BICSME, UMS, 2015. Preliminary study on educational robot kit in promoting interest toward science, mathematics, technology and engineering (STEM)

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Preliminary Study on EducationalRobot Kit in Promoting Interest Toward
Science, Mathematics, Technology and Engineering (STEM)
Anna Felicia, Sabariah Sharif, Muralindran Mariappan, WK Wong
Faculty of Education and Social Sciences, Universiti Malaysia Sabah, Kota Kinabalu, Sabah,
Malaysia
Abstract: Robotics is an excellent platform in promotion of STEM (Science, Technology,
Engineering and Mathematics) due to its multidisciplinary combination of the various fields.
This paper presents preliminary results in promotion of robotic activity as an outreach
platform to promote STEM using a prototype Robotic Kit system that is cost effective and
involves only basic elements. Results showed that 90% of the participants would like to
participate more in after school such robotic classes indicating an increased interest in such
Robotic classes. This preliminary research showed that such robotic activity can be further
developed in the specified location as a platform to promote STEM.
Keywords: Educational Robotics, Robotic Curriculum, Open Source Graphical Visual
Programming
1. Introduction
Robotics is often adopted as a platform to introduce STEM (Science, Technology,
Engineering and Mathematics). Robotics platform enables the multidisciplinary combination
of all STEM elements can be viewed as a high immersive platform for learning and develop
interest in STEM. Hence, this study serves as a preliminary study to investigate the effect of
robotic activity in learning and the interest level towards such activities. The robotic platform
used in this research is an experimental platform developed using Arduino microcontroller
and S4A (Variant of the popular Scratch software) software as GUI (Graphic user interface).
Scratch like programs are highly popular among schools due to its graphical programming
styles and open source development.
2. Literature review
The 21st century dawned as the beginning of the Digital Age – a time of unprecedented
growth in technology and its subsequent information explosion. The term “computational
thinking” (CT) has been at the center of recent efforts to describe and promote new ways of
thinking in an increasingly digital age. Computational Thinking provides foundational
knowledge in problem solving and design. Computational thinking is being considered as a
critical skill for students in the 21st century. Computational thinking (CT) was first described
by Papert (1993), and then pioneered by Jeannette Wing. Seymour Papert is seen by many as
the pioneer of computing in schools. Jeannette Wing’s (2006) influential article on

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computational thinking argued for adding this new competency to every child’s analytical
ability as a vital ingredient of science, technology, engineering, and mathematics (STEM)
learning. Educational robotics and its programming known as a transformational tool for
computational thinking, coding or programming, and engineering, all increasingly being
viewed as critical ingredients of STEM (science, technology, engineering and math) learning
in education (Eguchi, A. 2014). Computational tools have been shown to enable deeper
learning of STEM content areas for students (National Research Council, 2011; Sengupta,
Kinnebrew, Basu, Biswas, & Clark, 2013).
Papert’s (1980) constructionism is rooted in Piaget’s (1954) constructivism – which
conveys the idea that the child actively builds knowledge through experience – and the related
“learn-by-doing” approach to education. While Piaget’s (1954) theory was developed to
explain how knowledge is constructed in an individual’s mind, Papert (1980) expands on it to
focus on the ways that internal constructions are supported by constructions in the world,
including through the use of computers and robotics. A constructionist teaching approach
provides children the freedom to explore their own interests through technologies (Bers,
2008) while investigating domain-specific content learning and also exercising meta-
cognitive, problem-solving, and reasoning skills.
Computational thinking is being considered as a critical skill for students in the 21st
century (2011). Computational thinking facilitates new ways of seeing existing problems,
emphasizes creating knowledge rather than using information, presents possibilities for
creatively solving problems ,and facilitates innovation (Dede, et al. 2013). It involves many
skills, but programming abilities seem to be a core aspect since they foster the development of
a new way of thinking that is the key to the solution of problems that require a combination of
human power and computing power capacity (Ambrosio, et al, 2014). Figure 2.1 shows the
Computational thinking explained by Cury, J. et al. (2010). Embedding CT in STEM
coursework can address the issues of practicality of implementation, especially with teachers’
comfort with the material. (National Research Council, 2011; Sengupta, Kinnebrew, Basu,
Biswas, & Clark, 2013).
On the other hand, Scrath is a popular open source for coding. Scratch is a computer
programming language for children, with a graphical drag-and-drop user interface (Harvey, B.
& Monig, J. 2010). Scratch is a free application, developed by MIT Media Lab, which allows
users to create and share their own interactive stories, animations and games. It is easier to use
rather than traditional programming languages as it consists of graphical blocks which snap
together. Figure 2.2 is the interface of Scratch (Lero, 2012). Table 2.2 is the implementation
of Scratch by Wilson, A., Hainey, T. & Connolly, T.M. (2013).

