Technology-based Interdisciplinary Approaches to Accelerated
Learning of Mathematics
Aija Cunska
Socio-Technical Systems Engineering Institute, Vidzeme University of Applied Sciences, Cesu 4, Valmiera, Latvia
Keywords: Mathematics Learning, Interdisciplinary Approaches, Technology-based Learning.
Abstract: As technology enters everyday life more quickly and purposefully, the education system is also becoming
more accessible and efficient. In 2020, during distance learning in Latvia general education schools, based on
a survey of the Latvian Ministry of Education and Science, 18 main problems were identified that most
directly relate to learning mathematics and require a change in teaching strategies and approaches. These
problems raised much debate and led to think about the need for a more efficient education system in the
future, where close cross-sectoral cooperation with an interdisciplinary approach can make a new
contribution. The research question is: What interdisciplinary digital technology-based approaches stimulate
students' interest in learning maths, motivate them and improve attitudes in the long term? The aim of the
study is to point out to educators, policy makers, industry entrepreneurs and researchers the necessity for
collaborative and interdisciplinary approaches for accelerated learning in mathematics in general schools. In
the future this will contribute to the development of AI solutions and a quality support system for mathematics
teachers. The study identifies and describes eight technology-based interdisciplinary approaches to
accelerated learning of mathematics that can make mathematics a more accessible and meaningful subject.
1 INTRODUCTION
We live in a rapidly changing world and face
increasingly global and complex challenges on a daily
basis, such as income disparities, environmental
problems, migration issues, organized crime and
more. These complex problems cannot be solved in
isolation from the perspective of individual sectors.
Complex problems require an interdisciplinary
approach. We are living in an unprecedented period
of history, when the Covid19 pandemic is demanding
rapid changes in many aspects of our lives, and this is
especially true in the education sector. In March
2020, schools were closed almost overnight and till
now were available mostly online. And it became
clear that in the age of Artificial Intelligence (AI),
with the faster and more targeted entry of technology,
the education system will change radically in the
future and will never be the same again. These
changes have raised much debate and led
policymakers, researchers and educators to think
together about the necessity for a more efficient
education system in the future that meets the
requirements of the Fourth Industry, providing
students with tomorrow's jobs and eliminating any
inequalities.
One of the most sensitive and important subjects
in schools is mathematics, which is the basis of many
professions. If students are well acquainted with
mathematics, then in the future they will have better
access to many fields, such as finance, economics,
engineering, IT, medicine and others. Mathematics
must keep pace with technological advances such as
AI, robotics, virtual reality, big data analytics, 5G
data transmission, 3D modeling, genetic engineering,
and more. Today, technology is developing much
faster than general education, leading to uncertainty
and social tensions, also known today as the digital
gap. Only when the curve of the general education
system intersects the curve of technological
development, social tensions will decrease and the
well-being of society increase (OECD, 2019).
2 PROBLEM STATEMENT
It is written in the research of Professor Zanda
Rubene of the University of Latvia that the current
114
Cunska, A.
Technology-based Interdisciplinary Approaches to Accelerated Learning of Mathematics.
DOI: 10.5220/0010473901140121
In Proceedings of the 13th International Conference on Computer Supported Education (CSEDU 2021) - Volume 2, pages 114-121
ISBN: 978-989-758-502-9
Copyright
c
2021 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
target audience of schools is “Generation Z” or digital
age children born between 2001 and 2015, whose
everyday life is fully merged with modern
technologies that read little printed text, have visual
world perception, accept AI solutions, have
insufficient social skills, are sensitive to criticism, are
over-cared for and grow up in a child-centered society
(Rubene, 2020).
Our challenge is to create a digitally based
education system and support so that social tensions
do not increase. Therefore, outdated books,
uninteresting environment and inert teachers will not
seem attractive to the younger generation. Researcher
A. Persico has pointed out that the strategies and
methods of teaching mathematics that were popular
several years ago are now being replaced by more
effective research and Big Data-based methods aimed
at making mathematics a more accessible and
meaningful subject (Persico, 2019).
During distance learning in Latvia general
education schools in 2020, based on information in
interviews and media, focus group discussions and a
survey of the Latvian Ministry of Education and
Science (IZM, 2020), the author identified 18 main
problems most directly related to mathematics and
changing strategies and approaches, and supporting
technology, in particular AI:
Lack of computer equipment and data
transmission for both schools and households,
Lack of digital skills for both teachers and
students,
Disproportionate involvement of parents in
ensuring the learning process,
Different effects on urban and rural schools, on
talented and less able pupils,
Lack of a unified methodology for the use of
technology in the teaching process of
mathematics,
Lack of a unified system and digital platform for
communication and solving various tasks,
In the effort to ensure quality, part of the topics
of mathematics remained untaught,
Inability to plan time, anxiety and stress for both
students and teachers,
Lack of motivation, encouragement and support
for both students and teachers,
Lack of patience for students to read and
understand math problems independently,
Teachers’ suspicions about students' honesty in
solving math problems independently,
Lack of explanation by teachers for especially
more complex mathematical tasks,
Lack of socialization for both students and
teachers,
Too much time for teachers to provide feedback
and correct work,
Overloading of teachers in preparing for digital
online lessons, looking for more creative tasks,
creating more options and correcting students'
work,
Lack of interdisciplinary approaches and
activities in nature,
Passive lifestyle at home and lack of sports
activities,
Lack of cooperation between education and IT
professionals to create innovative solutions and
reduce the tensions created by digital
technologies.
Teaching higher mathematics to students of the
Faculty of Engineering of Vidzeme University of
Applied Sciences in a 3-year period (2018, 2019 and
2020), the author surveyed 253 students to find what
their main interests are, which occupy a large part of
their lives and make their daily lives happier and more
creative. Students were able to provide answers in a
free-form form, and the summary provided a daily
student profile (Figure 1) that accurately
demonstrated the necessity of interdisciplinary
approaches to learn math with interest and pleasure as
a creative and multidimensional subject.
Figure 1: IT specialty freshman students interest profile.
As shown in Figure 1, 62% of students are
interested in sports, 42% of students are interested in
Information Technology, 30% of students are
interested in music, 21% of students are interested in
literature and poetry, 17% of students are interested
in traveling and outdoor recreation, 15% of students
are interested in video games, 11% of students are
interested in cars. Students are also interested in art
and drawing (11%), dance (8%), garden and field
work (8%), dogs and cats (8%), photography (8%),
social sciences and history (8%). Other student`s
interests include: handicrafts (6%), logic puzzles
(4%), films (4%), cooking (2%), languages (2%),
theaters (2%), self-improvement (2%).
Technology-based Interdisciplinary Approaches to Accelerated Learning of Mathematics
115
The research question is what interdisciplinary
digital technology-based approaches stimulate
students' interest in learning math, motivate them and
improve attitudes in the long term?
The aim of the study is to point out to educators,
policy makers, industry entrepreneurs and researchers
the necessity of collaborative and interdisciplinary
approaches to accelerated learning in mathematics in
general schools. This will in the future contribute to
the development of AI solutions and a quality support
system for mathematics teachers to stimulate the
emergence of innovative learning approaches and
enable mathematics to be taught as a creative and
multidimensional subject.
3 METHODOLOGY
The study is a compilation of current information and
many years of experience with an interdisciplinary
approach, and the methodology includes:
3-year student survey (2018, 2019 and 2020) of
253 first-year students of Vidzeme University of
Applied Sciences, who come from the whole
Latvia;
Compilation, analysis, comparison of the survey
results and creation of a student's daily interest
profile, which shows the necessity of
interdisciplinary approaches;
A selection and brief description of eight
technology-based interdisciplinary approaches
based on experience, 30 years of mathematics
lessons, teacher success stories from around the
world and expert advice;
Qualitative research methods (observations, semi-
structured interviews, focus groups, secondary
research) to explore the views and experiences of
pupils, teachers, students, parents and industry
professionals during distance learning through
daily conversations, information in the media,
success stories, social media profiles;
Primary data, so as to reveal the problems of
distance learning, the Ministry of Education and
Science of Latvia (IZM) in cooperation with the
company Edurio surveyed 4662 teachers, 8352
parents, 10177 students in May and June, 2020
(IZM, 2020).
4 THEORETICAL FRAMEWORK
4.1 Interdisciplinary Approach
In the field of education, the word "interdisciplinary"
has been around for years. Several studies (Kim,
2020; AldertKampAdvies, 2017; RSE, 2020) indicate
that interdisciplinary learning is innovative, attractive
and exciting, as well as driving 21st century education
reforms. Interdisciplinary learning is a way of
learning and thinking that is based on several
disciplines in order to acquire new knowledge and
skills. For interdisciplinary training to be effective,
researchers (McPhee et al., 2018; RSE, 2020)
emphasize the following framework conditions: 1)
interactivity of different fields, 2) teamwork and
cooperation between people, 3) internship in relevant
fields in the workplace, 4) breadth of knowledge and
skills, 5) creativity and curiosity, 6) constant access
to knowledge and lifelong learning, 7) changes in
school curricula , 8) support for teacher education and
development, 9) digital and social skills.
4.2 Accelerated Learning of
Mathematics
Our brains are adaptable, and when students learn or
change their approach to learning, incredible
developmental results can be created. In recent years,
a new science has developed, neuroplasticity, which
specifically studies improvements in brain function
and emphasizes that brain function can and should be
improved at any age (Boaler, 2019). Based on
research (Accenture, 2018; Area9, 2020; Boaler,
2019; Duval, 2019), seven basic principles can be
identified that significantly improve and accelerate
the learning of mathematics:
For growth to take place, the learning process
must be regular and continuous;
Mistakes and error correction improve the long-
term sustainability of mathematical skills;
Positive communication from parents and
teachers, which inspires faith in the student's
strengths, is especially important for promoting
growth;
Applying an interdisciplinary approach activates
neural pathways and learning in general;
Open and creative math problems are important,
which promote deeper learning and retain
attention;
Meaningful collaboration and exchange of ideas
accelerates neuronal flow and improves learning.
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That's why group and project work is so
important in math lessons.
There is a strong correlation between memory and
time, and by repeating the subject, students are
able to learn mathematics much faster.
Neuroscientists (Boaler, 2019; Duval, 2019) point
out that the knowledge we currently have about brain
function is so important that it should change the way
we teach students and run schools. Our brains have a
tremendous ability to grow and change at any stage of
life. This is demonstrated by a study of black cab
drivers in London, which showed that extensive and
complex spatial training has led to a significant
increase in the amount of brain hippocampus in
humans, which is important for all spatial and
mathematical perceptions (Maguire et al., 2000). Taxi
drivers in London must undergo extensive training,
learning how to navigate between thousands of places
in the city. This training is colloquially known as
“being on The Knowledge” and takes about 2 years
to acquire on average. To be licensed to operate, it is
necessary to pass a very stringent set of police
examinations (Maguire et al., 2000). Similarly,
neuroscience researchers (Coyle, 2009; Duval, 2019;
Moser et al., 2011) confirm that the best time for brain
growth is when people work on challenges, make
mistakes, correct them, fight, and move on. But
teachers usually do their best to make students' work
easier by breaking down problems into smaller tasks,
or by giving answers in front of them, or by
facilitating the content of teaching. As another
important piece of evidence for neuroscience,
researchers (Boaler, 2016; Boaler et al., 2016;
Menon, 2015) point out that five impulses act on the
brain when working on math problems, two of which
are related to visual perception (Figure 2). This leads
to the conclusion that brain connections will be much
more productive if mathematical tasks if they are
designed as visible interdisciplinary combinations of
numerical expressions and images.
Figure 2: Brain networks for mental arithmetic (Duval,
2019).
4.3 Artificial Intelligence
A study (Guo & Han, 2020) indicates that AI is a
cross-disciplinary discipline that encompasses
several disciplines, such as neuroscience,
psychology, mathematics (including statistics),
information science, and computer science. Today,
AI, represented by deep data-based learning, is
developing rapidly and is widely used in many fields.
It is believed (Southgate et al., 2019) that AI
algorithms have existed since the late 1970s, but their
widespread use with the available computing power
in the world and modern AI chips began only 5-7
years ago. AI is a term used to describe a set of
computer systems and computer programs that use
human-like thinking features to perform tasks. AI
systems are able to analyze images and videos, listen
to sounds, understand and synthesize language,
predict exchange rate fluctuations, predict electricity
consumption and perform many other tasks that only
humans have been able to do so far. If more and more
new AI solutions appear in production (for example,
in Latvia company Balticovo the quality of eggs is
analyzed with the support of AI, before the eggs reach
the final tests), then in school education AI is still at
an early stage of development.
