Agriculture
June 9, 2024
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Read SolutionImplemented by
TuvaTech
Product Description
M-Shule is an AI/SMS platform that analyzes the student progress and performance and provides personalized learning content to the user according to their abilities. The application has a machine learning algorithm that understands each individual child’s competency and delivers the right lesson for them at the right time. This product was developed by M-Shule.
Target SDGs
SDG 4: Quality Education
SDG 10: Reduced Inequalities
Target Users (Target Impact Group)
Household
Distributors / Implementing Organizations
M-Shule
Competitive Landscape
Direct competitors include KCPE Revision, Hadithi! Hadithi!, and M-Lugha.
Manufacturing/Building Method
N/A
Intellectural Property Type
Trademark
User Provision Model
Users have to send "MSHULE" to 40606 to get access to the services.
Distributions to Date Status
Unknown
Telecommunication service required
SMS
Level of connection service needed
GSM, 2G, 3G, 4G
Device(s) required
Basic Phone
Additional features required
None
Permanent network connectivity required (Y/N[specify],Other [specify])
No
Two way communication (Y/N)
Yes
Usage rate (%)
Unknown
Literacy support (Y (specify) /N)
Yes
Languages available (list)
English and Swahili
Operating system and version
Android
Power requirements
N/A
eEducation application
Education Provider
Design Specifications
M-Shule is an AI/SMS platform that analyzes the student progress and performance and provides personalized learning content to the user according to their abilities. The application has a variety of mini-lessons designed to help students in their study process. A machine learning algorithm analyzes the student progress and performance and delivers personalized lessons to the student through SMS. The application is built on top of Ruby on Rails and Laravel.
Product Schematics
Technical Support
Provided by the developers of the app.
Replacement Components
N/A
Lifecycle
N/A
Manufacturer Specified Performance Parameters
This product aims to improve the performance of students in Africa
Vetted Performance Status
No testing has been completed.
Safety
No known safety hazards are related to this product.
Complementary Technical Systems
N/A
Academic Research and References
Kehdinga, G., 2020. Theorising Machine Learning as an alternative pathway for higher education in Africa. International Journal of Education and Practice
“M-Shule.” n.d. Mshule.Com. Accessed June 11, 2024. https://www.mshule.com/
“Goal 4.” n.d. Sdgs.Un.Org. Accessed June 10, 2024. https://sdgs.un.org/goals/goal4
“M-Shule.” n.d. ZoomInfo. Accessed June 11, 2024. https://www.zoominfo.com/c/m–shule/449048374
Compliance with regulations
Unknown
Evaluation methods
Unknown
Other Information
More information in this video.
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