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Smart Technology for Sustainable Curriculum: Using Drone to Support Young Students' Learning

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Smart Technology for Sustainable Curriculum: Using Drone to Support Young Students' Learning

Abstract and Figures

The study developed a sustainable curriculum in which one smart technology (drone) was employed to inspire student learning. The study investigated the effect of using drones on the development of students' spatial visualization and sequencing skills and examined related instructional tasks for drone use in the classroom. An after-school drone-flying program was developed at a public elementary school in Taiwan, with 10 third-grade students voluntarily participating in a six-week educational experiment. During drone programming training, young children used a visual block programming language on tablet computers to code lightweight drones. A two-phase research model was adopted to collect the necessary information. In the first phase of the model, a design-based research methodology facilitated the overall instruction preparation process for the four-week workshops. The second phase of the model emphasized a mixed-method research approach, employing a quasi-experimental pretest and post-test design to analyze the effect of drone use and a qualitative method to observe students' learning behavior and programming work. The results showed that drone programming significantly improved students' learning of spatial visualization and sequencing skills. Gender, as a potential variable, only influenced students' programming patterns. Specific programming styles, learning behaviors, and instructional design issues were identified for further discussion.
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sustainability
Article
Smart Technology for Sustainable Curriculum:
Using Drone to Support Young Students’ Learning
Pao-Nan Chou
Department of Education, National University of Tainan, Tainan 70005, Taiwan; pnchou@gm2.nutn.edu.tw
Received: 11 September 2018; Accepted: 19 October 2018; Published: 22 October 2018


Abstract:
The study developed a sustainable curriculum in which one smart technology
(drone) was employed to inspire student learning. The study investigated the effect of
using drones on the development of students’ spatial visualization and sequencing skills and
examined related instructional tasks for drone use in the classroom. An after-school drone-flying
program was developed at a public elementary school in Taiwan, with 10 third-grade students
voluntarily participating in a six-week educational experiment. During drone programming training,
young children used a visual block programming language on tablet computers to code lightweight
drones. A two-phase research model was adopted to collect the necessary information. In the
first phase of the model, a design-based research methodology facilitated the overall instruction
preparation process for the four-week workshops. The second phase of the model emphasized a
mixed-method research approach, employing a quasi-experimental pretest and post-test design to
analyze the effect of drone use and a qualitative method to observe students’ learning behavior and
programming work. The results showed that drone programming significantly improved students’
learning of spatial visualization and sequencing skills. Gender, as a potential variable, only influenced
students’ programming patterns. Specific programming styles, learning behaviors, and instructional
design issues were identified for further discussion.
Keywords:
sustainable curriculum; drones in education; children’s programming; spatial visualization
1. Introduction
Agenda 21 plan of UNESCO states that education is a way to solve potential problems threatening
our future society [
1
]. Teaching and learning for sustainable future program at UNESCO also declared
that education “as one of the most powerful instruments for bringing about the changes required
to achieve sustainable development [
2
].” Specifically, regarding sustainable development goal on
education by UNESCO, one of goals (SDG4) states that quality education and lifelong learning
opportunities for all must be addressed [3].
Information and Communication Technologies (ICT) as efficient pedagogical tools have
the potential to respond and fulfill the SDG4 [
4
]. For example, in Velázquez and Méndez’s
study [
5
], augmented reality and mobile devices have been confirmed to support student learning
(quality education) and improve students’ skills in using emerging technologies (lifelong learning).
In Deaconu et al.’s study [
6
], ICT integrated in vocational education and training provided promising
results in which students’ learning outcomes were improved (quality education) and specific skills
were acquired for lifelong learning.
The current study examined the opportunities and difficulties in integrating ICT in education.
In the study, one ICT (drone) was incorporated in an after school program at a public elementary school
in Taiwan. Students participating in the curriculum were empowered to employ flying drones to foster
their understanding of spatial visualization and sequencing (quality education) and to enhance their
awareness of computational thinking (lifelong learning for future society).
Sustainability 2018,10, 3819; doi:10.3390/su10103819 www.mdpi.com/journal/sustainability
Sustainability 2018,10, 3819 2 of 17
2. Literature Review
2.1. Potential Learning Benefits of Drone use
Drones (or unmanned aerial vehicles) equipped with tools such as robotic arms or high-definition
digital cameras have been employed in many fields for various purposes. In the corporate
domain, for example, Amazon announced drone use to deliver products to targeted customers [
7
].
Farmers employ drones to monitor livestock, manage irrigation plans, and spray pesticides [
8
],
and firefighters dispatch them to collect damage assessment information during wildfires [9].
The drone adoption trend has also spread to educational environments, gaining considerable
attention. Walsh [
10
] proposed that flying drones were suitable for seven learning activities: logic and
deductive reasoning, debate, geography, higher mathematics, electronics, and hand-eye coordination.
In addition, Cenejac [
11
] argued that drone image-capturing might benefit both students’ thinking
process in speaking and writing classes and exercise procedures in physical education classes.
Because of its potential for supporting student learning, drone use is generally regarded as an
alternative instructional strategy to innovate learning environments [
12
,
13
]. However, whether drone
use in classrooms can produce more effective learning compared with traditional instruction requires
further investigation.
2.2. Lack of Drone Programming Research
Drones for educational use can be categorized by weight into two types: heavyweight
(above 1 pound) and lightweight (below 1 pound). Because of their superior wind resistance,
heavyweight drones (e.g., DJI Mavic) are suited for navigation in outdoor learning activities [
13
].
By contrast, lightweight (e.g., Parrot Mambo) drones are suitable for indoor learning tasks [
14
].
Currently, both types of drones are equipped with a remote control but the lightweight drones
often offer programming design possibilities. Hussey [
15
] and Wakefield [
16
] reported that several
elementary schools in the United States enabled young children to program lightweight drones
to fly in classrooms. However, although these reports noted students’ high learning motivation,
further educational evaluation of drone programming remains unavailable.
Research regarding drone use in education has tended to focus on theoretical discussions,
whereas empirical-based studies with quantitative or qualitative evaluation data are uncommon.
For example, Schaeffer and Olson [
17
] designed a special topics course in a graduate-level information
technology program that emphasized theoretical discussion of drone application and development.
Although the study reported initially positive responses from students, no specific educational
evaluation was conducted. Carnahan and Crowley [
18
] simply proposed that adoption of drones in
the curriculum might enable students to actively engage in the learning process. In an educational
experiment conducted by Palaigeorgiou, Malandrakis, and Tsolopani [
19
], one group of students went
on a field trip while another group stayed in the lab to watch drone-captured videos of the same outing.
The findings indicated that students in the drone group enjoyed their virtual learning experience,
particularly the superior overview of the field.
2.3. Potential for Developing Spatial Visualization Skills
Spatial visualization is the ability to mentally manipulate two-dimensional (2D) or
three-dimensional (3D) objects [
20
]. Through scientific training, students’ spatial visualization skills
can be effectively improved [
21
]. Traditionally, visual aids such as plastic-made geometric objects
were often used for instruction in spatial visualization [
22
]. However, with the development of
advanced computer technologies, the instructional role of such aids has gradually been assumed by 3D
multimedia software. For example, Baki, Kosa, and Guven [
23
] employed dynamic geometry software
to support students’ spatial visualization skills. Students in a study by Chou, Chen, Wu, and Carey [
24
]
used open-source 3D software to improve their understanding of spatial visualization concepts.
Sustainability 2018,10, 3819 3 of 17
Similar to the function of 3D multimedia software, drone use in education can provide 3D learning
experiences. However, in contrast to observing virtual objects on a computer screen, operating a drone
enables users to physically experience 3D sensations of their surroundings. Students can use a remote
controller or a programming language to manipulate a drone’s flight direction and movement in
learning environments [
12
,
13
]. During immersion in learning to fly a drone, students exercise their
spatial reasoning to design flight patterns by understanding the 3D geographical information around
them [
25
]. Therefore, given the capability of emerging technologies, drone integration in the curriculum
has the potential for fostering spatial visualization skills.
2.4. Potential for Developing Sequencing Skills
Sequencing refers to the ability to organize objects or plan actions in a logical order [
26
].
Sequencing skills have often been identified in young children’s play activities. For example,
young children often demonstrate sequencing when reorganizing or retelling a story in a specific
order [
27
]. In addition, sequencing has been associated with mathematical and problem-solving
skills. For instance, Sarama and Clements [
28
] argued that the sequencing skills shown in using
building blocks exemplified the fundamental mathematical thinking by which children perceive the
world. Zelazo, Carter, Reznick, and Frye [
29
] observed that planning—one of the critical elements in a
problem-solving framework—involves the sequencing of actions in a well-organized fashion.
Computer programming is an alternative method for developing sequencing skills.
Students engaged in programming must arrange symbolic commands in sequence to design the
desired actions [
30
]. The visual block programming languages (e.g., Scratch) commonly used in
elementary schools also require children to sequence various color-based blocks to perform animation
tasks [
31
]. In the framework proposed by Brennan and Resnick [
32
], the sequential procedure of
Scratch programming is a fundamental prerequisite for computational thinking. Students in the study
by Kazakoff et al., [
26
] significantly improved their sequencing skills through training in computer
programming similar to Scratch. In the current study, students were given a learning opportunity to
constantly organize visual blocks in various types of sequential patterns for solving programming
tasks. Such learning process has the potential for developing sequencing skills.
2.5. Smart Technology for Sustainable Curriculum
For sustainable educational development, teaching and learning for sustainable future program
at UNESCO [
33
] proposed that several instructional issues should be integrated into the curriculum.
Among those issues, “a future perspective” and “citizenship education” are two critical teaching
themes. In the study, the rationale (a combination of two themes) of adopting smart technologies for
sustainable curriculum was:
Creating a digital learning environment for young children (digital citizenship) is a future trend.
The educators need to empower students to use emerging digital technologies to investigate
various aspects of learning problems. The drones as one of digital smart technologies provided
a valuable learning opportunity that enabled young kids to become innovative designers
(programming design) and computational thinkers (computing experience) for the future
society [34].
3. Research Questions
Against this background, this study aimed to investigate the potential effect of drone use
on students’ development of spatial visualization and sequencing skills and to examine related
instructional tasks for using drones in the classroom. Four-week design-based workshops within
a 6-week educational experiment were conducted to achieve the research purpose. Drones were
integrated in an after-school program in which elementary school students used a visual block
Sustainability 2018,10, 3819 4 of 17
programming language called Tynker to control lightweight drones. Specifically, the following four
research questions (RQ) were formulated:
RQ1.
What instructional effects did drone use have on students’ spatial visualization and
sequencing skills?
RQ2.
What learning patterns were identified in drone programming tasks?
RQ3.
What were students’ learning responses to classroom drone use?
RQ4.
What were the instructional design problems of classroom drone use?
4. Research Methods
4.1. Research Design
This study adopted a two-phase research model (Figure 1) to collect the necessary information.
In the first phase of the model, a design-based research methodology guided the research and facilitated
the entire instruction preparation process, enabling the research team and school administration
to constantly modify instructional content [
35
], including curriculum structure, technology use,
learning material, and learning environment. In addition, problems regarding drone use in the
classroom were discussed on the basis of results from pilot tests and solutions were continually
updated in weekly workshops.
Sustainability 2018, 10, x FOR PEER REVIEW 4 of 17
programming language called Tynker to control lightweight drones. Specifically, the following four
research questions (RQ) were formulated:
RQ1. What instructional effects did drone use have on students’ spatial visualization and
sequencing skills?
RQ2. What learning patterns were identified in drone programming tasks?
RQ3. What were students’ learning responses to classroom drone use?
RQ4. What were the instructional design problems of classroom drone use?
4. Research Methods
4.1. Research Design
This study adopted a two-phase research model (Figure 1) to collect the necessary information.
In the first phase of the model, a design-based research methodology guided the research and
facilitated the entire instruction preparation process, enabling the research team and school
administration to constantly modify instructional content [35], including curriculum structure,
technology use, learning material, and learning environment. In addition, problems regarding drone
use in the classroom were discussed on the basis of results from pilot tests and solutions were
continually updated in weekly workshops.
Figure 1. Two-phase research model used in the study.
The second phase of the model emphasized a mixed-method research approach [36]. In the
quantitative part, a quasi-experimental pretest and posttest design was used to examine the effect of
drone programming on students’ spatial visualization and sequencing skills. The educational
experiment lasted for 6 weeks. The independent variable was instructional intervention, and the
dependent variable was skills development outcome (spatial visualization and sequencing). Prior to
Figure 1. Two-phase research model used in the study.
The second phase of the model emphasized a mixed-method research approach [
36
]. In the
quantitative part, a quasi-experimental pretest and posttest design was used to examine the effect
of drone programming on students’ spatial visualization and sequencing skills. The educational
experiment lasted for 6 weeks. The independent variable was instructional intervention, and the
dependent variable was skills development outcome (spatial visualization and sequencing). Prior to
the experiment, students were given a spatial visualization and sequencing pretest. Next, during the
educational experiment, students were immersed in drone programming training. Upon completion
Sustainability 2018,10, 3819 5 of 17
of the experiment, students received the same test (post-test) with different item numbers. Because no
control group was involved in the experimental design, the quantitative part served as an explorative
purpose for related research questions.
In the qualitative part, students’ learning behaviors were documented through class observation,
work analysis, and interviews. These three qualitative sources formed a data triangulation
mechanism [
37
]. During weekly learning activities, the researchers used a participatory observation
method to directly monitor students’ drone use and then summarized their observation notes after
class. When students completed class assignments, their programming work was automatically saved
for further analysis. After competition of the weekly unit lessons, the researchers also interviewed some
students about their learning experiences. The interview format was a casual five-minute conversation
without guidelines, thus avoiding placing learning pressure on young children.
4.2. Research Instruments
4.2.1. Spatial Visualization Test
A test was designed to measure students’ spatial visualization skills. Chou et al., [
24
] reported
that mathematics for fifth-grade students in Taiwan contains a learning unit on spatial visualization.
Following the framework of this unit, basic entry-level spatial visualization questions with an emphasis
on spatial comparison and rotation were developed to fit the cognitive development level of the
participants (i.e., third-grade students). The test comprised six major scenarios with 26 multiple choice
questions, with scores ranging from 0 to 26. The validity and reliability of the measurements were
established during the 4-week pilot stage. Three mathematics teachers from a public elementary school
in Taiwan thoroughly reviewed the content validity of the initial test items. A KR-21 reliability test
was performed to verify the final version of the test, using a pool of 25 elementary school students.
The overall Cronbach’s alpha value was 0.89. Figure 2presents one scenario. Figure 3is an English
version of the scenario.
Sustainability 2018, 10, x FOR PEER REVIEW 5 of 17
the experiment, students were given a spatial visualization and sequencing pretest. Next, during the
educational experiment, students were immersed in drone programming training. Upon completion
of the experiment, students received the same test (post-test) with different item numbers. Because
no control group was involved in the experimental design, the quantitative part served as an
explorative purpose for related research questions.
In the qualitative part, students’ learning behaviors were documented through class
observation, work analysis, and interviews. These three qualitative sources formed a data
triangulation mechanism [37]. During weekly learning activities, the researchers used a participatory
observation method to directly monitor students’ drone use and then summarized their observation
notes after class. When students completed class assignments, their programming work was
automatically saved for further analysis. After competition of the weekly unit lessons, the researchers
also interviewed some students about their learning experiences. The interview format was a casual
five-minute conversation without guidelines, thus avoiding placing learning pressure on young
children.
4.2. Research Instruments
4.2.1. Spatial Visualization Test
A test was designed to measure students’ spatial visualization skills. Chou et al., [24] reported
that mathematics for fifth-grade students in Taiwan contains a learning unit on spatial visualization.
Following the framework of this unit, basic entry-level spatial visualization questions with an
emphasis on spatial comparison and rotation were developed to fit the cognitive development level
of the participants (i.e., third-grade students). The test comprised six major scenarios with 26 multiple
choice questions, with scores ranging from 0 to 26. The validity and reliability of the measurements
were established during the 4-week pilot stage. Three mathematics teachers from a public elementary
school in Taiwan thoroughly reviewed the content validity of the initial test items. A KR-21 reliability
test was performed to verify the final version of the test, using a pool of 25 elementary school
students. The overall Cronbach’s alpha value was 0.89. Figure 2 presents one scenario. Figure 3 is an
English version of the scenario.
Figure 2. Scenario from the spatial visualization test. (The five questions which follow aim to assess
students’ spatial comparison and rotation skills.).
Figure 2.
Scenario from the spatial visualization test. (The five questions which follow aim to assess
students’ spatial comparison and rotation skills.).
Sustainability 2018, 10, x FOR PEER REVIEW 6 of 17
Figure 3. Scenario from the spatial visualization test (English version).
4.2.2. Sequencing Test
A picture-sequencing test developed by a Taiwanese publisher was used to assess the
sequencing skills of elementary school students in grades 1–3 [38]. The test comprised 13 story
categories with 50 picture cards, in which three or four picture cards match each story. When
performing picture-sequencing tasks, students had to arrange the cards in a logical order. Completing
the story successfully earned one point, with scores ranging from 0 to 13. To administer the test
efficiently, the original picture cards were redesigned and printed on A4 paper. Students only wrote
the sequence number on the picture cards. The publisher reported high test validity [38] but lacked
information on reliability. Therefore, a KR-21 reliability test using a pool of 25 elementary school
students was performed to confirm test reliability. The overall Cronbach’s alpha value was 0.91.
4.3. Research Participants
After a 1-month recruitment process at a public elementary school in Taiwan, 10 third-grade
students (aged 8 years) were selected for voluntary participation. There was sex equivalence (male:
5; female: 5) among the participants. None of the students had any programming experience prior to
the study, but they were skilled with tablet computers because of the mobile devices they used at
home.
4.4. Drone Programming
The drone used in the study was a lightweight type (Parrot Mambo; Parrot Co., Ltd.), which
could be operated with a virtual remote controller in the app or by using programming languages.
In this study, young students were instructed to code the drones on their tablet computers using a
visual block programming language called Tynker (The interface is very similar to Google Blocky
and MIT Scratch). Although Tynker offers several programming functions, students focused on basic
programming blocks, such as loops and conditionals, as well as drone blocks for directly controlling
flight movement. Advanced blocks involving complex mathematics and variable computing were
not covered in the learning material. Figure 4 shows one drone programming example.
Figure 3. Scenario from the spatial visualization test (English version).
Sustainability 2018,10, 3819 6 of 17
4.2.2. Sequencing Test
A picture-sequencing test developed by a Taiwanese publisher was used to assess the sequencing
skills of elementary school students in grades 1–3 [
38
]. The test comprised 13 story categories
with 50 picture cards, in which three or four picture cards match each story. When performing
picture-sequencing tasks, students had to arrange the cards in a logical order. Completing the story
successfully earned one point, with scores ranging from 0 to 13. To administer the test efficiently,
the original picture cards were redesigned and printed on A4 paper. Students only wrote the sequence
number on the picture cards. The publisher reported high test validity [
38
] but lacked information
on reliability. Therefore, a KR-21 reliability test using a pool of 25 elementary school students was
performed to confirm test reliability. The overall Cronbach’s alpha value was 0.91.
4.3. Research Participants
After a 1-month recruitment process at a public elementary school in Taiwan, 10 third-grade
students (aged 8 years) were selected for voluntary participation. There was sex equivalence (male: 5;
female: 5) among the participants. None of the students had any programming experience prior to the
study, but they were skilled with tablet computers because of the mobile devices they used at home.
4.4. Drone Programming
The drone used in the study was a lightweight type (Parrot Mambo; Parrot Co., Ltd.), which could
be operated with a virtual remote controller in the app or by using programming languages. In this
study, young students were instructed to code the drones on their tablet computers using a visual block
programming language called Tynker (The interface is very similar to Google Blocky and MIT Scratch).
Although Tynker offers several programming functions, students focused on basic programming
blocks, such as loops and conditionals, as well as drone blocks for directly controlling flight movement.
Advanced blocks involving complex mathematics and variable computing were not covered in the
learning material. Figure 4shows one drone programming example.
Figure 4. Drone programming example (flying in a large circle).
4.5. Instruction Implementation
The educational experiment was conducted in an assembly hall that offered ample space for flying
drones. The physical size of this learning environment was equivalent to that of three classrooms,
but with a higher ceiling. All students received one tablet computer (iPad mini) and one lightweight
drone (Parrot Mambo). Figure 5shows a student programming his drone.
Sustainability 2018,10, 3819 7 of 17
Sustainability 2018, 10, x FOR PEER REVIEW 7 of 17
Figure 4. Drone programming example (flying in a large circle).
4.5. Instruction Implementation
The educational experiment was conducted in an assembly hall that offered ample space for
flying drones. The physical size of this learning environment was equivalent to that of three
classrooms, but with a higher ceiling. All students received one tablet computer (iPad mini) and one
lightweight drone (Parrot Mambo). Figure 5 shows a student programming his drone.
Figure 5. Student coding his drone.
Drone programming training was an after-school program with a 6-week course. Three
instructors with different teaching roles administered the program. One principal instructor taught
the weekly classes, and the two assistant instructors were responsible for facilitating student learning
and maintaining classroom discipline. The weekly class was scheduled as a 3-h session. However,
due to accidents (e.g., a drone hitting the wall) or debugging issues, the sessions were often extended
to 3.5 h of learning activity. Table 1 displays the curriculum design.
Figure 5. Student coding his drone.
Drone programming training was an after-school program with a 6-week course. Three instructors
with different teaching roles administered the program. One principal instructor taught the weekly
classes, and the two assistant instructors were responsible for facilitating student learning and
maintaining classroom discipline. The weekly class was scheduled as a 3-h session. However, due to
accidents (e.g., a drone hitting the wall) or debugging issues, the sessions were often extended to 3.5 h
of learning activity. Table 1displays the curriculum design.
Table 1. Curriculum design of drone programming training.
Week Learning Unit (3h)
1 Introduction to drone programming
2
Drone programming 1: Basic flying movements
3 Drone programming 2: Flying pattern design
4 Drone programming 3: Passing obstacles
5 Drone programming 4: Two drones together
6 Drone programming 5: Drone dancing
Each weekly unit was based on a three-stage learning progression model (Figure 6), namely, copy,
tinker, and create. In the first stage (approximately 30 min), students copied programming examples
from learning material for practice purposes. In the second stage (approximately 50 min), they modified
those examples by adding more programming blocks, and in the final stage (approximately 100 min),
they had to create a whole new programming pattern.
Sustainability 2018, 10, x FOR PEER REVIEW 8 of 17
Table 1. Curriculum design of drone programming training.
Week Learning Unit (3h)
1 Introduction to drone programming
2 Drone programming 1: Basic flying movements
3 Drone programming 2: Flying pattern design
4 Drone programming 3: Passing obstacles
5 Drone programming 4: Two drones together
6 Drone programming 5: Drone dancing
Each weekly unit was based on a three-stage learning progression model (Figure 6), namely,
copy, tinker, and create. In the first stage (approximately 30 min), students copied programming
examples from learning material for practice purposes. In the second stage (approximately 50 min),
they modified those examples by adding more programming blocks, and in the final stage
(approximately 100 min), they had to create a whole new programming pattern.
Figure 6. Three-stage learning progression model.
4.6. Rationale of Instructional Implementation Model
The current study modified Chou’s [39] three-stage design model (pre-design, in-design and
post-design) and proposed a three-stage learning progression model (copy, tinker, and create) for
teaching drone programming. The copy stage is similar to the learning process (copy idea and try
out) in the pre-design stage. The create stage is similar to the learning process (re-design and build)
in the in-design process. However, in order to decrease young children’s learning loads [40], the
tinker stage as a practice purpose was added to enable students to smoothly move the first stage
(copy) to the last stage (create).
According to constructive developmental learning theories [40], students in different ages may
construct their knowledge base in various cognitive learning levels. In Chou’s study, students (fifth
grade) participated in the after school program were more mature than students (third grade) in the
study. Higher order thinking (e.g., reflection) in the post-design from Chou’s learning model might
not be suitable for third-grade students, which forced the current study to abandon the post-design
stage.
4.7. Aviation Rule for Drone Use in Classrooms
Adopting drones in schools needs to follow aviation regulations [12]. According to aviation rules
by the Ministry of Transportation and Communications in Taiwan [41], it is illegal to fly any drones
for outdoor activities in schools that are located near airports or military institutions. In addition,
there were rules for aviation height restriction for the heavyweight drone use in outdoor activities.
However, no rules were given to lightweight drones that are used for indoor learning tasks in
classrooms. In the study, the lightweight drone use is legal in the school vicinity.
4.8. Data Analysis
In the quantitative part of the study, a t test and descriptive statistics were used to investigate
the learning process of spatial visualization and sequencing skills as well as the gender effect. The
instructors also employed a 10-point scale (from 0 to 10) to quantify students’ programming work
Figure 6. Three-stage learning progression model.
4.6. Rationale of Instructional Implementation Model
The current study modified Chou’s [
39
] three-stage design model (pre-design, in-design and
post-design) and proposed a three-stage learning progression model (copy, tinker, and create) for
teaching drone programming. The copy stage is similar to the learning process (copy idea and try out)
in the pre-design stage. The create stage is similar to the learning process (re-design and build) in the
Sustainability 2018,10, 3819 8 of 17
in-design process. However, in order to decrease young children’s learning loads [
40
], the tinker stage
as a practice purpose was added to enable students to smoothly move the first stage (copy) to the last
stage (create).
According to constructive developmental learning theories [
40
], students in different ages
may construct their knowledge base in various cognitive learning levels. In Chou’s study,
students (fifth grade) participated in the after school program were more mature than students
(third grade) in the study. Higher order thinking (e.g., reflection) in the post-design from Chou’s
learning model might not be suitable for third-grade students, which forced the current study to
abandon the post-design stage.
4.7. Aviation Rule for Drone Use in Classrooms
Adopting drones in schools needs to follow aviation regulations [
12
]. According to aviation
rules by the Ministry of Transportation and Communications in Taiwan [
41
], it is illegal to fly
any drones for outdoor activities in schools that are located near airports or military institutions.
In addition, there were rules for aviation height restriction for the heavyweight drone use in outdoor
activities. However, no rules were given to lightweight drones that are used for indoor learning tasks
in classrooms. In the study, the lightweight drone use is legal in the school vicinity.
4.8. Data Analysis
In the quantitative part of the study, a ttest and descriptive statistics were used to investigate
the learning process of spatial visualization and sequencing skills as well as the gender effect.
The instructors also employed a 10-point scale (from 0 to 10) to quantify students’ programming
work from the final stage of the learning progression model. The evaluation results were subsequently
compared with other quantitative data (i.e., two post-tests) through partial correlation analysis.
For the qualitative data, the qualitative analysis method of Moustakas [
42
] was employed to
interpret observation notes and interview transcripts. Moreover, qualitative content analysis was
performed to examine students’ programming work. To confirm differences in drone flight movements,
the frequency of certain programming patterns identified during this process was also analyzed using
the chi-square test.
Regarding the data reliability in the study, after the three instructors evaluated students’
programming work, one research assistant was hired to confirm the evaluation consistency among
three raters. In addition, the study employed Patton’s [
37
] data triangulation method to ensure data
consistency among observation notes, interview transcripts, and students’ programming work.
5. Results and Discussion
Overall, the research design of the study only fitted in a specific learning scenario. Because of a
small sample size, the following quantitative information only reported the phenomenon occurred
at the after-school program and cannot be generalized into other learning contexts. In addition,
the following qualitative information was used for interpreting unique learning patterns and
corroborating the quantitative findings.
5.1. Instructional Effects of Drone Use
The results of descriptive statistics and ttests are summarized in Tables 2and 3, respectively.
These show that significant gains were identified in the sequencing (t= 4.70, p< 0.01) and spatial
visualization (t= 4.42, p< 0.01) tests, with a major improvement (mean difference = 5.4) demonstrated
for spatial visualization. Therefore, drone programming training could significantly enhance young
students’ sequencing and spatial visualization skills development, and drone use had a particularly
large learning effect on their spatial visualization.
Sustainability 2018,10, 3819 9 of 17
Table 2. Descriptive statistics. M: mean; SD: standard deviation.
Measurement M SD
Sequencing Pre-Test 10.7
1.33
Sequencing Post-Test 12.3
0.78
Spatial Pre-Test 17.0
1.16
Spatial Post-Test 22.4
1.84
Table 3. Results of ttests.
Comparison Mean Difference t df Sig.
Sequencing Post-Test & Sequencing Pre-Test 1.6 4.70 9 0.00 **
Spatial Post-Test &Spatial Pre-Test 5.4 4.42 9 0.00 **
Note: ** p< 0.01.
5.2. Gender Effect
Although the study group was sex equivalent, the research team attempted to assess whether
gender affected on students’ skills development. The ttest results for gender effect are reported in
Tables 4and 5. Regardless of the measurement type, the statistical information indicated that gender
as a potential variable did not influence students’ performance in sequencing (pretest: t= 0.22,
p> 0.01
;
post-test: t= 0.63, p> 0.01) and spatial visualization (pretest: t= 0,
p> 0.01
; post-test: t= 0, p> 0.01).
Thus, male students demonstrated the same learning patterns as female students throughout this
educational experiment.
Table 4. Results of ttest for gender effect (pretest).
Measurement M/SD (Male) M/SD (Female) t df Sig.
Sequencing Pre-Test 10.8/1.3 10.6/1.5 0.22 8 0.83
Spatial Pre-Test 17/1.09 17/1.61 0 8 1
Table 5. Results of ttest for gender effect (post-test).
Measurement M/SD (Male) M/SD (Female) t df Sig.
Sequencing Post-Test 12.4/0.54 12.2/0.45 0.63 8 0.55
Spatial Post-Test 22.4/1.83 22.4/1.51 0 8 1
5.3. Drone Programming Patterns
Three major programming patterns were found through analysis of students’ work:
Pattern 1: No relationship between drone programming and skills development.
Removing the effects of the two pretests yielded the partial correlation analysis results reported
in Table 6. Overall, students’ programming work in the last stage of the learning progression model
was not significantly related to their performance in the sequencing (r = 0.08, p> 0.05) and spatial
visualization (r = 0.24, p> 0.05) posttests. Therefore, no relationship between students’ drone
programming work and the development of their sequencing and spatial visualization skills was found.
Table 6. Results of partial correlation analysis (removing effect of pretests).
Item Sequencing Post-Test Spatial Post-Test
Programming quality 0.08 0.24
p0.83 0.51
Sustainability 2018,10, 3819 10 of 17
Pattern 2: Avoidance of loop concepts.
Loop blocks in the programming language (Tynker) enabled students to reduce redundant blocks.
However, most students preferred to use basic blocks to sequence their programming rather than use
advanced loop blocks. For example, if a drone was designed to fly two times in a circle, students tended
to repeat the same blocks twice; they would not employ the loop blocks to shorten the programming
pattern. Although these two approaches yielded the same programming outcomes, students preferred
the more inefficient programming design.
Pattern 3: Gender difference in drone movement.
When designing drone movements, male students demonstrated bolder learning patterns than
their female counterparts. A flip block (Figure 7) often appeared in male students’ programming
work. Moreover, in the same learning scenario male students preferred wide flight movements,
whereas female students focused on narrow flight paths (Figure 8). The comparative frequency of
flight movement patterns between male and female students was analyzed using a chi-square test,
the results of which are summarized in Table 7. The statistical findings showed a significant difference
between male and female students for flip block use (
χ2
= 10, p< 0.05) and flight pattern width (
χ2= 10
,
p< 0.05).
Sustainability 2018, 10, x FOR PEER REVIEW 10 of 17
Table 4. Results of t test for gender effect (pretest).
Measurement M/SD (Male) M/SD (Female) t df Sig.
Sequencing Pre-Test 10.8/1.3 10.6/1.5 0.22 8 0.83
Spatial Pre-Test 17/1.09 17/1.61 0 8 1
Table 5. Results of t test for gender effect (post-test).
Measurement M/SD (Male) M/SD (Female) t df Sig.
Sequencing Post-Test 12.4/0.54 12.2/0.45 0.63 8 0.55
Spatial Post-Test 22.4/1.83 22.4/1.51 0 8 1
5.3. Drone Programming Patterns
Three major programming patterns were found through analysis of students’ work:
Pattern 1: No relationship between drone programming and skills development.
Removing the effects of the two pretests yielded the partial correlation analysis results reported
in Table 6. Overall, students’ programming work in the last stage of the learning progression model
was not significantly related to their performance in the sequencing (r = 0.08, p > 0.05) and spatial
visualization (r = 0.24, p > 0.05) posttests. Therefore, no relationship between students’ drone
programming work and the development of their sequencing and spatial visualization skills was
found.
Table 6. Results of partial correlation analysis (removing effect of pretests).
