TY - JOUR
T1 - Bayesian estimation for assessment based learning ICT
AU - Alvarez-Cedillo, J.
AU - Herrera-Lozada, J.
AU - Sandoval-Gutierrez, J.
AU - Olguin-Carbajal, M.
AU - Hernandez-Bolaños, M.
AU - Rivera-Zarate, I. L.
AU - Alvarez-Sanchez, T.
AU - Cadena-Martinez, R.
N1 - Publisher Copyright:
© 2005 - 2015 JATIT & LLS. All rights reserved.
PY - 2015
Y1 - 2015
N2 - Incorporating Information Technology and Communication (ICT) in education improves the level with sophisticated tools to increase a competence system in education. Bayes theorem is valid in all applications of the probability theory. In essence, the followers of traditional statistical probabilities only support repeatable experiments and have empirical confirmation while so-called Bayesian statistics allow subjective probabilities. The theorem can then serve to indicate how our subjective probabilities should be modified when receiving additional information from an experiment. Bayesian statistics prove their utility in certain estimates based on the subjective prior knowledge and reviews these estimates based on the empirical evidence. This feature is opening up new ways of understanding. This situation has had a strong tendency envisioned by offering new interpersonal communication systems worldwide and obtains and provides information of all kinds, instantaneously. This paper shows the tests performed in a study to measure learning under a Bayesian approach.
AB - Incorporating Information Technology and Communication (ICT) in education improves the level with sophisticated tools to increase a competence system in education. Bayes theorem is valid in all applications of the probability theory. In essence, the followers of traditional statistical probabilities only support repeatable experiments and have empirical confirmation while so-called Bayesian statistics allow subjective probabilities. The theorem can then serve to indicate how our subjective probabilities should be modified when receiving additional information from an experiment. Bayesian statistics prove their utility in certain estimates based on the subjective prior knowledge and reviews these estimates based on the empirical evidence. This feature is opening up new ways of understanding. This situation has had a strong tendency envisioned by offering new interpersonal communication systems worldwide and obtains and provides information of all kinds, instantaneously. This paper shows the tests performed in a study to measure learning under a Bayesian approach.
KW - Bayesian algorithms
KW - Bayesian statistics
KW - Education
KW - Information technology and communication
KW - Learning
UR - http://www.scopus.com/inward/record.url?scp=84925307813&partnerID=8YFLogxK
M3 - Artículo
SN - 1992-8645
VL - 73
SP - 290
EP - 295
JO - Journal of Theoretical and Applied Information Technology
JF - Journal of Theoretical and Applied Information Technology
IS - 2
ER -