Publication Date
| In 2026 | 0 |
| Since 2025 | 1 |
| Since 2022 (last 5 years) | 5 |
| Since 2017 (last 10 years) | 6 |
| Since 2007 (last 20 years) | 7 |
Descriptor
Source
| British Journal of… | 1 |
| Educational Studies in… | 1 |
| International Educational… | 1 |
| International Journal of… | 1 |
| Journal of Education and… | 1 |
| Journal of Statistics and… | 1 |
| North American Chapter of the… | 1 |
Author
| A. Gobbi | 1 |
| A. Raffaele | 1 |
| Abdennabi Lakrim | 1 |
| Biza, Irene | 1 |
| Bouazza El Wahbi | 1 |
| Chao, Jie | 1 |
| Cosyn, Eric | 1 |
| Cuevas-Vallejo, Carlos A. | 1 |
| E. Taranto | 1 |
| Finzer, William | 1 |
| G. Colajanni | 1 |
| More ▼ | |
Publication Type
| Reports - Research | 6 |
| Journal Articles | 5 |
| Speeches/Meeting Papers | 2 |
| Multilingual/Bilingual… | 1 |
| Opinion Papers | 1 |
Education Level
| Secondary Education | 7 |
| High Schools | 3 |
| Grade 10 | 1 |
| Higher Education | 1 |
| Junior High Schools | 1 |
| Middle Schools | 1 |
| Postsecondary Education | 1 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Abdennabi Lakrim; Mohamed Chergui; Bouazza El Wahbi – Journal of Education and Learning (EduLearn), 2025
This study is a contribution to efforts to promote practices for dealing with the difficulties encountered by learners in probabilistic modeling situations. We attempt to elucidate as precisely as possible the types of difficulties that secondary school students face in the process of modeling with probability tools. By referring to a large and…
Descriptors: Probability, Difficulty Level, Correlation, Classification
Jiang, Shiyan; Nocera, Amato; Tatar, Cansu; Yoder, Michael Miller; Chao, Jie; Wiedemann, Kenia; Finzer, William; Rosé, Carolyn P. – British Journal of Educational Technology, 2022
To date, many AI initiatives (eg, AI4K12, CS for All) developed standards and frameworks as guidance for educators to create accessible and engaging Artificial Intelligence (AI) learning experiences for K-12 students. These efforts revealed a significant need to prepare youth to gain a fundamental understanding of how intelligence is created,…
Descriptors: High School Students, Data, Artificial Intelligence, Mathematical Models
E. Taranto; G. Colajanni; A. Gobbi; M. Picchi; A. Raffaele – International Journal of Mathematical Education in Science and Technology, 2024
Operations Research (OR) is a branch of applied mathematics that deals with optimization problems arising from different real contexts. The solving process of its problems is based on the construction and resolution of mathematical models, showing the possible connections between mathematics and the real world. Nevertheless, OR is not typically…
Descriptors: Problem Solving, Cooperative Learning, Information Technology, Mathematics Instruction
Pérez Martínez, Helen Mariel; Cuevas-Vallejo, Carlos A.; Islas Ortiz, Erasmo; Orozco-Santiago, José – North American Chapter of the International Group for the Psychology of Mathematics Education, 2022
In this paper, we present the development of an investigation on the promotion of covariational reasoning in high school students (14-15 years old) in Mexico. The study consists of designing and applying a sequence of didactic activities that simulate a real situation virtually. The activities are organized through a Hypothetical Learning…
Descriptors: Thinking Skills, Mathematics Instruction, High School Students, Learning Trajectories
Zieffler, Andrew; Justice, Nicola; delMas, Robert; Huberty, Michael D. – Journal of Statistics and Data Science Education, 2021
Statistical modeling continues to gain prominence in the secondary curriculum, and recent recommendations to emphasize data science and computational thinking may soon position algorithmic models into the school curriculum. Many teachers' preparation for and experiences teaching statistical modeling have focused on probabilistic models.…
Descriptors: Mathematical Models, Thinking Skills, Teaching Methods, Statistics Education
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
Nardi, Elena; Biza, Irene; Zachariades, Theodossios – Educational Studies in Mathematics, 2012
In this paper, we propose an approach to analysing teacher arguments that takes into account field dependence--namely, in Toulmin's sense, the dependence of warrants deployed in an argument on the field of activity to which the argument relates. Freeman, to circumvent issues that emerge when we attempt to determine the field(s) that an argument…
Descriptors: Classification, Mathematics Teachers, Teaching Methods, Mathematics

Peer reviewed
Direct link
