JTUS, Vol. 02, No. 9
September 2024
E-ISSN: 2984-7435,
P-ISSN: 2984-7427
|
DOI: https://doi.org/ |
Development of Artificial Intelligence-Based Logic Mind
Applications in Improving Computational Thinking Skills
Hefty Magda Lestari1*,
Ekohariadi2
1,2 Universitas Negeri Surabaya,
Indonesia
Email: [email protected]1*, [email protected]2
|
Abstract Life in the 21st century demands human resources who have many skills
and competencies. Indirectly, human resources who are always creative and
innovative in developing technology are also needed. Technological
developments occur very rapidly depending on the quality of human resources
themselves. If human resources are able to process technological
sophistication properly and carefully, technological development can develop
rapidly. Likewise, if the quality of human resources is lacking in processing
existing technology, then technological development will also be slow.
Integrating technology in a targeted and meaningful way is the right
foundation of education today. Nowadays amazing technologies based on
Artificial Intelligence have emerged. The problems that occur during the
learning process when students are given stimulus are problems where students
are less active in responding. The results of students in providing solutions
are still not precise and coherent. This shows that students' computational
thinking skills are still lacking. The ADDIE approach is used to conduct
research. Meanwhile, a quantitative descriptive approach will be used to
collect and analyze research data using the T-test. The results of the
validation of learning media or mobile routing applications give a rating of
80%, meaning that they are considered suitable for use. Based on research
conducted on students who took the pretest and posttest, their average score
was 71.69 in the pretest and 88.13 in the posttest. Thus, this can indicate
that there is a significant impact and variation in the results of the
averages achieved. Keywords:
Computational
Thinking, Application, Artificial Intelligence, Android, Education. |
INTRODUCTION
Life in the 21st Century demands human resources to have many
skills and competencies. Indirectly, it also demands to become human resources
who are always creative and innovative in developing technology (Mardhiyah et al., 2021). Technological developments occur very rapidly depending on
the quality of human resources. If the human resources are able to utilize
technological sophistication well, wisely and carefully, then technological
development is able to develop rapidly (Faiza & Firda, 2018). Likewise, vice versa, if the quality of human resources is
lacking in processing existing technology, technological development is also
slow.
Some of the skills that should be possessed include critical
thinking, problem-solving, cognitive, and digital literacy (Cynthia & Sihotang, 2023). The skill of always thinking critically in developing
creative ideas and innovations to solve every problem, including computational
thinking, gets special attention. Because this skill is the main thing that
must be applied to basic problem-solving.
Computational thinking requires several development
components, including (a) the ability to analyze problems and decipher them
into elements or parts (analytical thinking); (b) the ability to plan a series
of actions or steps to achieve problem-solving (algorithmic thinking); (c) the
ability to monitor and correct errors in the implementation of the plan
(debugging, (Buitrago Fl�rez et al., 2017) and (d) the ability to identify the most relevant aspects of
the problem and generalizable algorithms (abstractions), which allow
application to other problems what has been studied (Rom�n-Gonz�lez et al., 2017).
Integrating technology in a directional and meaningful way is
the basis of proper education today. This must be done in order to be able to
keep up with technological developments that occur so that education is able to
compete in accordance with the latest conditions. The call to use AI as a means
to improve student skills in the 21st century is already happening in research (Asunda et al., 2023). In the study, it is argued that schools need to provide
opportunities to facilitate the development of AI competencies. This is
supported by research (Su & Yang, 2023), which ensures that to keep up with changes in the field of
education, educational institutions can take advantage of the latest
technological advances. Without realizing it, in everyday life AI has done its
job and interacted with humans, for example, when searching on the internet and
getting recommendations from search results that you want to search for or some
videos recommended by YouTube (Celik et al., 2022). The advantages of AI are the ability to change the way
people live and work in a more positive direction.
Currently, extraordinary technologies based on Artificial
Intelligence have emerged, one of which was developed by OpenAI, namely
ChatGPT. This technology is able to be in the spotlight for providing solutions
with common generative models (Klimova et al., 2023). In particular, this technology is capable of providing its
users with multiple answers to questions asked in a conversation to complete
several tasks, such as essays and coding (Lo, 2023). The potential and ability possessed by ChatGPT is to create
exercises that are in line with students' proficiency levels, interests, and
goals (Baskara, 2023). The sophistication of today's technology is able to give
rise to several Artificial Intelligence whose uses are almost the same or
similar. The Artificial Intelligence technologies are WriteSonic and Claude.
The relationship between Artificial Intelligence and education has important
relationships, such as E-Learning, engineering education and computing
education that are integrated with each other (Polat et al., 2024).
The problems during the learning process when students are
given a stimulus are in the form of students being less active in responding.
