Artificial Intelligence a Disruptive Innovation in Higher Education Accreditation Programs: Expert Systems and AACSB

Chedrawi, Charbel; Howayeck, Pierrette

doi:10.1007/978-3-030-10737-6_8

Cited by 12 publications

(4 citation statements)

References 15 publications

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“…Several decisions on the effective management of resources can be done with the use of ES . Even in higher education, it can be used for programme accreditation (Chedrawi & Howayeck, 2019). The entire management of basic education is possible (Inusah et al, 2021) and (Inusah et al, 2023a).…”

Section: Educational Es For Resource Managementmentioning

confidence: 99%

“…This did not only help in improving graduate-advisor e ciency but also minimized the cost. Attempting to nd out if AI can improve education and enhance accreditation as indicated in (Chedrawi & Howayeck, 2019) proves that AI can reshape educational processes. This supports the evidence in Radwan et al (2016) which dwells on the evaluation of the Learning Management System (LMS) to support teaching and learning.…”

Section: Related Work Educational Expert Systemmentioning

confidence: 99%

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Systematic Review of Literature on Expert System in Education.

Inusah

2023

Preprint

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The use of Artificial Intelligence (AI) in addressing challenges of education is an innovation in education which addresses a series and sequence of problems that humans cannot solve. Specifically, Expert Systems (ES) in education have helped tremendously in handling tasks that the human expert has limitations in handling. This review explores the use of ES in education to identify the trends and the possible gaps in the application of ES to improve education. Four (4) academic databases were searched to retrieve research works related to ES in education. These are; academia, research gate, google scholar and semantic scholar. The found results were filtered to avoid duplicates, and the titles and abstracts were then screened before the full text was read and captured in the literature. The findings reveal more than 80% of the research works on ES in education are centred on higher education leaving basic education which is the foundation for growth and development in education. Also, over 70% of the literature was on teaching and learning at the expense of resource management.

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Section: Educational Es For Resource Managementmentioning

confidence: 99%

Section: Related Work Educational Expert Systemmentioning

confidence: 99%

Systematic Review of Literature on Expert System in Education.

Inusah

2023

Preprint

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“…IT awareness is essential to business management because few resources in every company, and IT expenditure are typically expensive with a high risk of failure. This IT knowledge includes the prospective and shortcomings of the enterprise's IT technology, the use of IT by competitors, and the prospects for new technology to increase business (Chedrawi and Howayeck 2019). The lack of business executive visionary in Company A is also because they are not well informed with the standard best practices that should be looked at to achieve the competitive advantage such as Gartner.…”

Section: Lack Of Business Executive Visionarymentioning

confidence: 99%

Exploring the Misalignment between Business and Information Technology on the Implementation of Balanced Scorecard: Case Study of State-Owned Telecommunication Companies in Indonesia

Sundoro¹,

Wandebori

2021

J. Sistem Inf. (J. Inf. Sys.)

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Many organisations around the world have faced misalignment in attaining the alignment between business and IT. The positive effect of alignment on overall company success has been focused on previous research. On the other hand, the misalignment in the implementation of a balanced scorecard was primarily unexplored. This study aimed at identifying and evaluating the factors that contribute to a misalignment of businesses and IT. The case study methodology is conducted in two state-owned telecommunication companies in Indonesia. The telecommunication industry’s selection as the case study is because of their nature closely related to technology development and implementation. Five semi-structured interviews, field notes and business records are used to produce the data, which have been thematically analysed and further follow by cross-case analysis to compare the thematic analysis result from each company. This study has resulted in 12 factors of misalignment between business and IT that can inhibit achieving alignment in implementing a balanced scorecard. The main findings showed that human factors, enterprise architecture, and IT project implementation factors could be three main source themes that can potentially contribute to misalignment. The findings may allow researchers to devise frameworks for how misalignments can be minimised to align business and IT better. This finding also useful in practice for companies that are seeking to achieve business-IT alignment by focusing on human factors, enterprise architecture factors, and IT project implementation factors.

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“…Additionally, AI chatbots boost the development of higher-order cognitive skills among students. Chedrawi and Howayeck (2019) discuss the implementation of AI through expert systems in higher education accreditation programs, which can lead to more reliable and efficient results. Hemachandran et al (2022) highlight the need for information bridge technology and AI to augment tutoring in higher education while also addressing the psychological impact of this technology on faculty and students.…”

Section: Introductionmentioning

confidence: 99%

AI in Academic Writing: Ally or Foe?

Kouam Arthur William

2024

IJRP

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This paper delves into the burgeoning field of AI in academic writing, exploring the complex interplay between technology and scholarly communication. By examining the advantages, limitations, and ethical considerations of employing AI tools in academic writing, this study sheds light on the potential impact of AI on writing processes and academic work quality. The findings offer a nuanced understanding of the benefits of using AI in academic writing, such as enhanced efficiency, accuracy, and accessibility, alongside the challenges posed by lack of subjectivity, bias in algorithms, and overreliance on technology. Ethical considerations surrounding AI use in academic writing, including plagiarism detection, data privacy, and fairness, are also discussed. The study contributes to the existing literature by providing a comprehensive analysis of the implications of AI technology on academic writing processes and ethical practices, highlighting the need for collaboration, education, and responsible technology use in promoting academic integrity and innovation. Future research avenues are suggested further to explore the impact of AI on critical thinking, develop ethical guidelines for AI use in academia, and examine the effectiveness of AI tools in diverse writing genres. This study underscores the importance of navigating the complexities of AI technology in academic writing to harness its benefits while upholding ethical standards and fostering a culture of responsible technological innovation.

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Artificial Intelligence a Disruptive Innovation in Higher Education Accreditation Programs: Expert Systems and AACSB

Cited by 12 publications

References 15 publications

Systematic Review of Literature on Expert System in Education.

Systematic Review of Literature on Expert System in Education.

Exploring the Misalignment between Business and Information Technology on the Implementation of Balanced Scorecard: Case Study of State-Owned Telecommunication Companies in Indonesia

AI in Academic Writing: Ally or Foe?

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