Innovations in Education

Advances in educational technologies and instructional design book series, Год журнала: 2024, Номер unknown, С. 19 - 52

Опубликована: Окт. 11, 2024

As the digital revolution transforms education, Explainable AI (XAI) plays a key role in advancing educational intelligence. This chapter examines how XAI is reshaping education by making machine learning processes transparent. Unlike traditional AI's “black boxes,” clarifies algorithms make recommendations, assessments, and personalized pathways. transparency helps educators understand trust tools, them effective partners education. The also explores XAI's practical uses adaptive platforms intelligent tutoring systems, showing clarity can enhance environments. It allows to address biases, customize strategies, track outcomes more precisely. Through real-world case studies theoretical insights, illustrates bridges advanced technology with teaching practices, promoting transparent equitable system.

Язык: Английский

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LEVERAGING HR ANALYTICS FOR STRATEGIC DECISION MAKING: OPPORTUNITIES AND CHALLENGES

International Journal of Management & Entrepreneurship Research, Год журнала: 2024, Номер 6(4), С. 1304 - 1325

Опубликована: Апрель 25, 2024

In the evolving landscape of human resources (HR), organizations are increasingly leveraging HR analytics to drive strategic decision-making. This review explores opportunities and challenges associated with integration in organizational practices. involves systematic analysis data inform decision-making, enhance performance, optimize workforce management strategies. By harnessing power data, can gain valuable insights into employee behavior, performance trends, dynamics, enabling them make more informed decisions. One key is ability identify address trends issues proactively. analyzing on engagement, turnover rates, metrics, patterns that may impact their business outcomes. proactive approach allows anticipate mitigate potential challenges, leading improved satisfaction. Furthermore, help recruitment talent candidate profiles, sources, most effective channels selection criteria. data-driven enables attract retain top talent, a skilled engaged workforce. However, also presents several challenges. primary availability quality data. Organizations must ensure they have access reliable relevant derive meaningful insights. Additionally, overcome related privacy security protect sensitive information. conclusion, significant for decision-making performance. analytics, operations, decisions success. availability, quality, realize full driving paper will examine use as tool resources. It cover methodologies technologies involved collection, analysis, interpretation, how these be used decision making HR. The study limitations including risk misinterpretation, propose solutions risks. Keywords: Leveraging, Analytics, Strategic Decision making, Opportunities, Challenges.

Язык: Английский

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AI‐driven adaptive learning for sustainable educational transformation

Sustainable Development, Год журнала: 2024, Номер unknown

Опубликована: Окт. 3, 2024

Abstract This paper scrutinizes how adaptive learning technologies and artificial intelligence (AI) are transforming today's education by making it personalized, accessible, efficient as well leading people to accepting, addressing, mitigating sustainable development. Recently, witnessed a remarkable technological surge driven various advances in technology, which can be demonstrated the increase of number scientific publications on this topic from just 1 1990 636 2023. Ongoing digitalization revolution together with novel approach respect each student's unique style abilities paved way for represented innovative tools that personalize educational experiences cater individual learners. All contributes preparing more educated informed citizens, drives innovation, supports economic growth necessary achieving future. Our bibliographic study employs VOSviewer conduct bibliometric analysis total 3518 selected using keywords “adaptive learning” “AI” (represented articles, proceeding papers, book chapters) indexed Web Science (WoS) database 2024. results demonstrate recent changes played key role learning, was rather reinforced “digital surge” brought about COVID‐19 pandemic. findings useful further development field where they employed relevant stakeholders policymakers scholars researchers.

Язык: Английский

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LEVERAGING QUANTUM COMPUTING FOR INCLUSIVE AND RESPONSIBLE AI DEVELOPMENT: A CONCEPTUAL AND REVIEW FRAMEWORK

Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(3), С. 671 - 680

Опубликована: Март 22, 2024

This paper proposes a novel conceptual framework that integrates the advanced capabilities of quantum computing to address urgent need for responsible and inclusive Artificial Intelligence (AI) development. It reviews current challenges in AI, such as bias, lack inclusivity, computational limitations faced by classical methods solving complex societal problems. By harnessing computing, this aims overcome these barriers, enabling faster, more efficient AI solutions are ethically grounded universally accessible. adopting holistic approach technical innovation with ethical considerations stakeholder engagement, we believe can serve catalyst development technologies not only but also inclusive, responsible, beneficial society whole. concept serves foundational further research, collaboration, action intersection ultimate goal transformative potential pressing promote human well-being. Keywords: Quantum Computing, Development, Responsible.

Язык: Английский

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A review of strategic decision-making in marketing through big data and analytics

Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(5), С. 1126 - 1144

Опубликована: Май 13, 2024

This review paper delves into the transformative impact of big data and analytics on strategic marketing decision-making. Examining integration vast datasets analytical tools in strategies highlights how these technological advancements enable a deeper understanding customer behavior, enhance product development, provide competitive edge. The underscores importance data-driven insights formulating personalized critical role predictive prescriptive It addresses challenges ethical considerations associated with usage, emphasizing need for robust governance practices. suggests future research directions, focusing emerging technologies methodologies that could further influence decisions. Keywords: Big Data, Analytics, Strategic Marketing, Data-Driven Decision-Making, Ethical Considerations, Emerging Technologies.

