Exploring the Effects of Open Social Student Model Beyond Social Comparison
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The document discusses hypotheses for improving an open social student model (OSM) by making it more fine-grained. It hypothesizes that a fine-grained OSM could increase self-awareness, help students find difficult concepts and set goals, de-incentivize competition by favoring guidance, and show students' knowledge at the concept level by connecting concepts as they are practiced in pairs. It also describes a concept map mastery grid that would group student data and concepts by topic and allow students to navigate exercises from concepts or the connections between them.
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![Hypotheses
• Allows to find "difficult" concepts, and set goals
• Increase awareness (at a finer grain)
• De-incentivate competition and favours guidance
Mastery Grids
(Open Social Student Model)
Exploring the Effects of Open Social Student Model Beyond Social Comparison
Concept-Map
(fine-grained OSM + Social Awareness features)
PAWS Lab
http://adapt2.sis.pitt.edu/wiki/Main_Page
• Designed to foster comparison and competition [1,4]
• Increase awareness (metacognition) [3]
• Increase amount and effectivity of work [1]
(paper accepted in UMAP 2015: The Value of Social: Comparing Open
Student Modeling and Open Social Student Modeling)
Hypotheses
• Increase awareness (at a finer grain) and self-assessment
performance
• Allows to find difficult concepts and to set goals
• De-incentivate competition and support better guidance
• Detailed OSM shows knowledge in concept level
• Connects concepts as the student practices pairs of concepts
• Mastery considers successful practices and the connections
(more connections means more practices together with other concepts)
• Navigate to exercises from concepts or edges
• Set concepts as goals and receive recommendations
• Group data shown within the user model
Selected
References
Towards
metacognition
support and
social guidance
Complement
with a fine-
grained OSM
concepts are
grouped by
topic
by clicking a node,
the connections are
shown
colors represent
mastery of the
student or the group
size represent
"popularity" (group
practices)
clck an edge to
access exercises
containing the pair
of concepts
[1] [2] [3] [4]
Problems
• Favors competition over effective guidance
• Guidance exists, but is conservative
(poster in AIED 2015: Off the Beaten Path: The Impact of Adaptive
Content Sequencing on Student Navigation in an Open Social Student
Modeling Interface)
• Lack a detailed view of knowledge [2], i.e. no support for
learning-oriented students
prototype v.1
Julio Guerra, jdg60@pitt.edu; Yun Huang, yuh43@pitt.edu; Roya Hosseini, roh38@pitt.edu; Peter Brusilovsky, peterb@pitt.edu
University of Pittsburgh – School of Information Sciences and University of Pittsburgh – Intelligent Systems Program1 2
1 1,22 2](https://image.slidesharecdn.com/jguerraposterislg2015v6-151026184826-lva1-app6892/85/Exploring-the-Effects-of-Open-Social-Student-Model-Beyond-Social-Comparison-1-320.jpg)
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IUI2017 SmartLearn keynote: Intelligent Interfaces for Open Social Student M...
In this talk I will introduce the emerging technology of
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projects performed in our research lab to investigate the
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aggregated model of the class. The idea to make OSM
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The Value of Social: Comparing Open Student Modeling and Open Social Student ...
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Exploring the Effects of Open Social Student Model Beyond Social Comparison
- 1. Hypotheses • Allows to find "difficult" concepts, and set goals • Increase awareness (at a finer grain) • De-incentivate competition and favours guidance Mastery Grids (Open Social Student Model) Exploring the Effects of Open Social Student Model Beyond Social Comparison Concept-Map (fine-grained OSM + Social Awareness features) PAWS Lab http://adapt2.sis.pitt.edu/wiki/Main_Page • Designed to foster comparison and competition [1,4] • Increase awareness (metacognition) [3] • Increase amount and effectivity of work [1] (paper accepted in UMAP 2015: The Value of Social: Comparing Open Student Modeling and Open Social Student Modeling) Hypotheses • Increase awareness (at a finer grain) and self-assessment performance • Allows to find difficult concepts and to set goals • De-incentivate competition and support better guidance • Detailed OSM shows knowledge in concept level • Connects concepts as the student practices pairs of concepts • Mastery considers successful practices and the connections (more connections means more practices together with other concepts) • Navigate to exercises from concepts or edges • Set concepts as goals and receive recommendations • Group data shown within the user model Selected References Towards metacognition support and social guidance Complement with a fine- grained OSM concepts are grouped by topic by clicking a node, the connections are shown colors represent mastery of the student or the group size represent "popularity" (group practices) clck an edge to access exercises containing the pair of concepts [1] [2] [3] [4] Problems • Favors competition over effective guidance • Guidance exists, but is conservative (poster in AIED 2015: Off the Beaten Path: The Impact of Adaptive Content Sequencing on Student Navigation in an Open Social Student Modeling Interface) • Lack a detailed view of knowledge [2], i.e. no support for learning-oriented students prototype v.1 Julio Guerra, jdg60@pitt.edu; Yun Huang, yuh43@pitt.edu; Roya Hosseini, roh38@pitt.edu; Peter Brusilovsky, peterb@pitt.edu University of Pittsburgh – School of Information Sciences and University of Pittsburgh – Intelligent Systems Program1 2 1 1,22 2