Abstract
In real-time systems with changes in specifications, resources status, and ambient conditions, the computational support requires adapting to new conditions to satisfy the goals defined for those applications. Technology-enhanced learning applications (TEL) can be formalized by Educational Modelling Languages (EML), which provides a mechanism to design, deploy, and execute learning activities providing pedagogical flexibility. However, this flexibility is focused on design time and not in execution. Consequently, compliance satisfaction is a challenge when flexibility in workflows is provided. In addition, deadlock-freeness and reachability are critical properties in learning design execution of applications because learning objectives must be achieved by students without avoidable impediments provided by the execution of learning applications and their corresponding technical infrastructure. Currently, to provide flexibility to learning design scenarios, real-time flexibility and real-time compliance cannot be balanced since the improvement of flexibility mechanism affects compliance assessment, and vice-versa. The aim of this work is to explore real-time flexibility features in a workflow specification, supporting deadlock-freeness and reachability as compliance parameters during application in learning design scenarios. An extension of Petri-Net formalism was developed as a workflow specification. To validate this approach, a learning scenario with a set of test cases were formulated to define pedagogical and validation constraints. Results show that a learning scenario involving changes to the run-time can be successfully created, deployed, and executed. These changes can be based on properties that are intrinsic to the learning scenario, as well as on others that are related to the proposed workflow specification base Petri-net.
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Calderon, J.F., Rojas, L.A. (2023). Flexible Formal Specifications to Design Robust Technology-Enhanced Learning Applications. In: Coman, A., Vasilache, S. (eds) Social Computing and Social Media. HCII 2023. Lecture Notes in Computer Science, vol 14026. Springer, Cham. https://doi.org/10.1007/978-3-031-35927-9_2
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