences, tasks students (n = 10) with collecting and analyzing…
Descriptors: Undergraduate Students, Honors Curriculum, Student Research, Data Collection
Ford, Karly; Rosinger, Kelly; Zhu, Qiong – Educational Researcher, 2020
One ethnoracial reporting category perplexes higher education researchers: "race and ethnicity unknown." Using the Integrated Postsecondary Education Data System (IPEDS), we constructed a 28-year panel of 4,401 institutions. We find that the for-profit sector ranges from 5% to 18% "race unknown" students. In addition, almost…
Descriptors: Racial Identification, Institutional Characteristics, Higher Education, Enrollment Trends
Heritage, Margaret – Educational Assessment, 2020
This concluding essay offers a reflection on the set of the papers contained in this special issue of the Educational Assessment journal. In it the author situates formative assessment squarely in the realm of teachers' continuous professional learning and considers the essential nature of formative assessment as centering on three questions that…
Descriptors: Formative Evaluation, Professional Continuing Education, Faculty Development, Educational Objectives
Vartiainen, Henriikka; Tedre, Matti; Kahila, Juho; Valtonen, Teemu – Educational Media International, 2020
While much has been written about the personal, social, and democratic benefits of networked communities and participatory learning, critics have begun to draw attention to the ubiquitous data collection and computational processes behind mass user platforms. Personal and behavioral data have become valuable material for statistical and machine…
Descriptors: Social Networks, Participation, Artificial Intelligence, Ethics
Sullivan, Alice – International Journal of Social Research Methodology, 2020
The UK census authorities have proposed guidance for the 2021 census indicating that the sex question may be answered according to subjective gender identity. This raises issues about the measurement of sex and gender identity which other data collection exercises are also contending with. This paper addresses the questions that have arisen…
Descriptors: Foreign Countries, National Surveys, Census Figures, Test Items
Kane, Maggie; King, Carlise – Early Childhood Data Collaborative, 2020
While home visiting services are an important component of the early childhood (EC) landscape, few states include home visiting data in their early childhood integrated data systems (ECIDS). An ECIDS links together data from different early care and education programs to generate data used to support program and policy decisions. One reason for…
Descriptors: Home Visits, Early Intervention, Young Children, Data Collection
Balgalmis, Esra; Temiz, Zeynep – Journal of Inquiry Based Activities, 2018
This study aimed to investigate pre-service pre-school education teachers' data representation activities in terms of their relation to real life, the appropriateness of the data that the children can collect, the conformability of the graphs required for the data representation to the children's level, and the clarity of open-ended questions…
Descriptors: Preservice Teachers, Preschool Teachers, Data, Visual Aids
Aguilar, Stephen J. – Journal of Research on Technology in Education, 2018
This qualitative study focuses on capturing students' understanding two visualizations often utilized by learning analytics-based educational technologies: bar graphs, and line graphs. It is framed by Achievement Goal Theory--a prominent theory of students' academic motivation--and utilizes interviews (n = 60) to investigate how students at risk…
Descriptors: Comparative Analysis, Visualization, At Risk Students, College Students
Apfeldorf, Michael – Social Education, 2018
Big data analysis involves the examination of large sets of data in order to uncover patterns and trends. Within the social studies or history classroom, such analyses can be effective for gaining insights into historical trends over time or across geographical regions. For instance, using simple technology tools, students can perform word…
Descriptors: Data Collection, Data Analysis, Social Studies, Geographic Regions
Bruhn, Allison L.; McDaniel, Sara C.; Rila, Ashley; Estrapala, Sara – Beyond Behavior, 2018
Students who are at risk for or show low-intensity behavioral problems may need targeted, Tier 2 interventions. Often, Tier 2 problem-solving teams are charged with monitoring student responsiveness to intervention. This process may be difficult for those who are not trained in data collection and analysis procedures. To aid practitioners in these…
Descriptors: Progress Monitoring, Behavior Problems, Student Behavior, At Risk Students
Moodie, Nikki; Ewen, Shaun; McLeod, Julie; Platania-Phung, Chris – Higher Education Research and Development, 2018
Over the last decade, there has been a steady increase in the number of Indigenous graduate research students in Australia, yet research and pedagogy has not kept pace with changes underway in the sector. From an extensive search of literature published between 2000 and 2017, 15 papers (representing 10 research projects conducted by seven teams or…
Descriptors: Foreign Countries, Indigenous Populations, Graduate Students, Educational Research
Wilks, Judith; Kennedy, Gillian; Drew, Neil; Wilson, Katie – Australian Universities' Review, 2018
In the Australian higher education sector, the challenges to successful engagement and retention experienced by Aboriginal and/or Torres Strait Islander students and communities are considerable. They persist despite many well-intentioned attempts to address this issue and to strengthen equity in participation in the sector. Implicated in this is…
Descriptors: Foreign Countries, Indigenous Populations, Academic Persistence, Higher Education
Niemi, David, Ed.; Pea, Roy D., Ed.; Saxberg, Bror, Ed.; Clark, Richard E., Ed. – IAP - Information Age Publishing, Inc., 2018
This book provides a comprehensive introduction by an extraordinary range of experts to the recent and rapidly developing field of learning analytics. Some of the finest current thinkers about ways to interpret and benefit from the increasing amount of evidence from learners' experiences have taken time to explain their methods, describe examples,…
Descriptors: Educational Research, Data Collection, Data Analysis, Educational Benefits
Chen, Bodong; Zhang, Jianwei – Journal of Learning Analytics, 2016
Innovation and knowledge creation call for high-level epistemic agency and design-mode thinking, two competencies beyond the traditional scopes of schooling. In this paper, we discuss the need for learning analytics to support these two competencies, and more broadly, the demand for education for innovation. We ground these arguments on a…
Descriptors: Epistemology, Educational Research, Data Collection, Data Analysis

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