5 FINDINGS
Based on the identified problems during distance
learning, neuroscience research and pedagogical
success stories, the following technology-based
interdisciplinary approaches to accelerated learning
in mathematics can be suggested:
5.1 Contextualizing: Mathematics
through the Prism of History
Research (Nikitina & Mansilla, 2003) indicates that
contextualization is a review of mathematics and
science in history. It shows the connections between
the theories of science and mathematics and their
historical and cultural roots. The historical
foundations of a particular mathematics topic can
serve as a core for a better understanding and more
effective acquisition of the topic. In the lessons, it is
valuable to create a link between the natural sciences
and the humanities by creating an interdisciplinary
link. For several years now, in the course of studying
applied mathematics with students, studying specific
topics, we look at the history of the origin of this
topic.
Technology-based Interdisciplinary Approaches to Accelerated Learning of Mathematics
117
A good example of this approach can be seen by
studying the topic of solving systems of linear
equations with the Gaussian method, when students
find the answers to many mathematically mediated
questions: Why is the ingenious German scientist
Karl Gauss called the King of Mathematicians and the
Innovator of Science? How can I count the numbers
from 1 to 100 the fastest? How to divide a circle into
equal parts using a circle and a ruler? How did
number theory become science? How can astronomy
solve complex mathematical problems? What are
trigonometric or Gaussian sums? How did the surface
theory for the development of geodesy come about?
How did the unit of measurement “gauss” in physics
come about? The example shows that in one lesson,
mathematics can successfully meet history, science,
art, astronomy, astrology, geography and physics to
stimulate students' interest in real applications of
mathematics. The strength of this approach is the
creation of a cultural-historical reference, which
forms a strong basis and support for the development
of students' personal knowledge of mathematics.
5.2 Problem-Centering Approach:
Applying Math and Science to
Solving Real-World Problems
Research (Biccard & Wessels, 2011) indicates that
problem-focused approaches give students the
opportunity to explore mathematics for themselves
and offer sensible solutions. All attention in the
classroom is focused on the problem to be solved, as
a result of which there is an active discussion both
among the students and between the teacher and the
students. In addition, these types of classes can take
place in nature, outside classrooms, using digital
technologies and other aids (maps, tape measures,
rulers, compasses, measuring instruments,
thermometers, etc.).
The strength of this approach is personal
involvement, which increases motivation and
interest. Leading a math group for 3rd to 7th grade
students during the Covid19 pandemic, when distance
learning was identified and students mostly learned
from home, we developed 10 sets of tasks that
encouraged students to go to nature to find the
information they needed and make calculations
independently.
For example, one of the tasks was as follows: A
number is called symmetric if it can be read equally
from the right and the left. There has been one
important symmetrical year in the development of the
Kalnamuiža park territory. Find this year on the
information board of the park territory. Name the next
symmetric year. Calculate the difference between the
two symmetric years. Is the difference a symmetric
number? If not, can the digits make a symmetric
number and which one?
5.3 Visualization: Combinations of
Mathematical Numbers and Images
It is said that a picture is worth a thousand words. This
is especially true in mathematics, where an image or
some other type of visual model can be useful in
describing a mathematical idea (Tenannt, 2006). Over
the last twenty years, with the development of
computer visual imaging capabilities, a new field of
mathematics called visual mathematics has emerged.
Especially for younger students, it is important to
work with constructions and colors. In this way,
students can better see how planes and three-
dimensional shapes are formed and how formulas
work. Today, many students have a visual perception.
They learn the substance best when they can see what
is happening, and a non-visual approach can even
hinder their efforts to solve the problem.
A good example of a visualization strategy for
learning mathematics is the famous Königsberg
“bridge walking” problem, which can be easily
explained by creating a graph diagram as a visual
representation of the situation.
