ADDIE_01.pptx

Developing an intelligent virtual
reality interactive system based on
the ADDIE model for learning pour-
over coffee brewing
Titin Rahmiatin
Riris Marito Tamba
Chao-Yun
JULY 2021
COMPUTERS AND EDUCATION: ARTIFICIAL INTELEGENT

Presentation
Timeline
INTRODUCTION
LITERATURE REVIEW
THE DEVELOPMENT OF AN INTELLIGENT VR
INTERACTIVE SYSTEM BASED ON THE ADDIE MODEL
CONCLUSIONS, LIMITATIONS, AND FUTURE WORK
JULY 2021

Are you familiar with this technology?
https://www.youtube.com/watch?v=bdUzALQVNYM&t=2150s

What is Head-
mounted-display
(HMD) virtual
reality (VR)
?
has been widely used in education since 2016 in
applications such as HTC Vive, Oculus Rift (Calvert &
Abadia, 2020), and Google cardboard (Lin et al., 2019)
VR structures a simulated environment in virtual space
and provides users with a high-quality and immersive
experience (Makransky & Lilleholt, 2018)
Past researches
The differences in learning between traditional teaching and
HMD VR teaching, and the results have shown that HMD VR
enhances students’ learning performance, interest (Ray & Deb,
2016), and germane cognitive load (Lin et al., 2019).
Alhalabi’s (2016) study indicated that HMD VR improved
learning performance and interest more than other VR
systems
From 2000 to 2017, the ratio of 18- to 24-year-old individuals who drink
coffee every day grew to 50 % in the U.S. (FONA, 2017), and 79 % of
coffee drinkers prepare their coffee at home (National Coffee
Association, 2018).

https://www.msfttechdays.com/a-brief-overview-of-
artificial-intelligence/
Making pour-over coffee emphasizes the
manipulative ability to maintain the high-
quality flavor of coffee. Because the
extraction pressure, time, water-to-coffee
ratio, and many steps need to be controlled,
the person who makes coffee must practice
and take the time needed.
Learners have used HMD VR to train their manipulative behaviors,
which is an effective way to acquire knowledge and transfer skills to the
real world (Kahlert et al., 2015). However, learners exhibit individual
differences, which may mean that traditional education is not suitable
for everyone (Chen et al., 2020).
Compared to adaptive systems, intelligent
systems provide more personalized
information for evalu- ating the learning
requirements as well as personalized
feedback based on artificial intelligence (AI)
(Vandewaetere & Clarebout, 2014).
AI can simulate human reasoning,
information processing, and
decision making (Colchester et al.,
2017). It can help intelligent
systems collect more accurate and
objective data to perform extensive
learning evaluations. One-to-one
tutoring is also an intelligent system
feature (Luckin et al., 2016).
https://weaverscoffee.com/blogs/blog/how-
to-make-the-perfect-pour-over-coffee
JULY 2021

The present study attempts to develop an
intelligent VR interactive system based on the
ADDIE model that integrates an intelligent system
and HMD VR to monitor the behaviors of
students learning pour-over coffee brewing.
The analysis, design, development, implementation, and evaluation
(ADDIE) model is a common ISD that can create an efficient learning
environment and improve learners’ performance (Branch, 2010). The
ADDIE model provides systematic phases to guide instructors to ideate
and develop the instructional system (Gagne et al., 2005). Stapa and
Mohammad (2019) and Ibrahim (2015) indicated that the ADDIE model
is an element of other ISDs.
https://www.google.com/search?q=addie+model&rlz=1C5CHFA_
enTW971TW971&source=lnms&tbm=isch&sa=X&ved=2ahUKEwix
9pX6_OHzAhXZBIgKHQ9IArkQ_AUoAXoECAEQAw&biw=1440&bih
=789&dpr=2#imgrc=jGXLhrE_xmYxuM
COMPUTERS AND EDUCATION: ARTIFICIAL INTELEGENT JULY 2021

AI and intelligent feedback on behavior
general AI
narrow AI
Purpose
The European
Commission
(2019)
Wearable technologies can construct an environment that enhances
multiple scenarios and sensors in learning activities (Ciolacu et al.,
2018).
Enable AI to analyze more authentic and multiple data to create
feedback
VR techniques are used to simulate the real world and display
visual feedback, which allows learners to be close to the actual
learning environment

The development of
an intelligent VR
interactive system
based on the
ADDIE model ADDIE
Phases
JULY 2021

Fig. 1. The process of pour-over coffee brewing.
JULY 2021

JULY 2021
Fig. 2-a. The decision tree of the intelligent VR interactive system.
Note: The blue line indicates the path to the full module.