The results of students in providing solutions are still not appropriate and
lacking. This shows that the computational thinking skills possessed by
students are still lacking. This happens because students lack practice to
develop critical thinking skills. In addition, the use of technology as a
learning medium to support the progress of the teaching and learning process is
also still lacking in its use due to the limited time that teachers have in
making learning media. This makes the learning process less effective.�
Previous research shows that the use of AI-based
technologies, including in the development of computational thinking skills,
has been shown to be effective in some contexts. However, research on
applications specifically designed to develop AI-based logical thinking skills
among students is still relatively limited. Research by (Hakim et al., 2024) highlights the potential of AI in education, but does not
specifically address the application of AI-based logic in improving
computational thinking skills. The research gap of this study lies in the lack
of research that focuses on the development of AI-based applications for
logical thinking skills in the Indonesian educational context, especially those
that integrate between technological and pedagogical aspects in improving
computational thinking skills. The novelty of this research is the development of
an artificial intelligence-based application specifically designed to improve
students' computational thinking skills, with an integrated approach between
technology and innovative teaching strategies. This research will not only fill
the gap in the literature on the use of AI in education, but also make a
practical contribution to the development of technology-based learning media.
Based
on the background description above, the purpose of this study is to determine
and analyze the development of artificial intelligence-based logic mind
applications in improving computational thinking skills. The benefits of this
research are to make theoretical and practical contributions in the field of
education, especially in the development of innovative learning technologies.
Theoretically, this research is expected to add to the literature on the use of
artificial intelligence to improve computational thinking skills. This research
can also provide new insights into the effectiveness of AI-based applications
in the context of education. Practically, the results of this study are
expected to be a reference for educational application developers and educators
in designing and implementing technology that can strengthen computational
thinking skills among students.
METHOD
This study uses an experimental method to achieve certain
goals on several variables to be tested. This goal is able to influence the
independent variable to the bound variable. This experimental research will be
carried out by conducting a scientific examination where one variable will be
changed and applied to one dependent variable to see its effect. The influence
that occurs is observed and recorded to help researchers reach conclusions
between the relationships between variables. The experimental research design
consists of time in establishing cause-and-effect relationships, consistent
cause-and-effect behaviors and understanding the importance of cause and
effect.
Outlining the steps involved in conducting research,
including how to prepare research materials, research design, research
processes (such as using pseudocode or algorithms), testing, and gathering
results. There is also a theoretical foundation in this section. Pretest and
posttest are part of the quasi-experimental research design used. The ADDIE
development model is the method used in this study which consists of five
steps:
Analyze
The first stage is the process of analyzing the condition of
students' computational thinking skills. This analysis process is given by
providing a trigger question to find out how active and critical the student is
in solving a problem. It turns out that the results of students in solving
problems are still not solved properly. This means that students' competence in
computational thinking or thinking to solve problems critically and logically
is still lacking. This is a fairly serious problem and there must be follow-up
action, because thinking computing is the basic foundation in all fields to
solve problems. The action that can be taken in solving this problem is to
develop learning media. These problems can arise due to the lack of use of
technology to train students' thinking skills.
Anonymous
According to ADDIE's research and
development model, design activities are a methodical process that begins with
the creation of concepts and content for the final product. Three steps make up
this design stage. The first involves creating learning materials at the same
time as the design production stage. The process of designing an application
storyboard consists of parts: practice questions, AI, videos, materials, KI KD,
home, and evaluation. The collection of learning media research tools is the
second stage of design. Gathering content for the app is the third design step.
It includes understanding computational thinking, the basics of computational
thinking, practice questions, and assessment. To make it easier for students to
understand, take a look at some of the accompanying videos.
Development
In ADDIE's research and development
methodology, development refers to the actions taken to bring to life a product
design that has been previously developed. A conceptual framework for the
implementation of the new product has been created in the early phases. After
that, the conceptual framework is transformed into a ready-to-use finished
product. This product is in the form of an android application called
"Logic Mind". This application is made using GlideApps which offers
the facility of creating applications without coding. The Logic Mind
application contains materials, audio, video, practice questions and is
integrated with Artificial Intelligence. The results of the design that have
been made are:
Home
Home view is the initial view seen by the user. This
page is the main homepage of the application that displays various information
and access to the features provided. The information contained on the home page
is a brief introduction to the application and its functions. Contains a video
about the importance of having the ability to think computationally.
Figure 1. Home Page
In
the image above, it can be seen that on the Home menu, there is access in the
form of a button on the left side to go to the KI KD page, Material, Video,
Practice Questions, Artificial Intelligence, and Evaluation. Below is also the
app creator's profile. Finally, there is the written made wiht Glide is a
marker that the application was made using GlideApps.
