Publication Date
| In 2025 | 0 |
| Since 2024 | 3 |
Descriptor
Author
| Aamir Wali | 1 |
| Achim J. Lilienthal | 1 |
| Constantinos Christou | 1 |
| Demetra Pitta-Pantazi | 1 |
| Eleni Demosthenous | 1 |
| Habiba Akram | 1 |
| Jen Weiss | 1 |
| Jim Burke | 1 |
| Lukas Baumanns | 1 |
| Maike Schindler | 1 |
| Phillip A. Morris | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 3 |
| Reports - Research | 2 |
| Information Analyses | 1 |
Education Level
| Higher Education | 2 |
| Postsecondary Education | 2 |
| Early Childhood Education | 1 |
| Elementary Education | 1 |
| Grade 1 | 1 |
| Primary Education | 1 |
Audience
Location
Laws, Policies, & Programs
| G I Bill | 1 |
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkLukas Baumanns; Demetra Pitta-Pantazi; Eleni Demosthenous; Achim J. Lilienthal; Constantinos Christou; Maike Schindler – International Journal of Science and Mathematics Education, 2024
Recognizing patterns is an essential skill in early mathematics education. However, first graders often have difficulties with tasks such as extending patterns of the form ABCABC. Studies show that this pattern-recognition ability is a good predictor of later pre-algebraic skills and mathematical achievement in general, or the development of…
Descriptors: Pattern Recognition, Grade 1, Elementary School Students, Mathematics Education
Download full textPhillip A. Morris; Jim Burke; Jen Weiss – Journal of Student Financial Aid, 2024
This study examined the relationship between individual and institutional characteristics for student veterans who borrow money while enrolled in degree-seeking programs. Using data from the National Postsecondary Student Aid Study (NPSAS 16), we established predictors of borrowing, implications of borrowing, and examined patterns in total aid…
Descriptors: Veterans, Student Financial Aid, Nontraditional Students, Individual Characteristics
Zareen Alamgir; Habiba Akram; Saira Karim; Aamir Wali – Informatics in Education, 2024
Educational data mining is widely deployed to extract valuable information and patterns from academic data. This research explores new features that can help predict the future performance of undergraduate students and identify at-risk students early on. It answers some crucial and intuitive questions that are not addressed by previous studies.…
Descriptors: Data Analysis, Information Retrieval, Content Analysis, Information Technology
