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Jennifer L. Chiu; James P. Bywater; Tugba Karabiyik; Alejandra Magana; Corey Schimpf; Ying Ying Seah – Journal of Science Education and Technology, 2024
Despite an increasing focus on integrating engineering design in K-12 settings, relatively few studies have investigated how to support students to engage in systematic processes to optimize the designs of their solutions. Emerging learning technologies such as computational models and simulations enable rapid feedback to learners about their…
Descriptors: Engineering, Middle School Students, High School Students, Building Design
Mindorff, David – ProQuest LLC, 2023
Practical work involving laboratory experiments is agreed upon to be an essential component of secondary science education. Practical work encompasses a broad range of activity types. The different forms of practical work are not equal in terms of cognitive demand and learning benefit. Inquiry-based investigations provide experience of cognitive…
Descriptors: Secondary Education, Science Education, Biology, Information Retrieval
Hong Xiao – International Journal of Web-Based Learning and Teaching Technologies, 2024
Relying on the background of big data, this paper introduces the blended teaching model into the secondary vocational Japanese oral classroom and explores whether the teaching model is conducive to the improvement of the secondary vocational Japanese oral learning effect and teaching effect. In order to make this research more scientific and…
Descriptors: Foreign Countries, Japanese, Language Teachers, Data Processing
Cohausz, Lea; Tschalzev, Andrej; Bartelt, Christian; Stuckenschmidt, Heiner – International Educational Data Mining Society, 2023
Demographic features are commonly used in Educational Data Mining (EDM) research to predict at-risk students. Yet, the practice of using demographic features has to be considered extremely problematic due to the data's sensitive nature, but also because (historic and representation) biases likely exist in the training data, which leads to strong…
Descriptors: Information Retrieval, Data Processing, Pattern Recognition, Information Technology
Sainan Xu; Jing Lu; Jiwei Zhang; Chun Wang; Gongjun Xu – Grantee Submission, 2024
With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…
Descriptors: Educational Assessment, Bayesian Statistics, Statistical Inference, Item Response Theory
Turkkila, Miikka; Lavonen, Jari; Salmela-Aro, Katariina; Juuti, Kalle – Frontline Learning Research, 2022
Lately, new materialism has been proposed as a theoretical framework to better understand material-dialogic relationships in learning, and concurrently network analysis has emerged as a method in science education research. This paper explores how to include materiality in network analysis and reports the development of a method to construct…
Descriptors: Theories, Network Analysis, Science Education, Educational Research
Christine G. Casey, Editor – Centers for Disease Control and Prevention, 2024
The "Morbidity and Mortality Weekly Report" ("MMWR") series of publications is published by the Office of Science, Centers for Disease Control and Prevention (CDC), U.S. Department of Health and Human Services. Articles included in this supplement are: (1) Overview and Methods for the Youth Risk Behavior Surveillance System --…
Descriptors: High School Students, At Risk Students, Health Behavior, National Surveys
Bondaryk, Leslie G.; Hsi, Sherry; Van Doren, Seth – IEEE Transactions on Learning Technologies, 2021
Sensor systems have the potential to make abstract science phenomena concrete for K-12 students. Internet of Things (IoT) sensor systems provide a variety of benefits for modern classrooms, creating the opportunity for global data production, orienting learners to the opportunities and drawbacks of distributed sensor and control systems, and…
Descriptors: Internet, Systems Development, Computer Uses in Education, Secondary School Science
Esomonu, Nkechi Patricia-Mary; Esomonu, Martins Ndibem; Eleje, Lydia Ijeoma – International Journal of Evaluation and Research in Education, 2020
As a result of increasing complexity of assessing all aspects of human behaviours, a lot of data are generated on individual learner and from teachers and the system. What qualifies as big data in assessment in Nigeria? This research identifies the sources of assessment big data in Nigeria, investigates how the big data are generated and…
Descriptors: Foreign Countries, Expertise, Learning Analytics, Student Evaluation
Livieris, Ioannis E.; Drakopoulou, Konstantina; Tampakas, Vassilis T.; Mikropoulos, Tassos A.; Pintelas, Panagiotis – Journal of Educational Computing Research, 2019
Educational data mining constitutes a recent research field which gained popularity over the last decade because of its ability to monitor students' academic performance and predict future progression. Numerous machine learning techniques and especially supervised learning algorithms have been applied to develop accurate models to predict…
Descriptors: Secondary School Students, Academic Achievement, Teaching Methods, Student Behavior
Pangrazio, Luci; Selwyn, Neil – Pedagogy, Culture and Society, 2021
The ongoing 'datafication' of contemporary society has a number of implications for schools and schooling. One is the increasing calls for schools to help develop young people's understandings about the role that digital data now plays in their everyday lives -- especially in terms of the 'data economy' and 'surveillance capitalism'. Reporting on…
Descriptors: Data Collection, Data Analysis, Technology Uses in Education, Data Processing
Duprey, Michael A.; Pratt, Daniel J.; Wilson, David H.; Jewell, Donna M.; Brown, Derick S.; Caves, Lesa R.; Kinney, Satkartar K.; Mattox, Tiffany L.; Ritchie, Nichole Smith; Rogers, James E.; Spagnardi, Colleen M.; Wescott, Jamie D. – National Center for Education Statistics, 2020
This data file documentation accompanies new data files for the High School Longitudinal Study of 2009 (HSLS:09) Postsecondary Education Transcript Study and Student Financial Aid Records Collection (PETS-SR). HSLS:09 follows a nationally representative sample of students who were ninth-graders in fall 2009 from high school into postsecondary…
Descriptors: Longitudinal Studies, High School Students, Sampling, Data Collection
Avci, Esat; Coskuntuncel, Orkun – Pegem Journal of Education and Instruction, 2019
The purpose of this research is to examine the views of middle school mathematics teachers about the usability of VUstat and TinkerPlots software in data processing learning in the Curriculum of Mathematics Teaching in Middle School (5th, 6th, 7th and 8th grades). In the study, the phenomenology design from qualitative research patterns was…
Descriptors: Middle School Teachers, Mathematics Teachers, Teacher Attitudes, Computer Uses in Education
Liu, Ran; Stamper, John; Davenport, Jodi – Journal of Learning Analytics, 2018
Temporal analyses are critical to understanding learning processes, yet understudied in education research. Data from different sources are often collected at different grain sizes, which are difficult to integrate. Making sense of data at many levels of analysis, including the most detailed levels, is highly time-consuming. In this paper, we…
Descriptors: Intelligent Tutoring Systems, Learning, Data Analysis, Student Development
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