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S4A (Scratch for Arduino) is a drag and drop programming environment based on the
MIT creation “Scratch”. It has been modified to connect to an Arduino plugged in via USB,
offering a variety of additional code blocks to implement and create scripts to control the
Arduino and attached components. Arduino is a micro-controller, which is a small computer
that can be use to send and receive messages to and from other electrical components. It used
is similar to a motherboard, inside the computer - and can be connected to various
components to it and build up electrical circuits. Figure 2.3 below is the interface of S4A.
Figure 2.4 is the Arduino Uno micro-controller board.
Teaching robotics to young people frequently implies a constructivist approach which
emphasizes “learning by doing” as the main teaching strategy (Bilotta, D., Gabriele, D.,
Servidio, R. & Tavernise, A., 2009). It involves electric motors, sensors, pieces such as gears,
axles, and beams and tool for programming and control of them. So, by using this learning
method, the student is able to learn how to construct, program and control a robot (Thomaz,
S., Aglae, A., Fernandes, C., Pitta, R., Azevedo, S., Burlamaqui, A., Silva, A. & Goncalves,
L.M.G., 2009). The robotics tools made it possible for the students to practice and learn many
necessary skills, like collaboration, cognitive skills, self-confidence, perception and spatial
understanding, active reasoning and critical thinking, and also enhancing students’ interest
and motivation to address often complex subjects (Eija, K-L., Kaisa, P-B., Erkki, S. & Marjo,
V., 2006). The skills may be related to multiplication and division operations for example in
mathematics subjects.
According to Alimisis (2013), robots are becoming an integral component of our society
and have great potential in being utilized as an educational technology. Robotics has attracted
the interest of teachers and researches as a valuable tool to develop cognitive and social skills
for students from pre-school to high school and to support learning in science, mathematics,
technology, informatics and other school subjects or interdisciplinary learning activities. A
four wheel drive robotic platform was developed Alimisis, D. (2012) and E-puck educational
robot was constructed in Mondada, F. et al. (2009).

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2. Hardware Development
The robot was constructed on a minimalist concept to reduce production cost and experiments
to evaluate the interest levels towards the robotic programming curricular. The robot kit is non
– assemble type and on the shelf which means that no assembling is required. Table 1 shows
the specification of the robotic Kit.
Table 1 : Specification of Robotic system
Size 20 cm (width) x 20 cm (length) x 10 cm (height)
Weight 2.6 Kg
On Board
Processor
Arduino Uno Microcontroller
Sensor 3 line sensor (Infra Red)
3 Obstacle sensor (Digital type, distance adjustable type)
Approximate
cost
USD 120
Communication
link
Bluetooth
Programming
Language
S4A (Scratch for Arduino)
The robot Kit consist of an Arduino microcontroller that communicates with the laptop via a
USB link using HC 06 bluetooth module. The microcontroller communicates with other
motor (actuator) and sensor via the analogue ports. Figure 2 shows the block diagram shows
communication module. The robot kit is shown in Figure 3 (a) and the scratch GUI is shown
in Figure 3 (b). As shown in figure 3 b), the programming is entirely graphical.

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Figure 2 :Block diagram of communication and Interfacing
Arduino microcontroller
Laptop
processor
Bluetooth link
Motor controller Obstacle sensor IR line sensor

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(a) (b)
Figure 3 : a) Shows the hardware of the the Arduino BasedRobot Kit. b) Printscreen of
the S4A program executing a Program
The S4A program does not have function program unlike their text based counterpart.
Hence, the ‘broadcasting’ concept was used to replace the function concept. Five states of
robot movement were introduced that is ‘Move Straight’, ‘Turn Left’, ‘Turn Right’, ‘Veer
Left’ and ‘Veer Right’. The five states are based on the differential speed of the left and right
motor. The speed which ranges (0-255) in which the motor moves. It was tested that any
number specified below 50 was unable to make the motor move. The motor is driven by the 2
A motor driver shield for Arduino. The value for the specified movements were fixed in
which the participants only need to ‘Broadcast’ the states such as ‘Move straight’ Or ‘Veer
Right’ to execute the movements. The values for the movements is shown in Table 3.2.
‘Veer’ refers to the slight steering to the left or right as compared to ‘turn’. ‘Veer’-ing is
normally for performing line tracking which requires a slight turning to move back into the
track. However, in research activity, the veer function is not used and only turning required.
The time of ‘turning’ and ‘straight’ is depending on the delay time applied after specifying the
value on the left and right motor. The pin connected to both the motor is analogue pin 5 and
pin 6. The value given to veer and turn are shown in table 2 in which the participants are
allowed to changed but it was found that eventually all participants used the value as
proposed.

