Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Mathematical Modeling: Problem Solving01:29

Mathematical Modeling: Problem Solving

214
Mathematical modeling transforms real-world scenarios into mathematical expressions, allowing for structured problem-solving and analysis. This process involves defining the situation, assigning variables to measurable quantities, selecting an appropriate model, and solving the resulting equation. Such models are invaluable in finance, providing precise methods to evaluate investments, loans, and repayment structures.A widely used example is the calculation of fixed monthly payments on a loan,...
214
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

466
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
466

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Prevalence and Determinants of Breastfeeding Duration Among Women of Reproductive Age in a Fragile Setting: A Survival Analysis Using Demographic and Health Survey Data.

Clinical nutrition ESPEN·2026
Same author

A pediatric case of measles with gastrointestinal complications in an urban hospital setting: A clinical and public health perspective.

IDCases·2026
Same author

Surgical site infection prevention among surgical healthcare workers in Syria: a nationwide cross-sectional study.

Antimicrobial resistance and infection control·2026
Same author

Determinants of BCG vaccine coverage among 0-2 months aged Somali children: Promoting equality in vaccination.

Human vaccines & immunotherapeutics·2026
Same author

From pulsed disturbance to steady-state mixing: Succession of microbial ecological strategies in the estuarine ecosystem.

Water research·2026
Same author

Tracking progress towards sustainable development goal 3.2 in Somalia using time series models: a comparative forecasting analysis.

Conflict and health·2026

Related Experiment Video

Updated: Jan 7, 2026

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA
10:58

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

Published on: August 28, 2021

4.9K

Supervised machine learning models for predicting student mathematics performance in Somaliland primary examinations

Mukhtar Abdi Hassan1, Abdisalam Hassan Muse1, Saralees Nadarajah2

  • 1Faculty of Science and Humanities, School of Postgraduate Studies and Research (SPGSR) , Amoud University, Borama, 25263, Somalia.

Scientific Reports
|January 3, 2026
PubMed
Summary

Declining math performance in Somaliland primary schools is linked to regional, sex, and school-type disparities. The Naive Bayes machine learning model effectively predicted performance, offering insights for targeted educational interventions.

Keywords:
Logistic regressionMachine learningMathematical performancePrediction

More Related Videos

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

5.2K

Related Experiment Videos

Last Updated: Jan 7, 2026

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA
10:58

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

Published on: August 28, 2021

4.9K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

5.2K

Area of Science:

  • Educational Data Mining
  • Machine Learning in Education
  • Somaliland Primary Education

Background:

  • Mathematics performance among primary school students in Somaliland shows a concerning decline, with failure rates rising from 51.9% in 2020 to 65.58% in 2023.
  • Significant regional and demographic disparities influence student outcomes, with specific regions and school types exhibiting higher failure rates.

Purpose of the Study:

  • To compare the effectiveness of six supervised machine learning models in predicting primary school students' mathematics performance.
  • To identify key factors contributing to disparities in mathematics achievement in Somaliland.

Main Methods:

  • Utilized data from the 2022/2023 Somaliland National Examinations, encompassing 20,950 students.
  • Applied and evaluated six supervised machine learning models: logistic regression, decision tree, random forest, Naïve Bayes, support vector machine (SVM), and K-Nearest Neighbors (KNN).
  • Assessed model performance using metrics including accuracy, sensitivity, specificity, F1-score, and AUC.

Main Results:

  • The Naïve Bayes model demonstrated the highest prediction accuracy (98.6%), followed by the K-Nearest Neighbors (KNN) model (80.3%).
  • Significant performance disparities were observed across regions (e.g., Awdal, Maroodi Jeeh vs. Sheekh, Sanaag), sex (males higher failure rate), and school type (urban schools underperforming rural schools).
  • SVM showed the least effectiveness, while Random Forest and Logistic Regression yielded moderate results.

Conclusions:

  • Regional, sex, and school-type factors significantly impact mathematics performance among Somaliland primary students.
  • The Naïve Bayes model is the most effective for predicting mathematics performance in this context.
  • Findings provide crucial insights for developing targeted interventions to enhance educational outcomes in mathematics.