=Paper=
{{Paper
|id=Vol-2879/paper29
|storemode=property
|title=Computer simulation of processes that influence adolescent learning motivation
|pdfUrl=https://ceur-ws.org/Vol-2879/paper29.pdf
|volume=Vol-2879
|authors=Larysa O. Kondratenko,Hanna T. Samoylenko,Arnold E. Kiv,Anna V. Selivanova,Oleg I. Pursky,Tetyana O. Filimonova,Iryna O. Buchatska
}}
==Computer simulation of processes that influence adolescent learning motivation==
https://ceur-ws.org/Vol-2879/paper29.pdf
Computer simulation of processes that influence
adolescent learning motivation
Larysa O. Kondratenko1 , Hanna T. Samoylenko2 , Arnold E. Kiv3 , Anna V. Selivanova2 ,
Oleg I. Pursky2 , Tetyana O. Filimonova2 and Iryna O. Buchatska2
1
G.S. Kostiuk Institute of Psychology of the National Academy of Educational Sciences of Ukraine, 2 Pankivska Str., Kyiv,
01033, Ukraine
2
Kyiv National University of Trade and Economics, 19 Kioto Str., Kyiv, 02156, Ukraine
3
Ben-Gurion University of the Negev, P.O.B. 653, Beer Sheva, 8410501, Israel
Abstract
In order for the learning process to always retain personal value for the learner, it is necessary that his or
her motivation be maintained through an awareness of his or her purpose and goals. This article presents
a local model (at the individual object level) of enhancing external motivation, which give to determine
students’ efforts to get rewards. The concept of this model based on describing the behavior of agents (in
our case students). The characteristics of the phenomenon in the motivation of learning at different stages
of adolescent development are analyzed. The problem of computer modeling of educational processes
with the help of agent modeling on the example of studying student motivation is considered. Internal
and external factors that may strengthen or weaken the adolescent’s motivation to study have been
studied. The expediency of using information technologies of agent modeling to study the dynamics of
strengthening or weakening student motivation is substantiated. Using the AnyLogic Cloud computing
environment the change of dynamics of strengthening of motivation of teenagers on an example of
model of strengthening of external motivation is defined.
Keywords
computer simulation, behavior of agents, educational processes, adolescent learning motivation
1. Introduction
Adolescence is a phase of lifespan associated with greater independence, and thus greater
demands to make self-guided decisions in the face of risks, uncertainty, and varying outcomes
CTE 2020: 8th Workshop on Cloud Technologies in Education, December 18, 2020, Kryvyi Rih, Ukraine
" Lorusz@ukr.net (L. O. Kondratenko); h.samoylenko@knute.edu.ua (H. T. Samoylenko); kiv@bgu.ac.il (A. E. Kiv);
ann.selivanova1@gmail.com (A. V. Selivanova); o.pursky@knute.edu.ua (O. I. Pursky); t.filimonova@knute.edu.ua
(T. O. Filimonova); i.buchatska@knute.edu.ua (I. O. Buchatska)
~ http://psychology-naes-ua.institute/read/330/ (L. O. Kondratenko);
https://knute.edu.ua/blog/read/?pid=12695&uk (H. T. Samoylenko);
https://www.linkedin.com/in/arnold-kiv-55980821/ (A. E. Kiv); https://knute.edu.ua/blog/read/?pid=12695&uk
(A. V. Selivanova); https://knute.edu.ua/file/MTcyNjQ=/98717622ed46f90a934d4e922d214fbc.pdf (O. I. Pursky);
https://knute.edu.ua/file/MTcyNjQ=/c79f2c8aa84be4d68e9bcbefcd56fc8f.pdf (T. O. Filimonova);
https://knute.edu.ua/file/MTIyMzc=/0fa912ad1527ff6a2ed19293f1fa57a5.pdf (I. O. Buchatska)
0000-0001-7271-7439 (L. O. Kondratenko); 0000-0002-4692-6218 (H. T. Samoylenko); 0000-0002-0991-2343
(A. E. Kiv); 0000-0001-6559-1508 (A. V. Selivanova); 0000-0002-1230-0305 (O. I. Pursky); 0000-0001-9467-0141
(T. O. Filimonova); 0000-0003-2413-7370 (I. O. Buchatska)
© 2020 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
Workshop
Proceedings
http://ceur-ws.org
ISSN 1613-0073
CEUR Workshop Proceedings (CEUR-WS.org)
495
[1]. Evidence is mounting to suggest that multiple decision processes are tuned differently in
adolescents and adults including reward reactivity, uncertainty-tolerance, delay discounting,
and experiential assessments of value and risk [1]. The motivation of adolescents in learning
contexts has emerged as an important issue of educational research over the last 20 years,
because adolescence is a time of change and preparation for adulthood, and because academic
achievement at this time can have significant implications on employment or career opportuni-
ties, understanding adolescents’ motivation is vital to ensuring students achieve their potential
[2].
