The winning projects were School Eye by St Marys College Kisubi, TowerTVUg by Tororo Girls School, and #VimboScholar by St. Henry’s College, Kitovu.
NCC2022 has been organized by the College of Engineering, Design, Art and Technology (CEDAT), Makerere University, in collaboration with Uganda Communications Commission (UCC) and partners.Below is the YouTube St. Mary’s College Kisubi ICT Club Innovations 2022 Presentation
Poor/ inefficient supervision of syllabus coverage in schools on a countrywide scale as well as co-curricular activities such as clubs, games projects. However, through the development of the Project, other problems that are solved include; Inefficient system to assess students’ capabilities on an individual basis. Tedious registration of students both by UNEB and NIRA. High rates of dropouts. Poor co-ordination among schools. The major problem relates to the Sustainable Development Goal Four (SDG4) Quality Education which states; Ensure inclusive and equitable quality education and promote lifelong opportunities for all. The effect of this problem is that schools are not efficiently monitored as they offer education to the students.
The project entailed the design of an interface that contains an integrated syllabus for all classes where all schools shall be required to update the Ministry of Education and Sports on the coverage of curriculum, co-curricular such as games, clubs, practical skills and projects to be done by students. Inefficient teaching and poor-quality education is also tackled. The same interface connects financially needy students to sponsors from governments or Non- government Organizations thus lowering dropouts. Lastly, this interface integrates schools together in that schools shall connect to ministry easily for resource materials and possibly good co-ordination between the schools as they share materials. Thus, education will be more of learning rather than competing.
In terms of the innovative nature of this project, aptitude tests are done virtually by the best students of the school in order to assess the extent of syllabus coverage by the school and a measure that counteracts wrong data input in the system by the school is built in the system. Also basing on data from aptitude tests, a student’s future performance can be visualized as an estimate of in the final exams. Using of Machine learning, Artificial Intelligence (AI) can base on these estimations to suggest viable options for further studies.Download full detailed book of abstracts: