A study into the feasibility of generic programming for the construction of complex software

A high degree of abstraction and capacity for reuse can be obtained in software design through the use of Generic Programming (GP) concepts. Despite widespread use of GP in computing, some areas such as the construction of generic component libraries as the skeleton for complex computing systems with extensive domains have been neglected. Here we consider the design of a library of generic components based on the GP paradigm implemented with Java. Our aim is to investigate the feasibility of using GP paradigm in the construction of complex computer systems where the management of users interacting with the system and the optimisation of the system’s resources is required.Postprint (author's final draft

Distributed-based massive processing of activity logs for efficient user modeling in a Virtual Campus

This paper reports on a multi-fold approach for the building of user models based on the identification of navigation patterns in a virtual campus, allowing for adapting the campus’ usability to the actual learners’ needs, thus resulting in a great stimulation of the learning experience. However, user modeling in this context implies a constant processing and analysis of user interaction data during long-term learning activities, which produces huge amounts of valuable data stored typically in server log files. Due to the large or very large size of log files generated daily, the massive processing is a foremost step in extracting useful information. To this end, this work studies, first, the viability of processing large log data files of a real Virtual Campus using different distributed infrastructures. More precisely, we study the time performance of massive processing of daily log files implemented following the master-slave paradigm and evaluated using Cluster Computing and PlanetLab platforms. The study reveals the complexity and challenges of massive processing in the big data era, such as the need to carefully tune the log file processing in terms of chunk log data size to be processed at slave nodes as well as the bottleneck in processing in truly geographically distributed infrastructures due to the overhead caused by the communication time among the master and slave nodes. Then, an application of the massive processing approach resulting in log data processed and stored in a well-structured format is presented. We show how to extract knowledge from the log data analysis by using the WEKA framework for data mining purposes showing its usefulness to effectively build user models in terms of identifying interesting navigation patters of on-line learners. The study is motivated and conducted in the context of the actual data logs of the Virtual Campus of the Open University of Catalonia.Peer ReviewedPostprint (author's final draft

CLPL: Providing software infrastructure for the systematic and effective construction of complex collaborative learning systems

Over the last decade, e-Learning and in particular Computer-Supported Collaborative Learning (CSCL) needs have been evolving accordingly with more and more demanding pedagogical and technological requirements. As a result, high customization and flexibility are a must in this context, meaning that collaborative learning practices need to be continuously adapted, adjusted, and personalized to each specific target learning group. These very demanding needs of the CSCL domain represent a great challenge for the research community on software development to satisfy. This contribution presents and evaluates a previous research effort in the form of a generic software infrastructure called Collaborative Learning Purpose Library (CLPL) with the aim of meeting the current and demanding needs found in the CSCL domain. To this end, we experiment with the CLPL in order to offer an advanced reuse-based service-oriented software engineering methodology for developing CSCL applications in an effective and timely fashion. A validation process is provided by reporting on the use of the CLPL platform as the primary resource for the Master's thesis courses at the Open University of Catalonia when developing complex software applications in the CSCL domain. The ultimate aim of the whole research is to yield effective CSCL software systems capable of supporting and enhancing the current on-line collaborative learning practices.Peer ReviewedPostprint (author's final draft

A review on massive e-learning (MOOC) design, delivery and assessment

MOOCs or Massive Online Open Courses based on Open Educational Resources (OER) might be one of the most versatile ways to offer access to quality education, especially for those residing in far or disadvantaged areas. This article analyzes the state of the art on MOOCs, exploring open research questions and setting interesting topics and goals for further research. Finally, it proposes a framework that includes the use of software agents with the aim to improve and personalize management, delivery, efficiency and evaluation of massive online courses on an individual level basis.Peer ReviewedPostprint (author's final draft

Security in online learning assessment towards an effective trustworthiness approach to support e-learning teams

(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.This paper proposes a trustworthiness model for the design of secure learning assessment in on-line collaborative learning groups. Although computer supported collaborative learning has been widely adopted in many educational institutions over the last decade, there exist still drawbacks which limit their potential in collaborative learning activities. Among these limitations, we investigate information security requirements in on-line assessment, (e-assessment), which can be developed in collaborative learning contexts. Despite information security enhancements have been developed in recent years, to the best of our knowledge, integrated and holistic security models have not been completely carried out yet. Even when security advanced methodologies and technologies are deployed in Learning Management Systems, too many types of vulnerabilities still remain opened and unsolved. Therefore, new models such as trustworthiness approaches can overcome these lacks and support e-assessment requirements for e-Learning. To this end, a trustworthiness model is designed in order to conduct the guidelines of a holistic security model for on-line collaborative learning through effective trustworthiness approaches. In addition, since users' trustworthiness analysis involves large amounts of ill-structured data, a parallel processing paradigm is proposed to build relevant information modeling trustworthiness levels for e-Learning.Peer ReviewedPostprint (author's final draft