Cloud technologies has great potential to address the problem solving process of adolescent
learning motivation which is a complex activity [3, 4]. In the modern world, it is extremely
important to study the complex processes in learning, the development of which can only be
effectively predicted by computer simulation [5, 6, 7, 8, 9, 10, 11, 12, 13]. This paper discusses
the peculiarities of cloud computing simulation of educational processes with the help of agent
modeling based on the study of adolescent learning motivation. Learning motivation [14, 15],
due to its multidimensionality, the presence of various (sometimes even opposite) factors that
cause its emergence, development and disappearance, is one of the most difficult problems in
psychology. A great deal of research is devoted to its solution, but there is still not a sufficiently
convincing model of this phenomenon that would allow teachers to successfully control changes
in pupils’ learning motivation. The reason for this is not only the complexity of the phenomenon,
but also its distinctive manifestations at different stages of the child’s development.
The latest achievements of psychologists on learning motivation issues are presented in
the 2018 annual edition of “How People Learn II” [16] by the American National Academies
of Sciences, Engineering, and Medicine, which regularly provides thorough reviews of the
latest views in various scientific and technical fields. According to it, learning motivation
is defined as a condition that activates and sustains behavior toward a goal. It is critical to
learning and achievement across the life span in both informal settings and formal learning
environments. For example, children who are motivated tend to be engaged, persist longer, have
better learning outcomes, and perform better than other children on standardized achievement
tests [17]. Motivation is distinguishable from general cognitive functioning and helps to explain
gains in achievement independent of scores on intelligence tests [18]. It is also distinguishable
from states related to it, such as engagement, interest, goal orientation, grit, and tenacity, all of
which have different antecedents and different implications for learning and achievement [19].
People are motivated to develop competence and solve problems by rewards and punishments
but often have intrinsic reasons for learning that may be more powerful.
2. Results and discussion
Learners tend to persist in learning when they face a manageable challenge (neither too easy nor
too frustrating) and when they see the value and utility of what they are learning. Children and
adults who focus mainly on their own performance (such as on gaining recognition or avoiding
negative judgments) are less likely to seek challenges and persist than those who focus on
learning itself. Learners who focus on learning rather than performance or who have intrinsic
motivation to learn tend to set goals for themselves and regard increasing their competence
496
to be a goal. Teachers can be effective in encouraging students to focus on learning instead of
performance, helping them to develop a learning orientation. Given the above characteristic of
the phenomenon, it is possible to distinguish several blocks in the learning motivation.
Block 1. The personal meaning of learning for the student (learning subject). For
a young child learning is a natural process, he or she learns constantly, exploring the world,
knowing and realizing it. In the first stages, learning motivation is the innate need to understand
the world in which you live. This understanding has always been and is a prerequisite for
survival. Senior preschoolers and junior pupils are deepening their knowledge of the world
in two ways: practically exploring it and purposefully studying it with the help of specially
organized learning. For teens, learning is the main source of knowledge. Learning, according
to the “Ukrainian Psychological Terminology dictionary” is “purposeful personal assignment
of knowledge and skills of social experience, in the process of which their content is not only
transformed to the individual experience of the student, but also directed at the formation of the
subject’s personalities through his or her needs and motivational sphere” [20]. APA dictionary,
which is one of the most respected psychological dictionaries in the world today, views teaching
as “the acquisition of novel information, behaviors, or abilities after practice, observation, or
other experiences, as evidenced by change in behavior, knowledge, or brain function” [21, 16].
Despite some differences in understanding of the concept of learning in both dictionaries, it is
noted that learning is a purely personal process, in contrast to teaching, which is based on the
interaction between the teacher (someone, or something that teaches) and the student. A final
point to make is that, in the context of the growing expansion of virtual learning systems, the
important question is whether such learning systems provide interaction between the learner
and the teacher (or program). In the absence of such interaction, even a motivated learning
process can stop at the first stage of the assimilation of information, and not proceed to the
second main stage of the internalization of information and its transformation into knowledge.
In order for the learning process to always retain personal value for the learner, it is necessary
that his or her motivation be maintained through an awareness of his or her purpose and goals.
