Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Teaching Robotics Programming via Mobile Learning Apps in Rural Ethiopia: Skills Development Impacts

Domaine:

education
Créateur:
Asf
Éditeur:
Zenodo
Hôte:avatar
This study addresses a current research gap in Computer Science concerning Teaching Robotics Programming to Rural Ethiopian Youth via Mobile Learning Apps: Skills Development Outcomes in Ethiopia. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Teaching Robotics Programming to Rural Ethiopian Youth via Mobile Learning Apps: Skills Development Outcomes, Ethiopia, Africa, Computer Science, comparative study This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.

Visit

doi.orgzenodo.org

Languages

Amharic

Tags

EthiopiaGeographic Information SystemsMobile LearningRobotics EducationTechnological IntegrationParticipatory Action ResearchPedagogical Innovation

Licenses

Creative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

Similaires

Mobile Learning Apps in Science Instruction: Student Outcomes in Rural Tanzanian Secondary SchoolsMobile Learning for Programming Education: A Case Study of SoloLearn and Self-Directed Learning SkillsAdoption and Impacts of Mobile Agriculture Apps on Food Security in Ethiopian Villages,Development of Mobile-Interfaced Machine Learning-Based Predictive Models for Improving Students Performance in Programming CoursesThe Usefulness of Mobile Compilers for Learning Computer ProgrammingMobile Apps in Rural South Africa: Adherence and Outcomes for Tuberculosis Treatment Monitoring

Mobile Learning Apps in Science Instruction: Student Outcomes in Rural Tanzanian Secondary Schools

Mobile learning applications have gained popularity in recent years as a tool for enhancing

Mobile Learning for Programming Education: A Case Study of SoloLearn and Self-Directed Learning Skills

This study investigates how mobile learning supports self-directed learning (SDL) in programming edu

Adoption and Impacts of Mobile Agriculture Apps on Food Security in Ethiopian Villages,

Mobile agriculture apps have gained attention as a tool for enhancing food security in rura

Development of Mobile-Interfaced Machine Learning-Based Predictive Models for Improving Students Performance in Programming Courses

Student performance modelling (SPM) is a critical step to assessing and improving students performan

The Usefulness of Mobile Compilers for Learning Computer Programming

This study examines the usefulness of mobile compilers for learning computer programming in higher l

Mobile Apps in Rural South Africa: Adherence and Outcomes for Tuberculosis Treatment Monitoring

Mobile apps have gained traction in healthcare monitoring worldwide, particularly for chron