=Paper=
{{Paper
|id=Vol-2555/paper3
|storemode=property
|title=Examining the role of STEM in Twelfth-grade Robot Subject Instruction using the UTAUT
model
|pdfUrl=https://ceur-ws.org/Vol-2555/paper3.pdf
|volume=Vol-2555
|authors=Chi-Chieh Hsieh,Fu-Yuan Chiu
}}
==Examining the role of STEM in Twelfth-grade Robot Subject Instruction using the UTAUT
model==
https://ceur-ws.org/Vol-2555/paper3.pdf
Examining the role of STEM in Twelfth-grade Robot
Subject Instruction using the UTAUT model
Chi-Chieh Hsieh1, Fu-Yuan Chiu2*
National Tsing Hua University/Hsinchu, Taiwan R.O.C
magic2000566@gmail.com, chiu.fy@mx.nthu.edu.tw
Abstract. Since the rise of the waves toward artificial intelligence,
more and more countries robot education has changed from Robot-
Assisted Instruction (RAI) to Robot-Subject Instruction (RSI). This
study mainly compares the differences between the two teaching
methods of RSI using traditional single subject teaching and STEM
cross-disciplinary teaching. Through the data of Unified Theory of
Acceptance and Use of Technology (UTAUT) and Course Satisfaction,
this study finds out the advantages and disadvantages of STEM
integration into RSI. Therefore, schools that are ready to promote RSI
in the future can consider whether to use STEM-based RSI based on the
analysis of this study.
Keywords: Robot Subject Instruction, STEM education, Unified
Theory of Acceptance and Use of Technology
1 Introduction
In the new 12-years basic education curricula in Taiwan, a new field of
technology has been added, and a course called "Robotics Project" has been
developed in this field. It means that Taiwan's robot education has changed from
Robot-Assisted Instruction (RAI) to Robot-Subject Instruction (RSI). The course
focuses on developing student competencies including programming, data access and
computing, electromechanical integration, computational thinking and design thinking.
This study conducted a two-year lead study before the start of the new RSI. The first
year of RSI used traditional teaching, meaning that the course taught only the
hardware and software operations of the robot, and then began using the STEM-based
RSI in the second year. The research tools section of this study used a unified theory
of acceptance and use of technology (UTAUT) and course satisfaction to compare the
differences between the two teaching methods. Schools. The results of the study can
be used as a reference for future RSI schools. The overarching research question for
this study is “To find out the advantages and disadvantages of STEM integration into
Copyright c 2019 for this paper by its authors. Use permitted under Creative Commons
License Attribution 4.0 International (CC BY 4.0).
RSI”. To focus the study, this overarching question is divided into the following three
sub-questions:
RQ1. What is the difference in UTAUT Questionnaires between traditional RSI and
STEM-based RSI?
RQ2. What is the difference between the pre-test and post-test of the UTAUT
questionnaire for implementing STEM-based RSI?
RQ3. What is the difference in Course Satisfaction between traditional RSI and
STEM-based RSI?
2 Literature Review
2.1 Robot Subject Instruction, RSI
With the advent of artificial intelligence, the application of robots in education has
become more diverse. Qi, Dong, Chen, Qi, & Okawa proposed such as "Robot
Subject Instruction (RSI)", "Robot-Assisted Instruction (RAI)” and “Robot-Managed
Instruction (RMI)” [1]. Fridin suggests that robots are developmental and potential
educational tools with broad appeal and learning relevance [2]. Chalmers proposed
that the educational robot interface design has an intuitive visual effect, which helps
students to learn programming at the teaching site [3], but the biggest bottleneck of
the existing curriculum is the lack of specific teacher training [4]. The use of
educational robots in both formal and informal learning can effectively build students'
critical thinking and problem-solving skills and improve the study of mathematics and
science. [5] [6] [7], Nag, Katz, & Saenz-Otero mentioned that robotics courses
combined with competitions even helped students to cross-domain learning in STEM
(science, technology, engineering, mathematics) [8].
2.2 Unified Theory of Acceptance and Use of Technology, UTAUT
The UTAUT model comes from the Technology Acceptance Model (TAM)
proposed by Davis [9]. The TAM has two major determinants are "Perceived
Usefulness" and "Perceived Ease of Use". Perceived Usefulness means that the user's
operation of a specific application or system will improve the performance or learning
of the individual, while another Perceived Ease of Use refers to the user's learning to
use the operating application or the ease of the system. The UTAUT model through
the past research on “users accepting behaviors in technology”, and this model found
that predicting and interpreting users' access to information technology has more than
70% explanatory power [10]. Therefore, most of the follow-up studies will omit
attitudes. The facets and Moderators of UTAUT as follows:
Performance Expectancy (PE), PE as the extent to which users believe that using
the system will help improve or improve job performance. PE is affected by three
moderators such as Gender, Age, and Experience, which affects male more obvious.
Effort Expectancy (EE), EE as the extent to which users can easily manipulate
new technologies, systems, and applications. For example, the user interface of the IT
device and the design of the operating system will affect the user's information
technology acceptance. EE is affected by three moderators such as Gender, Age and
Experience, which affects female more obvious, but EE will decrease with the growth
of experience.
Social Influence (SI), SI as the extent to which the user feels that the existing
organization believes that the user should use this new technology and system to what
extent. SI is affected by four moderators such as Gender, Age, Experience and
Voluntariness of Use, which affects female more obvious, but SI will decrease with
the growth of experience. SI will directly affect the intent of the user to use the new
technology, coupled with Ahmad & Love research indicates that lecture incentives
can help them adapt to the new technology to learn [11]. So this study, SI was defined
as the use of robots for students to be recommended by teachers. Students also believe
that it is feasible to use robots to learn.
Facilitating Conditions (FC), FC as the extent to which users believe that existing
organizations support users in using new technologies and systems. FC is affected by
two moderators such as Age and Experience, which affects older workers more
obvious and increasing as experience increases. Since the quality of RSI equipment
provided by the school will affect the students' learning behavior and willingness, FC
is defined in this study as the degree to which students assessed the school's support
for the RSI by equipment quality.
Behavioral Intention (BI) was originally proposed by Fishbein and Ajen [12] and
is defined as the degree of personal willingness of users to participate in certain
behaviors. However, in this study, behavioral intentions were defined as students'
willingness to continue to support RSI in the future or would like to further
recommend RSI to others.
Since RSI is an open innovation course, users with a high degree of Personal
Innovation are more likely to develop new technologies [11], and personal
innovations in new information technologies will positively influence the adoption
behavior [13] , so this study adds the “Personal Innovation” proposed by Agarwal &
Prasad to investigate the willingness of users to accept and use new technologies [14].
Based on the above, this UTAUT model will explore the changes of the six items
including Performance Expectancy, Effort Expectancy, Social Influence, Facilitating
Conditions, Behavioral Intention, and Personal Innovation.
3 Methodology
In the first year of the study, RSI carried out traditional teaching (only teaching
software and hardware operations). In the second year, STEM was integrated into RSI.
After completing the six-unit course, Course Satisfaction and Traditional UTAUT
questionnaire were performed, only in the second. The experiment of the year was
added to the "UTAUT-based Expectation situation questionnaire" for pre- and post-
test analysis (Fig. 1).
Fig. 1 Research architecture diagram
As shown in Fig. 1, the RSI course has six units including Servo motor control,
Infrared sensing module, Bluetooth communication module, Ultrasonic sensing
module, Line following control, and Bluetooth control self-propelled obstacle
avoidance control. The Course Satisfaction has four dimensions including Course
Content, Teaching Activity, Learning Outcome, and Learning Attitude. The UTAUT
questionnaire and the UTAUT-based Expectation situation questionnaire have six
items including Performance Expectancy, Effort Expectancy, Social Influence,
Facilitating Conditions, Behavioral Intention, and Personal Innovation.
3.1 Participants
In this study, two consecutives 12th grade students in a high school in northern
Taiwan were Participants. The experiment lasted for two years. In the first year, 41
students participated in the study and 49 students participated in the second year. The
two-year class hours (three hours a week for a total of 18 weeks) and the instructors
are the same, the difference is that the second year of the course has introduced
STEM cross-disciplinary teaching.
3.2 Research Tools
In this study, the robot uses Explore Board as the main controller, control software
for the InnoBASIC ™ Workshop (Fig. 2), this software platform provides students to
write programs, functional testing, to download code to the robot.
Fig. 2 The interface of InnoBASIC™ Workshop
3.3 Research framework
The RSI contains the following six units, as explained below:
Unit 1. Servo motor control: After explaining through the teacher's instructions,
the student programmatically controls the robot to move forward, backward, turn left,
and turn right.
Unit 2. Infrared sensing module: After the teacher explained the working principle
of the infrared sensor, the student programmed to control the robot to walk along the
black line.
Unit 3. Bluetooth communication module: After the teacher explained the working
principle of the Bluetooth communication module, the student programmed to control
the robot by the mobile APP.
Unit 4. Ultrasonic sensing module: After the teacher explained the working
principle of the ultrasonic sensor, the student programmed to control the robot to
detect the distance of the obstacle and return the data to the computer.
Unit 5. Line following control (Competition activities I): In this unit, students
must use the Bluetooth device of the mobile phone to control the robot to follow the
line from the starting point to the end point.
Unit 6. Bluetooth control self-propelled obstacle avoidance control (Competition
activities II): In this unit, students must use the Bluetooth device of the mobile phone
to control the robot to automatically avoid obstacles and get out of the maze with the
ultrasonic sensor.
