Using planning techniques in intelligent tutoring systems
International Journal of Man-Machine Studies
ICALT '01 Proceedings of the IEEE International Conference on Advanced Learning Technologies
Automated Planning: Theory & Practice
Automated Planning: Theory & Practice
IMS Learning Design Support for the Formalization of Collaborative Learning Patterns
ICALT '04 Proceedings of the IEEE International Conference on Advanced Learning Technologies
CSCL '05 Proceedings of th 2005 conference on Computer support for collaborative learning: learning 2005: the next 10 years!
Planning and scheduling in an e-learning environment. A constraint-programming-based approach
Engineering Applications of Artificial Intelligence
Interoperable Competencies Characterizing Learning Objects in Mathematics
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
Adventures in the Boundary between Domain-Independent Ontologies and Domain Content for CSCL
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III
Incorporating assessment in a pattern-based design process for CSCL scripts
Computers in Human Behavior
Journal of Artificial Intelligence Research
Looking Into Collaborative Learning: Design from Macro-and Micro-Script Perspectives
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Deployment of ontologies for an effective design of collaborative learning scenarios
CRIWG'07 Proceedings of the 13th international conference on Groupware: design implementation, and use
Pedagogically founded courseware generation for web-based learning: an HTN-planning-based approach implemented in PAIGOS
Ontological support for a theory-eclectic approach to instructional and learning design
EC-TEL'06 Proceedings of the First European conference on Technology Enhanced Learning: innovative Approaches for Learning and Knowledge Sharing
An authoring tool to support the design and use of theory-based collaborative learning activities
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part II
Web Collage: An implementation of support for assessment design in CSCL macro-scripts
Computers & Education
Automating educational processes implementation by means of an ontological framework
Computer Standards & Interfaces
Hi-index | 12.05 |
In Computer Supported Collaborative Learning (CSCL), one of the most important tasks for instructional designers is to define scenarios that foster group learning. Such scenarios, defined as Units of Learning (UoLs), comprise different components and are organized according to pedagogical approaches to orchestrate group learning processes. Examples of UoL components are learning objects, student roles, student characteristics (e.g., background, preferences, learning styles, etc.), instructional/learning goals, and activities, among others. Thus, the instructional design (ID) of a proper UoL for CSCL is a complex task that requires practice and experience. This is particularly true when designing, developing, adapting, and customizing UoLs, taking into consideration different instructional/learning goals and individual preferences of students. This paper therefore proposes using a Hierarchical Task Network (HTN) planning approach to automate and optimize the tasks of designers. To accomplish that, we define an initial CSCL scenario as ''an ID task'' and ''a set of information related to students and the domain to be taught.'' Then we propose a model that formally describes ID for CSCL as HTN planning, where the initial CSCL scenario is adapted and refined according to student needs. In this model, the ID strategies are defined as hierarchical tasks and methods into a planning domain definition, and the initial CSCL scenario is defined as a planning problem definition. To validate our approach, we develop a CSCL courseware generator that (i) helps designers to set up an initial CSCL scenario; (ii) automatically generates a personalized UoL based on a given initial scenario; and (iii) supports the adaptation of UoLs.