TORONTO, June 26, 2019 /PRNewswire/ -- Recently, the AERA 2019 was held under the
title of "Integrated Application of Technologies to Mathematics
Teaching and Learning" in Toronto,
Canada. Sam Wang, a senior
data scientist at the SRI International, was invited to the summit
and gave a speech titled "Putting Technology to the Test: Efficacy
Studies of an Adaptive System in China" on behalf of Squirrel AI Learning by
Yixue Group, describing to the other participants a wonderful
blueprint of fully utilizing the Internet, AI technology and
high-level educational resources to enhance the personalization of
educational content.
![Sam Wang, a senior data scientist at the SRI International, is making a presentation on behalf of Squirrel AI Learning Sam Wang, a senior data scientist at the SRI International, is making a presentation on behalf of Squirrel AI Learning](https://mma.prnewswire.com/media/929122/Sam_Wang_Squirrel_AI_Learning.jpg)
The host American Educational Research Association (AERA) is one
of the largest U.S. education industry associations, a globally
influential educational academic organization, and the largest
national inter-disciplinary research association. Founded in 1916,
the association is committed to upgrading and disseminating
educational knowledge, encouraging scholars to do research into
education and promoting the improvement of educational and public
services through scientific research.
The AERA Annual Meeting is the world's largest gathering of
education researchers and is
attended by more than 14,000 AERA members, as well as scholars,
policy experts and practitioners from related fields of discipline.
The AERA Annual Meeting is always focused on the showcase of
groundbreaking research and innovations, including studies of all
the educational phases from early education to higher
education.
Felice J. Levine, the executive
director of AERA, talked about the AERA 2019 and said, "The AERA
Annual Meeting is an excellent opportunity for educational
researchers to share important new discoveries and innovations.
These studies and innovations will lead to a continuous
optimization and improvement in educational practices and
policies.
It is worth noting that a number of speeches on digital
technology and higher-order analysis were given at the AREA 2019.
The speech titled "A Bayesian Look at Reliability", given by
Charles Lewis, a professor at
Department of Psychology, Fordham
University, was one of the eight keynote speeches made at
the annual meeting. In the speech, Charles
Lewis discussed the challenge posed to the reliability of
the Bayesian classification algorithm when it was used for modeling
in the education industry. The research project led by Charles Lewis won the E. F. Lindquist Award at
the AREA 2018.
Dr. Lewis expounded the principles of test reliability in simple
terms in his speech. He also explained their similarities and
differences in the CTT and IRT models from the traditional
perspective and Bayesian perspective. Then, he further pointed out,
"Either of the pedagogical testing and measurement theory is better
or worse than the other from the traditional perspective and
Bayesian perspective, but we can deepen our research of this issue
on a larger scale from different perspectives."
As a pioneer in China's
education industry, Squirrel AI Learning attended this grand event
of education and gave a speech titled Putting Technology to the
Test: Efficacy Studies of an Adaptive System in China, drawing high attention from the
attendees. Dr. Sam Wang showed the
rest the difference in teaching effect between the Squirrel AI
Learning system and human teachers in different teaching scenes and
class sizes. The SRI International found in their research that
after using the Squirrel AI Learning system, the students in both
big classes (20-30 students) and small classes (about 3 students)
improved their academic performance more significantly than the
students in the control group.
As we all know, the Internet has produced a subversive impact on
all traditional industries. Like all the other traditional
industries, the education industry has begun to introduce digital
means to improve the educational effectiveness and educational
resource utilization rate.
Subversion usually begins with a response to challenges hard to
overcome by the traditional industries. As we know, teaching and
learning are two sides of an educational activity: there should be
not only high-quality content, but also an individualized learning
plan. However, the traditional education industry is just facing
the following two challenges: prevailing disequilibrium of
educational resources and lack of individualized educational
content.
The revolution in education on the Internet aims to eliminate
the disequilibrium of educational resources first.
Geographical limitations and different levels of economic
development contribute to the difference in teaching strength from
region to region, and many students have no way to acquire
high-quality local education resources. Fortunately, "online
schools" have risen at the historic moment. Academy, Coursera and
New-oriental Teach-on-line, have sprung up quickly and achieved
fast expansion.
However, the MooC as an "online school" has obvious defects. On
the one hand, due to low entry barriers, lack of classroom
discipline management, and shortage of support from a learning
community, learners feel it easy to study online at the beginning,
but they also feel it "easy" to give up learning. On the other
hand, due to unified content of courseware, personalized content or
learning plans cannot be provided for students that have different
knowledge structures and learning capacities. In the end, the two
reasons lead to a low course completion rate of "online education".
A large number of learners give up halfway due to their poor
self-discipline or failure to adapt to the teaching content.
As there is increasing demand for personalized education,
"one-to-one" long-distance education has come into being on the
Internet to solve the contradiction between the demand for
personalized education and the lack of personalized education.
When one teacher teaches one student "face to face" on the
Internet, specific educational services can indeed be offered to
improve the quality. The teacher can adjust the teaching content in
a timely manner according to the student's mastery of knowledge,
and thus provides intensive training for the student. But this
model also has very obvious weaknesses. The first is the teacher's
low teaching ability. In most cases, "one-to-one" teaching cannot
be truly provided in a personalized way, because there are, after
all, only a limited number of high-level teachers, while most
teachers just have average teaching abilities. Second, "one-to-one"
teaching is costly, and one teacher can merely offer a service to
one teacher each time.
So in the final analysis, neither "online school" education nor
"one-to-one" teaching can ameliorate the above two issues, i.e.,
the disequilibrium of educational resources and lack of
individualized educational content. These two challenges can only
be radically resolved with artificial intelligence (AI), e.g., the
machine learning model can be used to meet individualized needs
while raising teaching quality to a high level.
As AI technology has become
increasingly mature in recent years, many industries have begun to
enable the use of AI. Educationally developed countries such as the
USA have achieved many positive
results in using AI for personalized teaching. But Asia, including China, hasn't widely applied AI to the
education industry yet.
Rome was not built in a
day. Adaptive education, which
originated in the USA, has
accurately located the bloodline of the educational reform.
However, due to the imperfection of system functions and the high
requirements for education providers' assessment and teaching and
research capacities, the adaptive education always developed slowly
in the past. However, on the eve of the AI revolution, the
empowerment from AI brightened the future of the adaptive
education.
The AI technology-based adaptive learning system can not only
further intensify stratification, but also clearly identify any
imperceptible change between each two capacity levels. According to
students' real-time learning status, the system can dynamically
adjust the next step of learning content and path, and build a more
complex learning model to provide personalized education on a large
scale.
The world's first AI adaptive education provider Knewton has
offered services to 20 million North American students. RealizeIt,
the largest provider of personalized and adaptive learning products
in the U.S. higher education sector, offers more than 40,000
adaptive courses.
As the first Chinese education provider to use AI for
education, Squirrel AI Learning has achieved remarkable
achievements in primary and secondary education.
Squirrel AI Learning primarily provides AI adaptive learning
programs services for primary and secondary school students.
Squirrel AI Learning has successfully developed an advanced
algorithm-based intelligent adaptive learning engine with complete
independent intellectual property rights. The Squirrel AI Learning
system can work as an expert teacher, but its efficiency is 5-10
times as high as the traditional educational efficiency.
The Squirrel AI Learning system has four main
characteristics:
- Combination of online teaching and offline training center
The core teaching content is
taught, recorded and analyzed on the Internet, while a good
learning environment is created at the offline training center to
enhance the concentration on learning and ensure a reasonable time
schedule.
- Combination of AI learning system and human guidance
The AI intelligent learning system
teaches students in accordance with their aptitude, remedies
weaknesses, timely identifies and helps master fail-to-master
knowledge points, and assists in building a complete knowledge
structure in which different knowledge points are connected to one
another. The human instructor creates a group-learning atmosphere,
adjusts students' attitude towards learning, and guides and
encourages them to improve learning the efficiency.
- Combination of a complete knowledge map and a hierarchical
knowledge point structure
The panoramic knowledge map helps
students master knowledge points and clearly understand the
relationship among different knowledge points. The multi-level
knowledge points can be learned little by little and finally
summarized by students in a scientific and effective way.
- The AI discrimination technology in the intelligent system
Students can clearly see their
current knowledge structure graph with their knowledge application
ability tested. Then the shortest path can be designed using the
analytical model built based on Bayesian Discrimination for an
improvement in students' knowledge level. Moreover, students'
learning path can be adjusted at any time based on feedback from
them so that they can maximize the learning efficiency.