Item Sequencing Post-Test Spatial Post-Test
Programming quality 0.08 0.24
p 0.83 0.51
Pattern 2: Avoidance of loop concepts.
Loop blocks in the programming language (Tynker) enabled students to reduce redundant
blocks. However, most students preferred to use basic blocks to sequence their programming rather
than use advanced loop blocks. For example, if a drone was designed to fly two times in a circle,
students tended to repeat the same blocks twice; they would not employ the loop blocks to shorten
the programming pattern. Although these two approaches yielded the same programming outcomes,
students preferred the more inefficient programming design.
Pattern 3: Gender difference in drone movement.
When designing drone movements, male students demonstrated bolder learning patterns than
their female counterparts. A flip block (Figure 7) often appeared in male students’ programming
work. Moreover, in the same learning scenario male students preferred wide flight movements,
whereas female students focused on narrow flight paths (Figure 8). The comparative frequency of
flight movement patterns between male and female students was analyzed using a chi-square test,
the results of which are summarized in Table 7. The statistical findings showed a significant
difference between male and female students for flip block use (χ2 = 10, p < 0.05) and flight pattern
width (χ2 = 10, p < 0.05).
Figure 7. A flip block in Tynker.
Figure 7. A flip block in Tynker.
Sustainability 2018, 10, x FOR PEER REVIEW 11 of 17
Figure 8. Flight movement patterns of male and female students.
Table 7. Results of chi-squared test by gender.
Item Flip Block Use Wide Flying Pattern
Gender X
2
= 10, df = 3 X
2
= 10, df = 3
p 0.02 * 0.02 *
Note: * p < 0.05.
5.4. Students’ Learning Responses
Qualitative analysis of the informal interviews and class observation yielded the following five
themes.
Theme 1: Learning enthusiasm
In weekly learning sessions, the students all demonstrated interest in learning about drone
programming and motivation to engage in different types of learning activities. However, students’
desire to learn sometimes created a noisy environment in which they enthusiastically and loudly
shared their work with instructors and peers. Under such circumstances, the instructors had to insist
on classroom discipline to control student behavior. Students’ increased learning motivation could
be attributed to the study’s innovative instructional design. Most students perceived the learning
content of the experimental program as more attractive and enjoyable than conventional school
learning. For example, one boy said, “I love to make something using technology. But my classes in
school do not provide such opportunities. That’s why I was so excited about the program.”
Theme 2: Self-reported learning gains
Because these young students did not have programming experience, they perceived
programming as the major educational benefit. Several students overestimated the complexity of
programming and expressed a desire to learn programming tasks. For example, one girl said, “In the
beginning, I was worried about my programming skills. But, to my surprise, the visual programming
blocks were not very hard to understand. I began to love coding.” Or, as one boy stated:
“Programming looked like building with physical blocks. It was not very hard and more fun than
with traditional blocks. The most important thing was that it allowed me to generate something by
combining different blocks.” The second self-reported learning gain was spatial training. Several
students considered spatial visualization to be their learning weakness. However, with the assistance
of drone use, they gradually gained knowledge of 3D space and could then mentally visualize flight
direction and movement. For example, one boy said, “I often had difficulty identifying right or left.
But I improved my spatial skills through drone programming design.” Or, as one girl stated: “When
I began to design the drone flight path, I would visualize the direction in my mind. … When I got
home, I even showed my mom and brothers how 3D space worked.”
Figure 8. Flight movement patterns of male and female students.
Table 7. Results of chi-squared test by gender.
Item Flip Block Use Wide Flying Pattern
Gender X2= 10, df = 3 X2= 10, df = 3
p0.02 * 0.02 *
Note: * p< 0.05.
5.4. Students’ Learning Responses
Qualitative analysis of the informal interviews and class observation yielded the following
five themes.
Theme 1: Learning enthusiasm
Sustainability 2018,10, 3819 11 of 17
In weekly learning sessions, the students all demonstrated interest in learning about drone
programming and motivation to engage in different types of learning activities. However,
students’ desire to learn sometimes created a noisy environment in which they enthusiastically and
loudly shared their work with instructors and peers. Under such circumstances, the instructors had to
insist on classroom discipline to control student behavior. Students’ increased learning motivation
could be attributed to the study’s innovative instructional design. Most students perceived the
learning content of the experimental program as more attractive and enjoyable than conventional
school learning. For example, one boy said, “I love to make something using technology. But my
classes in school do not provide such opportunities. That’s why I was so excited about the program.”
Theme 2: Self-reported learning gains
Because these young students did not have programming experience, they perceived
programming as the major educational benefit. Several students overestimated the complexity of
programming and expressed a desire to learn programming tasks. For example, one girl said, “In the
beginning, I was worried about my programming skills. But, to my surprise, the visual programming
blocks were not very hard to understand. I began to love coding.” Or, as one boy stated: “Programming
looked like building with physical blocks. It was not very hard and more fun than with traditional
blocks. The most important thing was that it allowed me to generate something by combining different
blocks.” The second self-reported learning gain was spatial training. Several students considered spatial
visualization to be their learning weakness. However, with the assistance of drone use, they gradually
gained knowledge of 3D space and could then mentally visualize flight direction and movement.
For example, one boy said, “I often had difficulty identifying right or left. But I improved my spatial
skills through drone programming design.” Or, as one girl stated: “When I began to design the drone
flight path, I would visualize the direction in my mind.
. . .
When I got home, I even showed my mom
and brothers how 3D space worked.”
Theme 3: Learning support from the instructor
During the first 2 weeks, perhaps because students were not familiar with programming language,
they required constant learning support from the instructors. Under such circumstances, the three
instructors were busy moving around the classroom to provide programming guidance, and this
directly affected the pace of the lesson plan. As students gradually gained programming knowledge
in subsequent weeks, a major problem with programming debugging appeared in the classroom.
For example, students easily passed through the first two stages of the learning progression model
(copy and tinker) but tended to fail to complete their programming work in the last stage (create).
Several students frequently sought help because the flight movement did not match their programming
design. Once the instructors explained the debugging principles, however, students were able to adopt
them to solve problems.
Theme 4: Gender difference in programming block use
When asked why they had added more flip blocks in their programming work, all the male
students responded that such flying tricks could generate creative programming. For example, one boy
said, “Wasn’t it cool to flip the drone? It was so boring to have the drone just flying around.” Or,
as another boy stated: “Flipping was such a dynamic movement. It added value to my work.”
By contrast, some female students viewed flipping as a dangerous movement, whereas others thought
that simpler programming blocks were adequate. For instance, one girl said, “I was afraid that using
the flipping function I might hit something. I only used that block a couple of times.” Or, as another
girl stated: “The other blocks already served my needs. I only wanted my drone to fly a specific
movement, not do special tricks.”
Sustainability 2018,10, 3819 12 of 17
Theme 5: Gender difference in flight patterns
Similar to the results in Theme 4, a gender difference was identified in flight patterns. When male
students discussed their programming works during the interview process, they claimed to have done
their programming work without thinking and gave no specific reasons. One boy said, “It is just what
I did. I could not tell you the reason. Maybe it is my intuition.” Another boy said, “I have no idea.
Probably all male students prefer a wide flying pattern.” Although female students similarly did not
offer detailed reasons, they did hint at concerns regarding safety. One girl stated, “I realized that I
made this pattern only when you pointed it out. Maybe I did not want my drone to hit something.”
Another girl said, “I have no idea about my pattern. But the best reason for it might be that narrow
flight would not affect other classmates’ learning.”
Theme 6: No preference for loop block use
The students were asked about using loop blocks. They were basically unanimous in stating
that both methods achieved the same outcome. In their opinion, traditional block sequencing in
programming work did not create an extra burden on them. Although the loop block reduced the
numbers of blocks, they still preferred to build their blocks in repeated fashion. For example, one boy
said, “I understood the function of the loop block. But I still liked using the traditional way.” Or, as one
girl stated: “I knew that both ways would work. Even though I used a lot of blocks to build my project,
the outcome was still accurate.”
5.5. Instructional Design Problems
Instructional design problems from the pilot and formal stages of the study are summarized
as follows:
Issue 1: Protective measures
The blades of the drone posed a threat to student safety. During the pilot stage of the study,
flying drones often accidently hit some of the schoolteachers and students, directly causing a severe skin
wound. Therefore, creating drone management rules was necessary for student safety. For example,
in the formal stage of the study when students were completing their programming work, they were
required to obtain the instructors’ approval for their drone tests. Only one drone was allowed to
take off at a given moment, and the other students were obliged to be aware of a drone flying in
their surroundings. Although some students may have to wait some time for their drone’s departure,
preventive measures can create a safe learning environment.
