Collaborative Learning and Authoring in the Frame of e-Projects

It is presented a research on the application of a collaborative learning and authoring during all delivery phases of e-learning programmes or e-courses offered by educational institutions. The possibilities for modelling of an e-project as a specific management process based on planned, dynamically changing or accidentally arising sequences of learning activities, is discussed. New approaches for project-based and collaborative learning and authoring are presented. Special types of test questions are introduced which allow test generation and authoring based on learners’ answers accumulated in the frame of given e-course. Experiments are carried out in an e-learning environment, named BEST.

Collaborative Learning and Assessment in e-Learning

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2016

Knowledge Construction Technology through Hypermedia-Based Intelligent Conversational Channel

There have been multifarious approaches in building expert knowledge in medical or engineering field through expert system, case-based reasoning, model-based reasoning and also a large-scale knowledge-based system. The intriguing factors with these approaches are mainly the choices of reasoning mechanism, ontology, knowledge representation, elicitation and modeling. In our study, we argue that the knowledge construction through hypermedia-based community channel is an effective approach in constructing expert’s knowledge. We define that the knowledge can be represented as in the simplest form such as stories to the most complex ones such as on-the-job type of experiences. The current approaches of encoding experiences require expert’s knowledge to be acquired and represented in rules, cases or causal model. We differentiate the two types of knowledge which are the content knowledge and socially-derivable knowledge. The latter is described as knowledge that is earned through social interaction. Intelligent Conversational Channel is the system that supports the building and sharing on this type of knowledge.

Challenges of Teaching Written Communication in the Cloud

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014

Applying Data Mining Tools in E-Learning

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014

Towards e+Learning or How to Increase the Learning into e-Learning

It is discussed some changes in the traditional e-learning notion on the point of view of R. Koper’s question 'where is the learning in e-learning?’. We put a focus on the conception of learning as a management process and present the project Bulgarian Educational Site (BEST) – a possible answer to Koper’s question. The BEST is a virtual learning environment, based on the following principles: learning is a goal-directed and didactics-managed process; learners may define their own learning objectives, monitor and regulate the learning process; collaborative e-learning is more effective; etc. The BEST is based on two famous e-learning systems (Moodle, LAMS) and Plovdiv e-University (versions 1.0 and 2.0). The paper brings up a mater about the new ‘electronic’ pedagogy and proposes an approach for pedagogical modeling and interpretation of e-learning applied in the BEST.

Automating Exersises Validation in e-Learning Environments

E-learning is supposing an innovation in teaching, raising from the development of new technologies. It is based in a set of educational resources, including, among others, multimedia or interactive contents accessible through Internet or Intranet networks. A whole spectrum of tools and services support e-learning, some of them include auto-evaluation and automated correction of test-like exercises, however, this sort of exercises are very constrained because of its nature: fixed contents and correct answers suppose a limit in the way teachers may evaluation students. In this paper we propose a new engine that allows validating complex exercises in the area of Data Structures and Algorithms. Correct solutions to exercises do not rely only in how good the execution of the code is, or if the results are same as expected. A set of criteria on algorithm complexity or correctness in the use of the data structures are required. The engine presented in this work covers a wide set of exercises with these characteristics allowing teachers to establish the set of requirements for a solution, and students to obtain a measure on the quality of their solution in the same terms that are later required for exams.

An eMathTeacher Tool for Active Learning Fleury’s Algorithm

An eMathTeacher [Sánchez-Torrubia 2007a] is an eLearning on line self assessment tool that help students to active learning math algorithms by themselves, correcting their mistakes and providing them with clues to find the right solution. The tool presented in this paper is an example of this new concept on Computer Aided Instruction (CAI) resources and has been implemented as a Java applet and designed as an auxiliary instrument for both classroom teaching and individual practicing of Fleury’s algorithm. This tool, included within a set of eMathTeacher tools, has been designed as educational complement of Graph Algorithm active learning for first course students. Its characteristics of visualization, simplicity and interactivity, make this tutorial a great value pedagogical instrument.

Teaching Strategies and Ontologies for E-Learning

* The work is partially suported by Russian Foundation for Basic Studies (grant 02-01-00466).

Using Problems to Introduce some Tools and Technologies for Implementation of Graphics and Animation in C#

This paper is devoted to the learning of event programming by using Visual C# in specialized training in Informatics in high schools. Some basic tools and technologies for the implementation of graphics and animation in C# are discussed. Two example problems are proposed.

