Adaptive E-learning Content Design and Delivery Based on Learning Styles and Knowledge Level

ACM Computing Classification System (1998): K.3.1, K.3.2.

Towards New Teaching in Mathematics How to Realize Inquiry Based and Problem Oriented Mathematics Lessons?

Дагмар Рааб Математиката е вълнуваща и забавна. Можем ли да убедим учениците, че това може да стане действителност. Задачите са най-важните инструменти за учителите по математика, когато планират уроците си. Планът трябва да съдържа идеи как да се очертае и как да се жалонира пътят, по който учениците ще стигнат до решението на дадена задача. Учителите не трябва да очакват от учениците си просто да кажат кой е отговорът на задачата, а да ги увлекат в процеса на решаване с подходящи въпроси. Ролята на учителя е да помогне на учениците • да бъдат активни и резултатни при решаването на задачи; • самите те да поставят задачи; • да модифицират задачи; • да откриват закономерности; • да изготвят стратегии за решаване на задачи; • да откриват и изследват различни начини за решаване на задачи; • да намират смислена връзка между математическите си знания и проблеми от ежедневието. В доклада са представени избрани и вече експериментирани примери за това как учители и ученици могат да намерят подходящ път към нов тип преживявания в преподаването и изучаването на училищната математика.

Provision of Mobile Learning in Higher Schools

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

Automatized Generation of Metadata and Calibrated Test Item Banks for E-learning

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

Social - Oriented Applications of the Folklore Heritage for the Needs of the Non-formal Learning and Cultural Tourisms

The report presents a description of the most popular digital folklore archives in the world. Specifications for designing and developing web-based social-oriented applications in the field of education and cultural tourism are formulated on the basis of comparative analysis. A project for structuring and categorizing the content is presented. A website for accessing the digital folklore archive is designed and implemented.

Extending the GUIDE@HAND Tourist Guide Application with QR Codes for Museum Learning

The following paper attempts to encompass the opportunities for applying QR codes for museums and exhibits through the example of the Hungarian Museum of Environmental Protection and Water Management (Esztergom, Hungary). Besides providing interactivity in the museum for the mobile phone generation through the utilization of a device and a method that they are familiar with, it is important to explain how and why it is worthwhile to “adorn” the exhibits with these codes. In this paper we also touch upon the technical issues of how an existing mobile phone application can be incorporated into and used for the presentation of the museum.

Learning by Doing in the Context of Modern Information and Media Literacy of Students in “Library and Information Management” in ULSIT Using the Digital Collection “Bulgarian Revival”

The purpose of this article is to evaluate the effectiveness of learning by doing as a practical tool for managing the training of students in "Library Management" at the ULSIT, Sofia, Bulgaria, by using the creation of project 'Data Base “Bulgarian Revival Towns” (CD), financed by Bulgarian Ministry of Education, Youth and Science (1/D002/144/13.10.2011) headed by Prof. DSc Ivanka Yankova, which aims to create new information resource for the towns which will serve the needs of scientific researches. By participating in generating the an array in the database through searching, selection and digitization of documents from these period, at the same time students get an opportunity to expand their skills to work effectively in a team, finding the interdisciplinary, a causal connection between the studied items, objects and subjects and foremost – practical experience in the field of digitization, information behavior, strategies for information search, etc. This method achieves good results for the accumulation of sustainable knowledge and it generates motivation to work in the field of library and information professions.

Discover the Thracians - An Approach for Use of 2D and 3D Technologies for Digitization of Cultural Heritage in the Field of E-learning

Information and communication technologies (ICT) offer an easier access to and a multi-perspective view of cultural heritage artifacts and may also enrich and improve cultural heritage education through the adoption of innovative learning/teaching methods. This paper examines the different practices and opportunities for digitization of cultural artifacts with historical significance and describes the work on a pilot project concerning the development of e-learning materials in the Thracian cultural and historical heritage. The proposed method presents an approach based on a combination of 2D and 3D technologies to facilitate the overall process of digitization of individual objects. This approach not only provides greater opportunities for presenting the Thracian heritage but also new perspectives for studying it - students, scientists, PhD students will have the opportunity to work with the materials without having access to them.

Approaches to Organization of Teaching for Creating Digital Learning Materials

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

Intercultural Learning and Entrepreneurship

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

A Multi-View Learning Algorithm

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

Developing Financial Expertise Through Mathematics and IT School Curricula

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

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.