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Table 2: The States and Speed of Motor
States
Left motor
speed
Right Motor
Speed
Move straight 120 120
Veer Right 80 50
Veer Left 50 80
Turn Right 120 80
Turn Left 80 120
3. Study Design
The study conducted is to study the effects of the low cost robotic kit developed in promoting
the interest towards STEM. Table 3 shows the details and duration of the activities proposed.
The introduction include a small demonstration of line following robot and some videos to
show the full potential and to enable the participants to have an overview and future activities.
The subsequent overall activity for every group is approximately 3 hours but students.
Table 3 : Details and duration of activity
Phase Details Description Duration
1 Introduction to
robot Kit
Demonstration of robot. Include line following
with the robot kit and video explanation
30 minutes
2 Learning
activity
Robotic learning activity given template
coding.
Approximately
3 hours
3 Discussion Discussion on what the students wish to do
with the technology. The participants were also
shown the application of sensors in coding to
encourage them to involve in future activities
5 minutes
The participants aged between 10-11 years old, 61% female students and the rest are male
students. Thirty participants take parts that are divided into 6 small groups. Phase 1 took 30
minutes while phase 2 took 3 hours to complete. Due to the preliminary exposure, the students
are given a set of codes to study and modify before start coding. Four scenarios/case study
are prepared for the students to program the robot.

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(Activity a) Move straight
(Activity b) Move straight and turn left
(Activity c) Move straight and turn right until reaching a destination
(Activity d) Move straight and U-turn to point of origin
In activity a, the robot will be program by the participants to move straight indicated by
colored cones. Activity b and c are similar in which robot must be program to navigate in a ‘L’
path in which the starting and ending was indicated by the cones. The final activity requires
the participant to navigate the robot straight and perform a U-turn. In all the activities, a
sample code is given to the participants to modify as this was their first exposure to such
activity.
In order to assess learning outcomes after each activity, teachers evaluated the program
made by each groups. In each lesson, students were scored on multiple concepts using the
Likert scale below as attached in appendix. Figure 4 shows the learning environment showing
students participation and involvement. Only 3 students were allowed to participate in a single
group but participant were often seen sharing ideas intergroup. Figure 4 shows the activity d
in which participant are required to perform a U- turn as indicated by the colored cone.
Figure 4: Learning Environment During robotic learning activity
It was observed that most discussions are about the delay time setting. It was observed that at
one instances, a participant noted that the delay time to and from back to the cones are the
same whereas some continue trying indicating varying higher order thing capacity of
participants. This preliminary activity shows that interaction can happen in order to solve a
problem by trial and testing which is the core principle of constructivism leaning

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4. Result
Pre-interviews analysis revealed that robotics programme introduced as the first robotics
programme they have ever attended. Most of them never participated in such activities before,
and they participated in the programme because of curiosity. Post-interview analysis revealed
that they are very excited to participate in the edu-robot programme. They stated that they
have learned much about technology during the programme and also indicated what they can
do with the technology that they learn. Some participants stated that they wish to use the
technology to create a robot that washes dishes while more observant students realized that
the activities would directly enable them to create a robotic vacuum cleaner. This shows that
participant realized that they can actually innovate based on the technology that they learn.
They enjoyed the most in programming the edu-robot to move around and can compete
with other groups. All of them would like to further continue their participation in robotics
programme. The 5-likert scale post-questionnaires analysis shown that 90% (total-up of agree
and strongly agree frequencies) of the participants would like to participate more in after
school STEM projects and classes. And 90% (total-up of agree and strongly agree
frequencies) of them also have changed their mind about how interesting learning STEM is.
Another 10% which responded on the neutral scale (answered don’t know) were mostly found
not able to catch up in the coding activity. This could be due to the rural demography in
which low exposure to computers causing them to be left out and to familiarize to the learning
environment. Hence, for in the future, instructors need to note these student and possibly
reduce number of participants to 2 person per group. The descriptive statistics is shown in
Appendix B and the Post Activities Interview is shown in Appendix A. The variable 1-4
shows the question number as shown in Appendix A.
It was also observed that the activities proposed was suitable for preliminary
exposure to rural children with minimal exposure to computers. The coding only required
sequential Coding and no decision loops such as ‘if-else’ and ‘while’ decision loops were
required. This research shows that as a preliminary introduction to robotics to cultivate STEM
interest, such navigation based robot activity could be a good starting point to progress into to
learn about robots and STEM in general even though it was noted the participant are from
rural demography.
5. Future Works
This involves only the preliminary study in introducing the children (10-11 years old) in a
rural demography with low exposure to robots. The robot kit development involves only the
basic set for cost reduction and making the activities more available. Further work in
development will include refinement of both activities and the robotic kit itself. The robotic
Kit will only focus only ‘Higher order thinking’ problems to promote computational thinking
that is solving a particular problem through computational means.

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For future development, the research will focus on using A-D-D-I-E instructional
for designing Instructional activity in promotion of STEM interest and computational thinking
skills.
References
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Science & Technology Education, 6(1) : 63-71.
Alimisis, D. 2012. Simple educational robot design. 3rd International Conference on Robotics
in Education, Prague.
Ambrosio, A. P., Almeida,L.D.S., Macedo, J. & Franco, A. 2014. Exploring core cognitive
skills of computational thinking, University of Sussex.
Beers, S.Z. 2011, 21st Century Skills: Preparing Students for THEIR Future,STEM.
Bers, M.U.2010. The TangibleK Robotics Program : Applied computational thinking for
young children. Early Childhood Research & Practice, 12 (2).
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learning tool”, in Z. Pan, A., Chcok, W. Muller and M. Chand (eds), Transactions on
Edutainment III, Lecture Notes in Computer Science 5940, pp.25-35.
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in 21st century learning. International Summit on ICT in Education.
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Conference on Advanced Learning Technologies (ICALT’06).
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Lero, (The Irish Software Engineering Research Centre). 2012. Scratch programming and
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APPENDIX A
Post-robotic survey
SKALA
1 2 3 4 5
Strongly
disagree
Disagree Do not know Agree Strongly agree
Questions Scale
1 2 3 4 5
1 This project made
me want to do more
after school STEM
projects if they are
available.
2 This project
changed my mind
about how
interesting learning
STEM is.
3 This project made
me want to take
more classes in
STEM if they are
available.
4 This project made
me consider career
in STEM path.

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Post student interview questions
1. What are some things you learned
about being in robotics?
2. What did you enjoy the most about
being in robotics?
3. What would you tell someone about
being in robotics that has never been in
it?
4. Is there anything else you want to
share about being in robotics?
Pre student interview questions
1. What do you think you will learn
from your participation in robotics?
2. What do you know about robot?
3. Why did you choose to participate in
robotics?
4. Is there anything else you would like
to tell me?

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APPENDIX B
DESCRIPTIVE STATISTIC FOR POST ACTIVITY ANALYSIS
Gender
Frequency Percent
Valid
Percent
Cumulative
Percent
Male 13 43.3 43.3 43.3
Female 17 56.7 56.7 100.0
Total 30 100.0 100.0
VARIABLE 1
Frequency Percent
Valid
Percent
Cumulative
Percent
Do not know 3 10.0 10.0 10.0
Agree 16 53.3 53.3 63.3
Strongly
agree
11 36.7 36.7 100.0
Total 30 100.0 100.0
VARIABLE 2
Frequency Percent
Valid
Percent
Cumulative
Percent
Do not know 3 10.0 10.0 10.0
Agree 15 50.0 50.0 60.0
Strongly
agree
12 40.0 40.0 100.0
Total 30 100.0 100.0

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VARIABLE 3
Frequency Percent
Valid
Percent
Cumulative
Percent
Do not know 3 10.0 10.0 10.0
Agree 14 46.7 46.7 56.7
Strongly
agree
13 43.3 43.3 100.0
Total 30 100.0 100.0
VARIABLE 4
Frequency Percent
Valid
Percent
Cumulativ
e Percent
Do not
know
3 10.0 10.0 10.0
Agree 14 46.7 46.7 56.7
Strongly
agree
13 43.3 43.3 100.0
Total 30 100.0 100.0