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Bendikson, Linda; Meyer, Frauke; Le Fevre, Deidre – set: Research Information for Teachers, 2020
School goal setting is often described as a key leadership practice for school improvement. Important for the effectiveness of goal setting is the close monitoring of progress. This article examines goal-monitoring practices in three schools that were seen as being effective and contributing to improvement. The findings highlight the importance of…
Descriptors: Educational Improvement, Goal Orientation, Progress Monitoring, Educational Strategies
Williams, Peter – European Journal of Special Needs Education, 2020
Inclusive research with people with learning disabilities often involves audio-recording interviews. However, although barely acknowledged in the literature, participants may not understand that every word recorded will be scrutinised forensically, from which possibly erroneous conclusions may be drawn. This paper describes an alternative method:…
Descriptors: Participatory Research, Inclusion, Learning Disabilities, Data Collection
Gorard, Stephen – International Journal of Social Research Methodology, 2020
Social science datasets usually have missing cases, and missing values. All such missing data has the potential to bias future research findings. However, many research reports ignore the issue of missing data, only consider some aspects of it, or do not report how it is handled. This paper rehearses the damage caused by missing data. The paper…
Descriptors: Data, Research Problems, Social Science Research, Statistical Analysis
Lenz, A. Stephen – Measurement and Evaluation in Counseling and Development, 2020
A guide for professional counselors and counseling researchers for calculating and interpreting Percent Improvement as an indicator of clinical significance is provided. Strategies for reporting findings are described and illustrated. Guidelines for contextualizing discussions of clinical significance within the boundaries of psychometric evidence…
Descriptors: Counseling, Research, Computation, Improvement
Petteway, Ryan J. – Health Education & Behavior, 2020
April is National Minority Health Month in the United States. The first week of April is National Public Health Week. This year, both occasions passed as the COVID-19 pandemic unfolded and, in the process, rendered remarkably clear the magnitude of the United States' collective shortcomings in advancing population health equity--particularly as…
Descriptors: COVID-19, Pandemics, Public Health, Justice
Fisher, Aidan A. E. – Journal of Chemical Education, 2020
The drive in computational methods and more intuitive software has seen a rise in the number of publications in this area in recent years. Computational simulations can be found in many areas of science from computational biology and chemistry to fundamental physics. These may help synthetic chemists in their drug discovery endeavors and…
Descriptors: Chemistry, Computation, Kinetics, Computer Software
Maio, Shannon; Dumas, Denis; Organisciak, Peter; Runco, Mark – Creativity Research Journal, 2020
In recognition of the capability of text-mining models to quantify aspects of language use, some creativity researchers have adopted text-mining models as a mechanism to objectively and efficiently score the Originality of open-ended responses to verbal divergent thinking tasks. With the increasing use of text-mining models in divergent thinking…
Descriptors: Creative Thinking, Scores, Reliability, Data Analysis
Fahrenbach, Florian; Revoredo, Kate; Santoro, Flavia Maria – European Journal of Training and Development, 2020
Purpose: This paper aims to introduce an information and communication technology (ICT) artifact that uses text mining to support the innovative and standardized assessment of professional competences within the validation of prior learning (VPL). Assessment means comparing identified and documented professional competences against a standard or…
Descriptors: Prior Learning, Competence, Information Retrieval, Data Analysis
Kuha, Jouni; Mills, Colin – Sociological Methods & Research, 2020
It is widely believed that regression models for binary responses are problematic if we want to compare estimated coefficients from models for different groups or with different explanatory variables. This concern has two forms. The first arises if the binary model is treated as an estimate of a model for an unobserved continuous response and the…
Descriptors: Comparative Analysis, Regression (Statistics), Research Problems, Computation
Nakagawa, Yoshifumi; Verlie, Blanche; Kim, Misol – Australian Journal of Environmental Education, 2020
In this article, we collectively explore the significance of engaging with theory in environmental education research. Inspired by Jackson and Mazzei's (2011) postqualitative research methodology, each researcher provides a short sample of engaging with his/her chosen theoretical concept for one shared data source. Through our three individual…
Descriptors: Environmental Education, Educational Research, Educational Theories, Research Methodology
Blair, Morgan; Zanidean, Alex – Strategic Enrollment Management Quarterly, 2020
Data interpretation can be difficult. Data visualization techniques from the manufacturing industry make interpretation easier. Control charts display trends in context, so it is clear when performance is truly changing and when it is not. Decision makers know when to act, when to maintain, and when to celebrate. This article discusses the use of…
Descriptors: Enrollment Management, Decision Making, Data Interpretation, Visualization
McKay, Heather; Lane, Patrick; Haviland, Sara; Michael, Suzanne – Western Interstate Commission for Higher Education, 2020
The Multistate Longitudinal Data Exchange (MLDE) facilitates data sharing between states from K-12 education, higher education, and labor agencies. Its goal is to provide practitioners, policymakers, and researchers with a comprehensive data source to understand educational and career trajectories, including how these trajectories can cross state…
Descriptors: Credentials, Postsecondary Education, Interstate Programs, Data Use
Burgos, Daniel, Ed. – Lecture Notes in Educational Technology, 2020
Learning Analytics become the key for Personalised Learning and Teaching thanks to the storage, categorisation and smart retrieval of Big Data. Thousands of user data can be tracked online via Learning Management Systems, instant messaging channels, social networks and other ways of communication. Always with the explicit authorisation from the…
Descriptors: Learning Analytics, Individualized Instruction, Integrated Learning Systems, Data Collection
Brahman, Faeze; Varghese, Nikhil; Bhat, Suma; Chaturvedi, Snigdha – International Educational Data Mining Society, 2020
Despite several advantages of online education, lack of effective student-instructor interaction, especially when students need timely help, poses significant pedagogical challenges. Motivated by this, we address the problems of automatically identifying posts that express confusion or urgency from Massive Open Online Course (MOOC) forums. To this…
Descriptors: Automation, Online Courses, Discussion Groups, Identification
Aran Wells Glancy – ProQuest LLC, 2020
Preparing students to use and consume data both inside and outside of school is an important goal in mathematics, science, and engineering education, but even basic data analysis tasks can quickly become complex. Planning and designing classroom data analysis tasks that support students' learning of statistical principals requires an understanding…
Descriptors: Engineering Education, Science Education, Elementary School Students, Grade 5

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