Model-Driven Development of Context-aware Adaptive Learning Systems

Malek, Jihen; Laroussi, Mona; Derycke, Alain; Ghezala, Henda Ben

doi:10.1109/icalt.2010.125

Cited by 9 publications

(4 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [24], Malek et al proposed CAAML (Context-aware Adaptive Activities Modeling Language) which aims at modeling context-aware adaptive learning activities in the E-learning domain. is language focuses on modeling two classes of rules: rules for context adaptation and rules for activity adaptation to support pedagogical designing.…”

Section: Discussion and Related Workmentioning

confidence: 99%

ContextServ: A platform for rapid and flexible development of context-aware Web services

Sheng

Pohlenz

et al. 2009

2009 IEEE 31st International Conference on Software Engineering

View full text Add to dashboard Cite

show abstract

Section: Discussion and Related Workmentioning

confidence: 99%

ContextServ: A platform for rapid and flexible development of context-aware Web services

Sheng

Pohlenz

et al. 2009

2009 IEEE 31st International Conference on Software Engineering

View full text Add to dashboard Cite

show abstract

“…define in [16] a malleable learning scenario as a new learning philosophy adapted to "Digital Native" generations. It's flexible, context-aware, co-adaptive, extensible and technology-enhanced learning.…”

Section: A Challenges Of Restart-mementioning

confidence: 99%

An evaluation framework based on timed automata for Malleable Learning Scenario

BenSassi

Laroussi

2014

2014 IEEE Global Engineering Education Conference (EDUCON)

Self Cite

View full text Add to dashboard Cite

The evaluation of educational scenario is important to educators. It is one of the more challenging tasks that the pedagogical designer is faced with. In fact, the higher cost of the implementation of learning scenarios in distance learning and the complexity of their context and their functionalities emphasize the need to evaluate and to simulate them in order to detect potential inconsistencies and then to provide valuable feedback and recommendations to designers. For these reasons, we propose, in this paper, a framework based on Timed Automata Theory for Malleable Learning Scenarios. The evaluation framework is based on four elements: time, space, role and activity. These elements can be used in order to evaluate if or not our educational scenario reveals inconsistencies. The result of this formal evaluation could be greatly useful to designers in order to increase their understanding of the learner's behavior with the existing scenario by revealing ambiguities and incompleteness that might otherwise go undetected before starting the implementation. Thus, designers could return on the phase of design to add missing elements.

show abstract

“…First, the bindings for ontology classes used in the rule as well as an enabler helper-class are defined (Lines 5-6), followed by the condition statement as translated into Drools syntax (Lines 8). If the condition is evaluated as true, the Web service associated with the BookT icket will be invoked, using the enabler helper class (Lines [12][13][14][15][16][17][18][19][20][21][22][23][24][25].…”

Section: Transformationmentioning

confidence: 99%

“…Accordingly, state constraints, which are defined by logical predicates on the value of the attributes of a state-based context, and event constraints, which are defined as patterns of event, are used to specify context-aware adaptation feature of the application. CAAML (Context-aware Adaptive Activities Modeling Language) [17] aims at modeling context-aware adaptive learning activities in the E-learning domain. This language focuses on modeling two classes of rules -rules for context adaptation and rules for activity adaptation -to support pedagogical designing.…”

Section: Related Workmentioning

confidence: 99%

PerCAS: An Approach to Enabling Dynamic and Personalized Adaptation for Context-Aware Services

Han

Sheng

et al. 2012

Service-Oriented Computing

View full text Add to dashboard Cite

Context-aware services often need to adapt their behaviors according to physical situations and user preferences. However, most of the existing approaches to developing context-aware services can only do adaptation based on globally defined adaptation logic without considering the personalized context-aware adaptation needs of a specific user. In this paper, we propose a novel model-driven approach called PerCAS to developing and executing personalized context-aware services that are able to adapt to a specific user's adaptation needs at runtime. To enable dynamic and personalized context-aware adaptation, user-specific adaptation logic is encoded as rules, which are then weaved into a base process with an aspect-oriented mechanism. At runtime, the active user-specific rule set will be switched depending on who is using/invoking the service. A model-driven platform has been implemented to support the development and maintenance of personalized context-aware services from specification, design, to deployment and execution. Initial in-lab performance experiments have been conducted to demonstrate the efficiency of our approach.

show abstract

Model-Driven Development of Context-aware Adaptive Learning Systems

Cited by 9 publications

References 3 publications

ContextServ: A platform for rapid and flexible development of context-aware Web services

ContextServ: A platform for rapid and flexible development of context-aware Web services

An evaluation framework based on timed automata for Malleable Learning Scenario

PerCAS: An Approach to Enabling Dynamic and Personalized Adaptation for Context-Aware Services

Contact Info

Product

Resources

About