Tuesday , October 23 2018

Volume 18-Issue2-2009-MOISE

Applying Fuzzy Control in the Online Learning Systems

Gabriela MOISE
Petroleum-Gas University of Ploiesti
no. 39 Blvd. Bucuresti, Ploiesti

Abstract: Current computer-assisted instructional systems are mostly oriented towards offering flexible, adaptive and personalized instruction solutions. Managing the learning process in a computer-assisted instructional system may be done manually, a case in which the instructional decisions belong to the learner, or automatically, when the decisions are made by the computer program. Literature designates the manual management of the online instructional process with the term learner control, whereas the one used for denominating the automatic management is program control.

Taking into consideration the characteristic of the online instruction process, defined by a virtual communication between the teacher/trainee and the learner, that may be realized by synchronic or asynchronic communication media, the issue of managing the instruction process poses two problems/aspects. The former refers to defining the management method, i.e. manual or automatic, and the latter relates to the way the automatic management of the instruction process may be fulfilled, considering the nontechnical aspect of the process.

This paper analyzes the terms learner control and program control in the context of the online instruction process and the factors that influence reaching the performance/proficiency objectives in the online instruction process learner control or program control approaches. It also proposes a fuzzy type regulator that is able to regulate the online instruction process working regime. Theoretical results presented in this paper are simulated by using MatLab program, FIS Module

Keywords: Elearning, fuzzy control, learner control, machine (program) control

Gabriela Moise received her M. Sc. in Mathematics, specialization Informatics (1992) from Bucharest University and Ph.D in Automatic Control (2008) from Petroleum-Gas University of Ploiesti. Her research fields are: e-learning, graph theory, pedagogical agents, knowledge representation, systems engineering. She has (co)authored seven books and more than twenty research papers. She has participated in many international conferences in the e-learning and e-business area.

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CITE THIS PAPER AS:
Gabriela MOISE, Applying Fuzzy Control in the Online Learning Systems, Studies in Informatics and Control, ISSN 1220-1766, vol. 18 (2), pp. 165-172, 2009.

1. Introduction

The control of the learning process in a computer-assisted instructional system can be carried out manually, case in which the instructional decisions are to be taken by the instructors or automatically, case in which a software program is to control the instructional process. The term used to define the manual control of the online learning process is learner control and the term used to define the automatic control is machine (program) control.

The control mode of the online learning process has two aspects. The former aspect refers to the regime of control: manual or automatic. The latter aspect refers to the structure, components and implementation mode of an online learning automatic system, taking into consideration the nontechnical aspect of the process.

The term metacognition designates the knowledge of a person over the cognitive process itself and the ability of a person to optimize the functionality of his/her cognitive process. The concept of metacogniton is a fuzzy concept. [16] This concept has a determinant role in the regulation of the online instruction process. This aspect requires a fuzzy control to regulate the working regime of an instructional system.

The new paradigm of the computer-based instruction is directed to the flexible learning, adaptive learning and personalized learning. In a computer-based instruction system, the control over the learning process can be performed by the learner or by the machine. The literature in the field of education provides a lot of experiences about the control in the online learning process. The challenges of the control in the online learning have two sides: in the former, we report to who controls the process: the learner or the machine, and in the latter, we report to the manner to realize an automatic controller to the online learning process.

So, the major challenges are: to establish the degree of the learner control and the machine control, the moment when it is needed to transfer the control from learner to machine (software program), or from machine (software program) to learner and so forth and what components of the e-courses, seen as control objects have to be controlled by the learner or by the software program.

So, we can summarize these aspects in the following questions: who, how much, when, what controls the online learning process.

To manage these problems, we have to define the concepts of the learner control and the machine (or program control) control.

4. Conclusions

The problem of the online instruction may be approached through different techniques from fields that are not apparently connected. Investigations and researches in the domain of the online instruction have revealed the possibility to use methodologies based on fuzzy inductive reasonss. The fuzzy regulator that was presented in this paper mediates the working regime of the online instructional processes management. In case of automatic control, the online instructional process is controlled by a computer program, and orders are generated by using techniques of artificial intelligence, whereas in manual control, instructional decisions belong to the student/trainee that acts as his/her own instruction regulator.

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