Artificial Intelligence Enabled Personalised Assistive Tools to Enhance Education of Children with Neurodevelopmental Disorders-A Review

Stress, resilience, and emotional well-being in children and adolescents with specific learning disabilities

This article reviews the prevalence of stress and explores resilience factors in children and adolescents with specific learning disabilities (SLDs). We show that the increased stress and emotional challenges faced by this group are likely due to societal pressures and stigma. Recent findings on neuroendocrine changes in this population are discussed, suggesting a predisposition to psychiatric disorders. This review advocates for a societal shift towards the neurodiversity paradigm, which recognizes SLDs as natural variations in brain function, emphasizing individual strengths and promoting a more inclusive approach that values cognitive diversity. Such advocacy is likely important to combat stress and stigma in those with SLDs. This article also reviews recent work identifying resilience-promoting factors, such as perception of self and peer/teacher relationships, for enhancing emotional well-being and mental health for children and adolescents with SLD.

Improving communication and promoting social inclusion for hearing-impaired users: Usability evaluation and design recommendations for assistive mobile applications

This study examines the usability of communication-assistive applications for hearing-impaired users, with a focus on enhancing user experience and promoting social inclusion. Although such applications have been developed and evaluated previously, interface designs that consider the intimacy needs of hearing-impaired users remain under-explored. We performed a comprehensive usability evaluation employing a mixed-method approach, which involved hearing-impaired individuals as well as field experts. The findings revealed areas for improvement in the design, validated the feasibility of implementing these applications, and emphasized the importance of incorporating the unique needs and preferences of hearing-impaired users. Furthermore, this paper discusses the importance of introducing guidelines and evaluation scales for the "Design for Emotion and Life Knowledge" levels to facilitate smooth and effective human-computer interactions. Such measures will promote the development of intelligent assistive technologies that reflect the qualitative needs of people with disabilities and contribute to social rights for hearing-impaired users. With the growing demands of artificial-intelligence-powered assistive technologies, the inclusion of individuals with disabilities in the design and research process is anticipated to increase. In future, studies should be conducted to blend the culturally shared experiences and emotional bonds expressed by users (having mild-to-severe hearing impairment) with the design and development process of assistive devices or services.

AI-Enhanced Dyscalculia Screening: A Survey of Methods and Applications for Children

New forms of interaction made possible by developments in special educational technologies can now help students with dyscalculia. Artificial intelligence (AI) has emerged as a promising tool in recent decades, particularly between 2001 and 2010, offering avenues to enhance the quality of education for individuals with dyscalculia. Therefore, the implementation of AI becomes crucial in addressing the needs of students with dyscalculia. Content analysis techniques were used to examine the literature covering the influence of AI on dyscalculia and its potential to assist instructors in promoting education for individuals with dyscalculia. The study sought to create a foundation for a more inclusive dyscalculia education in the future through in-depth studies. AI integration has had a big impact on educational institutions as well as people who struggle with dyscalculia. This paper highlights the importance of AI in improving the educational outcomes of students affected by dyscalculia.

From "online brains" to "online lives": understanding the individualized impacts of Internet use across psychological, cognitive and social dimensions

In response to the mass adoption and extensive usage of Internet-enabled devices across the world, a major review published in this journal in 2019 examined the impact of Internet on human cognition, discussing the concepts and ideas behind the "online brain". Since then, the online world has become further entwined with the fabric of society, and the extent to which we use such technologies has continued to grow. Furthermore, the research evidence on the ways in which Internet usage affects the human mind has advanced considerably. In this paper, we sought to draw upon the latest data from large-scale epidemiological studies and systematic reviews, along with randomized controlled trials and qualitative research recently emerging on this topic, in order to now provide a multi-dimensional overview of the impacts of Internet usage across psychological, cognitive and societal outcomes. Within this, we detail the empirical evidence on how effects differ according to various factors such as age, gender, and usage types. We also draw from new research examining more experiential aspects of individuals' online lives, to understand how the specifics of their interactions with the Internet, and the impact on their lifestyle, determine the benefits or drawbacks of online time. Additionally, we explore how the nascent but intriguing areas of culturomics, artificial intelligence, virtual reality, and augmented reality are changing our understanding of how the Internet can interact with brain and behavior. Overall, the importance of taking an individualized and multi-dimensional approach to how the Internet affects mental health, cognition and social functioning is clear. Furthermore, we emphasize the need for guidelines, policies and initiatives around Internet usage to make full use of the evidence available from neuroscientific, behavioral and societal levels of research presented herein.

Digital Dialogue-How Youth Are Interacting With Chatbots

This Viewpoint describes the use of large language model chatbots in social, educational, and therapeutic settings and the need to assess when children are developmentally ready to engage with them.

AI Syndrome: an intellectual asset for students or a progressive cognitive decline

PURPOSE

To investigate and to raise awareness about the influence of AI-powered software on the cognitive development of medical students, as well as the possible long-term ramifications.

METHOD

This study combed through the literature on the use of AI in clinical settings and medical education, including chatbots powered by AI such as Chatgpt and Dale. The potential advantages and disadvantages of employing AI software for learning and complementing medical education, as well as its influence on critical thinking and problem-solving abilities, were assessed.

