COGNITIVE ASPECTS OF THE FRAME ...

COGNITIVE ASPECTS OF THE FRAME APPLICATIONS IN THE EDUCATION

Walentyna Szwec

Instytut Edukacji Zawodowo-Technicznej, Narodowa Akademja Nauk Pedagogicznych Ukrainy, czapajewske szose 98, Kijów, Ukraina e-mail: [email protected] . ABSTRACT This paper presents the results of experimental implementation of new knowledge representation system. The problem of the investigation was to develop a new system of knowledge presentation, frame-based approach, and verification of the effectiveness of a leadership by students’ educational activity. The new forms of activation of the student’s cognitive abilities have been used to teach physics. Experimental verification of the effectiveness of the model was carried out with 416 students. The improvement of students’ knowledge quality was revealed as a result of research. The didactic system of the management of students’ educational activity that is constructed with use of frames and graphs allows the increase of the efficiency of educational process. The results of experimental investigations confirm the efficiency of proposed didactic model. Keywords: frame, graph, educational activity, didactic model. Introduction From the beginning of the 70-th of the XX-th century our society has been named “information society” due to the appearance of information technologies. The development of information technologies is determined by such factors as: the construction of personal computers, the development of versatile operation systems for computers, the creation and the development of fiber-optic communication and high-capacity data-storage devices. The authors of philosophical theories of information society (D. Bell, 1978; J. Baudrillard, 2005; M. Serre, 2011) determine such characteristic features of new society as: the high role of theoretic knowledge (D. Bell), the high degree of importance of the image in knowledge representation (J. Baudrillard), the externalization of the memory (M. Serre). These features of the information society give a new impulse to the development of activation of the students’cognitive abilities and educational activity management. The first attempts of solving this problem have been made by B. F. Skinner, 1953; N. Crowder, 1960; C. Kupisiewicz, 1980; A. Berg, 1966 etc. Significant

contribution to the problem of activation of the student’s cognitive abilities and the students’ educational activities management is “mind mapping” by A. Buzan. The one of modern approaches for the resolution of this problem is, for example, the Model of Educational Reconstruction (R. Duit, 2013). Problems of modern cognitive science and the various methods of converting the information in the human brain were examined by B. Siemieniecki, 2013. These authors considered the problem of optimization of the management of pedagogical system without taking into account the opportunities offered by the notion of “frame” – one of the basic concepts of information technologies. The aim of this article consists in the development of the didactic model of educational activity management, which would be in agreement with above-mentioned features of information society and would use the “frame” term for the construction of knowledge presentation (V. Shvets, The influence of knowledge representation on knowledge quality, 2012). Methodology The methodological framework for the management of training activities is based on classical theories of psychologists and educators: the theory of reflexes (I. Sechenov, I. Pavlov), the theory of interiorization (J. Piaget, 1972; P. Galperin) and the theory of algorithmization (L. Landa, 1966). These theories explain well the activity of the pedagogical system without computer. The appearance of computers in the pedagogical system brings two new conceptions: the graph and the frame. Flowcharts of computer programs are graphs. For the first time the concept of “graph” has been applied by the Swiss mathematician Leonhard Euler to solve the problem of the bridges of Könnigsberg city. The attempts to use graphs in teaching were made by Professor H. Paynter, 1961 (“bond graphs”), then – by E. Barhudaryan, 1974 and others. The shortcomings of their attempts consist of that the graphs were built for each task therefore they cannot be an instrument for solving of the class of problems. The computer in modern literature is called “frame”. The concept of the “frame” was proposed by M. Minsky in 1974. According to M. Minsky frame is the cognitive scheme that can be filled out by various information. The frame can be expressed in a graphic or a verbal form. The frame in a verbal form consists of slots which have a name and a value. The frame in a graphic form consists of vertices and arcs. The vertices have the values and the arcs that express the relationship between vertices. The frame that is unfilled by information (vertices and arcs) is called “proto-frame”, the filled frame is called “exo-frame”.

The frames have become the main link in the creation of programs called “expert systems”. Expert systems use the relationship of “is”, “has”, “there”. The graphs that present the information in expert systems called “semantic networks”. The example of such semantic network in physics, starting from the term “pressure” is presented on the fig. 1.

