Probabilistic student modelling to improve exploratory behaviour

被引:54
作者
Bunt, A [1 ]
Conati, C [1 ]
机构
[1] Univ British Columbia, Dept Comp Sci, Vancouver, BC V6T 1W5, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
adaptive feedback; Bayesian networks; exploration; open learning environments; student modelling;
D O I
10.1023/A:1024733008280
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 [计算机科学与技术];
摘要
This paper presents the details of a student model that enables an open learning environment to provide tailored feedback on a learner's exploration. Open learning environments have been shown to be beneficial for learners with appropriate learning styles and characteristics, but problematic for those who are not able to explore effectively. To address this problem, we have built a student model capable of detecting when the learner is having difficulty exploring and of providing the types of assessments that the environment needs to guide and improve the learner's exploration of the available material. The model, which uses Bayesian Networks, was built using an iterative design and evaluation process. We describe the details of this process, as it was used to both define the structure of the model and to provide its initial validation.
引用
收藏
页码:269 / 309
页数:41
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