Based on automatically collected data, MoMo helps users quickly and easily find “the best solution” – the best teaching material for a given course, for example.
Automatic data collection
With MoMo, users are free to concentrate on engaging in a teaching/learning process. The teacher can concentrate on preparing and delivering good courses, and the student can concentrate on the learning process and the actual learning activities s/he is presented with. MoMo automatically gathers information on the basis of how each person actually uses MoMo.
One feature of this is that a course is assessed as good if the teacher decides to re-use it. If the student achieves level of high learning progression, it is also an indication that the course is good. These indications stem directly and immediately from users’ actions.
Second-stage indications also undergo analysis. If a teaching aid is used in a good course, it is an indication that the particular material is also good. If a teaching aid is used in a process with a specific set of goals, it is an indication that the material is relevant to those particular objectives. If some learning objectives are used in a good process with a certain set of shared curriculum objectives, it is an indication that those particular objectives are good compared to that specific set of curriculum objectives. And so on.
Automatic statistical analysis
The collected data undergoes statistical analysis to identify correlations. This reveals data about which courses can be empirically shown to be good in terms of resulting in the highest levels of learning progression for most students, etc. Materials and learning objectives associated with particular courses are also analysed.
Automatically collected data from many users combined with automatic statistical analysis form the basis for MoMo’s ability to focus on and highlight “the best solution” quality for users.
When using MoMo, there is no need for time-consuming manual “tagging” and meta dating. Advanced, continuous analysis of the collected data automatically indexes all information, making it subsequently available for search and contextual suggestions.
MoMo provides individual users with ongoing relevant suggestions based on the current context – acting almost like “a good colleague”.
When a teacher is working on building a new course, MoMo highlights other similar existing courses that might be relevant either for inspiration or for re-use. MoMo also proposes appropriate learning objectives and relevant digital resources from existing, similar courses.