Competency 5.2

Competency 5.2: Understand core uses of prediction modeling in education.

Prediction modelling in education is the process of applying statistical techniques in examining education data with the intention of constructing a model to infer (predict) one perspective of the data from some combination of other perspectives of the data.

Educators are able to leverage on insights from “prediction models” to analyse learners’ behavior traits as they interact during the learning process and left as data in some databases of the learning community.  “Learning Models”, when appropriately applied, would “infer” certain aspects of the learners and fuel as insight to educators to:

• Design course content which impacts positively to learners;
• Introduce automatic software to provide instant help/assistant to learners as and when necessary during the learning interactions;
• Prompt teachers of at-risk students for necessary follow up and/or intervention.

My ideas in using prediction modeling for education:

1. Predict future career path and train accordingly:

If we are able to predict the future career path of students based on their interests in subjects, we can give more field-level training. That kind of education will be more meaningful to students to gain the skills required in the industry. Students will also be more interested to learn what they like, rather than being forced upon to learn something they don't prefer.

2. Provide help for weak students:

Not all students require the same amount of help to understand the subject. Some students may learn easier than others. If we predict the different possible points where students may find difficulties, we can provide help in the specific areas.

3. Identify competencies:

If we can identify the competencies of students and what they lack, we can provide more guidance in that area. For example, a student does his work perfectly and exhibits good leadership, but doesn't practice teamwork, we can guide him to learn teamwork competency better.