Development of a Refactoring Learning Environment

This paper describes a Refactoring Learning Environment, which is intended to analyze and assess programming code, based on refactoring rules. The Refactoring Learning Environment architecture includes an intelligent assistant – Refactoring Agent, which is responsible for analysis and assessment of the code, written by students in real time by using a set of refactoring methods. According to the situation and based on the refactoring method, which should be applied, the agent could react in different ways. Its goal is to show the student, as much as possible, the weak places of his programming code and the possible ways to makes it better.

Digital Libraries and Portals Saving National Cultural Heritage (IMI–BAS Experience)

The current research activities of the Institute of Mathematics and Informatics at the Bulgarian Academy of Sciences (IMI—BAS) include the study and application of knowledge-based methods for the creation, integration and development of multimedia digital libraries with applications in cultural heritage. This report presents IMI-BAS’s developments at the digital library management systems and portals, i.e. the Bulgarian Iconographical Digital Library, the Bulgarian Folklore Digital Library and the Bulgarian Folklore Artery, etc. developed during the several national and international projects: - "Digital Libraries with Multimedia Content and its Application in Bulgarian Cultural Heritage" (contract 8/21.07.2005 between the IMI–BAS, and the State Agency for Information Technologies and Communications; - FP6/IST/P-027451 PROJECT LOGOS "Knowledge-on-Demand for Ubiquitous Learning", EU FP6, IST, Priority 2.4.13 "Strengthening the Integration of the ICT research effort in an Enlarged Europe" - NSF project D-002-189 SINUS "Semantic Technologies for Web Services and Technology Enhanced Learning". - NSF project IO-03-03/2006 ―Development of Digital Libraries and Information Portal with Virtual Exposition "Bulgarian Folklore Heritage". The presented prototypes aims to provide flexible and effective access to the multimedia presentation of the cultural heritage artefacts and collections, maintaining different forms and format of the digitized information content and rich functionality for interaction. The developments are a result of long- standing interests and work in the technological developments in information systems, knowledge processing and content management systems. The current research activities aims at creating innovative solutions for assembling multimedia digital libraries for collaborative use in specific cultural heritage context, maintaining their semantic interoperability and creating new services for dynamic aggregation of their resources, access improvement, personification, intelligent curation of content, and content protection. The investigations are directed towards the development of distributed tools for aggregating heterogeneous content and ensuring semantic compatibility with the European digital library EUROPEANA, thus providing possibilities for pan- European access to rich digitalised collections of Bulgarian cultural heritage.

Modern Training Tools for Binding Design and Paper Conservation of Antique Books, Albums and Documents (BBINDING)

Report published in the Proceedings of the National Conference on "Education in the Information Society", Plovdiv, May, 2013

Group Work as a Strategy to Improve the Effectiveness of the Learning Process

Report published in the Proceedings of the National Conference on "Education in the Information Society", Plovdiv, May, 2013

A Taxonomy of Big Data for Optimal Predictive Machine Learning and Data Mining

Big data comes in various ways, types, shapes, forms and sizes. Indeed, almost all areas of science, technology, medicine, public health, economics, business, linguistics and social science are bombarded by ever increasing flows of data begging to be analyzed efficiently and effectively. In this paper, we propose a rough idea of a possible taxonomy of big data, along with some of the most commonly used tools for handling each particular category of bigness. The dimensionality p of the input space and the sample size n are usually the main ingredients in the characterization of data bigness. The specific statistical machine learning technique used to handle a particular big data set will depend on which category it falls in within the bigness taxonomy. Large p small n data sets for instance require a different set of tools from the large n small p variety. Among other tools, we discuss Preprocessing, Standardization, Imputation, Projection, Regularization, Penalization, Compression, Reduction, Selection, Kernelization, Hybridization, Parallelization, Aggregation, Randomization, Replication, Sequentialization. Indeed, it is important to emphasize right away that the so-called no free lunch theorem applies here, in the sense that there is no universally superior method that outperforms all other methods on all categories of bigness. It is also important to stress the fact that simplicity in the sense of Ockham’s razor non-plurality principle of parsimony tends to reign supreme when it comes to massive data. We conclude with a comparison of the predictive performance of some of the most commonly used methods on a few data sets.