Fig. 1. The example of the semantic network in physics. Source: own work.

Such semantic network has the shortcoming that is common with graphs: they could be built for each task only therefore they are not an instrument for solving the class of problems. The solution of this problem consists of the semantic network construction that uses different type of relationships between the values. Let us use the relationships called “differentiation” and “integration”. Let us build the proto-frame with use of these relationships: if B1 and B2 are the values, D1 is the operator of differentiation and D2 is the operator of integration (fig. 2).

Fig. 2. The proto-frame with use of differentiation and integration relationships. Source: own work. Let us fill out the vertices and arcs of the proto-frame by information from kinematics: linear and circular motion. We receive the exo-frames (fig. 3).

Fig. 3. The exo-frames in kinematics showing relation between the distances (s, φ), velocities ( , ω) and accelerations (a, ε) defined for the linear and circular motions. Source: own work.

The exo-frames use the operator of differentiation (D1= integration (D2= distance

). The action of the operators

and the velocity

and

) and the operator of

can be demonstrated for the

with use of equations (1, 2): (1) (2)

Let’s connect the vertices which have the equal values; the values which are different by a coefficient we can connect by ribs. We receive the graph for knowledge representation in kinematics (fig. 4).

5

1

Fig. 4. The graph for knowledge representation in kinematics. Source: own work.

This graph allows to solve and to construct the problems in a way of route search. Let’s solve the problem: find

for the body on the filament wound on the block with the radius

if the equation of the block rotation is:

(fig. 5).

5

1

A

B Fig. 5. The problem (A) and the route for its solving (B). Source: own work.

Let’s solve this problem according to the graph route, which is shown on fig.5, executing it in a several steps. 1. The first link of this route is the differential transition from the vertex . Let’s reperent this link as:

to the vertex

and run its action. We receive:

. 2. The second link of the route is the differential transition from the vertex vertex :

to the

. Runnig the action of this link we receive:

3. On the third step of the problem solving we receive the linear acceleration:

4. On the fourth step of the solution we execute the integral transition from the vertex to the vertex :

, receiving:

5. The last step consist of the next link: receive the solution of the task:

. Running the action of this link we

Similar graphs are built for themes “Electrostatics” and “Magnetism” (V. Shvets, Management of educational activity of future experts in programming and computing engineering, 2013) and “Termodynamics” (V. Shvets, Physical Chemistry Teaching in Conditions of Information Society, 2014). The built graphs also allow solving problems by finding the routes in the graph structure. It should be noted though, that not all problems are covered by these graphs. Sometimes the problems solution is more convenient with the use of the other view of the frame called frame-script. The frame-script allows organize the verbal form of the problem solving. Let’s solve the problems for determination of the magnetic field induction. Frame-script for solving of these problems has 4 steps, with details easy to implement with any textbook bringing just the physical formulae. The frame-script for solving of the problems for determination of the magnetic field induction. 1. The determination of the circulation induction vector, according to definition. 2. The determination of circulation induction vector according to the Ampère’s circulational law. 3. The equation of circulation obtained in two ways, and the definition of the magnetic field induction. Let’s use this frame-script for solving of such problem: “On a thin tube of radius R currents the flow I A. Find the induction of magnetic field pipe tube at a distance r from the tube surface”.

Fig. 6. The determination of magnetic induction. Source: own work.

Algorithmic instructions to solve the problem based on the frame-script. 1. Write down the expression for the circulation of magnetic field vector on a circle of radius (R + r) in according to definition of a circulation. 2. Find the significance of magnetic induction circulation in according to Ampère’s circulational law. R

За в

3. Equate the right-hand sides of the equalities obtained in paragraphs 1 and 2 and find magnetic induction. The results of these algorithmic instructions are shown below:

The frame-scripts can be used for management of educational activity in the course of laboratory work performance. Let’s use the frame-script for performance of the laboratory work “The research of thin structure of the yellow D-line in Na spectrum”. The frame-script of this laboratory work has 3 steps: 1. The research of calibration spectra of the spectral device. 2. The creation of calibration curve of the spectral device. 3. The supervision of an unknown spectra and the determination of the wave length by the calibration curve. The frames, the frame-scripts and graphs of knowledge representation are the basis for knowledge presentation. The graphs allow creating the tests for measurements of knowledge. We give examples of the test questions, which can be easily obtained from the graph presentation of knowledge in kinematics in fig.4. Each question realizes one route of the knowledge representation graph. Question 1. The material point rotates in a circle according to law: . Find angular velocity of material point. The solution consists of the following route execution: Question 2. The velocity of the load on the spring changes according to law: . Find the law of acceleration change. The solution consists of the following route execution: Question 3. The velocity of material point which moves linearly changes according to law:

Find a way passed by the material point for 5 seconds from the beginning of

motion. The solution consists of the following route execution: Question 4. The angular velocity of small ball which rotates in a circle changes according to law:

. At what angle the ball turns during 3 seconds from beginning of motion? The

solution consists of the following route execution:

The full list of such questions for “General physics” discipline contains 180 questions, received from 600 questions by a standart procedure of the test validization (V. Shvets, The valid tests for a testing of students of higher educational instituts of information and telecommunication profiles on discipline “general physics”, 2012). This didactic model allows using the frames and the graphs of knowledge presentation for educational activity management in course of lectures, problems solving, performance of laboratory works, tests and for a creating of e-books (W. Szwec, E-learningowy podręcznik „Podstawy fizyki klasycznej” dla edukacji na odległość, 2007). The described methodology was applied to the management of knowledge presentation process for students of the first and second years (16-18 years old), which studied information specialties at the following Ukrainian universities: National Technical University of Ukraine “Kyiv Polytechnic Institute” (Kyiv), State University of Telecommunications (Kyiv), Open International University of Human Development “Ukraine” (Kyiv). These universities are leading universities of Ukraine in the IT specialists preparation. The students such specialties as: “computer ecology-economic monitoring”, “computer systems and networks”, “software engineering” participated in the experiment. Results and Discussions The test of this model efficiency was based on simple representative selection. The volume of representative selection was carried out according to the specified formula (3):

(3) where  x — beforehand set accuracy which is, as a rule, equal to 0.1 in statistical researches;  — selective dispersion; t — argument of normalized Laplace function

. In the pedagogical experiment took part 416 participants, from whom 208 were in the control groups and 208 were in the experimental groups. The results of modular computer testing were compared to results of written examination. The average arithmetic assessment received by the student for performance of the test tasks and

written examination was used for the assessment of efficiency of the offered didactic model. The estimation was made in a 5-mark scale of estimation. The recalculation of ESTS to the 5-mark scale is presented in the tab. 1. Tab. 1. The comparison of estimates in ESTS and the 5-mark scales.

ESTS 5-mark scale

0-59 2

60-74 3

75-89 4

90-100 5

The results of experiment are displayed on fig. 7. The group number is shown on the horizontal axis; the average assessment is shown on the vertical axis.

Fig.7. The comparison of pedagogical experiment results in control groups (light color, left-side bars) and experimental groups (dark color, right-side); the number of pair of groups (control and experimental) is shown on the axis X; the average assessment is shown on the axis Y.

The data from the fig. 5 testify that results of the pedagogical control in experimental groups tend to exceed the corresponding results in the control groups. The efficiency of the pedagogical experiment is measured with “null hypothesis”. The “null hypothesis” states that difference in the results of pedagogical control consists in purely accidental causes, thus the real efficiency of applied methods of teaching consist in its refutation. The null hypothesis is tested with estimations of the  2 criterion according to the formula (A. Kyverialg, 1980): (4) where

- relative frequency of a quantity of control works estimated as i in experimental

group (EG) and control group (CG). Acceptable value of  2 for significant level of pedagogical experiment research has to be equal to   0.05 , when the number of degrees of freedom equal to 3 (one less than the number of points, "2", "3", "4", "5") is

(A. Kyverialg, 1980).

Calculated data for the evaluation of the  2 criterion is listed in the tab. 2.

