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Feng, Luxi; Lindner, Amanda; Ji, Xuejun Ryan; Malatesha Joshi, R. – Reading and Writing: An Interdisciplinary Journal, 2019
According to the simple view of writing (Berninger, Abbott, Abbott, Graham, & Richards, 2002), the two important components of transcription in writing are handwriting and keyboarding, the third one being spelling. The purpose of this paper is to review the contribution of two writing modes--handwriting and keyboarding to writing performance.…
Descriptors: Handwriting, Keyboarding (Data Entry), Correlation, Writing Skills
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Hernández-Leo, Davinia; Martinez-Maldonado, Roberto; Pardo, Abelardo; Muñoz-Cristóbal, Juan A.; Rodríguez-Triana, María J. – British Journal of Educational Technology, 2019
The field of "learning design" studies how to support teachers in devising suitable activities for their students to learn. The field of "learning analytics" explores how data about students' interactions can be used to increase the understanding of learning experiences. Despite its clear synergy, there is only limited and…
Descriptors: Instructional Design, Data Analysis, Guidelines, Decision Making
Agarwal, Nikhil; Somaini, Paulo J. – National Bureau of Economic Research, 2019
Preferences for schools are important determinants of equitable access to high-quality education, effects of expanded choice on school improvement and school choice mechanism design. Standard methods for estimating consumer preferences are not applicable in education markets because students do not always get their first choice school. This review…
Descriptors: School Choice, Models, Educational Quality, Data Analysis
Colorado Department of Education, 2019
The Colorado Growth Model (CGM) was developed jointly by the Colorado Department of Education (CDE), the Technical Advisory Panel for Longitudinal Growth (TAP), and the National Center for the Improvement of Educational Assessment (NCIEA). Its development was required by state statute (SB09-163) and assigned to the Technical Advisory Panel. The…
Descriptors: Growth Models, Elementary Secondary Education, Accountability, Academic Achievement
Selent, Douglas; Patikorn, Thanaporn; Heffernan, Neil – Grantee Submission, 2016
In this paper, we present a dataset consisting of data generated from 22 previously and currently running randomized controlled experiments inside the ASSISTments online learning platform. This dataset provides data mining opportunities for researchers to analyze ASSISTments data in a convenient format across multiple experiments at the same time.…
Descriptors: Intelligent Tutoring Systems, Data, Randomized Controlled Trials, Electronic Learning
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Wonsavage, F. Paul – Mathematics Teacher: Learning and Teaching PK-12, 2022
Quadratic modeling problems are commonplace in high school mathematics courses; they typically situate quadratic patterns of change and their corresponding parabolic graph within real-world contexts. Traditional approaches to this type of problem lend themselves to making connections across different representations (e.g., Garofalo and Trinter…
Descriptors: Mathematics Instruction, Secondary School Mathematics, Problem Solving, High School Students
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Yong, Binbin; Jiang, Xuetao; Lin, Jiayin; Sun, Geng; Zhou, Qingguo – Educational Technology & Society, 2022
Deep learning (DL), as the core technology of artificial intelligence (AI), has been extensively researched in the past decades. However, practical DL education needs large marked datasets and computing resources, which is generally not easy for students at school. Therefore, due to training datasets and computing resources restrictions, it is…
Descriptors: Electronic Learning, Artificial Intelligence, Shared Resources and Services, Instructional Materials
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Lu, Chang; Macdonald, Rob; Odell, Bryce; Kokhan, Vasyl; Demmans Epp, Carrie; Cutumisu, Maria – Journal of Computing in Higher Education, 2022
The field of computational thinking (CT) is developing rapidly, reflecting its importance in the global economy. However, most empirical studies have targeted CT in K-12, thus, little attention has been paid to CT in higher education. The present scoping review identifies and summarizes existing empirical studies on CT assessments in…
Descriptors: Computation, Thinking Skills, Higher Education, Educational Trends
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Pellegrini, Mason – Journal of Technical Writing and Communication, 2022
Fierce competition has made innovation increasingly necessary for business success, and this has increased the importance of user-based innovation strategies like design thinking (DT). While many studies in technical and professional communication (TPC) have explored how DT can be used pedagogically, no studies have done this through investigating…
Descriptors: Teaching Methods, Design, Thinking Skills, Web Sites
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Yang, Yuqin; Zhu, Gaoxia; Sun, Daner; Chan, Carol K. K. – International Journal of Computer-Supported Collaborative Learning, 2022
Helping pre-service teachers (PSTs) develop competencies in collaborative inquiry and knowledge building is crucial, but this subject remains largely unexplored in CSCL. This study examines the design and process of collaborative analytics-supported reflective assessment and its effects on promoting PSTs to develop their competencies in…
Descriptors: Preservice Teachers, Knowledge Level, Cognitive Mapping, Learning Processes
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Wise, Kit; MacDonald, Abbey; Badham, Marnie; Brown, Natalie; Rankin, Scott – Australian Educational Researcher, 2022
The role of interdisciplinarity in achieving authentic and transformative learning outcomes is both contested and complex. At the same time, traditional disciplinary ways of being, doing and knowing have been further tested by the impact of COVID-19 on students, schools and communities. In Tasmania, already experiencing amongst the lowest levels…
Descriptors: Interdisciplinary Approach, Social Justice, Outcomes of Education, Pandemics
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Nejstgaard, Camilla Hansen; Lundh, Andreas; Abdi, Suhayb; Clayton, Gemma; Gelle, Mustafe Hassan Adan; Laursen, David Ruben Teindl; Olorisade, Babatunde Kazeem; Savovic, Jelena; Hróbjartsson, Asbjørn – Research Synthesis Methods, 2022
Randomised trials are often funded by commercial companies and methodological studies support a widely held suspicion that commercial funding may influence trial results and conclusions. However, these studies often have a risk of confounding and reporting bias. The risk of confounding is markedly reduced in meta-epidemiological studies that…
Descriptors: Medical Research, Randomized Controlled Trials, Corporations, Financial Support
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Held, Leonhard; Matthews, Robert; Ott, Manuela; Pawel, Samuel – Research Synthesis Methods, 2022
It is now widely accepted that the standard inferential toolkit used by the scientific research community--null-hypothesis significance testing (NHST)--is not fit for purpose. Yet despite the threat posed to the scientific enterprise, there is no agreement concerning alternative approaches for evidence assessment. This lack of consensus reflects…
Descriptors: Bayesian Statistics, Statistical Inference, Hypothesis Testing, Credibility
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Helsabeck, Nathan P.; Justice, Laura M.; Logan, Jessica A. R. – Journal of Computer Assisted Learning, 2022
Background: Process data, data generated by a user's interaction with a web-based application, is an emerging tool in educational research. The current study explores using process data as a measure of implementation fidelity to a randomized control trial (RCT) of the Read It Again Mobile (RIA-M) curricular supplement. Objectives: To determine the…
Descriptors: Fidelity, Program Implementation, Early Intervention, Handheld Devices
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Bornn, Luke; Mortensen, Jacob; Ahrensmeier, Daria – Canadian Journal for the Scholarship of Teaching and Learning, 2022
This paper presents a novel design for an upper-level undergraduate statistics course structured around data rather than methods. The course is designed around curated datasets to reflect real-world data science practice and engages students in experiential and peer learning using the data science competition platform Kaggle. Peer learning is…
Descriptors: Undergraduate Study, Cooperative Learning, Peer Influence, Undergraduate Students
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