KI KD
On this KID KD page, it displays a list of
core competencies with basic competencies that students should master. This
menu explains in detail what competencies must be mastered along with their
achievement indicators. There are two core competencies, 2 basic competencies
and 2 learning objectives.
Figure
2. KI KD Page
Based on Figure 2 on the KI KD page of the
Logic of the Mind application, there are two core competencies, namely: 4.
Trying to process and present in the concrete realm (using, parsing, handling,
modifying, and creating) and in the abstract realm (writing, reading,
calculating, drawing, and composing) in accordance with what is learned in
school and other sources that have the same viewpoint/theory. 5. Understand
knowledge (factual, conceptual, and procedural) based on their curiosity about
science, technology, art, and culture related to phenomena and visible events.
The two fundamental abilities are: 3.4
Thinking computationally for more complex computational problems and 4.4
Solving computational problems including networks, patterns, and algorithms. There
are 2 learning objectives that must be achieved, namely explaining that
computational thinking is a more complex computational problem than before and
understanding computational problems that contain patterns, networks, and
algorithms.
Material
On
the material page, learning materials that are arranged based on basic
competencies will be displayed. Material on the meaning of computational
thinking, basic concepts of computational thinking, application in everyday
life and the advantages of having computational thinking skills. In this
feature, it is explained in full and uses language that is easy for students to
understand. The following is a display of material features like Figure 3
below.
Figure 3. Material Page
Video
On the video page provide several videos related to the
material. With this video video, it will make it easier for students to
understand the material. By seeing moving and vocal visuals, students are more
interesting and understand them more easily. The content of the videos includes
the introduction to computational thinking, the definition of computational
thinking, the basic concepts of computational thinking, the application of
computational thinking to examples of questions to train computational thinking
improvement. Students will not be bored and interested in learning more. The
video page display is as shown in figure 4 below.
Figure 4. Video Page
Practice
questions
This practice question page contains questions that are
used to train students' computational thinking skills so that they are used to
solving problems critically, concisely and logically. These questions will test
how high the level of students' computational thinking skills is. It is hoped
that by continuing to train with various kinds of problems, students will be
able to solve by thinking computationally. Because solving by thinking
computing has many advantages, including problems can be solved faster, more
effectively and efficiently. The display of the practice page can be seen from
figure 5 below.
Figure 5. Practice Questions Page
Artificial
Intelligence
This
Artificial Intellegene page is a solution for students in solving the problems
they face. This is a mainstay feature for students in practicing solving
problems critically, logically and logically. By using AI features consisting
of ChatGPT, WriteSonic and Claude. With the latest technology, it can be used
as a medium for student learning. The following is the view of the Artificial
Intelligence page as shown in figure 6 below.
Figure 6. Artificial Intelligence Page
Evaluation
The Evaluation Page is the last page on the Logic Mind
Application that provides various questions as evaluation materials. This
evaluation material is to find out how students feel in using the Logic Mind
Application. The page view can be seen in figure 7 below.
Figure 7. Evaluation
Page
Implementation
At the implementation stage, there are two
steps that must be completed. The first step is called black box testing. The
lower and upper limits of data are the basis of the black box testing
methodology (Cholifah et
al., 2018). This experimental phase of "black
box" testing focuses on the functionality or functional requirements of
the software (Vikasari,
2018). This stage does not discuss the internal
aspects of the application, such as coding, program code or the programming
language used. Input, processing, output, and test results of buttons with
additional functions are the main focus in the testing process of this
application. Testing the results of the pretest and posttest completed by
students is the second stage. In conducting the test, the t-test is used to
find out if there is a difference between the pretest and posttest that is
carried out.
Evaluation
After
the implementation stage, the evaluation stage is the last. All the results of
the previous stages will be combined in this stage. Black box testing has
yielded results that show that the app's features can operate flawlessly when
used, free from errors or obstacles. The mobile routing program may load on
Android 7 or Nougat phones up to Android 11, according to the findings of the
testing stage. The high specifications of today's smartphones are no longer a
barrier. In addition, the app's small size also contributes to its ability to
function properly and without difficulty.
The
application is tested to students at the evaluation stage, which is the last
stage. The purpose of this trial is to ensure how suitable the application is
for the educational process. The trial phase of this application involved 32
students of grade VIII Multimedia MTsN 2 Mojokerto. Students are immediately
subjected to a trial during the learning process. Based on the findings of the
research, it is evident that this application provides significant assistance
to students. It is easier for students to understand and solve challenges
successfully. The results of the pretest and posttest provide evidence of this.
As a result, the program functions well and is suitable for use during the
learning process.