Issue 2: Space selection
Originally, the targeted learning setting was a normal-sized classroom. However, after several
tests during the pilot stage of the study, the physical size (i.e., height and width) of the traditional
classroom was found to limit the drone’s flight potential. A spacious room with a higher ceiling such
as an assembly hall or a small sports stadium is a perfect location for instruction in flying drones.
In addition, to avoid wind effects, electric fans or air conditioners in the selected locations should be
turned off when students are ready for drone testing. For example, in the formal stage of this study,
electric fans often affected the accuracy of drone flight movements.
Issue 3: Bluetooth interference
The lightweight drones used in this study were connected to students’ tablet computers via
Bluetooth communications. Because only two drones were used for instruction preparation in the pilot
Sustainability 2018,10, 3819 13 of 17
stage of the study, Bluetooth interference problems did not occur at that time. However, in the formal
stage of the study when 10 students were using tablet computers simultaneously, Bluetooth signals
from the computers could interfere with each other. For example, one student’s tablet computer would
unintentionally connect to a classmate’s drone. To solve this problem, students were requested to
verify that the serial number labeled on the drone matched the one shown on their tablet before testing
their drones.
Issue 4: Programming check
During the formal stage of the study, students performed drone testing without instructors
reviewing their programming work. However, a landing problem often arose because several students
had forgotten to add a landing block, and thus their drones continued to float in the air. For a safe
landing, the students were required to terminate the programming language (Tynker) to stop the
flying drones. Therefore, to avoid potential safety problems the instructors were advised to conduct a
programming check before the drones took off.
Issue 5: Power supply
Testing in the pilot stage of the study showed that the battery life of lightweight drones only
permitted 20 min of flight (in standby mode battery life could be longer), and therefore one battery for
each student was not sufficient for practice. To facilitate learning, each drone was equipped with three
backup batteries during the formal stage of the study. Moreover, although a drone management rule
was created to ensure student safety, accidents such as unexpected wall impacts severely damaged the
blades, thus terminating the drone’s flight functions. The instructors had to prepare a reserve supply
of blades.
5.6. Overall Discussion
The statistical findings demonstrated a significant improvement in young student’s spatial
visualization and sequencing skills over the 6-week educational experiment. Drone programming
could thus have instructional effects on students’ spatial visualization and sequencing skills. Given that
drone programming enabled students to gain knowledge of visual block programming, the results
of this study supported those of Kazakoff et al. [
26
], who reported that using a Lego robot with
visual block programming significantly enhanced young children’s sequencing skills. Moreover,
a mean comparison indicated that the improvement in spatial visualization learning surpassed that of
sequencing, perhaps because the effect of the instructors’ intervention had a greater effect on spatial
visualization. These findings might also be attributed to drone flight movement design, which forced
students to constantly employ spatial thinking to understand 3D geographical locations [
25
].
Several students also indicated similar learning gains in the qualitative findings.
Other findings of this study indicated that gender as a potential variable did not have an effect on
students’ spatial visualization and sequencing; boys and girls demonstrated a similar performance
for each measurement. However, a gender difference was identified in drone programming patterns.
Compared with their female counterparts, male students tended to use bolder patterns in their
programming design (i.e., flip blocks and wide flying). This was fully explained in the qualitative
findings where boys stated that they were more likely to adventurously use unique programming
blocks and design wide flight movements, whereas girls performed their programming tasks more
conservatively, perhaps because of safety concerns. Although the study participants were elementary
school students, these results reflected the findings of another study that identified a gender difference
in programming patterns in a college computer course [43].
Students’ block use preferences showed a specific programming pattern, namely, less use of
loop blocks. Most students preferred to use basic blocks to complete their programming work even
though loop blocks enabled them to reduce redundant blocks and make their programming more
Sustainability 2018,10, 3819 14 of 17
efficient. The reason for this was identified in the qualitative results, in which most of students
stated that they viewed the loop concept as optional because they could use other blocks to achieve
the same purpose. In another study, lack of loop block use was suggested as a possible common
programming style [
44
] in young children. Another programming pattern was that students’ drone
movement design was unrelated to their spatial visualization and sequencing performance. The reason
for this could be that the programming design process enabled them to practice spatial thinking
and programming sequences, resulting in major learning improvements in these two measurements.
Students’ programming work in the last stage of the learning progression model exhibited only
outcomes rather than process.
Students participating in the drone programming program all showed an enthusiasm for
learning, echoing the findings reported by Hussey [
15
] and Wakefield [
16
] on drone use by young
children. Another reason for students’ desire to learn was perhaps a positive comparison between
this program’s innovative curriculum and conventional school learning [
39
]. Drone programming
offered attractive and enjoyable content, whereas normal classroom instruction did not provide such
learning opportunities for them. In addition to learning motivation, learning support is a primary
task in instructional settings. When facing difficulties in the learning process, young children require
instant learning support provided by instructors. Guidance in programming and debugging principles
might thus have served as learning scaffolding [
45
] that constantly decreased students’ cognitive
learning load.
On completion of the two-phase research model, five instructional design problems emerged:
protective measures, space selection, Bluetooth interference, programming check, and power supply.
Relevant solutions were proposed to achieve instructional effectiveness [
40
]. Because two of these
problems, protective measures and programming check, related to students’ personal safety, they must
be emphasized and treated as instructional priorities [
12
]. Other problems such as Bluetooth
interference and power supply directly influenced students’ learning. Without adequate preparation
and support, the pace of instruction and time for programming practice might be greatly compromised.
Regarding space selection, an ample space, particularly one with a high ceiling, could fully develop
the instructional potential of drone use, depending on the available school infrastructure.
6. Conclusions
6.1. Responses to Research Questions
The aim of this study was to investigate the effect of drone use on the development of students’
spatial visualization and sequencing skills and to examine related instructional tasks for drone use in
the classroom. Regarding the first research question, the results of the quantitative analysis confirmed
that drone programming might support the development of students’ spatial visualization and
sequencing skills. In particular, a major learning improvement in spatial visualization was observed.
Regarding the second research question, analysis of students’ programming work and student
interviews revealed preferences and gender differences in programming patterns. Regarding the
third research question, instructor observations and student interviews indicated that students were
motivated to participate in learning activities, but they required constant learning support from
their instructors. The students also perceived learning benefits in these instructor interventions.
Regarding the fourth research question, five major instructional design problems were defined and
appropriate solutions were proposed.
6.2. Research Limitations and Suggestions for Future Studies
Given the nature of the research design, this study had several limitations regarding the
generalization of its findings. First, the study did not form a control group for comparison.
Future studies might enable two groups of students to receive drone programming training
with different instructional strategies and compare their learning effectiveness in terms of spatial
Sustainability 2018,10, 3819 15 of 17
visualization and sequencing. Second, the study’s sample size was small. A larger number of
students might produce more diverse programming patterns. Future studies could also increase the
number of students to explore the gender effect on programming patterns. Third, the study did not
use quantitative measurements to assess students’ computational thinking process. Future studies
could correlate such quantitative information with spatial visualization and sequencing data. Finally,
although the students often demonstrated a desire to learn, their motivation fluctuated considerably
according to the complexity of the learning tasks. Future studies could document changes in motivation
during the three stages of the learning progression model.
6.3. Instructional Implications
Because this study emphasized the use of innovative technology in the classroom, its results could
serve as a reference point for educators involved in science, technology, engineering, and mathematics
or maker education. First, because drone use in the classroom posed a threat to student safety,
instructors might adopt the preventive measures proposed in this study to create a safe learning
environment. Second, in this study one principal instructor and two assistant instructors continually
supported student learning. To facilitate better learning, instructors might also designate students
with strong performance as assistants, because peer assistance could reduce the necessity of learning
scaffolding. Third, the three-stage learning progression model in this study may not fit all learning
scenarios. Depending on technological resources and students’ level of cognitive development,
appropriate modifications of the model could strengthen curriculum integration.
Funding:
This research was funded by Ministry of Science and Technology in Taiwan [grant number:
MOST 105-2511-S-024 -001 -MY3].
