The concept of using evolutionary algorithms as tools for optimal planning of multimodal composition in the didactic texts

• Autorzy: Jakubowski M. A. , Charlak M. , Gryniewicz-Jaworska M.
• Języki publikacji: EN

Abstrakty

EN

At the beginning we would like to provide a short description of the new theory of learning in the digital age called connectivism. It is the integration of principles explored by the following theories: chaos, network, complexity and self-organization. Next, we describe in short new visual solutions for the teaching of writing so called multimodal literacy 5–11. We define and describe the following notions: multimodal text and original theory so called NOS (non-optimum systems methodology) as a basis for new methods of visual solutions at the classes and audiovisual texts applications. Especially, we would like to emphasize the tremendous usefulness of evolutionary algorithms VEGA and NSGA as tools for optimal planning of multimodal composition in teaching texts. Finally, we give some examples of didactic texts for classrooms, which provide a deep insight into learning skills and tasks needed in the Internet age.

Słowa kluczowe

EN

algorithm; didactic text; connectivism

• Wydawca: Lublin University of Technology ; Polish Society of Ecological Engineering (PTIE), Branch of PTIE in Lublin
• Czasopismo: Advances in Science and Technology. Research Journal
• Rocznik: 2014
• Tom: Vol. 8, nr 24
• Strony: 83--89
• Opis fizyczny: Bibliogr. 10 poz., fig., tab.

Twórcy

autor

Jakubowski M. A.

• Management Faculty, Lublin University of Technology, Nadbystrzycka 38, 20-618 Lublin, Poland

autor

Charlak M.

• Fundamentals of Technology Faculty, Lublin University of Technology, Nadbystrzycka 38, 20-618 Lublin, Poland

autor

Gryniewicz-Jaworska M.

• Faculty of Electrical Engineering and Computer Science, Lublin University of Technology, Nadbystrzycka 38A, 20-618 Lublin, Poland

Bibliografia

• 1. http://www.connectivism.ca/about.html
• 2. Bearne E., Wolstencroft H.: Visual approaches to teaching writing. Paul Chapman Publishing, London 2007.
• 3. http://mpra.ub.uni-muenchen.de/31620/1/MPRA_ paper_31620.pdf
• 4. http://www.zam.iiar.pwr.wroc.pl/index.php?option =com_content&view=article&id=11&Itemid=19
• 5. Michalewicz Z.: Algorytmy genetyczne + struktury danych = programy ewolucyjne. WNT 1999.
• 6. http://aragorn.pb.bialystok.pl/~wkwedlo/EA1.pdf
• 7. http://www.michal.ejdys.pl/nauka/emh-pg.pdf
• 8. Technologie wiedzy w zarządzaniu publicznym. Zeszyty Naukowe Wydziałowe Uniwersytetu Ekonomicznego w Katowicach, Katowice 2012.
• 9. Ping He: Fuzzy non-optimum system theory and methods. Fuzzy sets, IFSA-EC, Warsaw 1986.
• 10. Charlak M., Jakubowski M.A.: The concept of integrated engineering and business (EB) education system. Advances in Science and Technology Research Journal, Vol. 7 (20), 2013, 99–103.