Continuous proactivity in Learning Management Systems

Reis

2013 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA

2013

Self Cite

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.

Section: A Learning Relatedsupporting

confidence: 79%

Experimentation of proactive computing in context aware systems: Case study of human-computer interactions in e-learning environment

Reis

2013 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA

2013

Self Cite

“…Such position, allows and encourages us to explore the proactive computing in different directions. Throughout our past research efforts, we investigated the deterministic side of proactive computing, where we studied the possibility of implementing the preprogrammed set of context aware-capable rules in order to enhance the system with proactive type of behaviour [8], [9]. However, it represents only a segment of the theoretical framework applied in development of the proactive system.…”

Section: A Proactive Computingmentioning

confidence: 99%

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

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.

“…Such measurement tools aim to collect the feedback from the users whether automatically through the statistics reports of the system or manually through online surveys, interviews, questionnaires, and live discussions. For some categories of experiment we will use the similar technics as in (Coronado & Zampunieris, 2010).…”

Section: Future Effortsmentioning

confidence: 99%

“…Thus, our system is capable of detecting an "anomalous" behaviour of e-learner and to communicate the details to concerned e-teacher; or, the system can check automatically the awaited behaviours of elearners, and react if these actions did not happen. In (Coronado & Zampunieris, 2010) we reported the statistical analysis of studies we conducted in a blended learning environment at the bachelor level. The idea consisted of comparing a study-group and a control-group of students in the same course with respect to their intermediate and final results.…”

Section: Introductionmentioning

confidence: 99%

Design of Proactive Scenarios and Rules for Enhanced E-Learning

Reis

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.