Search results

Students with developmental/intellectual disabilities (ID/DD) often have serious health issues that require additional medical care and supervision. Serious health issues also mean increased absence and additional lags in academic achievement and development of adaptive and social skills. The incorporation of artificial intelligence in the education of a child with ID/DD could ameliorate the educational, adaptive and social skill gaps that occur as a direct result of persistent health problems.

The literature regarding the use of artificial intelligence in education for students with ID/DD was collected systematically from international online databases based on specific inclusion and exclusion criteria. The collected articles were analyzed deductively, looking for the different gaps in the domain. Based on the literature, an artificial intelligence–based architecture is proposed and sketched.

The findings show that there are many gaps in supporting students with ID/DD through the utilization of artificial intelligence. Given that the majority of students with ID/DD often have serious and chronic and comorbid health conditions, the potential use of health information in artificial intelligence is even more critical. Therefore, there is a clear need to develop a system that facilitates communication and access to health information for students with ID/DD, one that provides information to caregivers and education providers, limits errors, and, therefore, improves these individuals' education and quality of life.

This review highlights the gap in the current literature regarding using artificial intelligence in supporting the education of students with ID/DD. There is an urgent need for an intelligent system in collaboration with the updated health information to improve the quality of services submitted for people with intellectual disabilities and as a result improving their quality of life.

This study contributes to the literature by highlighting the gaps in incorporating artificial intelligence and its service to individuals with ID/DD. The research additionally proposes a solution based on the confounding variables of students’ health and individual characteristics. This solution will provide an automated information flow as a functional diagnostic and intervention tool for teachers, caregivers and parents. It could potentially improve the educational and practical outcomes for individuals with ID/DD and, ultimately, their quality of life.

This study intends to examine the relationships between external knowledge sourcing (EKS), organizational ambidexterity (OA), and manufacturing performance (MP) in the context of large manufacturing firms within a dynamic environment setting. The research framework and derived hypotheses are grounded in the knowledge-based view (KBV) and dynamic capability (DC) theories.

A self-administered online survey was used in this study to gather data. Respondents were the operation leaders representing large manufacturing firms. The collected data were screened for invalid responses, and hypotheses were tested using structural equation modeling.

The study reveals that OA and EKS play key roles in achieving a better MP. Likewise, OA also mediates the relationship between EKS and MP.

Cross-sectional data were collected from large manufacturing firms within five focus sectors in Malaysia. A similar study can be conducted with more sectors of different contexts to confirm the findings.

Knowledge is critical for the firm to react to environmental dynamism, and the ability to manage it ambidextrously will enable the firm to enhance its performance.

This study offers empirical insights from the perspective of the large manufacturing firms in Malaysia, which are undergoing an Industrial Revolution 4.0 (IR4.0) transformation. This study bridges the knowledge gap by revealing the value that EKS can facilitate MP, exploring OA as the prevalent factor and demonstrating how KBV and DC can be applied in this study.