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Atsushi Miyaoka; Lauren Decker-Woodrow; Nancy Hartman; Barbara Booker; Erin Ottmar – Grantee Submission, 2023
More than ever in the past, researchers have access to broad, educationally relevant text data from sources such as literature databases (e.g., ERIC), an open-ended response from online courses/surveys, online discussion forums, digital essays, and social media. These advances in data availability can dramatically increase the possibilities for…
Descriptors: Coding, Models, Qualitative Research, Focus Groups
Tytler, Russell; Ferguson, Joseph; White, Peta – Learning: Research and Practice, 2020
Increasingly, learning in science and mathematics is considered in terms of induction into the multimodal language practices of the disciplinary community. A strong strand of research in this tradition has involved students being challenged to invent multimodal language forms, and their ideas refined through structured guidance. Often, however,…
Descriptors: Science Instruction, Mathematics Instruction, Inquiry, Teaching Methods
Fisher, Molly H.; Thomas, Jonathan; Schack, Edna O.; Jong, Cindy; Tassell, Janet – Mathematics Education Research Journal, 2018
This study examined the impact of an intervention, focused on professional noticing of children's conceptual development in whole number and arithmetic reasoning, on preservice elementary teachers' (PSETs') professional noticing skills, attitudes toward mathematics, and mathematical knowledge for teaching mathematics. A video-based professional…
Descriptors: Numeracy, Preservice Teachers, Intervention, Children
Aksoy, Esra; Narli, Serkan; Aksoy, Mehmet Akif – International Journal of Research in Education and Science, 2018
In the identification process, there may be gifted students who may be unnoticed or students who are misdiagnosed and are disappointed. In this context, this study is a step that may solve these two problems about the identification of mathematically gifted students with the help of data mining, which is data analysis methodology that has been…
Descriptors: Academically Gifted, Talent Identification, Data Collection, Mathematics Instruction
Koedinger, Kenneth R.; McLaughlin, Elizabeth A. – International Educational Data Mining Society, 2016
Many educational data mining studies have explored methods for discovering cognitive models and have emphasized improving prediction accuracy. Too few studies have "closed the loop" by applying discovered models toward improving instruction and testing whether proposed improvements achieve higher student outcomes. We claim that such…
Descriptors: Educational Research, Data Collection, Task Analysis, Cognitive Processes
Crossley, Scott; Barnes, Tiffany; Lynch, Collin; McNamara, Danielle S. – International Educational Data Mining Society, 2017
This study takes a novel approach toward understanding success in a math course by examining the linguistic features and affect of students' language production within a blended (with both on-line and traditional face to face instruction) undergraduate course (n=158) on discrete mathematics. Three linear effects models were compared: (a) a…
Descriptors: Success, Mathematics Instruction, Language Usage, Blended Learning
Liu, Ran; Koedinger, Kenneth R. – Journal of Educational Data Mining, 2017
As the use of educational technology becomes more ubiquitous, an enormous amount of learning process data is being produced. Educational data mining seeks to analyze and model these data, with the ultimate goal of improving learning outcomes. The most firmly grounded and rigorous evaluation of an educational data mining discovery is whether it…
Descriptors: Educational Technology, Technology Uses in Education, Data Collection, Data Analysis
Cafarella, Brian V. – Research & Teaching in Developmental Education, 2016
Due to poor student success rates in developmental mathematics, many institutions have implemented various forms of redesign into their developmental math curricula. Since the goal of redesign is to increase student success, it is salient to explore all aspects of the redesign process. Many studies have focused on the positive outcomes of redesign…
Descriptors: Misconceptions, Instructional Design, Developmental Programs, Mathematics Education
Tempelaar, Dirk T.; Rienties, Bart; Nguyen, Quan – IEEE Transactions on Learning Technologies, 2017
Studies in the field of learning analytics (LA) have shown students' demographics and learning management system (LMS) data to be effective identifiers of "at risk" performance. However, insights generated by these predictive models may not be suitable for pedagogically informed interventions due to the inability to explain why students…
Descriptors: Student Behavior, Integrated Learning Systems, Personality, Educational Research
Feng, Mingyu; Roschelle, Jeremy; Murphy, Robert; Heffernan, Neil – Grantee Submission, 2014
The field of learning analytics is rapidly developing techniques for using data captured during online learning. In this article, we develop an additional application: the use of analytics for improving implementation fidelity in a randomized controlled efficacy trial. In an efficacy trial, the goal is to determine whether an innovation has a…
Descriptors: Data Collection, Data Analysis, Intervention, Program Implementation
English, Lyn D. – Educational Studies in Mathematics, 2012
This paper argues for a renewed focus on statistical reasoning in the beginning school years, with opportunities for children to engage in data modelling. Results are reported from the first year of a 3-year longitudinal study in which three classes of first-grade children (6-year-olds) and their teachers engaged in data modelling activities. The…
Descriptors: Statistics, Science Curriculum, Mathematics Instruction, Data Analysis
Mendiburo, Maria; Williams, Laura; Segedy, James; Hasselbring, Ted – Society for Research on Educational Effectiveness, 2013
In this paper, the authors explore the use of learning analytics as a method for easing the cognitive demands on teachers implementing the HALF instructional model. Learning analytics has been defined as "the measurement, collection, analysis and reporting of data about learners and their contexts for the purposes of understanding and…
Descriptors: Educational Research, Data Collection, Data Analysis, Teaching Methods
Smith, Michael D. – PRIMUS, 2011
The purpose of this article is to present two very active applied modeling projects that were successfully implemented in a first semester calculus course at Hollins University. The first project uses a logistic equation to model the spread of a new disease such as swine flu. The second project is a human take on the popular article "Do Dogs Know…
Descriptors: Physical Activities, Calculus, Mathematics Instruction, College Mathematics
Oldknow, Adrian; Huyton, Pip; Galloway, Ian – School Science Review, 2010
Most students now have access to devices such as digital cameras and mobile phones that are capable of taking short video clips outdoors. Such clips can be used with powerful ICT tools, such as Tracker, Excel and TI-Nspire, to extract time and coordinate data about a moving object, to produce scattergrams and to fit models. In this article we…
Descriptors: Physics, Video Technology, Data Collection, Motion
Ozgun-Koca, S. Asli; Meagher, Michael; Edwards, Michael Todd – School Science and Mathematics, 2011
In this technology-oriented age, teachers face daily decisions regarding the use of advanced digital technologies--graphing calculators, dynamic geometry software, blogs, wikis, podcasts and the like--to enhance student mathematical understanding in their classrooms. In this case study, the authors use the Technological, Pedagogical, and Content…
Descriptors: Web Sites, Journal Writing, Electronic Publishing, Computer Uses in Education
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