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https://ceur-ws.org/Vol-3102/short2.pdf
DSAi: AI Powered Platform to Support the Use and Map-
ping of Educational Content for SLDs Students
Guido Di Fraia1
1 IULM University of Milan – guido.difraia@iulm.it
Keywords: AI application, NLP, education, training.
1 Background
Learning difficulties concern European researchers in the field of education and their
effort to improve the Education System in Europe. They are conducting research and
studies, aiming at mapping the problem through data that they can later use to identify
potential solutions.
Specific learning disorders (SLDs) are difficulties in acquiring and applying aca-
demic skills. They are “specific” because they concern only some learning processes,
that is, automatisms that do not develop during the school path.
According to the European Dyslexia Association in Europe, 15% of the population
is dealing with dyslexia or some sort of learning disorder. The group of European Cit-
izens with dyslexia and specific learning differences encompasses between 5 and 12
percent of the population, thereby navigating through life in a largely non-‘dys’ friendly
world [1]. Dyslexia is the most widespread specific learning difference, making the
acquiring and using of reading, spelling and writing skills and other communication-
related cultural abilities more difficult for the affected people (commonly known as
‘DYS-differences’). Academic surveys have highlighted that other learning differences
as dysphasia, dyscalculia, dyspraxia and attention deficit disorder (ADHD) commonly
exist with dyslexia, known as 'DYS-differences' (concluded under 'DYS'). The same
person can also accumulate some of these differences. Indeed, dyslexia is associated
with dysphasia, dyspraxia, dyscalculia or attention deficit [2].
Several approaches are present across Europe about issues related to SLDs. Different
countries adopt different definitions and have different norms concerning diagnosis and
regulations regarding support measures for dyslexic and SLDs pupils and students. The
scenario is further complicated by the increasing presence of immigrant plurilingual
individuals, who are often not granted adequate support.
In Italy, in the 2018/2019 school year, 298,114 students attending Italian schools
were diagnosed with a specific learning disorder, equal to 4.9% of the total [3]. In the
2019/2020 school year, Italian students with educational specials needs represented
11% of those enrolled in the secondary school and 6.5% in school primary of the first
degree. Compared to the 2017/2018 school year, the presence of students with special
educational needs within the school has grown by 29% on enrolled students (approxi-
mately +60,000) [4].
Copyright ©2021 for this paper by its authors. Use permitted under Creative Com-
mons License Attribution 4.0 International (CC BY 4.0).
2 Research objectives.
Our project aims to analyze the needs of students with specific learning disorders
(SLDs). It designs organizational and technological solutions based on artificial intel-
ligence. The keywords around which this project revolves and develops are essentially
three: inclusion, accessibility and innovation.
The main intellectual output consists in the development and validation of a digital
solution able to suggest the most appropriate supporting methodologies for dyslexic
students based on the student-specific issues.
Until now, the use of artificial intelligence and algorithms is still partly limited to
diagnostic use, such as for automatic detection of dyslexic children using a 3D Convo-
lutional Neural Network or for Automated Detection of Dyslexia Symptom Based on
Handwriting Image for Primary School Children [5].
Therefore, the goal of our project is to become a point of reference and fundamental
support for learning, with particular attention to dyslexia. It aims to develop Digital and
Artificial Intelligence Integrated Tools to Support Higher Education Students with
SLDs in secondary school and university.
Several efforts have been already made to help students with dyslexia by offering
adaptive e-learning methods. However, these efforts are completely addressed to chil-
dren of primary school; no online tool based on AI has been proposed in the university,
even though it is recognized that the inclusion of students with dyslexia in higher edu-
cation is an important issue to solve. An innovative factor of an e-learning platform for
dyslexic students is the use of artificial intelligence as the core of the architecture.
Moreover, it would be the first example of this technology application in this specific
field. The usage of AI will provide an adaptive interface that may support university
students with an age substantially greater than the one considered until now in similar
studies.
The field of Artificial Intelligence and Machine Learning over the past three decades
has developed faster. The expectation is that it can help fill the gaps that exist in learn-
ing and education. Looking at a potential growth of 47.5%, there is no doubt that Arti-
ficial Intelligence will become part of the education sector soon [6].
The project intends to develop Digital and Artificial Intelligence Integrated Tools to
Support Higher Education Students with specific learning disorders and, to do so, we
want to collaborate with SLDs students to ideate some possible technological solutions
that can improve the quality of their study experience, thereby using a participatory
design thinking approach.
The research project hypothesizes that solutions based on NLP [7] can constitute
effective aids to allow a dsy-friendly and therefore more inclusive education. As we
know, the higher levels of NLP, especially the discourse level, can empower an imple-
mentation that reduces a larger text into a shorter, yet richly constituted abbreviated
narrative representation of the original document.
3 Expected results.
Our research project strives to:
• analyze the actual and latent needs of students with SLDs certificates concerning
their experience of studying and participating in lessons;
• deepen the challenges that distance learning has imposed on students with SLDs;
• detect the use or not of enabling technologies in terms of devices and applications;
• explore areas for improvement of existing technologies and devise new possible
technological solutions AI based;
• develop a technological solution based on AI and virtual reality; the idea is an
immersive system able to offer a dsy-friendly digital environment where the student
can find helpful tools for his study;
• bring out the differences and similarities between European students from differ-
ent countries.
The study aims to obtain the following outputs:
• a mapping of the experiences of SLD students at the European level;
• a detection of the different support strategies and tools;
• the exploitation of some advantages of the sudden and pushed digitization that we
experienced during the Covid19 crisis so that they become structural;
• the development of new AI based technologies able to improve the quality of life
of SLD students.
Inclusion is a concept that presupposes equity and the task of each institution is to
encourage each student to educational success.
The development of the project is still ongoing. However, we believe that further
research and development activities in this field are necessary, especially in areas of
training not yet considered, such as company training activities.
The development of an AI powered platform to support the training needs of people
SLDs may also prove useful for the training of employees and collaborators.
References
1. IED Team. “Learning difficulties in Europe”. Institute of Entrepreneurship De-
velopment (2019). Available at: https://ied.eu/project-updates/learning-difficul-
ties-in-europe/
2. EDA Team. “About Us”. European Dyslexia Association. Available at:
https://eda-info.eu/about-the-eda/
3. MIUR Documents (2018), available at : https://miur.gov.it/docu-
ments/20182/0/Gli+alunni+con+DSA+-+a.s.+2018_2019.pdf/a2f114e9-b59a-
1c5d-730c-e4aecb5aad7e?version=1.0&t=1605006783113
4. ISTAT Team “Inclusion of student with disabilities”. National Institute of Sta-
tistics (2020). Available at: https://www.istat.it/it/files/2020/12/Report-alunni-
con-disabilit%C3%A0.pdf
5. Sofia Zahia, Begonya Garcia-Zapirain, Ibone Saralegui, Begoña Fernandez-
Ruanova, Dyslexia detection using 3D convolutional neural networks and
functional magnetic resonance imaging, Computer Methods and Programs in
Biomedicine, Vol. 197 (2020)
6. Iza Sazanita Isa, Wan Nurazwin Syazwani Rahimi, Siti Azura Ramlan, Siti
Noraini Sulaiman, Automated Detection of Dyslexia Symptom Based on Hand-
writing Image for Primary School Children, Procedia Computer Science, Vol-
ume 163 (2019), pp. 440-449, https://doi.org/10.1016/j.procs.2019.12.127.
7. Rashi Kohli et al. "Artificial Intelligence Technology to Help Students With
Disabilities: Promises and Implications for Teaching and Learning”. IGI Global
(2021)