Conflicts of Interest:
We declare no conflict of interest. The funding sponsor had no role in the design of the
study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to
publish the results.
References
1.
Agenda 21 & Chapter 36. Available online: http://www.un-documents.net/a21-36.htm (accessed on
8 October 2018).
2.
Teaching and Learning for Sustainable Future Program. Available online: http://www.unesco.org/
education/tlsf/mods/theme_gs/mod0a.html (accessed on 1 October 2018).
3.
Education for Sustainable Development Goals. Available online: http://unesdoc.unesco.org/images/0024/
002474/247444e.pdf (accessed on 8 October 2018).
4.
ICT in Education and Sustainable Futures. Available online: https://www.mdpi.com/journal/
sustainability/special_issues/ICTESF (accessed on 8 October 2018).
5.
Velázquez, F.C.; Méndez, G.M. Augmented reality and mobile devices: A binominal methodological resource
for inclusive education (SDG 4). An example in secondary education. Sustainability 2018,10, 1–14.
6.
Deaconu, A.; Dedu, E.; Ramona, S.; Igret, T.; Radu, C. The use of information and communications technology
in vocational education and training—Premise of sustainability. Sustainability 2018,10, 1–18. [CrossRef]
7.
Amazon Prime Air’s First Customer Delivery. Available online: https://www.youtube.com/watch?v=
vNySOrI2Ny8&t=9s (accessed on 2 January 2018).
8.
Margaritoff, M. Drones in Agriculture: How UAVs Farming more Efficient. Available online: http://www.
thedrive.com/tech/18456/drones-in-agriculture-how-uavs-make-farming-more-efficient (accessed on
4 February 2018).
9.
Branson-Potts, H.L.A. Fire Department Used Drones for the First Time During Skirball Fire. Available online:
http://www.latimes.com/local/lanow/la-me-ln-lafd-drone-skirball-fire-20171214-story.html (accessed on
11 January 2018).
10.
Walsh, K. 7 Fun Ways Teachers Can Use Drones for Teaching and Learning. Available online: http:
//www.emergingedtech.com/2017/10/7-fun-ways-teachers-can-used-drones-for-teaching-and-learning
(accessed on 12 January 2018).
Sustainability 2018,10, 3819 16 of 17
11.
Cenejac, J. 5 Ways to Use Drones in the Classroom: Cherishing Students’ Passion for Technology.
Available online: http://elearningindustry.com/drones-in-the- classroom-5-ways-cherishing-students-
passion-technology (accessed on 11 January 2018).
12.
Carnahan, C.; Zieger, L.; Crowley, K. Drones in Education: Let Your Students’ Imagination Soar;
International Society for Technology in Education: Arlington, Virginia, 2016.
13. Smith, B.; Mader, J. Drones for the science classroom. Sci. Teach. 2018,85, 16.
14.
Hoffert, F. Examining the possibility of using programming language with low-cost drones. In Proceedings
of the 2017 International Conference on Applied Computer and Communication Technologies, Jakarta,
Indonesia, 17–18 May 2017.
15.
Hussey, M. Drones in Woodland Elementary Classroom Soar, Flip and Teach. Available online:
http://www.tampabay.com/news/education/k12/drones-in-woodland- elementary-classroom-soar-flip-
and-teach/2260352 (accessed on 15 January 2018).
16.
Wakefield, J. Robots and Drones Take over Classrooms. Available online: http://www.bbc.com/news/
technology-38758980 (accessed on 16 January 2018).
17. Schaeffer, D.M.; Olson, P.C. Drones in the classroom. J. Comput. Sci. Coll. 2017,32, 85–91.
18.
Carnahan, C.; Crowley, K. Using Drones to Ensure Student Success. In Proceedings of the 2017 Society for
Information Technology & Teacher Education International Conference, Austin, TX, USA, 5 March 2018.
19.
Palaigeorgiou, G.; Malandrakis, G.; Tsolopani, C. Learning with Drones: Flying Windows for Classroom
Virtual Field Trips. In Proceedings of the 2017 IEEE 17th International Conference on Advanced Learning
Technologies, Timisoara, Romania, 3–7 July 2017.
20.
Gerson, B.P.; Sorby, S.A.; Wysocki, A.; Baartmans, B.J. The development and assessment of multimedia
software for improving 3D spatial visualization skills. Comput. Appl. Eng. Educ.
2001
,9, 105–113. [CrossRef]
21. Sorbi, S.A. Developing 3D spatial visualization skills. Eng. Des. Gr. J. 1999,63, 21–32.
22.
Sorbi, S.A. Educational research in developing 3D spatial skills for engineering students. Int. J. Sci. Educ.
2009,31, 459–480. [CrossRef]
23.
Baki, A.; Kosa, T.; Guven, B. A comparative study of the effects of using dynamic geometry software
and physical manipulative on the spatial visualization skills of preservice mathematics teachers. Br. J.
Educ. Technol. 2011,42, 291–310. [CrossRef]
24.
Chou, P.N.; Chen, W.F.; Wu, C.Y.; Carey, R.P. Utilizing 3D open source software to facilitate student learning
of fundamental engineering knowledge: A quasi-experimental study. Int. J. Eng. Educ. 2017,33, 382–388.
25.
Fombuena, A. Unmanned aerial vehicles and spatial thinking: Boarding education with geotechnology and
drones. IEEE Geosci. Remote Sens. 2017,5, 8–18. [CrossRef]
26.
Kazakoff, E.R.; Sullivan, A.; Bers, M.U. The effect of a classroom-based intensive robotics and programming
workshop on sequencing ability in early childhood. Early Child. Educ. J. 2013,41, 245–255. [CrossRef]
27.
Massachusetts Department of Elementary and Secondary Education. Kindergarten learning experience.
Available online: https://www.doe.mass.edu/frameworks/0408kle.docx (accessed on 21 January 2018).
28.
Sarama, J.; Clements, D.H. Building blocks of early childhood mathematics. Teach. Child. Math.
2003
,9,
480–484. [CrossRef]
29.
Zelazo, P.D.; Carter, A.; Reznick, J.S.; Frye, D. Early development of executive function: A problem-solving
framework. Rev. Gen. Psychol. 1997,1, 198–226. [CrossRef]
30.
Fessakis, G.; Gouli, E.; Mavroudi, E. Problem solving by 5–6 years old kindergarten children in a computer
programming environment: A case study. Comput. Educ. 2013,63, 87–97. [CrossRef]
31.
Saez-Lopez, J.M.; Roman-Gonzalez, M.; Vazquez-Cano, E. Visual programming languages integrated across
the curriculum in elementary school: A two year case study using scratch in five schools. Comput. Educ.
2016,97, 129–141. [CrossRef]
32.
Brennan, K.; Resnick, M. New frameworks for studying and assessing the development of computational
thinking. In Annual American Educational Research Association Meeting; American Educational Research
Association: Vancouver, BC, Canada, 2012.
33.
Teaching and Learning for Sustainable Future. Available online: http://www.unesco.org/education/tlsf/
(accessed on 1 October 2018).
34.
ISTE Standards for Students. Available online: https://www.iste.org/standards/for-students (accessed on
1 October 2018).
Sustainability 2018,10, 3819 17 of 17
35.
Amiel, T.; Reeves, T.C. Design-based research and educational technology: Rethinking technology and the
research agenda. Educ. Technol. Soc. 2008,11, 29–40.
36.
Creswell, J.W.; Clark, V.L. Designing and Conducting Mixed Method Research; Sage: Thousand Oaks, CA,
USA, 2007.
37. Patton, M.Q. Qualitative Research and Evaluation Methods, 3rd ed.; Sage: Thousand Oaks, CA, USA, 2002.
38.
Picture-Sequencing Test; Hsin-Yi: Taipei, Taiwan, 2011. Available online: http://store.kimy.com.tw/
category/productdetail.aspx?no=H000000017280 (accessed on 22 October 2018).
39.
Chou, P.N. Skill development and knowledge acquisition cultivated by maker education: Evidence from
Arduino-based educational robotics. EURASIA J. Math. Sci. Technol. Educ. 2018,14, 1–9. [CrossRef]
40. Smith, P.L.; Ragan, T.J. Instructional Design, 3rd ed.; Wiley: Hoboken, NJ, USA, 2005.
41. Aviation Rules for Drones. Available online: https://dronesplayer.com/ (accessed on 1 October 2018).
42. Moustakas, C. Phenomenological Research Methods; Sage: Thousand Oaks, CA, USA, 1994.
43.
