An intelligence system to manage teaching, learning and assessment more effectively and efficiently. SiSopen allows teachers in education to focus on the dream of the learners, rather than to fight against the deficit of learners, meaning that teachers will work with what they have, rather than complaining about what they don’t have.
Through the process of data decision-making, teachers in the system will be empowered to find solutions to problems that others have dealt with, through social networking and linking colleagues through the approach of connectivism.
The system uses the promotion schedules of the previous year to set the targets for each individual Learner taking into account their respective dream jobs
Is a questionnaire that each Learner completes which identifies a set of skills, experiences, relationships, and behaviors that enable young people to develop into successful and contributing adults
Each Learner should have a dream job which will assist with subject choices and targets to reach
The system uses the promotion marks to perform a risk analysis of learners’ performance, and projecting the level of performance of individual and grade groups of learners, at the beginning of the year as a forecasting exercise This will then assist the school leadership to put in place intervention strategies where the forecasted performance levels are not in line with the expected levels of performance
Has 6 levels of users which gives a unique ‘feel’ of data and information that is relevant to them, and how they can contribute to the success of every learner in the school system. The Portals are Principal, Learners, Parents, Teachers, HODs and Circuit Managers
Ensures that Learners receives the minimum of 170 teaching days per year
Data systems are focusing on depository functions of collecting data items or events out of context within not relation to other data in the same system,
Information systems are developing understanding between the relations of the data items and other information,
Knowledge systems attempts to understand the patterns among and between the data, information and possible other knowledge and,
An intelligent system, understands and recognizes that knowledge patterns arise from fundamental principles. And by understanding these deeper principles, we can influence the various data items to either ‘stay the same’ if we are happy with them, ‘change them’ if we are not happy with the results, and ‘replace them’ if we take on a new focus.