Proactive e-Learning Management System

Proceedings of the 4th International Conference on Computer Supported Education

2012

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.

Section: Proactivity As the Tool For Enhanced E-learningmentioning

confidence: 99%

Design of Proactive Scenarios and Rules for Enhanced E-Learning

Reis

Shirnin

Proceedings of the 4th International Conference on Computer Supported Education

2012

“…Our engine acts as it was initially defined in [3], where it is responsible for storing and executing the set of rules, by managing two queues of rules. The 'current queue' holds the rules to be executed in the current activation period (the amount of time allowed for the Proactive Engine to run its rules in a sequence).…”

Section: Rules Enginementioning

confidence: 99%

“…Every rule implements an Abstract Rule. The rules execution follows the algorithm defined in [3] and shown in Figure 2.…”

Section: Rule Execution (Abstract Rule)mentioning

confidence: 99%

See 1 more Smart Citation

Proactive Computing Based Implementation of Personalized and Adaptive Technology Enhanced Learning over Moodle(TM)

Dias

Reis

2012 IEEE 12th International Conference on Advanced Learning Technologies

2012

Self Cite

“…The rules themselves are part of the proactive system, which is connected to a target system. The rules are processed by the Rules Engine, which is responsible for storing, executing and iterating the rules [19], [20]. Initially, several rules are launched at the start of proactive system with the objective to be continuously activated in order to search for the first instance of a data input.…”

Section: A Statistical Structure Of the Cognitive Modelsmentioning

confidence: 99%

Evaluating the probabilistic side of proactive computing using cognitive modelling methodology and the statistical inference of user's cognitive states

Shirnin

2014 IEEE 13th International Conference on Cognitive Informatics and Cognitive Computing

2014

Self Cite

Abstract-In the following paper we present the work in progress, which aims to validate through theoretical and empirical study the probabilistic side of proactive computing. We choose the cognitive modelling methodology as an approach to implement the probabilistic inference of user's cognitive states during online activity. We create four cognitive models, which simulate various cognitive states of a user during the task of online search of medical terminology. Additionally, we elaborate several potential scenarios, which may take place during the given task, and we associate these scenarios with our models as the integral elements of the proactive system behaviour. Ultimately, by applying the rules of the Bayesian statistics, we envision to test the principles of proactive computing in the frame of probabilistic approach.