Processing Educational Data: From Traditional Statistical Techniques to an Appropriate Combination of Probabilistic, Interval, and Fuzzy Approaches
Olga M. Kosheleva, Martine C. Ceberio · scholarworks - UTEP (The University of Texas at El Paso) · 2005
Summary. There are many papers that experimentally compare effectiveness of different teaching techniques. Most of these papers use traditional statistical approach to process the experimental results. The traditional statistical approach is well suited to numerical data but often, what we are processing is either intervals (e.g., A means anything from 90 to 100) or fuzzy-type perceptions, words from the natural language like “understood well ” or ”understood reasonably well”. We show that the use of intervals and fuzzy techniques leads to more adequate processing of educational data. 1 Formulation of the Problem Practical problem: comparing teaching techniques. Teaching is very important, and teaching is not always very effective. There exist many different pedagogical techniques that help teach better, and new teaching techniques are being invented all the time. To select the techniques which are the most efficient for a given educational environment, we must experimentally compare effectiveness of different teaching techniques in this and similar