Recently, accounting academics have reported increased attention in the accounting profession toward the employment of various technologies. These studies only highlight the exploitation of these technologies in the profession and areas for future research, while missing the need for modernizing the accounting curriculum to meet the industry's technological needs. This paper follows an integrated model for curriculum redesign to reflect blockchain technology, business data analytics, and artificial intelligence employment in the accounting profession. By building on the main four educational curricula designs components, we propose ways to incorporate these technologies into the accounting curriculum. Current industry implementation of new technologies should be considered by academia when designing accounting curriculum to prepare graduates for the market and to ensure their employability. This paper calls for radical changes in the accounting curriculum to reach a balance between existing accounting knowledge and information technology skills relevant to the profession. JEL Classifications: M4; I23; O33.

Purpose: 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.Design/methodology/approach: 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.Findings: 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.Practical implications: 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.Originality/value: 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.

The COVID-19 pandemic has interrupted the education of millions of students across the world. The purpose of this study was to investigate the perceptions regarding the technological instruction and accommodations provided to deaf students in online distance learning during the COVID-19 pandemic. This study was qualitative in nature and used anonymous, one-to-one semi-structured interviews. In June 2020, we interviewed a convenience sample of deaf students (n = 15) and their instructors (n = 3) and analysed the responses thematically. Upon achieving theme saturation, the thematic structure analysis was finalised. The results revealed five main themes related to deaf students’ experience with online distance learning during COVID-19. The themes are as follows: course content delivered, technology used, delivery method, assessment tools used, and social interactions. Each theme is discussed and compared with the related literature to scientifically encapsulate its suggested dimensions.

In this paper, we describe the use of a modern learning classifier system to a data mining task. In particular, in collaboration with a medical specialist, we apply XCS to a primary breast cancer data set. Our results indicate more effective knowledge discovery than with C4.5.