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Çibik, Naz Fulya; Boz-Yaman, Burçak – Science Activities: Projects and Curriculum Ideas in STEM Classrooms, 2022
The purpose of this paper is to integrate mathematical modeling and ecology by presenting an activity involving an authentic environmental problem, which is called "Pine Processionary Caterpillars Invasion." Adopting Mathematical Modeling and Education for Climate Action (EfCA) approaches, it was aimed to encourage pre-service teachers…
Descriptors: Mathematical Models, Ecology, Climate, Problem Solving
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Jupri, Al; Drijvers, Paul – EURASIA Journal of Mathematics, Science & Technology Education, 2016
To investigate student difficulties in solving word problems in algebra, we carried out a teaching experiment involving 51 Indonesian students (12/13 year-old) who used a digital mathematics environment. The findings were backed up by an interview study, in which eighteen students (13/14 year-old) were involved. The perspective of mathematization,…
Descriptors: Foreign Countries, Grade 7, Algebra, Word Problems (Mathematics)
Wang, Yutao; Heffernan, Neil T.; Heffernan, Cristina – Grantee Submission, 2015
The well-studied Baker et al., affect detectors on boredom, frustration, confusion and engagement concentration with ASSISTments dataset were used to predict state tests scores, college enrollment, and even whether a student majored in a STEM field. In this paper, we present three attempts to improve upon current affect detectors. The first…
Descriptors: Majors (Students), Affective Behavior, Psychological Patterns, Predictor Variables
Kerr, Deirdre Song – ProQuest LLC, 2014
Educational video games have the potential to be used as assessments of student understanding of complex concepts. However, the interpretation of the rich stream of complex data that results from the tracking of in-game actions is so difficult that it is one of the most serious blockades to the use of educational video games or simulations to…
Descriptors: Video Games, Educational Games, Data Collection, Data Analysis
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Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
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Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
Advanced Technology, Inc., Reston, VA. – 1984
The impact of data discrepancies made by colleges on the Fiscal Operations Report and Application to Participate (FISAP) is addressed, with attention to both impact on the entire aid program and resource allocation to institutions. Brief descriptions are provided of the allocation formulas for the three campus-based aid programs (Supplemental…
Descriptors: Computation, Data Collection, Error Patterns, Evaluation Criteria
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection