Innovative Voice-Activated Robots for Computational Thinking
Education: Design and Development
JUDY C.R. TSENG
Department of Computer Science and Information Engineering
Chung Hua University
Hsinchu
TAIWAN
WEI LI
Ph.D. Program in Engineering Science
Chung Hua University
Hsinchu
TAIWAN
Abstract: - With the advent of the digital age, countries worldwide have begun to emphasize computational
thinking education, hoping to cultivate learners' abilities to meet the requirements of future talents. Currently,
computational thinking education in young children is mainly based on visual programming on computers or
robots. However, using computers requires a prior understanding of abstract thinking, which is difficult for
young children to master. To meet the need for cultivating computational thinking in younger children, this
study combines a tangible robot with a verbal user interface to develop a set of voice-activated programming
robots suitable for younger children. The learner gives verbal commands to make the robot perform the
specified actions and complete the problem-solving task. This approach allows children to ignore the syntax of
the programming language and thus focus more on problem-solving.
Key-Words: - Computational Thinking, Educational Robot, Verbal Programming Language
Received: June 19, 2022. Revised: March 20, 2023. Accepted: April 16, 2023. Published: May 26, 2023.
1 Introduction
Information technology has changed how people
work, live, learn, and play in this digital era.
Countries worldwide have begun emphasizing
computational thinking education to cultivate talent
suited to this digital era, hoping to foster learners'
problem-solving skills and creative thinking, [1].
Computational thinking uses computer logic for
problem-solving and system design, [2]. In
response to the rapidly changing digital era, many
scholars believe that it’s better to cultivate
computational thinking as earlier as possible, [3],
[4], [5]. Currently, the cultivation of computational
thinking in young children is mainly based on
visual programming languages such as Scratch.
Visual programming languages are more
manageable for young children than text-based
programming languages such as C and Python, [6],
[7]. For example, Scratch allows students to drag
and drop blocks without having to write a program,
overcoming the problem that beginners tend to get
lost in programming code or syntax, thus allowing
students to focus more on problem-solving and
facilitating the development of computational
thinking, [8], [9].
However, visual programming involves
computer operation, and learners must have a
certain level of abstract thinking, which is difficult
for young children to comprehend, [10]. Since
children aged 7 to 11 are in the concrete operational
stage, they tend to solve problems based on
concrete physical experiences, [11]. Using robots
as learning vehicles for computational thinking can
enable children to observe the results of
programming through the robot's actions, thereby
increasing their own concrete experiences and
making it easier to understand the concepts, [12].
For example, scholars have used tangible graphical
programming robots to teach computational
thinking to children aged 5-9 years old and found
that the children's computational thinking skills
improved significantly, [13]. Many studies have
applied robots to computational thinking learning,
[14], [15], [16] and have achieved promising
results. However, most of these studies only use
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robots to show the results of programming. The
programming work still needs to be done on a
computer, which is not advantageous for young
children whose abstract thinking is still developing.
On the other hand, as visual programming mainly
uses block-dragging to design programs, students
may use guesswork, intuition, or trial-and-error
methods to solve problems, disregarding
systematic, holistic operational thinking to solve
problems, [17].
Before children start speaking, their language
system in the brain processes phonology,
semantics, and pragmatics to fulfill the goal of
communicating, [18], enabling them to understand
what they are expressing and conveying the
concepts they possess. Thus, verbal programming
languages should be more suitable for cultivating
young children's computational thinking than visual
programming languages. Research has found that
students use language as a tool to help them solve
problems and think, [19]. However, there has yet to
be a programming robot that integrates a physical
robot and a verbal user interface to meet the needs
of younger children in fostering computational
thinking.
Given this, this study proposed a verbal
programming language for young children, called
the V language, and developed an educational robot
for computational thinking based on the V
language. The educational robot enables children to
give voice commands by the V language grammar
to make the robot perform specific actions to
complete problem-solving tasks. If the commands
are incorrect, appropriate feedback is provided to
help the children learn the correct grammar. With
the development of this educational robot, an
innovative computational thinking learning
approach suitable for young children is provided,
which is expected to effectively improve the
effectiveness of computational thinking education
for young children.
2 Literature Review
In this section, a review of related literature related
to this research is conducted. The literature is
divided into three sub-sections, which successively
discuss the related literature on computational
thinking, education robots, and programming
languages.
2.1 Computational Thinking
Computational thinking skills enable students to
analyze problems from different perspectives and
solve them effectively, [20], and thus incorporating
computational thinking into information education
has become a global trend, [21]. Many countries
have cultivated children in computational thinking,
critical thinking, and problem-solving skills from a
young age, [22]. Many scholars believe
computational thinking and problem-solving skills
development should begin as early as possible, [3],
[4].
Many scholars have proposed different
definitions of computational thinking, such as, [2],
who believes that computational thinking is a way
of thinking about problem-solving and system
design using computer logic. Google refers to it as
a problem-solving process, such as sorting and
analyzing data logically and producing solutions
through sequential steps, [23]. In summary,
computational thinking can be defined as the ability
to use computational methods and tools to solve
problems.
Since programming is a great way to create
computational works and demonstrate
computational thinking abilities, [24], Several
studies have found that learning programming can
improve students' computational thinking, [13],
[25]. As a result, most schools have students learn
computer programming to develop their
computational thinking abilities, [26]. However,
learners must have a certain level of abstract
thinking to operate computers, which is
unfavorable for young students whose abstract
thinking has yet to develop fully, [10].
2.2 Educational Robots
With the development of advanced technologies,
robots that integrate various technologies have been
developed and applied to various fields. The
applications of robots in education have also
become more and more versatile, [27], [28], [29].
By incorporating robots into teaching with the
creativity of teachers, students can learn in a
creative environment, thereby fostering their
technological integration ability, problem-solving
ability, and creativity, [30].
Research has indicated that robots can greatly
assist education at all education levels, [31].
Besides increasing students' motivation, [32], they
can also increase students' concrete experiences,
making it easier for them to understand the learning
material, [8]. Concrete experiences have varying
degrees of impact on students of different ages.
Piaget's theory of child cognitive development
states that children aged 7 to 11 are in the concrete
operations period and need to solve problems based
on concrete experiences, [11]. Therefore, robots
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can be a good learning vehicle for students at this
stage.
Previous research has also found that arranging
robot movements can cultivate students'
computational thinking skills and stimulate hand-
eye coordination, [3]. As a result, many scholars
have tried to develop learning strategies for
handling complex tasks through educational robots
to promote the development of students’
computational thinking, [11], [30]. Therefore,
robots are also considered to be a good platform for
learning computational thinking, [33]. However,
most of these studies only use robots to show the
results of programming, and the programming work
still needs to be done on a computer, which still
hinders young students' learning.
2.3 Programming Languages
Programming is a fundamental skill in information
technology and a way of solving problems through
programming languages, [34]. Programming
languages nowadays can be divided into three
types: textual, visual, and verbal.
Textual programming languages, including C,
Java, Python, etc., are constructed using strings that
conform to a specific syntax. For beginners in
programming, learning the syntax of text-based
programming languages is a big challenge and can
also be one of the reasons for feeling discouraged,
[35]. For beginners or younger learners, the
learning threshold for text-based programming
languages is higher and harder to start with, [36].
Visual programming languages were created to
reduce the barriers to programming entry, eliminate
syntax's complexity, and allow learners to
concentrate on visualizing solutions to problems,
[37]. Visual programming languages primarily use
blocks of images to express solutions to problems
and have simple operations, making them more
suitable for beginners or younger learners
compared to textual programming languages, [38].
Visual programming also enables learners to
concentrate on systematic, logical thinking for
problem-solving rather than being frustrated by a
lack of familiarity with programming syntax, [39].
However, the simplicity of visual programming
language's operations may lead learners to solve
problems through guessing, intuition, or trial-and-
error rather than systemic, computational thinking,
[17].
Verbal programming languages are written
through oral narrative. Before children start
speaking, their language system in the brain
processes phonology, semantics, and pragmatics to
fulfill the goal of communicating, [18], enabling
them to understand what they are expressing and
conveying the concepts they possess. Thus, verbal
programming languages should be more suitable
for cultivating young children's computational
thinking than visual programming languages. Its
language structure is also too complex for young
children to learn.
To help young children develop computational
thinking, this study proposes a verbal programming
language and creates an educational robot for
computational thinking accordingly. The robot
enables young children to use simple verbal
programming language to give commands and
complete specified tasks as instructed. By
organizing the logical structure of speech
commands and obtaining the concrete experience
by the robot feedback, the solution to the problem
can be constantly improved, thus enhancing their
computational thinking ability.
3 The Verbal Programming Language
for The Computational Thinking
Educational Robot
To develop a voice-activated educational robot
suitable for young children to cultivate
computational thinking, this research uses the
ASUS Zenbo robot as a platform and, based on the
actions that the Zenbo robot can perform, a verbal
programming language is designed called the V
language. Children can use spoken commands to
give instructions, which follow the syntax of the V
language, to the voice-activated computational
thinking educational robot developed in this
research. The Zenbo will perform the specified
actions to complete the problem-solving task. This
research uses BNF grammar to define the syntax of
the V language. The following sections will explain
the built-in actions of Zenbo and the designed V
language in order.
3.1 Built-in Features of Zenbo
Zenbo's built-in features are divided into two parts,
speech, and action. Speech-related features include
listening and speaking, while action-related
features include movement, rotation, and head
motion. Details are as follows:
1. Listening: When Zenbo is in listening
mode, the user can give Zenbo a voice command,
and Zenbo will analyze the voice command spoken
by the user and take subsequent actions based on
the command.
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2. Speaking: The speaking function allows
Zenbo to speak the text users specify, providing
feedback or informing the user of the content of an
error message.
3. Movement: The movement function allows
Zenbo to move forward or backward in a
longitudinal motion.
4. Rotation: The rotation function allows
Zenbo to rotate to the left or right.
5. Head Motion: The head motion function
allows Zenbo to perform head motions, such as
tilting, turning left or right, or stopping head sway.
As the educational robot for teaching
computational thinking developed in this study uses
Zenbo as a platform, the verbal programming
language designed only focuses on Zenbo's built-in
actions. Corresponding statements have been
designed to enable students to instruct Zenbo to
perform various actions and complete assigned
problem-solving tasks.
3.2 V Language
This research adopts BNF (Backus Normal Form)
to define the syntax of the V language. BNF is
widely used to represent syntax in programming
languages, instruction sets, and communication
protocols, [40]. Most programming languages
adopt BNF grammar to define their syntax. The
notations of the BNF grammar used in this study
are listed in Table 1.
Table 1. Notations of the BNF grammar
Notation
Meaning
::=
Defined as
|
choice
< >
Non-terminal
For example, "<seq::=<move>|<dance>|<turn>"
means that <seq> is defined as either <move>,
<dance>, or <turn>, not as <move><dance>,
<dance> <turn>, or a combination of
<move><dance> <turn>. The form of <move>,
<dance>, and <turn> are non-terminal symbols and
need to be defined separately.
This study designs the syntax of the V language
based on the actions that the Zenbo robot can
execute. The main purpose is to allow students to
use verbal commands to control the educational
robot developed for computational thinking using
syntax that conforms to the V language so that
Zenbo can perform the corresponding actions to
complete the problem-solving tasks assigned by the
teacher. To reduce the cognitive burden of young
children and avoid the frustration and decreased
learning motivation that can result from frequent
syntax errors, this study considered the problem-
solving requirements designed by code.org for
young children when designing the syntax of the V
language. Three main instructions are provided in
V language: sequential, for loop, and while loop. In
addition to setting parameters, each statement can
be nested with other statements, allowing the user
to design complete program codes using the V
language. The BNF Grammar of the V language is
shown in Table 2.
Table 2. The BNF Grammar of the V language
P1
P2
P3
P4
P5
P6
P7
P8
Sequential structure refers to the program
structure in which statements are sequentially
executed in the order they are written in the code.
The program statements were simplified according
to the needs of young children to accomplish their
tasks, and the complexity of the syntax was reduced
by removing parameters that could be adjusted for
action range and replacing them with fixed
parameters. The sequential instructions in V
language include "forward,” "turn left,” and "turn
right.” Each forward movement is 0.6 meters, and
the left and right turn angles are 90 degrees. If the
"forward" command is issued, Zenbo will walk
forward 0.6 meters; when the "turn-left" command
is issued, Zenbo will turn left 90 degrees; and when
the "turn-right" command is issued, Zenbo will turn
right 90 degrees. However, if the command
"forward 3" is issued, it will result in a syntax error,
and an error message will appear.
Loop structure refers to the program structure in
which a block of statements can be repeatedly
executed. Usually, a loop condition is defined in
the loop structure, and the loop structure will only
continue to execute as long as the loop condition
evaluates to true. This study's loop structure of V
language includes “for-loop” and “while loop.”
The syntax format of the for-loop instruction is:
repeat (number) times execute (statements) end.
The number after "repeat" is limited to 1 to 5, and
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the statements after "execute" can be any
combination of instructions. For example, if the
instruction "repeat 2 times execute forward, turn
left end" is issued, Zenbo will repeat the action of
forward 0.6 meters and then turn left 90 degrees 2
times. But if the command "repeat end" is given, it
will result in a syntax error, and an error message
will appear.
The syntax format of the while loop instruction
is repeated (statements) until stop, where the
statements after "repeat" can be any combination of
instructions. For example, if the instruction "repeat
forward until stop" is issued, Zenbo will keep
moving forward 0.6 meters each time until it
encounters an obstacle and stops. However, if the
instruction "repeat until stop" is issued, it will result
in a syntax error, and an error message will appear.
4 Development of the Voice-activated
Educational Robot
To apply educational robots to young students'
learning of computational thinking, this study
develops a voice-activated computational thinking
educational robot based on V language. We use
JAVA, HTML, CSS, JavaScript, jQuery, and PHP
as the programming language for system
development, Bootstrap as the frontend framework,
and Android Studio as the development
environment. Zenbo SDK toolkit and
phpMyAdmin database management tool are also
used to develop and deploy the educational robot
system. The system architecture of the educational
robot developed in this study is shown in Fig. 1.
Fig. 1: System Architecture
The system includes 4 data tables: vocabulary
table, syntax table, instruction code table, and error
code table, as well as six functional modules:
speech recognition module, lexical analysis
module, syntax analysis module, execution code
generation module, instruction execution module,
and error handling module.
The vocabulary table stores the legal vocabulary
in the syntax and its corresponding vocabulary
code. The syntax table keeps the BNF-Grammar
syntax of the V language. The instruction code
table keeps the instruction codes for the robot to
perform various actions. The error code table stores
the error codes and corresponding error messages
for syntax errors.
The speech recognition module converts verbal
instructions into textual instructions when given to
the Zenbo robot. The speech recognition module
utilizes the Google Speech Recognizer API to
transform voice commands into text by calling
Google's speech recognition engine. The text
strings are then delivered to the lexical analysis
module for processing. The lexical analysis module
will tokenize the text string and check whether the
token generated after tokenization is legitimate.
After lexical analysis, if the token is legal, it is
coded according to the lexical list and passed to the
syntax analysis module for further syntax analysis.
If it is illegal, it is sent back and the user is
informed of the lexical error by the Zenbo robot.
The syntax analysis module analyzes the lexical
code sequence obtained from the lexical analysis
module according to the syntax table. If the
analysis result matches the syntax, the execution
code or error code will be generated later using the
execution code generation module. The execution
code generation module generates execution codes
or error codes based on the syntax analysis results.
If the analysis results in a correct syntax, the word
code is converted into an execution code sequence
and then sent to the instruction execution module
for instruction execution. If the analysis results in a
syntax error, a negative error code is generated
according to the error so that the error handling
module can report the error message. Based on the
execution code generated by the execution code
generation module, the instruction execution
module calls the corresponding API in the Zenbo
SDK to let Zenbo perform the action that matches
the user's instruction. Suppose there is an error
occurred in the above modules. In that case, the
error handling module will convert the error code
into corresponding error messages and calls the
speak API in the Zenbo SDK to let the user know
where the instruction is wrong and give correct
examples.
The overall process of the system is as follows:
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Step 1: When a student issues a verbal
instruction to Zenbo, the speech recognition
module will convert the received verbal instruction
into a textual instruction and send it to the lexical
analysis module.
Step 2: The lexical analysis module separates the
textual instruction into word segments, converts
each into lexical code, and then sends the lexical
code sequence to the syntax analysis module.
Suppose any error is encountered during lexical
analysis, such as invalid vocabulary used in the
instruction. In that case, the corresponding error
codes will be sent to the error handling module to
prompt suitable error messages to the user.
Step 3: The syntax analysis module analyses the
lexical code sequence according to the syntax table
to see if it complies with the grammar of V
language. If the grammar is complied with, the
lexical code sequence will be passed to the
execution code generation module. If not, the
corresponding error codes will be sent to the error
handling module to prompt suitable error messages
to the user.
Step 4: The execution code generation module
generates an execution code according to the
instruction code table and sends it to the instruction
execution module.
Step 5: The instruction execution module calls
the corresponding API in the Zenbo SDK based on
the executable code to make Zenbo perform actions
that comply with the user's instructions.
Step 6: If an error occurs in the above steps, the
error handling module will convert the error code
received into the error message according to the
error code table and calls the speak API in the
Zenbo SDK to let Zenbo speak out the error
message, allowing the user to know where the error
lies in the instruction.
The scenario in which the educational robot
developed in this research is applied in the learning
activity of computational thinking education is
shown in Fig. 2.
5 Conclusions and Future Works
This study developed a voice-activated
computational thinking educational robot for young
children, using the ASUS Zenbo robot as the
platform. Based on the Zenbo robot’s actions, a
verbal programming language called V language
was defined by BNF grammar. While the learner
speaks an instruction in V language to the
developed educational robot, the robot will perform
the designated actions to execute the instruction.
The problem-solving tasks for cultivating
computational thinking can be completed through a
sequence of verbal instructions issued by the
learner.
This study attempts to develop verbal
programming robots for fostering computational
thinking in younger children. Compared to
graphical programming environments, Verbal
programming robots incorporate the features of
social robots, and children can communicate and
interact with the robots using conversations. As a
result, this learning approach is more innovative
than other programming robots in cultivating
children's computational thinking, freeing them
from programming syntax and allowing them to
focus more on problem-solving. The developed
educational robot is expected to improve the
effectiveness of computational thinking cultivation.
Nevertheless, whether verbal robots can facilitate
the development of computational thinking in
children needs to be further investigated. Therefore,
this study will design and integrate a series of field
experiments to investigate the effects of the
developed verbal robot on the computational
thinking of younger children.
Fig. 2: The scenarios of computational thinking
learning activity incorporating the developed
educational robot
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
All authors contributed to the study’s conception
and design. [Judy C.R. Tseng] and [Wei Li]
performed material preparation and data collection.
The first draft of the manuscript was written by
[Judy C.R. Tseng] and [Wei Li], and all the authors
have revised the manuscript. All authors read and
approved the final manuscript.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
This study was partly supported by the National
Science and Technology Council of Taiwan under
grant numbers MOST 109-2511-H-216-001-MY3
and the Ministry of Education of Humanities and
Social Science Project of the People's Republic of
China [21YJA880027]. The authors would like to
thank Xin Ci Wen for her assistance in developing
the system.
Conflict of Interest
The authors declare no conflicts of interest.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.e
n_US
WSEAS TRANSACTIONS on ADVANCES in ENGINEERING EDUCATION
DOI: 10.37394/232010.2023.20.8
Judy C. R. Tseng, Wei Li
E-ISSN: 2224-3410
59
Volume 20, 2023