JULY 2021
Fig. 2-b. The decision tree of the intelligent VR interactive system.
Note: The blue line indicates the path to the full module.

Fig. 3. HTC Vive HMD and controllers.
JULY 2021

Fig. 4. The mechanism of the intelligent virtual reality
interactive system.
JULY 2021

Fig. 5. Six steps of the intelligent VR interactive system.
JULY 2021

Fig. 6. The interface of the intelligent feedback in the coffee
tool introduction step.
JULY 2021

Fig. 7. The interface of the educational video.
JULY 2021

Fig. 8. The pour-over coffee unit.
JULY 2021

Fig. 9. The final score and detailed report.
JULY 2021

Fig. 10. The experimental design .
JULY 2021
*45 (43.7 %) were male and 58(56.3 %) were female,
*the average age was 22.41
*48 (46.6 %) engineering and computer science、55
(53.4 %)humanities and social sciences
*59 (57.3 %) undergraduate students、42 (40.8 %)
master’s students、2 (1.9 %) doctoral students.
There were 4 questions in the open-ended
questionnaire, including the advantages and
disadvantages of the system, suggestions for
correcting the disadvantages, and other
suggestions.
3.4. Implementation phase

JULY 2021
3.4. Implementation phase & 3.5Evaluation phase
Help the research team understand the advantages
and problems to improve the system and obtain
suggestions based on learners’ perceptions.

JULY 2021
3.5. Evaluation phase
The learners who used the intelligent VR interactive system could improve their
knowledge of pour-over coffee brewing. The learners commented that the
advantages of this system were as follows:
“Intelligent feedback can remind me of the behavior any time that assists me in
learning”;
“The content of intelligent feedback is clear, and it benefits learning by myself”;
“The objects and scenes are exquisite”;
“Using this system, I can experience VR”;
“The steps of pour-over coffee brewing are easy to understand, and I can operate
the process in person”;
“I do not fear making mistakes, and the VR environment lets me feel safe”; and
“I can use it to practice, and the frequency is unlimited.”

Fig. 12. The HMD VR scene.
JULY 2021

JULY 2021
3.5. Evaluation phase
The learners revealed that the red
words in the intelligent feedback
were fuzzy and unclear, and the
content could provide more
information to explain the reason
for the steps.
In the pour-over coffee unit, the
learners also hoped to understand
their scores for each unit.
we used magnified words to
replace the red words and added
a button for detailed intelligent
feedback to allow the learners to
select information.
Added the functions of calculating
the unit scores and error step
monitoring to the pour-over coffee
unit.
optimize

JULY 2021
3.5. Evaluation phase optimize
The trigger and collision sensors
were too sensitive, which made it
easy for objects to move and fall
over.
The learners thought they needed
more time to familiarize themselves
with the VR environment, and the
note function could help them
remember the contents.
We revised the weight of the objects and
adjusted the sensor area to make the
experience closer to the real-life experience.
Moreover, the distance between objects was
increased to avoid collision.
We also added a button that allowed
the learners to decide when to start to
count time, and we may add speech
recognition to the note function in the
future.

JULY 2021
3.5. Evaluation phase optimize
The learners still needed
more experience to
improve their acceptance
of the VR environment.
we encouraged them to attend VR ac-
tivities and practice easy tasks as useful
strategies to help them become
familiar with the VR system.

JULY 2021
4. Conclusions, limitations, and future work
The ADDIE model is an ISD flow that can help
instructors develop learning systems based on participants’
learning requirements to achieve teaching objectives.
When learning behaviors are incorrect, intelligent
feedback reminds learners of strategies to help them
revise their behaviors.
After completing the learning activity, the learners receive a
learning report and final score to help them understand their
learning outcome.
Meaning of
education

ADDIE_01.pptx

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