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Frischemeier, Daniel; Schnell, Susanne – Mathematics Education Research Journal, 2023
As data are 'numbers with context' (Cobb & Moore, 1997), contextual knowledge plays a prominent role in dealing with statistics. While insights about a specific context can further the depth of interpreting and evaluating outcomes of data analysis, research shows how it can also hinder relying on data especially if results differ from…
Descriptors: Elementary School Students, Context Effect, Data Analysis, Case Studies
Barollet, Théo; Bouchez Tichadou, Florent; Rastello, Fabrice – International Educational Data Mining Society, 2021
In Intelligent Tutoring Systems (ITS), methods to choose the next exercise for a student are inspired from generic recommender systems, used, for instance, in online shopping or multimedia recommendation. As such, collaborative filtering, especially matrix factorization, is often included as a part of recommendation algorithms in ITS. One notable…
Descriptors: Intelligent Tutoring Systems, Prediction, Internet, Purchasing
Fouh, Eric; Farghally, Mohammed; Hamouda, Sally; Koh, Kyu Han; Shaffer, Clifford A. – International Educational Data Mining Society, 2016
We present an analysis of log data from a semester's use of the OpenDSA eTextbook system with the goal of determining the most difficult course topics in a data structures course. While experienced instructors can identify which topics students most struggle with, this often comes only after much time and effort, and does not provide real-time…
Descriptors: Item Response Theory, Data Analysis, Mathematics, Intelligent Tutoring Systems
Rihák, Jirí; Pelánek, Radek – International Educational Data Mining Society, 2017
Educational systems typically contain a large pool of items (questions, problems). Using data mining techniques we can group these items into knowledge components, detect duplicated items and outliers, and identify missing items. To these ends, it is useful to analyze item similarities, which can be used as input to clustering or visualization…
Descriptors: Item Analysis, Data Analysis, Visualization, Simulation
Influence of Additive and Multiplicative Structure and Direction of Comparison on the Reversal Error
González-Calero, José Antonio; Arnau, David; Laserna-Belenguer, Belén – Educational Studies in Mathematics, 2015
An empirical study has been carried out to evaluate the potential of word order matching and static comparison as explanatory models of reversal error. Data was collected from 214 undergraduate students who translated a set of additive and multiplicative comparisons expressed in Spanish into algebraic language. In these multiplicative comparisons…
Descriptors: Error Patterns, Undergraduate Students, Spanish, Algebra
Thanheiser, Eva; Olanoff, Dana; Hillen, Amy; Feldman, Ziv; Tobias, Jennifer M.; Welder, Rachael M. – Journal of Mathematics Teacher Education, 2016
Mathematical task design has been a central focus of the mathematics education research community over the last few years. In this study, six university teacher educators from six different US institutions formed a community of practice to explore key aspects of task design (planning, implementing, reflecting, and modifying) in the context of…
Descriptors: Mathematics, Mathematics Instruction, Elementary School Teachers, Elementary School Mathematics
Zhou, Guojing; Wang, Jianxun; Lynch, Collin F.; Chi, Min – International Educational Data Mining Society, 2017
In this study, we applied decision trees (DT) to extract a compact set of pedagogical decision-making rules from an original "full" set of 3,702 Reinforcement Learning (RL)- induced rules, referred to as the DT-RL rules and Full-RL rules respectively. We then evaluated the effectiveness of the two rule sets against a baseline Random…
Descriptors: Learning Theories, Teaching Methods, Decision Making, Intelligent Tutoring Systems
Doabler, Christian T.; Clarke, Ben; Kosty, Derek; Turtura, Jessica E.; Firestone, Allison R.; Smolkowski, Keith; Jungjohann, Kathleen; Brafford, Tasia L.; Nelson, Nancy J.; Sutherland, Marah; Fien, Hank; Maddox, Steven A. – Exceptional Children, 2019
Well-designed mathematics instruction focused on concepts and problem-solving skills associated with measurement and data analysis can build a foundational understanding for more advanced mathematics. This study investigated the efficacy of the Precision Mathematics Level 1 (PM-L1) intervention, a Tier 2 print- and technology-based mathematics…
Descriptors: Mathematics Instruction, Problem Solving, Grade 1, Elementary School Students
Huang, Yun; González-Brenes, José P.; Kumar, Rohit; Brusilovsky, Peter – International Educational Data Mining Society, 2015
Latent variable models, such as the popular Knowledge Tracing method, are often used to enable adaptive tutoring systems to personalize education. However, finding optimal model parameters is usually a difficult non-convex optimization problem when considering latent variable models. Prior work has reported that latent variable models obtained…
Descriptors: Guidelines, Models, Prediction, Evaluation Methods
Pelánek, Radek; Rihák, Ji?rí – International Educational Data Mining Society, 2016
In online educational systems we can easily collect and analyze extensive data about student learning. Current practice, however, focuses only on some aspects of these data, particularly on correctness of students answers. When a student answers incorrectly, the submitted wrong answer can give us valuable information. We provide an overview of…
Descriptors: Foreign Countries, Online Systems, Geography, Anatomy
Ellis, Amy B.; Ozgur, Zekiye; Kulow, Torrey; Dogan, Muhammed F.; Amidon, Joel – Mathematical Thinking and Learning: An International Journal, 2016
This article presents an Exponential Growth Learning Trajectory (EGLT), a trajectory identifying and characterizing middle grade students' initial and developing understanding of exponential growth as a result of an instructional emphasis on covariation. The EGLT explicates students' thinking and learning over time in relation to a set of tasks…
Descriptors: Numbers, Mathematics, Mathematics Instruction, Middle School Students
Liu, Ran; Koedinger, Kenneth R. K – International Educational Data Mining Society, 2017
Research in Educational Data Mining could benefit from greater efforts to ensure that models yield reliable, valid, and interpretable parameter estimates. These efforts have especially been lacking for individualized student-parameter models. We collected two datasets from a sizable student population with excellent "depth" -- that is,…
Descriptors: Data Analysis, Intelligent Tutoring Systems, Bayesian Statistics, Pretests Posttests
National Assessment Governing Board, 2017
Since 1973, the National Assessment of Educational Progress (NAEP) has gathered information about student achievement in mathematics. Results of these periodic assessments, produced in print and web-based formats, provide valuable information to a wide variety of audiences. They inform citizens about the nature of students' comprehension of the…
Descriptors: Mathematics Tests, Mathematics Achievement, Mathematics Instruction, Grade 4
Pierce, Robyn; Chick, Helen – Mathematics Education Research Journal, 2013
As a consequence of the increased use of data in workplace environments, there is a need to understand the demands that are placed on users to make sense of such data. In education, teachers are being increasingly expected to interpret and apply complex data about student and school performance, and, yet it is not clear that they always have the…
Descriptors: Statistical Analysis, Misconceptions, Statistics, Data
Hunt, Jessica Heather; Tzur, Ron; Westenskow, Arla – Mathematical Thinking and Learning: An International Journal, 2016
The literature seems limited in what is known about conceptual processes that underlie evolution of students with learning disabilities (SLD) conceptions of fractions. This exploratory study examines how a foundational scheme of unit fractions (1/n) may evolve through the mathematical activity of two fifth grade girls. We analyze data segments…
Descriptors: Grade 5, Learning Disabilities, Mathematics, Mathematics Instruction