5.4 Active Approach: Mathematics in
Step with Sports
Parents, educators and health professionals have
pointed out that today's children do too little exercise,
which is further exacerbated by distance learning at
home. It is well known that without movement a child
cannot grow up healthy. The more and different
movements a child has, the more active the brain is
and the more intense intellectual development takes
place. The movement creates emotional well-being
and improves perception. Pre-school and primary
school teachers in particular have given a lot of
thought to developing an interdisciplinary approach
between sports and maths lessons.
But the most innovative solution has been created
by the Canadian technology company
(https://play-lu.com/). It has developed an interactive
area that uses light, sound and video effects to
transform any gym into an engaging and
comprehensive learning environment. is a smart
space that understands the behavior and interaction of
the people in it in real time. Using information from
ceiling-mounted 3D cameras, students can learn math
from wall-mounted tasks in sports.
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5.5 Parallel Approach: Mathematics in
Combination with a Foreign
Language
In Latvian schools, English is mostly studied as the
first foreign language and German or Russian is
chosen as the second foreign language. Taking into
account that teachers often lack digital mathematics
tasks and worksheets in Latvian, they search for them
on the Internet in foreign languages. In this way, an
interdisciplinary approach is promoted while learning
mathematics and a foreign language. Open tasks can
be mastered in this way especially productively. A
study (Pehkonen, 1999) indicates that tasks are
considered open if their starting or target situation is
not specified. Open problems usually have more than
one solution and can be accomplished in more than
one way. This leaves students free to tackle the task
and allows them to use different ways of thinking.
The approach works very well in mixed classrooms,
where the level of knowledge of the students is from
the lowest to the highest, because everyone can
provide answers according to their knowledge and
skills. The teacher has the opportunity to find tasks,
the simplest of which are possible for all students in
the class, but higher levels of difficulty challenge the
abilities of the most talented students.
A good example of an open problem strategy in
mathematics lessons is the task: 10 participants come
to the seminar, and each shakes hands with each other
exactly once. How many handshakes have occurred?
There is only one answer - and it is 45, but there are
at least seven methods of solving: looking at all
possibilities, with the help of graphs, with the help of
visualization, with the help of a table, with the method
of mathematical induction, with combinatorial
formulas. Finally, students can be asked to find a
general case for the task.
5.6 Modeling: Math Applications
Not all students love math at first glance. To some it
may seem tedious and complicated, especially if only
theory, formulas and methods are taught. Math
lessons can be made more interesting and digitally
engaging with apps that can be found on the Internet
for free and for different ages.
The following applications, for example, will
provide an interdisciplinary and visually appealing
approach between mathematics and technology
lessons: Mathspace (https://mathspace.co/us),
Buzzmath (www.buzzmath.com/en-us/), CK 12
(www.ck12.org), Shapes 3D (www.mathsisfun.com),
Khan Academy (www.khanacademy.org), Photo
Math (photomath.app), GeoGebra (www.geogebra.
org), etc. In turn, the application of mathematics and
modeling will be helped by more professional
programs, such as MATLAB (www.mathworks.com)
or Wolfram | Alpha (www.wolframalpha.com).
5.7 Coding and Programming: Math
through Logic and Algorithms
Coding and programming are great helpers and
powerful methods for students to better understand
mathematics. For example, first-year students of the
Faculty of Engineering learn applied mathematics
much more quickly and train algorithmic thinking if,
in parallel with theoretical lessons, the functions of
the mathematics math module of the Python
programming language are mastered. Primary school
students, on the other hand, become much more
interested in mathematics and develop logical
thinking more deeply if they attend robotics lessons
and are able to write working codes for robot
movements without errors.
5.8 Artificial Intelligence: Synergy of
Mathematics and Neuroscience
The highest point of the interdisciplinary approach is
AI solutions that promote socialization, quick
feedback, interactivity, involvement, multiple
repetition, generation of different tasks according to
each student's individual abilities. Research in the
new field of neuro-education (Bidshahri, 2017;
Wilson & Conyers, 2013) emphasizes that, in
collaboration with AI, individual brain activity data
can be used in the future to understand each student's
strengths and weaknesses and make math learning
much faster, deeper and more personalized. AI and
mathematics have the strongest synergies, as AI is
based on mathematics (linear algebra, statistics,
probabilities, logic, etc.) and AI-based solutions can
be successfully used to learn math faster.
