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Zhang, Zhidong – International Education Studies, 2018
This study explored a diagnostic assessment method that emphasized the cognitive process of algebra learning. The study utilized a design and a theory-driven model to examine the content knowledge. Using the theory driven model, the thinking skills of algebra learning was also examined. A Bayesian network model was applied to represent the theory…
Descriptors: Algebra, Bayesian Statistics, Scores, Mathematics Achievement
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Ting, Mu Yu – EURASIA Journal of Mathematics, Science & Technology Education, 2017
Using the capabilities of expert knowledge structures, the researcher prepared test questions on the university calculus topic of "finding the area by integration." The quiz is divided into two types of multiple choice items (one out of four and one out of many). After the calculus course was taught and tested, the results revealed that…
Descriptors: Calculus, Mathematics Instruction, College Mathematics, Multiple Choice Tests
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Smail, Linda – Journal on Mathematics Education, 2017
Mathematics is the foundation of all sciences, but most students have problems learning math. Although students' success in life related to their success in learning, many would not take a math course unless it is their university's core requirements. Multiple reasons exist for students' poor performance in mathematics, but one prevalent variable…
Descriptors: Bayesian Statistics, Study Habits, Personality Traits, Mathematics Anxiety
Tang, Steven; Gogel, Hannah; McBride, Elizabeth; Pardos, Zachary A. – International Educational Data Mining Society, 2015
Online adaptive tutoring systems are increasingly being used in classrooms as a way to provide guided learning for students. Such tutors have the potential to provide tailored feedback based on specific student needs and misunderstandings. Bayesian knowledge tracing (BKT) is used to model student knowledge when knowledge is assumed to be changing…
Descriptors: Intelligent Tutoring Systems, Difficulty Level, Bayesian Statistics, Models
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Pittayachawan, Siddhi; Macauley, Peter; Evans, Terry – Journal of Higher Education Policy and Management, 2016
This article reports how statistical analyses of PhD thesis records can reveal future research capacities for disciplines beyond their primary fields. The previous research showed that most theses contributed to and/or used methodologies from more than one discipline. In Australia, there was a concern for declining mathematical teaching and…
Descriptors: Databases, Doctoral Dissertations, Foreign Countries, Statistical Analysis
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Wulff, Shaun S.; Robinson, Timothy J. – Journal of Statistics Education, 2014
Bayesian methodology continues to be widely used in statistical applications. As a result, it is increasingly important to introduce students to Bayesian thinking at early stages in their mathematics and statistics education. While many students in upper level probability courses can recite the differences in the Frequentist and Bayesian…
Descriptors: Bayesian Statistics, Probability, College Mathematics, Mathematics Instruction
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Geary, David C.; vanMarle, Kristy – Developmental Psychology, 2016
At the beginning of preschool (M = 46 months of age), 197 (94 boys) children were administered tasks that assessed a suite of nonsymbolic and symbolic quantitative competencies as well as their executive functions, verbal and nonverbal intelligence, preliteracy skills, and their parents' education level. The children's mathematics achievement was…
Descriptors: Young Children, Mathematics, Mathematics Achievement, Mathematics Education
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Azevedo, Ana, Ed.; Azevedo, José, Ed. – IGI Global, 2019
E-assessments of students profoundly influence their motivation and play a key role in the educational process. Adapting assessment techniques to current technological advancements allows for effective pedagogical practices, learning processes, and student engagement. The "Handbook of Research on E-Assessment in Higher Education"…
Descriptors: Higher Education, Computer Assisted Testing, Multiple Choice Tests, Guides
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Käser, Tanja; Busetto, Alberto Giovanni; Solenthaler, Barbara; Baschera, Gian-Marco; Kohn, Juliane; Kucian, Karin; von Aster, Michael; Gross, Markus – International Journal of Artificial Intelligence in Education, 2013
This study introduces a student model and control algorithm, optimizing mathematics learning in children. The adaptive system is integrated into a computer-based training system for enhancing numerical cognition aimed at children with developmental dyscalculia or difficulties in learning mathematics. The student model consists of a dynamic…
Descriptors: Mathematics Instruction, Children, Computer Assisted Instruction, Educational Technology
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Kooken, Janice; Welsh, Megan E.; McCoach, D. Betsy; Johnston-Wilder, Sue; Lee, Clare – Measurement and Evaluation in Counseling and Development, 2016
The Mathematical Resilience Scale measures students' attitudes toward studying mathematics, using three correlated factors: Value, Struggle, and Growth. The Mathematical Resilience Scale was developed and validated using exploratory and confirmatory factor analyses across three samples. Results provide a new approach to gauge the likelihood of…
Descriptors: Mathematics, Mathematics Instruction, Student Attitudes, Thinking Skills
Pardos, Zachary A.; Heffernan, Neil T. – International Working Group on Educational Data Mining, 2009
Researchers who make tutoring systems would like to know which sequences of educational content lead to the most effective learning by their students. The majority of data collected in many ITS systems consist of answers to a group of questions of a given skill often presented in a random sequence. Following work that identifies which items…
Descriptors: Data Analysis, Bayesian Statistics, Statistical Analysis, Problem Sets
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Shaughnessy, J. Michael; Dick, Thomas – Mathematics Teacher, 1991
Included are probability models for various strategies that contestants on the television game show, "Let's-Make-a-Deal," might use when given the option to stick with their original choice of three unopened doors or switch to the unopened door after one of the other two doors has been opened. (JJK)
Descriptors: Bayesian Statistics, Elementary Secondary Education, High Schools, Mathematical Models