3.4 UTAUT Questionnaire
The questionnaire was revised to the original UTAUT and adopted a five-point
Likert scale according to 5,4,3,2,1 score. The content of the questionnaire is divided
into two parts. The first part is translated and modified [15] There are 4 questions for
students to assess their current status, and The second part is a study modified from
Milošević, Živković, Manasijević and Nikolić [16], including six facets, a total of 19
questions, including "Performance Expectancy" 4 questions, "Effort Expectancy" 3
questions, "Social Influence" 2 questions, "Facilitating Conditions 4 questions,
"Behavioral Intention" 4 questions and "Personal Innovation" 2 questions, 19 high
school students who did not participate in the experiment conducted a reliability test
to obtain a high reliability of Cronbach's α value of .980, which proves the feasibility
of the questionnaire.
3.5 UTAUT Questionnaire for Expectation situation
The main purpose of this questionnaire is to establish a pre-test of UTAUT
Questionnaire, so change the beginning of all topics to "I expect" so that it can be
tested before class.
3.6 Course Satisfaction
This questionnaire is mainly to explore the satisfaction of students after each PSI
unit and adopted a five-point Likert scale according to 5, 4, 3, 2, and 1 score. The
Course Satisfaction has four dimensions including Course Content, Teaching Activity,
Learning Outcome, and Learning Attitude. The questionnaire was tested by the 19
high school students who did not participate in the experiment. The reliability test
showed that Cronbach's α value was .979, which proved the feasibility of the
questionnaire.
4 Experiment Results
4.1 UTAUT Questionnaire Results
As shown in Fig. 3 that the average curves of the UTAUT experiment results of
Traditional RSI and STEM-based RSI are very similar. The similarities are that both
scored low on both Effort Expectancy and Behavioral Intention, indicating that some
students feel that RSI still has some difficulty and does not want to recommend it to
others.
Fig. 3 The UTAUT experiment results of Traditional RSI and STEM-based RSI
4.2 The UTAUT pre-test and post-test of the STEM-based RSI
From Table 1, it can be found that the students have significant differences in the
Performance Expectancy and Behavioral Intention (*p <.05) through the paired
samples t-test. However, the three sub-items Effort Expectancy, Social Influence, and
Facilitating Conditions More significant difference (**p <.01). This means that
students feel better than expected for the "STEM-based RSI" arrangement, and there
is no significant difference in their own "Personal Innovation" because it is always
high.
Table 1. The paired samples t-test of STEM-based RSI
Item pre-test post-test t
M SD M SD
Performance Expectancy 3.81 0.769 4.14 0.584 2.691*
Effort Expectancy 3.61 0.716 3.99 0.567 3.481**
Social Influence 3.85 0.751 4.18 0.61 2.714**
Facilitating Conditions 3.85 0.694 4.14 0.508 2.783**
Behavioral Intention 3.76 0.735 3.99 0.555 2.200*
Personal Innovation 4.19 0.749 4.39 0.637 1.839
*p <.05 **p <.01
4.3 Course Satisfaction Results
It can be seen from the average curve of Figures 4 and 5 that although the first
three units Course Satisfaction results of STEM-based RSI are not as high as that of
the Traditional RSI, the satisfaction of the last two competition activities units has
steadily increased, but the Traditional RSI has declined. This result shows that the
students of Traditional RSI have high satisfaction in each of the above four units
because they only need to complete the learning of software and hardware. However,
when the last two units need to use cross-domain knowledge to solve problems, they
have learning difficulties. In contrast, STEM-based RSI is students feel very
burdensome because each unit is integrated into science, technology, engineering, and
mathematics, but in the last two competition activities units, they can use what they
have learned to achieve satisfactory results.
Figure 4. The Course Satisfaction results of Traditional RSI
Figure 5. The Course Satisfaction results of STEM-based RSI
5 Discussion and Conclusions
This study mainly compares the differences between the two methods of Robot-
Subject Instruction (RSI) using traditional single subject teaching and STEM cross-
disciplinary teaching. Through the UTAUT Questionnaire data, the study found that
the six sub-item curves of the Traditional RSI and STEM-based RSI UTAUT are
close, indicating that students have similar views on the acceptance of the two RSIs.
The students' scores of the five sub-items (Performance Expectancy, Effort
Expectancy, Social Influence, Facilitating Conditions, Behavioral Intention, Personal
Innovation) of the STEM-based RSI UTAUT are significantly higher than the pre-
tests, which means that the students' acceptance after class is significantly higher than
the previous expectations of the course. Finally, in the Course Satisfaction
questionnaire data after six units, we can find that the satisfaction of STEM-based
RSI is low first and then high, and the traditional RSI is high first and then low. The
key factor is that the Traditional RSI has a lower learning burden in the first four units,
so the satisfaction is higher, but the Competition activities unit at the end of the period
is prone to problems, causing a decline in satisfaction, while the STEM-based RSI
students are the opposite. Therefore, schools that are ready to promote RSI in the
future can consider whether to use STEM-based RSI based on the analysis of this
study.
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