At the same time, more stable motivation for learning is manifested when purposes and goals
(the essence of the differences between these concepts will be discussed below) have a long-term
character, directly related to future planning and conscious life tasks. Such motivation can be
defined as “strategic”. Tactical or short-term motivation defines purposes or goals that can be
achieved in the near future (lesson, term, school year, etc.). Tactical motivation is often the
result of specific external stimulation when a student tries to receive the promised reward or
to avoid punishment. The least motivated to learn are those adolescents who do not associate
their personal purposes and goals with learning at all. The purpose of the study answers the
question “Why am I learning?”
The goal of the goal is to answer the question “What am I learning for?”.
Learning motivation of adolescents increases significantly when combined with a well-
understood goal and purpose.
Block 2. Extrinsic and intrinsic learning motivation. The effectiveness of learning
motivation depends largely on the values that are important to a particular individual. What
is most important for a adolescent is to achieve something (a life goal or a task); enjoy the
process of cognition; raise your image in the eyes of the environment; deserve praise or reward;
prove something to yourself or avoid anxiety and defeat. Personal values are directly related
497
to internal or external type of motivation. Intrinsic learning motivation is driven by cognitive
curiosity, pleasure from solving intellectual problems, curiosity, desire to learn more. Intrinsic
motivation does not need external stimulation (or reinforcement), because it is of value in itself,
it is not tied to a specific result. In essence, it contains both motive and stimulus [22, 23, 24].
Extrinsic motivation depends on extrinsic factors, is driven by additional reinforcements,
and is carried out using a reward incentive, which can be either tangible (money, valuation,
privileges, etc.) or intangible (praise, enhancement of image or status in society, punishment,
etc.). Important factors in influencing extrinsic motivation are the lack of real intrinsic moti-
vation and the student’s willingness to receive rewards for success in learning or preventing
punishment for failure. At the same time, the learning itself is perceived as a burden and does
not bring pleasure
Mixed motivation arises in the case of a combination of internal and external factors. This
combination can be both positive and negative. In particular, intrinsic motivation can be
reinforced by positive externalities when parents support and encourage the adolescent and
weaken in case of indifference to the student’s successes and failures. A special case of mixed
motivation, in E.R. Lai’s view, is learning motivation driven by internal pressures such as
obligation or guilt [25]. Numerous studies [26, 27, 28, 29, 30] indicate that good intrinsic
motivation correlates with both better learning outcomes and overall life success.
Block 3. Objectives of motivated activity are indicators of what an individual is
focused on when performing a particular task. Broussard and Garrison separate goals
of skill and performance. What’s the difference? The goals of skill are focused on learning
for the sake of learning, self-worth of learning, meeting one’s own cognitive needs, while the
goals of performance are to show others their achievements. Goals of skill are associated with
a high capacity for information analysis and planning, and the belief that effort enhances a
person’s capabilities. On the other hand, goals of performance are accompanied by thoughts
of achievements, evaluations, and external rewards. In the long run, goals of skill are better
motivators of learning than goals of performance.
Block 4. Locus of control is the tendency to attribute successes or failures to internal
or external factors. If an adolescent has an internal locus of control, then the student is aware
of the importance of his or her activity to achieve a specific goal and purpose, and therefore
his or her motivation for effective learning increases significantly. As research (Connell and
Wellborn [23], Weiner [24], Eccles and Wigfield [30]) found in this case. he or she will be as
motivated as he or she will feel that he or she is in control of his o her own successes and
failures.
The influence of the various factors can enhance or weaken adolescent learning motivation
is presented at figure 1 (included the number of conditional points that each factor can add
to the motivation). When an exterior locus of control is present in an adolescent, in difficult
situations his or her motivation for learning will decrease significantly. In particular, difficulties
in completing a task will lead to a decrease in effort and a drop in motivation in students with
extrinsic motivation, who believe that they lack skills, parents assist poorly, teachers explain
poorly and, conversely, increase motivation in students with an internal locus of control that
associates their success or failure with the effort spent, since failure for the first group means
impossibility that is difficult to change, whereas failure for the second group means that one
simply needs better try.
498
Figure 1: Graphical model of the influence of various factors that can enhance or weaken adolescent
learning motivation.
It is advisable to use agent modeling information technology to quickly track and respond
to changes in learning, as well as to depict the dynamics of enhancing or weakening learning
motivation. The basis for describing the behavior of agents (in our case students) is based on a
life cycle model: each agent develops according to his or her own behavior model, which can
change within his or her individual life cycle. The life cycle of a particular agent is presented as
a system that changes its internal states, and can be specified as a graph of transitions between
stages (modes) of its existence. The dynamic model of the transition of the agent from one
mode of operation to another is presented in the form of a production model, which consists of
agent functioning modes array; transformation rules array (knowledge base); and interpreter
(inference machines) [31]. There are two types of agent model definition levels:
• global models (multiple objects grouped on the basis of a particular attribute),
• local models (at the individual object level).
