In today's world, students have to analyze and solve problems creatively, collaborate with teammates, communicate clearly, adapt rapidly to new technologies, and deal with a flood of information. This forces education systems to adopt new teaching methods and tools. Many are already adopting the required changes, but there is still a long way to go. In 2017, researchers at the Weizmann Institute of Science, together with the Center for Educational Technologies (CET), joined forces to address this challenge and created Plethora, an online game-like environment, which helps improve complex problem-solving through algorithmic thinking skills. The authors are part of this endeavor and its implementation.

We present a development environment that proactively and interactively assists the software engineer in modeling complex reactive systems. Our framework repeatedly analyzes models of the system under development at various levels of abstraction, and then reasons about these models in order to detect possible errors and to derive emergent properties of interest. Upon request, the environment can then augment the system model in order to repair or avoid detected behavior that is undesired, or instrument it in order to monitor the execution for certain behaviors. Specialized automated and human-assisted techniques are incorporated to direct and prioritize the analysis and related tasks, based on the relevance of the observed properties and the expected impact of actions to be taken. Our development environment is an initial step in the direction of the very recent Wise Computing vision, which calls for turning the computer (namely, the development environment) into an equal member of the development team: knowledgeable, independent, concerned and proactively involved in the development process. Our tool is implemented within the context of behavioral programming (BP), a scenario-based modeling approach, where components are aligned with how humans often describe desired system behavior. Thus, our work further enhances the naturalness and incrementality of developing in BP.

We describe InterPlay, a simulation engine coordinator that supports cooperation and interaction of multiple simulation and execution tools, thus helping to scale up the design and development cycle of reactive systems. InterPlay involves a number of related ideas. In the first, we concentrate on the interobject design approach involving live sequence charts (LSCs) and its support tool, the play-engine, enabling multiple play-engines to run in cooperation. This makes possible the distributed design of large-scale systems by different teams, as well as the refinement of parts of a system using different play-engines. The second idea concerns combining the interobject approach with the more conventional intraobject approach, involving, for example, statecharts and Rhapsody. InterPlay makes it possible to run the play-engine in cooperation with Rhapsody, and is very useful when some system objects have clear and distinct internal behavior, or in an iterative development process where the design is implementation-oriented and the ultimate goal is to end up with an intraobject implementation. Finally, we have expanded the play-engine's ability to delegate some of the system's functionality to complex GUIs. This enables beneficial interaction with "smart" GUIs that have built-in behavior of their own, and which are more naturally implemented in code

We extend live sequence charts (LSCs), a highly expressive variant of sequence diagrams, and provide the extension with an executable semantics. The extension involves support for instances that can bind to multiple objects and symbolic variables that can bind to arbitrary values. The result is a powerful executable language for expressing behavioral requirements on the level of inter-object interaction. The extension is implemented in full in our play-engine tool, with which one can execute the requirements directly without the need to build or synthesize an intra-object system model. It seems that in addition to many advantages in testing and requirements engineering, for some kinds of systems this could lead to the requirements actually serving as the final implementation.