Abstract-In this paper we show the implementation of the concept of Proactivity applied as the core mechanism in our Proactive Context Aware System (PCAS), which is capable to detect and extract the related events of interest from the user's contextual situation and to provide the appropriate goal-oriented actions to this event with the objective to help or assist the user or the group of users. We have chosen the academic environment as the ongoing contextual setting for our system. From this perspective, we designed Proactive Scenarios for an automatic and enhanced management of the online learning and teaching activities on Moodle TM for both student and teacher users. Due to the diversity of the potential contexts and situations arising from the user's activity, we developed two kinds of Proactive Scenarios. The first type or Meta Scenarios are responsible for capturing the changes in the outward context. The second type or Target Scenarios are triggered off by Meta Scenarios and aim to undertake the appropriate actions in response to the conditions of the user's contextual situation. In order to test and validate the capability of our software as well as to analyse its context related outcomes we have performed empirical studies. The experiments consisted in creating two groups of students, on the one hand the study group, which used the Moodle TM platform enhanced by PCAS, and on the other hand the control group, which used the standard version of Moodle TM . The subsequent data analysis showed significant differences in specific related results such as notable advantage of the study group outcomes in the category of passing the final exam, where the study group has performed by 11 percentage points better than the control group.
We designed and implemented a prototype software system based on proactive computing, as an add-on to existing technology enhanced learning platforms. In this paper, we show how our proactive engine augmented with the adequate proactive scenarios enhances the assignments sub-system of the Moodle™ learning management system by providing personalized, adaptive and intelligent support to both online learners and teachers.Personalized and adaptive software systems; technology enhanced learning; proactive computing
In this paper, we show how to implement a system that adds proactivity to Moodle TM to reach a personalized and adaptive support for both students and teachers, by providing an engine to run proactive rules, based on events and non-events, to enhance the users' e-learning process.
Abstract:We show in this position paper how we designed Proactive Scenarios for an automatic and enhanced management of the online assignments on Moodle TM for both student and teacher users, through their implementation with Proactive Rules to be run on top of our prototype Proactive Engine developed for this LMS. According to the diversity of issues that arise from the users activity on LMS, Proactive Scenarios are of two main types, which differ in their main goals, features and complexity. Meta Scenarios are devoted to capture major events of interest and to trigger off the dedicated Target Scenarios, which will undertake the appropriate actions. These Proactive Scenarios will thus take care of specifically predefined situations such as notifications, reminders, problem prevention, user guiding etc. In our opinion, LMS supplemented by such capabilities could provide a boosted effect on the students learning process as it takes an individual approach for each user and therefore could be characterized as a type of intelligent tutoring system. However, in order to sustain or modify the direction of our research activity, we now consider to undertake empirical studies on real-life online courses using the Enhanced e-Learning Platform, which runs our Proactive Scenarios.
In this paper, we are going to consider a current challenge in a robotic software system. We consider a problem, which is the lack of separation of concerns in robotic systems, and propose a software model to address the problem and resolve the current challenges. The core purpose of this paper is to demonstrate the advantages of using separation of concerns principles to create a well-ordered model of independent components that address separated concerns individually. Considering the problem, we developed a software model with the help of a proactive engine to address the challenges. We use robotic operating systems to help us to implement the robot simulator.
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