Learning analytics is a hot issue in education these days. You can educate all you want, in any way you want, but if you cannot measure the corresponding output (change) you have no idea if the process is effective and efficient. Learning analytics deals with the analysis of learner-produced data. If you have full insight in the data, you can use it to optimize learning and even predict how students will act according to learning patterns.
E-learning is an ideal tool for the purpose of learning analytics because software is capable of registering everything a student does. Registration is one thing, but presenting the data in such a way that it makes sense and useful to use is another.
The progress reports in our e-learning platform help teachers and other educational professionals with this issue. All data is stored in the database and can be retrieved in any desired way. From a macro-level (a general progress indicator or percentage for an entire course or school) to a micro-level (through replay-functionality it’s possible to reproduce specific exercises answered by a specific student, including the errors made). A teacher can choose which types of reports he or she desires in the ‘dashboard’. For example the top-5 of least successful students and the worst-scored exercises (as showed in the screenshot). Data can also be presented in different dimensions, through subject, student, over time, and so on.
Finally another interesting feature is that all content (exercises) are classified by means of ‘tags’. These tags indicate the subject or skills associated with a particular exercise. Reports on these tags will for example help a student or teacher to gain insight in which subjects are perceived most difficult. The teacher can adapt his or her (classroom-)education to the needs of the student with the help of this information. The same holds for the possible mistakes a student can make. These mistakes are also classified in different categories. These categories don’t have to be limited to a specific subject: addition errors can be made in all types of exercises, just as differentiation rules have to be applied in multiple mathematical sub-themes. Reports on the meta-data of mistakes made by students are very useful for teachers. It’s nice to know that 75% of all questions are answered correct, but it’s way more interesting to know what has gone wrong with the other 25%.
SOWISO’s e-learning platform is not only a tool for testing and learning, but also a tool for learning analytics!