Automated Monitoring and Forecasting of the Development of Educational Technologies

Automated Monitoring and Forecasting of the Development of Educational Technologies

Ilya Andreyevich Kozlov (Bauman Moscow State Technical University, Russia), Ark M. Andreev (Bauman Moscow State Technical University, Russia), Dmitry Valeryevich Berezkin (Bauman Moscow State Technical University, Russia) and Marwa Ahmed Shouman (Menofiya University, Egypt)
Copyright: © 2019 |Pages: 20
DOI: 10.4018/978-1-5225-3395-5.ch027

Abstract

This chapter will describe an approach to monitoring and forecasting the development of innovative educational technologies based on text stream analysis. The approach will involve detecting education-related events in the stream of text documents, constructing situations, determining possible scenarios of further development of situations, and generating recommendations for successful introduction of detected innovations into the educational process of the university. The authors will propose a multicriteria model of an event reflecting its key aspects. The chapter will describe an event detection method based on incremental clustering, as well as a scenario generation method based on the principle of historical analogy. The authors will discuss several experiments to evaluate the quality of the methods.
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Introduction

Novel methods and technologies constantly emerge in education with a goal to provide students with knowledge and skills demanded by modern society. To meet modern standards of education, universities introduce methods into their educational process. However, it is risky to introduce innovative teaching approaches because it is impossible to guarantee future success.

There is a need to discover new educational technologies, track their development, and predict their future development to determine whether it is reasonable to introduce them into the educational process of a university. This can be achieved by periodically downloading and analyzing text documents from Web sites and domain-specific sources. However, experts cannot manually analyze a text stream because of the huge amounts of documents generated by the sources.

This chapter will describe an approach to automated monitoring and forecasting of educational technologies development based on text stream analysis. The authors will use the term educational technologies in broad sense, which will include teaching methods and promising innovations in science and engineering that should be considered when planning and implementing study programs in universities.

Background

The authors will consider the process of the monitoring and forecasting of educational technologies development as a sequence of the following steps:

  • Step 1: Detecting events in the text stream related to educational technologies.

  • Step 2: Tracking situations development based on detected events.

  • Step 3: Determining possible scenarios for development of tracked situations.

  • Step 4: Generating recommendations for decision-makers.

The original task has been divided into four subtasks which will be described in the following sections.

Key Terms in this Chapter

Event: A significant change in the real world that is reflected in the text stream.

Text Stream: A sequence of text documents that are regularly downloaded from web sites and domain-specific sources.

Scenario: A hypothetical chain of events that is a potential continuation of current situation.

Educational Technologies: Innovative technologies and methods that should be considered while planning curriculum in universities.

Situation: A sequence of interrelated events that reflects the development of a certain educational technology or method.

Situational Graph: An oriented graph in which vertices correspond to events. A pair of vertices connect by an edge if the respective events belong to the same situation.

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