RESULTS AND DISCUSSION
The research was conducted
at MTsN 2 Mojokerto for grade VIII students specializing in multimedia. This
research uses computational thinking material and is carried out on informatics
subjects. The five-stage ADDIE approach is the process used to build
applications. The phases consisting of several stages are analysis, design,
development, implementation, and assessment. Students undergo a pretest and
posttest as part of their research stage.
Pretest questions are used
to collect observations at the beginning of the learning process. The program
that students will use to navigate between mobile devices as they study is
being tested in the second stage. Students take a posttest at the end to gauge
their level of competence. The normality test is used to analyze the data
because each stage has its own achievements. To ascertain whether the numbers
are regularly distributed or not, a normality test is used. The next stage is
to conduct a t-test, namely the Paired Sample T-Test which is carried out to
find out the extent of student competency development. The following are the
results of student competencies:
Normality
Test
The normality test is a
test that is carried out with the aim of finding out whether the results of the
available value data are normally distributed or not (Sukestiyarno & Agoestanto, 2017).
This testing process was carried out using IBM SPSS Statistic 26 which obtained
the following results.
Table 1. Normality Test Results
|
Tests
of Normality |
||||||
|
Kolmogorov-Smirnova |
Shapiro-Wilk |
|||||
|
|
Statistic |
df |
Sig. |
Statistic |
df |
Sig. |
|
PRETEST |
.135 |
32 |
.145 |
.953 |
32 |
.177 |
|
POSTEST |
.175 |
32 |
0.14 |
.926 |
32 |
.030 |
|
a. Lilliefors
Significance Correction |
||||||
The
results of the normality test of the data obtained can be shown in table 1. The
data obtained were tested and considered to be normally distributed if the
significance value was greater than the value of a (0.05), in accordance with
the criteria of the Lilliefors Shapiro-Wilk test. A significance level of 0.05
indicates that the tested data is not normally distributed. The pretest results
obtained were 0.117 and the posttest value obtained was 0.030 in accordance
with the results of the research that had been carried out. Based on these
findings, the value data is distributed regularly because the sig > a
(0.05).
Uji
T-Test
When
comparing the average of a group observed at two separate times, or when
comparing the average of two groups of individuals or corresponding cases, a
paired sample t-test may be helpful. The t-test is known as a repeated-size
t-test if the same group is re-examined using the appropriate size (Ross et al., 2017).
After conducting a normality test passed, then the T-Sample test.
Table 2. Paired Sample Statistical Results
|
Paired Samples Statistics |
|||||
|
|
|
Mean |
N |
Std. Deviation |
Std. Error Mean |
|
Pair 1 |
PRETEST |
71.69 |
32 |
12.630 |
2.233 |
|
|
POSTTEST |
88.13 |
32 |
4.125 |
.729 |
Figure 2 shows that the average student gets a
score of 71.69 in the pretest, but 88.13 in the posttest after using the
application. The results showed an increase in posttest scores. This shows that
after utilizing the mind reasoning application, students' competence has
improved. Paired Sample T-Test is a parametric test that can be used in this
kind of research to test the average variation between two paired samples or
related to using two paired data sets (Agus, 2015).
Certain criteria or decision-making processes apply to this
exam, such as: The existence of influence and change can be shown by looking at
the significance value (2-tailed) < 0.05, which is the value of the
significant difference between the variables at the beginning and the end.
inserted after treatment. This can indicate that there is a significant change
in the treatment applied to each variable, if the significance value (2-tailed)
> 0.05, it indicates that there is no significant difference from the variable
at the beginning and at the end after the treatment. This may indicate that not
all variables are significantly affected by the given treatment.
The
paired t-test findings obtained by comparing the pretest and posttest results
are shown in Figure 9. The computed sig (2-tailed) value of 0.000 obtained the
result that there was a considerable influence and difference between the
variables at the beginning and the end. The treatment provided through the
Logic Mind program has a significant impact. Meanwhile, the difference between
the mean pretest and posttest yields a mean value of 16.437 in the first column
CONCLUSION
The results of the ongoing research have obtained results
with the conclusion that for use in the educational process, the results of the
application validity test show a percentage of 80% with a valid category.
Meanwhile, the results of the validity test of the pretest and posttest
questions of 73% were declared valid, meaning that it could be carried out.
Arikunto claimed that the pretest and posttest questions designed for the
Android platform, along with the table of eligibility criteria and the mobile
routing application, are suitable for use by students. The average pretest
score in the research conducted using the Logic Mind application was 71.69,
while the average posttest result was 88.13. These findings show that student
competence has increased. The results of the pretest and posttest that have
been completed are proof of this. Because the average score of the posttest is
more valuable compared to the results of the pretest.a hypertext link and the
bookmark� section will be removed. If
the paper needs to refer to an email address or URL in an article, the full
address or URL should be typed in plain font.
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