According to the principles of agents building models, there are several approaches (figure 2):
• the use of regression dependencies to determine logic at the level of agents arrays,
• the formation of a knowledge base of agents based on Data Mining to determine the logic
of individual agents behavior,
• the use of target functions to determine the logic of agents’ behavior.
499
Figure 2: Model of agent behavior.
Investigating the change in the dynamics of enhancing the motivation of agents can be
exemplified by the model of enhancing external motivation (figure 3). The first step in building
the model will be to determine the criteria and conditions under which the experiment will
be started. We will consider a comparatively small educational institution of 5000 people. To
implement the model, each student will be an agent. Because it is determined that contingent
rewards are new, no one will ever be interested in and will not use them from the very beginning,
interest in students may be influenced by advertising. After that, the number of interested
people will also be affected by the natural increase that will occur due to the fact that students
who have already received awards will share information about them with their acquaintances.
The latter will be added to the model indicators that can adversely affect the performance of
the system, since they will change the conditions of external motivation in the model under
consideration. Using the model implemented in the AnyLogic Cloud software environment [31]
(web service for applying simulation operationally) it is possible to determine students’ efforts
to get rewards (the transition of agents from state 1 to state 2) (figure 3).
Thus, the detected regression dependencies can be used to build models of system dynamics
(used in cases where it is impossible to take into account all external factors that affect the
behavior of a group of people in modeling the behavior of each person separately). Using the
500
Figure 3: Transition of agents.
knowledge base of agents enables the construction of local models that determine the logic of
behavior at the individual agent level.
This approach is based on the assumption that agents who have the same sets of characteristics
under the same conditions behave similarly (the likelihood of a positive decision on an issue
changes with the change in the characteristics of the agent). These approaches can be used in
the presence of a sufficient amount of statistics and the ability to distinguish stable relationships
between impact factors and outcomes. When modeling conditions that have not previously
been encountered (such as crises), it is appropriate to use target functions to determine the
behavior of agents that determine the behavior of model objects in different situations.
501
Changing the parameters will reflect the growth of agents of one or another category as a
graph. As a result, the diagram (figure 4) will show the approximate result that can be expected
after the model is started.
Figure 4: Changing the number of interested agents.
There is a significant group of agents who receive rewards from extrinsic motivation, further
some of them are interested and even fewer are completely uninterested. To test the work, you
must run the model and follow its execution. The number of interested agents is constantly
growing and does not exceed the number of agents who have already received rewards (on
most of the schedule). In a certain area (figure 5), agents also successfully switch from one state
to another, which is also accompanied by a change in color.
This indicates that the model successfully reflects the processes that occur when students are
externally motivated.
3. Conclusion
Motivation plays a key role in the learning process [25]. The effectiveness of learning motivation
depends largely on the values that are important to a particular individual [32]. Personal values
are directly related to internal or external type of motivation. It is advisable to use agent
modeling information technology to quickly track and respond to changes in learning. The
detected regression dependencies can be used to build models of system dynamics (used in
cases where it is impossible to take into account all external factors that affect the behavior
of a group of people in modeling the behavior of each person separately). This approach is
based on the assumption that agents who have the same sets of characteristics under the same
conditions behave similarly (the likelihood of a positive decision on an issue changes with the
change in the characteristics of the agent). These approaches can be used in the presence of a
sufficient amount of statistics and the ability to distinguish stable relationships between impact
502
Figure 5: Visualization of agent state transition.
factors and outcomes. When modeling conditions that have not previously been encountered
(such as crises), it is appropriate to use target functions to determine the behavior of agents
that determine the behavior of model objects in different situations.
Using the knowledge base of agents enables the construction of local models that determine
the logic of behavior at the individual agent level. Investigating the change in the dynamics
of enhancing the motivation of agents can be exemplified by the model of enhancing external
motivation. Using the model implemented in the AnyLogic Cloud software environment it is
possible to determine the stransition of agents from completely uninterested to receive rewards
from extrinsic motivation. The implementation of an agent model of enhancing external
503
motivation as an element of learning about student motivation provides a significant level of
growth for the group of students who receive rewards from external motivation. Involving
information technology to agent modeling provides an opportunity to track the conditions
when the motivation will be strengthened or weakened.
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