Tab. 2. The evaluation of the  2 criteria (EG - experimental group, CG - control group). ,%

2 3 4 5

EG 44 64 65 35 208

CG 44 89 59 16 208

EG 21.15 30.77 31.25 16.83 100

CG 21.15 42.79 28.37 7.69 100

0 12.02 2.88 9.14

0 144.48 8.29 83.54

0 3.38 0.29 10.86 14.53

We showed using the data from the tab.2 that Thus, there is a statistically significant difference between the experimental values and critical criteria:

(14.53>7.81) in the confidence level 0.05.

The improvement of the quality of students' knowledge of the experimental groups can be explained by sufficient efficiency of proposed didactic model. The efficiency of proposed didactic model could be explained as a consequence of factors: 1. The activation of the first signal system. This activation of the educational information is provided by the graph structure. The graph is a permanent tool for student’s educational activity therefore the process of information remembering is based on a mechanism of constant amounts (according to the theory of I. Sechenov). 2. The development of routs in the graph of knowledge representation which provides the repetition of visual impressions at different conditions of perception. This repetition is a necessary condition for the development of memory (according to the theory of I. Sechenov). 3. The transition from external management of student’s educational activity to the internal self-management by student. 4. The transition from activation of the first signal system with use of graphs of knowledge representation to activation of the second signal system with use frame-scripts for solution of problems (according to the theory of I. Pavlov). 9. The realization of conditions for interiorization which leads to the change of the subject making the activity as a result of that activity (according to the theory of J. Piaget) Conclusions The offered didactic model carries out a number of functions: cognitive, integration, diagnostic, controlling, correcting. These functions can be executed if the following conditions are realized:

1. The lecturers, the students and the head of the higher educational institution agree to apply this model in educational course. 2. The educational institution uses e-learning platform to test the students. 3. The lectures must be considerably in advance in time than the practical training for the creation of knowledge representation graphs. The offered didactic model solves a number of programmed training problems. The graphs of knowledge representations are the instruments for solving the class of problems. They allow finding of the different ways of problem solution. Their main advantage consists of the operation programming rather than programming of the text. Acknowledgment: I thank Prof. dr.hab. G. Karwasz, Director of the Establishment Of Physics Didactik at Nicolas Copernicus University, for useful discussions of this work. References E. Barhudaryan, Применение линейно–ориентированных графов при решении задач по физике в средней школе [The use of linear graph for solving of physical problems in school], autoreferat pracy doktorskiej, 1974, 25 s. (in Russian). J. Baudrillard, Symulakry i symulacja, Warszawa 2005, 197 s. D. Bell, The Cultural Contradictions of Capitalism, New York 1978, 301 p. A. I. Berg, Состояние и перспективы программированного обучения [The state and the perspective of programmed learning], Мoskwa 1966, 25 p. (in Russian). T. Buzan, Mind Mapping software from Tony Buzan, http://thinkbuzan.com [dostęp: 06.07.2015]. R. Duit, On the Nature of Science Education Research and Development A European Didaktik Position, http://ses.web.ied.edu.hk/ease2013/speaker.html [dostęp: 06.07.2015]. P. Galperin, Психология как объективная наука [Psychology as an objective science], Мoskwa 2006, 479 p. (in Russian). C. Kupisiewicz, Podstawy dydaktyki ogólnej, Warszawa 1980, 368 s. A. A. Kyverialg, Методы исследования в профессиональной педагогике [Research methods in professional pedagogics], Таllini 1980, 334 s. (in Russian). L. Landa, Алгоритмизация в обучении [Algorithmization in a teaching], Мoskwa 1966, 523 p. (in Russian). M. Minsky, A Framework for Representing Knowledge, Cambridge 1974, 152 s. I. Pavlov, Полное собр. Трудов. T. 3 [The complete collection of works.Vol. 3], Мoskwa-Leningrad 1949, 603 p. (in Russian). H. M. Paynter, Analysis and Design of Engineering System, Cambridge 1961. J. Piaget, Structuralizm, Warszawa 1972, 174 s. I. Sechenov, Элементы мысли [The thought elements], Мoskwa-Leningrad 1943, 223 p. (in Russian). M. Serres,

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