首页|Presuming Learner Personas from Portfolios with Non-negative Matrix Factorization
Presuming Learner Personas from Portfolios with Non-negative Matrix Factorization
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NETL
NSTL
In programming course, if a teacher gives supervisions inappropriate to motivation and learning strategy of the student who asked questions to the teacher, the student may get de-motivated. In order for the teacher to give supervisions appropriate to motivation and learning strategy of a student to motivate her to study programming, the paper proposes a method to figure out the weight a student belonging to a persona. Persona is a virtual user with motivation and learning strategy representing a group of students having similar motivation and learning strategy to learn programming. Persona gives the teacher a clear image of motivation and learning strategy in contexts of student groups before the course starts. A feature matrix P representing motivation and learning strategy characteristics of the personas are figured out, by decomposing the matrix of portfolio of last course students using nonnegative- matrix approximation method. Using P of the last course, we calculate the weight from the portfolio of the current course. The method is being under evaluation.
NETL
NSTL