Stoilescu, D.; Egodawatte, G. Gender differences in the use of computers, programming, and peer interactions
in computer science classrooms. Comput. Sci. Educ. 2015,20, 283–300. [CrossRef]
44.
Oman, P.W.; Cook, C.R. A Taxonomy for Programming Style. In Proceedings of the ACM Annual Conference
on Cooperation, Washington, DC, USA, 20–22 February 1990.
45.
Jonassen, D. Designing constructivist learning environments. In Instructional-Design Theories and Models:
A New Paradigm of Instructional Theory; Reigeluth, C.M., Ed.; Lawrence Erlbaum Associates: Hillsdale, NJ,
USA, 1999.
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2018 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
... To date, the majority of literature in the field of education mainly focuses on the use of drones by students. A number of researchers noted that students, following their interaction with drones, showed enhanced interest and engagement (Carnahan et al., 2016), critical and innovative thinking (Cliffe, 2019), decision making (Abarca et al., 2017), computational thinking (Bermúdez et al., 2019), increased motivation (Chen et al., 2019), understanding of aviation regulation (Chou, 2018), cross-domain learning as well as positive attitudes towards problem-solving and hands-on capabilities (Niedzielski, 2018). In general, it appears that drones create "an enjoyable learning environment" (Carnahan et al., 2016), enable pupils to explore the world through "bird's-eye view" via use of the camera (Ng & Cheng, 2019) and constitute "one of the most innovative educational tools" (Niedzielski, 2018). ...
... Another characteristic of drones relates to flight autonomy, i.e., the time during which the drone can remain airborne before its battery runs out. Even though the average flight autonomy of a drone for education depends on various factors (e.g., drone size, use of camera, maneuvers, speed, weather conditions, use in an interior or an exterior space), it is at any rate considered relatively small due to the limited capacity of its battery (Chou, 2018). For example, a drone for education can have an average flight time of 8-10 min (e.g., Ryze Tello EDU). ...
... These results show that drones could be used in almost every subject of primary education and possibly by all teachers depending on their interests and specialization. More specifically, all the characteristics of drones relate to Science, Technology, Engineering and Mathematics (STEM) (Chen et al., 2019;Chou, 2018;Goodnough et al., 2019). They can be constructed, assembled, and programmed to fly and collect various data through their technical affordances and sensors (Bermúdez et al., 2019;Carnahan et al., 2016;Ng & Cheng, 2019). ...
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This book brings together a collection of work from around the world in order to consider effective STEM, robotics, and mobile apps education from a range of perspectives. It presents valuable perspectives—both practical and theoretical—that enrich the current STEM, robotics, and mobile apps education agenda. As such, the book makes a substantial contribution to the literature and outlines the key challenges in research, policy, and practice for STEM education, from early childhood through to the first school-age education. The audience for the book includes college students, teachers of young children, college and university faculty, and professionals from fields other than education who are unified by their commitment to the care and education of young children.
... Cliffe (2019), Fung and Watts (2017a), Aji and Khan (2013), and Fung and Watts (2017b) warned about the short battery life of the UAV; so this might influence its flying range and endurance. Furthermore, Chou (2018) reported that there are restriction rules for the flying time and height of the UAV so that learning activities can be impacted. Voštinár and Klimová (2018) claimed that it was not suitable to use UAVs indoor (e.g. ...
... UAVs according to the local policy (Cliffe, 2019;Hodgson & Piovan, 2021). For example, Chou (2018) mentioned that it was illegal to fly any UAVs during their outdoor activities in schools that were located near airports or military institutions. ...
... no instructors reviewed students' programming work and gave feedback) and power supply (e.g. short flight time) (Chou, 2018). It is suggested that the UAV management rules can be created for students' safety, e.g. ...
... Participants gave a positive response after undergoing the activity even though they were less familiar with the work platform provided. Another study from [20] also uses drones as a smart technology in the curriculum where students use visual block programming language. Students highlighted good results when drone programming increased significantly for student learning in spatial visualization sequencing skills. ...
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In this high-technological era, cybersecurity is well-known due to various cybercrimes that happen from time to time. Adversarial thinking, which can be explained as one ability of strategic thinking commonly applied by the hacker, needs to be disclosed to society as one of cybersecurity awareness. Therefore, this study highlights the usage of adversarial thinking in education by adopting the adversarial thinking elements in the experiential learning model. The conceptual framework of adopting adversarial thinking has been developed by using the Matsuo- Nagata learning model 2020. The Matsuo-Nagata learning model has only been applied in the training programs; therefore, to apply the current learning model to the education and cybersecurity field, a new learning model has been revised and adopted with the adversarial thinking aspect. Robotic learning has been chosen as the learning tool for the revised experiential learning model. This study involves three elements of adversarial thinking: analytical, creative, and practical. By analyzing the previous study and the survey results from the expert, the findings show that adversarial thinking is suitable and essential to be adopted in the experiential learning model.
... However, there is a reported 6-weeks course during which high school students carry out the graphical programming of drones within a research methodology formulation with declared competencies. This course did not develop the dynamics of drones nor the simulation of the automatic control system because it was for K-12 education [23]. ...
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Accelerated advances in science and technology drive the need for professionals with flexible problem-solving abilities towards a collaborative working environment. The advances pose a challenge to educational institutions about how to develop learning environments that contribute to meeting the aforementioned necessity. Additionally, the fast pace of technology and innovative knowledge are encouraging universities to employ challenge-based-learning (CBL) approaches in engineering education supported by modern technology such as unmanned aerial vehicles (UAVs) and other advanced electronic devices. Within the framework of competency-based education (CBE) and CBL are the design, implementation, and evaluation of an intensive 40 h elective course which includes a 5-day challenge to promote the development of disciplinary and transversal competencies in undergraduate engineering students whilst relying on UAVs as the medium where the teaching–learning process takes place. Within this credit course, a case study was carried out considering the framework of an exploratory mixed-methods educational research approach that sought a broad understanding of the studied phenomena using various data collection instruments with quantitative and qualitative characteristics. An innovative academic tool was introduced, namely a thematic UAV platform that systematically exposed students to the principles underlying robotic systems and the scientific method, thereby stimulating their intellectual curiosity as a trigger to solve the posed challenge. Moreover, students came up with innovative teamwork-based solutions to a designed challenge while having an enjoyable and motivating time flying drones on an indoor obstacle course arranged by themselves. The preliminary findings may contribute to the design of other CBL experiences, supported by technology applied for educational purposes, which could promote the development of more disciplinary and transversal competencies in future engineers.
... 14 Their uses, at all level, have been widely documented. [15][16][17][18] As part of the "UE24-Automatique" course, the use of a quadrotor is perfectly adapted and allows the cadets to use it completely autonomously. Especially, to increase the autonomy during the course, it has been decided to provide a drone to each team for the entire duration of the course. ...
... For example, some educational practitioners have promoted drones as a platform to enhance teaching and learning processes (Norman, Nordin, Embi, Hafiz, & Ally, 2018). By using drones, Chou (2018) has established a comprehensive curriculum to investigate the impacts of using drones on the development of cognitive skills and sequencing skills (Bermúdez, Casado, Fernández, Guijarro, & Olivas, 2019). The finding revealed a significant relationship between drone application and students' learning improvement (Nordin & Norman, 2018) in both skills. ...
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Proceedings of the International University Carnival on e-Learning (IUCEL) 2021
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Pedagogy issues regarding the LEGO Spike kit remains unknown. The study aimed to investigate students’ engineering design thinking in robot projects. A quasi-experimental posttest with control group was used to answer the research purpose. Participants were two groups of students who participated in the Maker Program at different semesters (experimental: 2021 Fall; control: 2021 Spring). Students were 30 s graders from a public elementary school in Taiwan. The same teacher delivered 8-week program instruction for those students. In the experimental group, some well-performing students were encouraged to orally demonstrate their robot projects whereas students in the control group only focused on creating their projects without a need for a peer demonstration. Upon completion of the experiment, all students received programming and electrical engineering tests. Students’ weekly engineering design behaviors were cumulated to define engineering design performances. The findings indicated that all students achieved a medium-high level on the content knowledge of programming and electrical engineering. In addition, students immersing in peer oral presentation increased engineering design thinking behaviors morn than their counterparts in class.
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