Escape from the Skinner Box: The case for contemporary intelligent learning environments

2019 ◽  
Vol 50 (6) ◽  
pp. 2902-2919 ◽  
Author(s):  
Benedict du Boulay
Keyword(s):  
Learning Environments ◽  
Intelligent Learning Environments ◽  
Skinner Box

Design of a Laser Projection System for Intelligent Learning Environments

2021 ◽  
pp. 89-103
Author(s):  
Svetozar Ilchev ◽  
Alexander Alexandrov ◽  
Zlatoliliya Ilcheva
Keyword(s):  
Learning Environments ◽  
Projection System ◽  
Intelligent Learning Environments

The Use of ‘War Stories’ in Intelligent Learning Environments

1998 ◽  
pp. 619-619
Author(s):  
Benjamin Bell ◽  
Jan Hawkins ◽  
R. Bowen Loftin ◽  
Tom Carey ◽  
Alex Kass
Keyword(s):  
Learning Environments ◽  
Intelligent Learning Environments ◽  
War Stories

MODELLING STUDENT INTERACTIONS IN INTELLIGENT LEARNING ENVIRONMENTS: CONSTRUCTING BAYESIAN NETWORKS FROM DATA

2010 ◽  
Vol 19 (06) ◽  
pp. 733-753 ◽  
Author(s):  
MANOLIS MAVRIKIS
Keyword(s):  
Machine Learning ◽  
Human Computer Interaction ◽  
Bayesian Networks ◽  
Learning Environments ◽  
Student Interactions ◽  
Intelligent Learning Environment ◽  
Interaction Modelling ◽  
Intelligent Learning Environments ◽  
Future Work

Human-Computer Interaction modelling can benefit from machine learning. This paper presents a case study of the use of machine learning for the development of two interrelated Bayesian Networks for the purposes of modelling student interactions within Intelligent Learning Environments. The models predict (a) whether a given student's interaction is effective in terms of learning and (b) whether a student can answer correctly questions in an intelligent learning environment without requesting help. After discussing the requirements for these models, the paper presents the particular techniques used to pre-process and learn from the data. The case study discusses the models learned based on data collected from student interactions on their own time and location. The paper concludes by discussing the application of the models and directions for future work.

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