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Amy Adair; Michael Sao Pedro; Janice Gobert; Jessica A. Owens – Grantee Submission, 2023
Developing models and using mathematics are two key practices in internationally recognized science education standards such as the Next Generation Science Standards (NGSS, 2013). In this paper, we used a virtual performance-based formative assessment to capture students' competencies at both "developing" and "evaluating"…
Descriptors: Student Evaluation, Mathematical Models, Competence, Scientific Research
Matayoshi, Jeffrey; Uzun, Hasan; Cosyn, Eric – International Educational Data Mining Society, 2022
Knowledge space theory (KST) is a mathematical framework for modeling and assessing student knowledge. While KST has successfully served as the foundation of several learning systems, recent advancements in machine learning provide an opportunity to improve on purely KST-based approaches to assessing student knowledge. As such, in this work we…
Descriptors: Knowledge Level, Mathematical Models, Learning Experience, Comparative Analysis
Gruver, Nate; Malik, Ali; Capoor, Brahm; Piech, Chris; Stevens, Mitchell L.; Paepcke, Andreas – International Educational Data Mining Society, 2019
Understanding large-scale patterns in student course enrollment is a problem of great interest to university administrators and educational researchers. Yet important decisions are often made without a good quantitative framework of the process underlying student choices. We propose a probabilistic approach to modelling course enrollment…
Descriptors: Models, Course Selection (Students), Enrollment, Decision Making
Jazby, Dan; Pearn, Cath – Mathematics Education Research Group of Australasia, 2015
When viewed through a lens of embedded cognition, algorithms may enable aspects of the cognitive work of multi-digit multiplication to be "offloaded" to the environmental structure created by an algorithm. This study analyses four multiplication algorithms by viewing different algorithms as enabling cognitive work to be distributed…
Descriptors: Multiplication, Mathematics Activities, Mathematics Instruction, Cognitive Processes
Rollinson, Joseph; Brunskill, Emma – International Educational Data Mining Society, 2015
At their core, Intelligent Tutoring Systems consist of a student model and a policy. The student model captures the state of the student and the policy uses the student model to individualize instruction. Policies require different properties from the student model. For example, a mastery threshold policy requires the student model to have a way…
Descriptors: Prediction, Models, Educational Policy, Intelligent Tutoring Systems
Wilson, Tim; Barkatsas, Tasos – Mathematics Education Research Group of Australasia, 2014
This study investigates the relationship between students ability to answer reduced language dependency mathematical questions with their overall numeracy level. It investigates whether a student's success at reduced language mathematical questions translates into better overall numeracy scores. It was found, students have up to two years…
Descriptors: Numeracy, Grade 2, Mathematics Skills, Mathematics Instruction
Redmond, Trevor; Sheehy, Joanne; Brown, Raymond; Kanasa, Harry – Mathematics Education Research Group of Australasia, 2012
This paper seeks to compare the reflective writings of two cohorts of students (Year 4/5 and Year 8/9) participating in mathematical modelling challenges. Whilst the reflections of the younger cohort were results oriented, the older cohort's reflections spoke more to the affective domain, group processes, the use of technology and the acquisition…
Descriptors: Mathematical Models, Comparative Analysis, Reflection, Cohort Analysis

Prade, Henri; Testemale, Claudette – Journal of the American Society for Information Science, 1987
Compares and expands upon two approaches to dealing with fuzzy relational databases. The proposed similarity measure is based on a fuzzy Hausdorff distance and estimates the mismatch between two possibility distributions using a reduction process. The consequences of the reduction process on query evaluation are studied. (Author/EM)
Descriptors: Comparative Analysis, Databases, Information Retrieval, Mathematical Models
Edwards, Lynne K. – 1991
This study analytically examined the multiple comparison procedures for testing a combined set of planned and post hoc comparisons. To establish a practical guideline, the following issues were investigated: (1) when the generalized sequentially rejective Bonferroni method (GSRB) is and is not applicable; (2) the required alpha levels for the GSRB…
Descriptors: Comparative Analysis, Equations (Mathematics), Mathematical Models, Statistical Analysis
Millsap, Roger E.; Meredith, William – 1989
Conditional observed score (COS) and latent trait (LT) definitions of differential item functioning (DIF) are explored to determine when they are equivalent. COS methods rely solely on observed measurements, and LT methods model the response to an item as a function of an unobserved hypothetical latent ability or trait. For the case of dichotomous…
Descriptors: Comparative Analysis, Equations (Mathematics), Mathematical Models, Scores

Bookstein, A.; And Others – Information Processing & Management, 1994
Examines two models to study the consequences for coding efficiency of sample fluctuations, a specific type of error in the statistics on which data compression codes are based. The possibility that random fluctuation can be exploited for data compression is discussed. (six references) (KRN)
Descriptors: Coding, Comparative Analysis, Information Storage, Information Theory
Fan, Xitao – 1995
This paper, in a fashion easy to follow, illustrates the interesting relationship between structural equation modeling and canonical correlation analysis. Although computationally somewhat inconvenient, representing canonical correlation as a structural equation model may provide some information which is not available from conventional canonical…
Descriptors: Comparative Analysis, Correlation, Mathematical Models, Research Methodology
Algina, James; And Others – 1993
Type I error rates were estimated for three tests that compare means by using data from two independent samples: the independent samples t test, Welch's approximate degrees of freedom test, and James's second order test. Type I error rates were estimated for skewed distributions, equal and unequal variances, equal and unequal sample sizes, and a…
Descriptors: Comparative Analysis, Equations (Mathematics), Estimation (Mathematics), Mathematical Models
Kim, Gyenam; Edwards, Lynne K. – 1990
An integrated overview is provided of selected multiple comparison methods, with an emphasis on the sequentially rejective Bonferroni (SRB) test and its modifications. Multiple comparisons of means is a frequently used, and yet confusing, method in educational and psychological research. Seven multiple comparison methods are reviewed: (1) the…
Descriptors: Comparative Analysis, Equations (Mathematics), Mathematical Models, Research Methodology
Luh, Wei-Ming; Olejnik, Stephen – 1990
Two-stage sampling procedures for comparing two population means when variances are heterogeneous have been developed by D. G. Chapman (1950) and B. K. Ghosh (1975). Both procedures assume sampling from populations that are normally distributed. The present study reports on the effect that sampling from non-normal distributions has on Type I error…
Descriptors: Comparative Analysis, Mathematical Models, Power (Statistics), Sample Size