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What is Learner Profile

Chapter 7
Bayesian Networks for Managing Learner Models in Adaptive Hypermedia Systems: Emerging Research and Opportunities
A part of the learner model that only contain the static information of the learner that could be gathered before developing a learner model.
Published in Chapter:
A Learner Model Based on Multi-Entity Bayesian Networks in Adaptive Hypermedia Educational Systems
Copyright: © 2019 |Pages: 26
DOI: 10.4018/978-1-5225-7413-2.ch007
Abstract
This chapter presents a probabilistic and dynamic learner model based on multi-entity Bayesian networks and artificial intelligence. There are several methods for modelling the learner in AHES, but they're based on the initial profile of the learner created in his entry into the learning situation. They do not handle the uncertainty in the dynamic modelling of the learner based on the actions of the learner. The main purpose of this chapter is the management of the learner model based on MEBN and artificial intelligence, taking into account the different actions that the learner could take during his/her whole learning path. The approach that the authors followed in this chapter is marked initially by modelling the learner model in three levels: they started with the conceptual level of modelling with the unified modelling language, followed by the model based on Bayesian networks to be able to achieve probabilistic modelling in the three phases of learner modelling.
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Chapter 2
A Vision for Deeper Agency and Personalization in Micro-Credentials
A tool capturing a breadth of characteristics about a learner, including learning history/transcripts; assessment results; learning goals; learning artifacts; strengths and challenges; aspirations and motivations; passions, interests, and preferences.
Published in Chapter: A Vision for Deeper Agency and Personalization in Micro-Credentials; From: Career Ready Education Through Experiential Learning
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Chapter 2
A Comparative Study of the Modeling Techniques and Models of a Learner Model in Adaptive Hypermedia Educational Systems
A part of the learner model that only contain the static information of the learner that could be gathered before developing a learner model.
Published in Chapter: A Comparative Study of the Modeling Techniques and Models of a Learner Model in Adaptive Hypermedia Educational Systems; From: Bayesian Networks for Managing Learner Models in Adaptive Hypermedia Systems: Emerging Research and Opportunities
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Chapter 5
Managing the Learner Model With Multi-Entity Bayesian Networks in Adaptive Hypermedia Systems
A part of the learner model that only contain the static information of the learner that could be gathered before developing a learner model.
Published in Chapter: Managing the Learner Model With Multi-Entity Bayesian Networks in Adaptive Hypermedia Systems; From: Cognitive Computing in Technology-Enhanced Learning
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Chapter 12
Implementing a Probabilistic Learner Model Into a Course Creation Application
A part of the learner model that only contain the static information of the learner that could be gathered before developing a learner model.
Published in Chapter: Implementing a Probabilistic Learner Model Into a Course Creation Application; From: Personalization and Collaboration in Adaptive E-Learning
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Chapter 6
The Combination of Bayesian Networks and Stereotypes to Initialize the Learner Model in Adaptive Educational Hypermedia Systems
A part of the learner model that only contain the static information of the learner that could be gathered before developing a learner model.
Published in Chapter: The Combination of Bayesian Networks and Stereotypes to Initialize the Learner Model in Adaptive Educational Hypermedia Systems; From: Bayesian Networks for Managing Learner Models in Adaptive Hypermedia Systems: Emerging Research and Opportunities
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Chapter 5
Differentiating Instruction for Young English Language Learners in the Content Areas
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Chapter 4
A Learner Model Based on Bayesian Networks in Adaptive Educational Hypermedia Systems
A part of the learner model that only contain the static information of the learner that could be gathered before developing a learner model.
Published in Chapter: A Learner Model Based on Bayesian Networks in Adaptive Educational Hypermedia Systems; From: Bayesian Networks for Managing Learner Models in Adaptive Hypermedia Systems: Emerging Research and Opportunities
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Chapter 3
Development of Bayesian Networks From Use Case Diagrams for Managing the Learner Model
A part of the learner model that only contain the static information of the learner that could be gathered before developing a learner model.
Published in Chapter: Development of Bayesian Networks From Use Case Diagrams for Managing the Learner Model; From: Bayesian Networks for Managing Learner Models in Adaptive Hypermedia Systems: Emerging Research and Opportunities
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Chapter 5
The Determination of Learning Styles in a Learner Model Using the Combination of Bayesian Network and the Overlay Model
A part of the learner model that only contain the static information of the learner that could be gathered before developing a learner model.
Published in Chapter: The Determination of Learning Styles in a Learner Model Using the Combination of Bayesian Network and the Overlay Model; From: Bayesian Networks for Managing Learner Models in Adaptive Hypermedia Systems: Emerging Research and Opportunities
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Chapter 8
Combining the Overlay Model and Bayesian Networks to Determine Learning Styles in AHES
A part of the learner model that only contain the static information of the learner that could be gathered before developing a learner model.
Published in Chapter: Combining the Overlay Model and Bayesian Networks to Determine Learning Styles in AHES; From: Handbook of Research on E-Assessment in Higher Education
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Chapter 17
International School Teachers' Professional Development in Response to the Needs of Third Culture Kids in the Classroom
At the centre of the IB program is the “learner profile”, which defines the type of students the program is intended to develop, e.g., global citizens that are caring, balanced, open-minded, knowledgeable, communicative, risk-taking, principled, reflective, inquiring, and thinker.
Published in Chapter: International School Teachers' Professional Development in Response to the Needs of Third Culture Kids in the Classroom; From: Handbook of Research on Global Business Opportunities
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Chapter 1
A Comparative Study of the Functionalities and Characteristics of a Learner Model in Adaptive Hypermedia Educational Systems
A part of the learner model that only contain the static information of the learner that could be gathered before developing a learner model.
Published in Chapter: A Comparative Study of the Functionalities and Characteristics of a Learner Model in Adaptive Hypermedia Educational Systems; From: Bayesian Networks for Managing Learner Models in Adaptive Hypermedia Systems: Emerging Research and Opportunities
Full Text Chapter Download: US $37.50 Add to Cart
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