RESULTS

no data analysis was performed.

CONCLUSIONS

AI-powered software in medical education has potential benefits and drawbacks. While it can improve medical diagnosis and treatment and provide access to learning resources, the misuse of AI as a shortcut may hinder cognitive development and have long-term implications.

Breaking Barriers-The Intersection of AI and Assistive Technology in Autism Care: A Narrative Review

(Background) Autism increasingly requires a multidisciplinary approach that can effectively harmonize the realms of diagnosis and therapy, tailoring both to the individual. Assistive technologies (ATs) play an important role in this context and hold significant potential when integrated with artificial intelligence (AI). (Objective) The objective of this study is to analyze the state of integration of AI with ATs in autism through a review. (Methods) A review was conducted on PubMed and Scopus, applying a standard checklist and a qualification process. The outcome reported 22 studies, including 7 reviews. (Key Content and Findings) The results reveal an early yet promising interest in integrating AI into autism assistive technologies. Exciting developments are currently underway at the intersection of AI and robotics, as well as in the creation of wearable automated devices like smart glasses. These innovations offer substantial potential for enhancing communication, interaction, and social engagement for individuals with autism. Presently, researchers are prioritizing innovation over establishing a solid presence within the healthcare domain, where issues such as regulation and acceptance demand increased attention. (Conclusions) As the field continues to evolve, it becomes increasingly clear that AI will play a pivotal role in bridging various domains, and integrated ATs with AI are positioned to act as crucial connectors.

Systematic bibliometric and visualized analysis of research hotspots and trends in artificial intelligence in autism spectrum disorder

Background

Artificial intelligence (AI) has been the subject of studies in autism spectrum disorder (ASD) and may affect its identification, diagnosis, intervention, and other medical practices in the future. Although previous studies have used bibliometric techniques to analyze and investigate AI, there has been little research on the adoption of AI in ASD. This study aimed to explore the broad applications and research frontiers of AI used in ASD.

Methods

Citation data were retrieved from the Web of Science Core Collection (WoSCC) database to assess the extent to which AI is used in ASD. CiteSpace.5.8. R3 and VOSviewer, two online tools for literature metrology analysis, were used to analyze the data.

Results

A total of 776 publications from 291 countries and regions were analyzed; of these, 256 publications were from the United States and 173 publications were from China, and England had the largest centrality of 0.33; Stanford University had the highest H-index of 17; and the largest cluster label of co-cited references was machine learning. In addition, keywords with a high number of occurrences in this field were autism spectrum disorder (295), children (255), classification (156) and diagnosis (77). The burst keywords from 2021 to 2023 were infants and feature selection, and from 2022 to 2023, the burst keyword was corpus callosum.

Conclusion

This research provides a systematic analysis of the literature concerning AI used in ASD, presenting an overall demonstration in this field. In this area, the United States and China have the largest number of publications, England has the greatest influence, and Stanford University is the most influential. In addition, the research on AI used in ASD mostly focuses on classification and diagnosis, and "infants, feature selection, and corpus callosum are at the forefront, providing directions for future research. However, the use of AI technologies to identify ASD will require further research.

A social robot connected with chatGPT to improve cognitive functioning in ASD subjects

Neurodevelopmental Disorders (NDDs) represent a significant healthcare and economic burden for families and society. Technology, including AI and digital technologies, offers potential solutions for the assessment, monitoring, and treatment of NDDs. However, further research is needed to determine the effectiveness, feasibility, and acceptability of these technologies in NDDs, and to address the challenges associated with their implementation. In this work, we present the application of social robotics using a Pepper robot connected to the OpenAI system (Chat-GPT) for real-time dialogue initiation with the robot. After describing the general architecture of the system, we present two possible simulated interaction scenarios of a subject with Autism Spectrum Disorder in two different situations. Limitations and future implementations are also provided to provide an overview of the potential developments of interconnected systems that could greatly contribute to technological advancements for Neurodevelopmental Disorders (NDD).

Prioritizing educational initiatives on emerging technologies for Italian pediatricians: bibliometric review and a survey

BACKGROUND

Emerging technologies have demonstrated outstanding potential in improving healthcare, yet their full integration remains a challenge for all medical specialties, including pediatrics. To support the swift implementation of technologies, we identified the current trends through a bibliometric review, and we conducted a survey on Italian pediatricians to gauge educational needs and willingness to integrate technologies into clinical practice.

METHODS

A working group of pediatricians representing various backgrounds designed and coordinated the study. To identify relevant topics for educational strategy development, we focused on virtual reality, telehealth, natural language processing, smartphone applications, robotics, genomics, and artificial intelligence. A bibliometric analysis limited to 2018-2023 was performed to identify trends and emerging applications within each topic. Based on the results, a questionnaire was developed and made available online to all Italian pediatricians. The results were analyzed through descriptive analysis and a multivariable logistic regression to explore associations between technology adoption and sociodemographic characteristics.