Years of educational practice has confirmed that small class
teaching is of great help to improve the quality of education. In
order to verify the educational effectiveness of the Squirrel AI
Learning system, Squirrel AI Learning organized teaching comparison
testing to confirm whether:
- The Squirrel AI Learning system can achieve a much better
effect in whole class teaching than outstanding teachers.
- The Squirrel AI Learning system can achieve a much better
effect in group teaching (3 students) than outstanding
teachers.
Squirrel AI Learning did a control experiment by choosing 163
students in Grade 8 at a middle school in Sichuan Province to answer the first question.
The students were aged 14-15. The experiment implementer SRI
randomly divided these students into experimental group and control
group, and let them taught by the Squirrel AI Learning system and
outstanding teachers respectively. Each of the students in the
experimental group was equipped with a dedicated computer. The
control group was taught by mathematics teachers that had won an
award in Sichuan Province, with
20-30 students in each class.
Before the experimental group and the control group formally
started learning, the SRI International organized an examination on
the knowledge points to be learned in order to identify each
group's knowledge level.
After the test ended, the control group and the experimental
group studied for 5 hours and 50 minutes in the following three
days under the same conditions, including learning duration, rest
duration and class activities schedule. After the end of learning,
the SRI International tested the students' mastery of knowledge
points again. The test paper was designed and reviewed by
outstanding teachers who were not involved in the testing. 20 core
contents totaled 100 points.
In order to avoid interference from other factors, the SRI
International also collected basic information including the
students' age and gender and their parents' education level.
The test results show that for question 1, i.e., standard whole
class teaching, the grades in the experimental group increased by
1.58 points averagely, while that in the control group increased by
9.11 points on average. An analysis of covariance confirms that
there is a statistically significant difference between the two
groups.
For question 2, the SRI International adopted an almost same
experimental method and selected some students from Shandong Province and divided them into the
experimental group and control group. The students in either group
studied for 8 hours and 30 minutes. There were 3 students in each
small class.
The experimental results show that the grades in the
experimental group increased by 6.96 points averagely, while that
in the control group increased by 2.45 points on average. An
analysis of covariance confirms that there is a statistically
significant difference between the two groups.
The above control experiments clearly show that the Squirrel AI
Learning system has obvious advantages for both the traditional
class teaching and the small class teaching that boasts high
learning efficiency. One of the advantages is that grades can be
increased significantly, and the other is that it doesn't matter
whether the teacher's teaching level is high or low. With the aid
of the Squirrel AI Learning system, the government and educational
institutions can quickly and inexpensively promote the best
educational resources to any part of the country that can access
the Internet. This will greatly promote educational fairness,
improve the educational efficiency and increase the service
efficiency of educational resources, and lay a solid foundation for
the AI technology in comprehensively reforming the education
industry.
Squirrel AI Learning founded a Yixue AI Lab with SRI as the
primary research partner two years ago, and the AI laboratory is
committed to carrying out the work based on the SRI International's
unique advantages in AI and educational technology. Currently, the
lab is making a splash in three key collaborative areas: 1) core
adaptive education model and technology; 2) natural language
processing and semantic analysis, aimed at realizing the virtual
personalized assistance (VPA) function and using dialogue-based
interface to diagnose students' errors and receive feedback on AI
from instructors and students. 3) The multimodal integrated
behavioral analysis (MIBA) research enables Squirrel AI Learning to
understand students' emotional and psychological states and better
predict their behavior and in a adaptive learning environment, and
provide signals for human instructors to take intervention, remedy
and support measures or remind, recommend, and relax students
through the system.
Squirrel AI Learning is a leading Chinese AI education
application provider, and is active
in attending global education conferences. At the AERA Summit, it
briefed North American education experts on the fast development
and latest research results achieved by the Chinese education
industry, and conducted in-depth exchange of views with the North
American education experts present, especially the experts in data
science and AI application.
We believe that with the help of the AERA, we will effectively
promote the development of the Chinese education industry and the
implementation of advanced educational technologies in China. Driven by advanced AI enterprises
including Squirrel AI Learning by Yixue Group, China's education industry will soon fly up on
the wings of AI.
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SOURCE Squirrel AI Learning