On sharing and synchronizing groupware calendars under android platform

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Sharing a calendar of tasks and events is a cornerstone in collaborative group work. Indeed, the individual work of the members of the group as well as the group work as a whole need the calendar to guide their activity and to meet the deadlines, milestones, deliverables of a project, etc. Additionally the members of the group should be able to work both offline and online, which arises when members of the group use smartphones and can eventually run out of Internet connection from time to time, or simply want to develop some activities locally. In the former case, they should have access to the calendar locally, while in the later case they should access the calendar online, shared by all members of the group. In both cases they should be able to see eventually the same information, namely the local calendars of the members should be synchronized with the group calendar. For the case of smartphones under Android system, one solution could be using the Google calendar, however, that is not easily tailorable to collaborative group work. In this paper we present an analysis, design and implementation of group work calendar that meets several requirements such as 1) sharing among all of members of the group, 2) synchronization among local calendars of members and global group calendar, 3) conflict resolution through a voting system, 4) awareness of changes in the entries (tasks, members, events, etc.) of the calendar and 5) all these requirements under proper privacy, confidentiality and security mechanisms. Moreover, we extend the sharing of calendars among different groups, a situation which often arises in enterprises when different groups need to be aware of other projects' development, or, when some members participate in more than one project at the same time.Peer ReviewedPostprint (author's final draft

A grid-based approach for processing group activity log files

The information collected regarding group activity in a collaborative learning environment requires classifying, structuring and processing. The aim is to process this information in order to extract, reveal and provide students and tutors with valuable knowledge, awareness and feedback in order to successfully perform the collaborative learning activity. However, the large amount of information generated during online group activity may be time-consuming to process and, hence, can hinder the real-time delivery of the information. In this study we show how a Grid-based paradigm can be used to effectively process and present the information regarding group activity gathered in the log files under a collaborative environment. The computational power of the Grid makes it possible to process a huge amount of event information, compute statistical results and present them, when needed, to the members of the online group and the tutors, who are geographically distributed.Peer ReviewedPostprint (author's final draft

Apache Mahout’s k-Means vs. fuzzy k-Means performance evaluation

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.The emergence of the Big Data as a disruptive technology for next generation of intelligent systems, has brought many issues of how to extract and make use of the knowledge obtained from the data within short times, limited budget and under high rates of data generation. The foremost challenge identified here is the data processing, and especially, mining and analysis for knowledge extraction. As the 'old' data mining frameworks were designed without Big Data requirements, a new generation of such frameworks is being developed fully implemented in Cloud platforms. One such frameworks is Apache Mahout aimed to leverage fast processing and analysis of Big Data. The performance of such new data mining frameworks is yet to be evaluated and potential limitations are to be revealed. In this paper we analyse the performance of Apache Mahout using large real data sets from the Twitter stream. We exemplify the analysis for the case of two clustering algorithms, namely, k-Means and Fuzzy k-Means, using a Hadoop cluster infrastructure for the experimental study.Peer ReviewedPostprint (author's final draft

Efficient embedding of information and knowledge into CSCL applications

This study aims to explore two crucial aspects of collaborative work and learning: the importance of enabling CSCL applications, on the one hand, to capture and structure the information generated by group activity and, on the other hand, to extract the relevant knowledge in order to provide learners and tutors with efficient awareness and support as regards collaboration. To this end, we first identify and define the main types of information generated in on-line group activity and then propose a process for efficiently embedding this information and the knowledge extracted from it into CSCL applications for awareness and feedback purposes. The conceptual model proposed finally gave rise to the design and implementation of a CSCL generic platform, called the Collaborative Learning Purpose Library (CLPL), which serves as a basis for the systematic development of collaborative learning applications and for providing full support to the mentioned process of knowledge management.Peer ReviewedPostprint (author's final draft

A replication-based approach for the improvement of the online learning experience in distributed environments

Modern on-line collaborative learning environments need to be continuously adapted, adjusted, and personalized to each specific target learning group. Moreover, these environments are to enable and scale the involvement of an increasing large number of single/group participants who can geographically be widely distributed, and who need transparently share a huge variety of both software and hardware distributed resources. As a result, collaborative learning applications need to be designed in a way that overcome important non-functional requirements arisen in distributed contexts, such as scalability, availability, interoperability, and integration of different, heterogeneous, and legacy collaborative learning systems. In this paper, an innovative distributed-based approach is presented for increasing the overall performance of collaborative learning systems that contributes to the effectiveness of the collaborative activities, such as online discussions. The experimental results show an outstanding effect on the learning processes and outcomes by enhancing and improving the learning experience a great deal.Peer ReviewedPostprint (published version