RESULTS

A total of 3,253 publications were found, with Telehealth and Telemedicine having the highest number of publications and Natural Language Processing the lowest. The number of respondents to the online questionnaire was 1,540, predominantly medical doctors with over 20 years of experience working as family pediatricians. Telehealth had the highest level of knowledge (95.2%), followed by smartphone applications (89.1%) and genomics (63.2%). The greatest potential for increased use through education programs was projected for natural language processing (+ 43.1%), artificial intelligence (+ 39.6%), and virtual and mixed reality (+ 38.1%). Female respondents and older individuals were less likely to use emerging technologies. Hospital pediatricians and residents were more likely to use AI.

CONCLUSIONS

We developed a replicable strategy to identify emerging themes in medical technologies relevant to pediatrics and assess the educational needs of pediatricians. A significant gap still exists between current and potential usage of emerging technologies among Italian pediatricians although they showed a positive attitude towards implementing these technologies following specific education programs. The study highlights the need for comprehensive education programs on emerging technologies in pediatrics and recommends addressing gender and age disparities in technology adoption.

The threat, hype, and promise of artificial intelligence in education

The idea of building intelligent machines has been around for centuries, with a new wave of promising artificial intelligence (AI) in the twenty-first century. Artificial Intelligence in Education (AIED) is a younger phenomenon that has created hype and promises, but also been seen as a threat by critical voices. There have been rich discussions on over-optimism and hype in contemporary AI research. Less has been written about the hyped expectations on AIED and its potential to transform current education. There is huge potential for efficiency and cost reduction, but there is also aspects of quality education and the teacher role. The aim of the study is to identify potential aspects of threat, hype and promise in artificial intelligence for education. A scoping literature review was conducted to gather relevant state-of-the art research in the field of AIED. Main keywords used in the literature search were: artificial intelligence, artificial intelligence in education, AI, AIED, teacher perspective, education, and teacher. Data were analysed with the SWOT-framework as theoretical lens for a thematic analysis. The study identifies a wide variety of strengths, weaknesses, opportunities, and threats for artificial intelligence in education. Findings suggest that there are several important questions to discuss and address in future research, such as: What should the role of the teacher be in education with AI? How does AI align with pedagogical goals and beliefs? And how to handle the potential leak and misuse of user data when AIED systems are developed by for-profit organisations?

Deep Learning-Based Mental Health Model on Primary and Secondary School Students’ Quality Cultivation

The purpose was to timely identify the mental disorders (MDs) of students receiving primary and secondary education (PSE) (PSE students) and improve their mental quality. Firstly, this work analyzes the research status of the mental health model (MHM) and the main contents of PSE student-oriented mental health quality cultivation under deep learning (DL). Secondly, an MHM is implemented based on big data technology (BDT) and the convolutional neural network (CNN). Simultaneously, the long short-term memory (LSTM) is introduced to optimize the proposed MHM. Finally, the performance of the MHM before and after optimization is evaluated, and the PSE student-oriented mental health quality training strategy based on the proposed MHM is offered. The results show that the accuracy curve is higher than the recall curve in all classification algorithms. The maximum recall rate is 0.58, and the minimum accuracy rate is 0.62. The decision tree (DT) algorithm has the best comprehensive performance among the five different classification algorithms, with accuracy of 0.68, recall rate of 0.58, and F1-measure of 0.69. Thus, the DT algorithm is selected as the classifier. The proposed MHM can identify 56% of students with MDs before optimization. After optimization, the accuracy is improved by 0.03. The recall rate is improved by 0.19, the F1-measure is improved by 0.05, and 75% of students with MDs can be identified. Diverse behavior data can improve the recognition effect of students' MDs. Meanwhile, from the 60th iteration, the mode accuracy and loss tend to be stable. By comparison, batch_size has little influence on the experimental results. The number of convolution kernels of the first convolution layer has little influence. The proposed MHM based on DL and CNN will indirectly improve the mental health quality of PSE students. The research provides a reference for cultivating the mental health quality of PSE students.

Functionality of Apps for People with Autism: Comparison between Educators from Florence and Granada

BACKGROUND

Studies on the potential of smartphone apps for people with autism are currently increasing in number, given the large digital supply available and the benefits they offer. We analyzed the opinion of educators from Florence (Italy) and Granada (Spain) regarding the benefits and applicability of apps, frequency of their use, and the type of apps used for people with autism.

METHODS

The study involved 1261 professionals, of whom 286 worked with apps, using a non-experimental quantitative design, descriptive and frequency statistics, parametric inferential analyses (Student's t and one-factor ANOVA), and calculation of the effect size (Cohen's d and eta squared) and intrafactorial correlations.

RESULTS

Statistically significant differences were observed in respect of city, sex, age, years of experience, place of work, and type of teacher. The teachers from Granada found more benefits and applicability in apps, and revealed a slightly higher usage than those from Florence.

CONCLUSIONS

It is an arduous but worthy task for professionals from schools and associations that work with people with autism to acquire the necessary knowledge to apply methodologies based on information and communication technology (ICT), as this will help achieve the integrated development of people with different capabilities.