The Design of Web-learning Navigator Based on Artificial Psychology

Adaptive social network sites (ASNS) are an innovative approach to a web learning experience delivery. They try to solve the main shortcomings of classical social networks—“one-size-fits-all” approach and “lost-in-hyperspace” phenomena—by adapting the learning content and its presentation to needs, goals, thinking styles, and learning styles of every individual learner. This chapter outlines a new approach to automatically detect learners' thinking and learning styles, and takes into account that thinking and learning styles may change during the learning process in unexpected and unpredictable ways. The approach is based on the Felder learning styles model and Hermann thinking styles model.

Download Full-text

Modeling Learner's Cognitive Abilities in the Context of a Web-Based Learning Environment

End-User Computing ◽

10.4018/978-1-59904-945-8.ch043 ◽

2008 ◽

pp. 544-561

Author(s):

Maria Aparecida M. Souto ◽

Regina Verdin ◽

José Palazzo M. de Oliveira

Keyword(s):

Learning Environment ◽

Cognitive Abilities ◽

Target Population ◽

Learning Trajectory ◽

Web Based ◽

Experimental Learning ◽

Stage Development ◽

Two Phases ◽

The Individual ◽

Web Learning

Our study is concerned with making the instruction suitable to the individual learner’s characteristics. This chapter describes the methodology used to investigate how to model the learner’s Cognitive Ability Level (CAL) based on the observation and analysis of his/her behaviour in a Web-learning environment. In our study, the CAL represents the learner’s cognitive stage development according to Bloom’s taxonomy. The methodology encompasses two phases: (i) the generation of the CAL classes for the target population and (ii) the study of learning trajectories of CAL classes in an experimental learning module. As a result, we have identified the CAL classes’ parametersvalues that best discriminate these classes from the observation and analysis of their learning trajectory on the Web. The entire knowledge obtained from this investigation will make possible to automate the learners’ CAL diagnostic. It will also give us the background to develop Web-learning environment contents.

Download Full-text

Modeling Learner's Cognitive Abilities in the Context of a Web-Based Learning Environment

Advances in Web-Based Education ◽

10.4018/978-1-59140-690-7.ch002 ◽

2006 ◽

pp. 21-45

Author(s):

Maria A.M. Souto ◽

Regina Verdin

Keyword(s):

Learning Environment ◽

Cognitive Abilities ◽

Target Population ◽

Learning Trajectory ◽

Web Based ◽

Experimental Learning ◽

Stage Development ◽

Two Phases ◽

The Individual ◽

Web Learning

Our study is concerned with making the instruction suitable to the individual learner’s characteristics. This chapter describes the methodology used to investigate how to model the learner’s Cognitive Ability Level (CAL) based on the observation and analysis of his/her behaviour in a Web-learning environment. In our study, the CAL represents the learner’s cognitive stage development according to Bloom’s taxonomy. The methodology encompasses two phases: (i) the generation of the CAL classes for the target population and (ii) the study of learning trajectories of CAL classes in an experimental learning module. As a result, we have identified the CAL classes’ parametersvalues that best discriminate these classes from the observation and analysis of their learning trajectory on the Web. The entire knowledge obtained from this investigation will make possible to automate the learners’ CAL diagnostic. It will also give us the background to develop Web-learning environment contents.

Download Full-text