Researchers (Perera & Aboal, 2019) describe an
example where an online adaptive learning solution
called “Mathematical Adaptive Platform” (PAM) has
been developed in Uruguay, the content of which is
adapted to the national mathematics curriculum.
PAM provides personalized feedback according to
each student's skill level, based on an analysis of the
student's experience. PAM provides assistance to
students through more than 25,000 differentiated
tasks and 2,800 feedbacks to explain the solution to
each task.
Technology-based Interdisciplinary Approaches to Accelerated Learning of Mathematics
119
6 CONCLUSIONS
As technology enters everyday life more quickly and
purposefully, the education system is also becoming
more accessible and efficient. And teaching of
mathematics in general schools must keep pace with
technological advances, with the result that our task
is to create a digital technology-based education
system that does not increase social tensions and
inequalities.
In order to make school mathematics a more
accessible and meaningful subject, technology-based
interdisciplinary approaches are needed, which are
clearly indicated by the following trends:
the current target audience of schools is
“Generation Z” or children of the digital age,
born from 2001 to 2015, whose everyday life is
fully merged with modern technologies and AI
solutions (Rubene, 2020);
former teaching methods are being replaced by
more effective research and Big Data-based
methods (Persico, 2019);
currently (especially during distance learning in
2020) technologies have different effects on
urban and rural school students, talented and less
able students;
distance learning points to the necessity for
interdisciplinary approaches that promote sports
and outdoor activities;
distance learning points to the lack of
cooperation between education and IT
professionals in order to create innovative
solutions and reduce the tensions created by
digital technologies;
the student's daily interest profile modeled in the
research (Figure 1) indicates the desire to learn
mathematics in a modern way, with interest and
joy as a creative and multidimensional subject;
neuroscience researchers (Boaler, 2019; Duval,
2019) point out that the knowledge we currently
have about brain function is so important that it
should change the way we teach students and run
schools. Brain connections will be much more
productive if mathematical tasks are designed as
visible interdisciplinary combinations of
numerical expressions and images;
one of the most beautiful aspects of mathematics
is its many facets, when ideas, problems and
solutions can be represented in several visible
ways, for example, with numbers, algorithms,
codes, visual images, tables, models, graphs, etc.
A study (Guo & Han, 2020) indicates that AI itself
is an interdisciplinary discipline that combines
several disciplines, such as neuroscience,
psychology, mathematics, big data analytics, and
computer science. If more and more new AI solutions
emerge in production, AI in school education is still
at an early stage of development. Mathematics is one
of the most rewarding subjects where AI solutions
can be successfully used to foster collaboration and
individual approach, to speed up task correction and
feedback, to generate more and different tasks, to
relieve teacher time and respond to student emotions.
AI education is a feature of intelligence, and schools
need to keep pace with the times, make changes,
innovate and change the roles of teachers / students to
adapt future populations to the “age of artificial
intelligence” (Shen, 2020).
The most important questions in the near future
will be the following: Are today's teachers ready to
develop the leaders necessary for tomorrow? Will
educators be able to be active and collaborate with
industry professionals to improve mathematics
teaching in general? It is extremely important to look
for interdisciplinary collaborative solutions, because:
An important task is to reduce the technological
tension caused by the discrepancies between the
pace of technological development and people's
ability to apply it. And the education sector alone
will not be able to cope with it;
The task of the state is to create support and
preconditions so that every student and teacher is
not excluded from the development of digital
technologies;
As digital technologies take over everyday life,
the most important task is to create an
appropriate and flexible education system with
the opportunity to acquire more new skills;
During the Covid19 pandemic in 2020,
significant paradigm shifts have taken place,
such as no direct contacts, no traditional services,
information needs to be prepared in advance to
be passed on, etc.;
We must not lose value and the quality of
teaching, nor unduly reduce the content of
teaching.
ACKNOWLEDGEMENTS
The research is carried out within the framework of
the postdoctoral project “Artificial Intelligence (AI)
Support for Approach of Accelerated Learning of
Mathematics (AI4Math) (1.1.1.2/VIAA/ 3/19/564)”
at Vidzeme University of Applied Sciences with the
support of ERAF.
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120
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