Язык: Английский

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Comparative technical analysis of legal and ethical frameworks in AI-enhanced procurement processes

World Journal of Advanced Research and Reviews, Год журнала: 2024, Номер 22(1), С. 1415 - 1430

Опубликована: Апрель 26, 2024

This study presents a Comparative Technical Analysis of Legal and Ethical Frameworks in AI-Enhanced Procurement Processes. The research aims to evaluate the existing legal ethical frameworks governing use artificial intelligence (AI) procurement identify best practices for ensuring transparency, accountability, decision-making AI-driven processes. adopts mixed-methods approach, combining quantitative surveys qualitative interviews with professionals experts. design allows comprehensive analysis challenges associated AI deployment provides insights into practical strategies addressing these challenges. Findings from indicate growing recognition need clear guidelines regulations govern procurement. While respondents acknowledge potential benefits AI, such as improved efficiency cost savings, they also express concerns about algorithmic bias, data privacy, lack transparency Based on findings, recommends several enhancing AI-enhanced These include developing deployment, providing training support professionals, establishing mechanisms monitoring evaluating systems. Overall, highlights importance integrating considerations ensure decision-making. findings contribute body literature governance provide policymakers, other stakeholders involved

Язык: Английский

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Harnessing AI for sustainable higher education: ethical considerations, operational efficiency, and future directions

Discover Sustainability, Год журнала: 2025, Номер 6(1)

Опубликована: Янв. 13, 2025

As higher education faces technological advancement and environmental imperatives, AI becomes a key instrument for revolutionizing instructional methods institutional operations. can improve educational outcomes, resource management, long-term sustainability in education, according to this study. The research uses case studies best practices show how AI-driven innovations minimize impact, enhance energy efficiency, customize learning, creating more sustainable inclusive academic environment. document discusses ethics, including data privacy, algorithmic prejudice, the digital divide. It emphasizes need strong ethical frameworks use ethically make decisions with transparency fairness. study also robust rules infrastructure promote integration, protecting student privacy supporting fair access technologies. shows curriculum-building tools educate students future concerns stimulate innovation. prospects difficulties of are critically examined, its potential change traditional roles, performance, maintain profitability. Actionable recommendations educators, politicians, leaders contribute conversation. Focusing on creates framework where technology stewardship intimately connected, ensuring that institutions prosper fast-changing world.

Язык: Английский

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Shifting Dynamics: Who Holds the Reins in Decision‐Making With Artificial Intelligence Tools? Perspectives of Gen Z Pre‐Service Teachers

European Journal of Education, Год журнала: 2025, Номер 60(1)

Опубликована: Фев. 21, 2025

ABSTRACT Artificial intelligence (AI) is significantly shaping education and currently influencing pre‐service teachers' academic professional journeys. To explore this influence, the present study examines 389 Generation Z attitudes towards AI its impact on educational decision‐making at two state universities, using an explanatory sequential mixed‐methods research design. Quantitative data were collected through General Attitudes to Intelligence Scale (GAAIS) survey. It was followed by qualitative gathered via semi‐structured interviews enrich statistical trends with deeper thematic insights. SPSS used for quantitative analysis while MAXQDA employed a systematic of data. The revealed that female teachers held more positive AI, higher levels knowledge contributing these attitudes. Negative attitudes, however, independent gender, discipline or familiarity. Findings also reveal tools, particularly ChatGPT, are primarily as advisors, often adapt AI's suggestions their preferences. predominantly preferred assignments, reports, projects presentations. In acceptance, time effort savings, innovative unbiased recommendations stated key factors. However, there ongoing trust concerns highlighting necessity keeping final decisions under human control. Based findings, comprehensive training students in suggested.

Язык: Английский

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An Exploratory Study on the Efficacy and Inclusivity of AI Technologies in Diverse Learning Environments

Sustainability, Год журнала: 2024, Номер 16(20), С. 8992 - 8992

Опубликована: Окт. 17, 2024

This exploratory research conducted a thematic analysis of students’ experiences and utilization AI tools by students in educational settings. We surveyed 87 undergraduates from two different courses at comprehensive university Western Canada. Nine integral themes that represent AI’s role student learning key issues with respect to have been identified. The study yielded three critical insights: the potential expand access for diverse body, necessity robust ethical frameworks govern AI, benefits personalized AI-driven support. Based on results, model is proposed along recommendations an optimal environment, where facilitates meaningful learning. argue integrating into has promote inclusivity accessibility making more accessible students. also advocate shift perception among stakeholders towards calling de-stigmatization its use education. Overall, our findings suggest academic institutions should establish clear, empirical guidelines defining conduct what considered appropriate use.

Язык: Английский

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A systematic review of literature reviews on artificial intelligence in education (AIED): a roadmap to a future research agenda

Smart Learning Environments, Год журнала: 2024, Номер 11(1)

Опубликована: Дек. 9, 2024

Abstract Despite the increased adoption of Artificial Intelligence in Education (AIED), several concerns are still associated with it. This has motivated researchers to conduct (systematic) reviews aiming at synthesizing AIED findings literature. However, these diversified terms focus, stakeholders, educational level and region, so on. made understanding overall landscape challenging. To address this research gap, study proceeds one step forward by systematically meta-synthesizing literature reviews. Specifically, 143 were included analyzed according technology-based learning model. It is worth noting that most been from China U.S. Additionally, when discussing AIED, strong focus was on higher education, where less attention paid special education. The results also reveal AI used mostly support teachers students education other stakeholders (e.g. school leaders or administrators). provides a possible roadmap for future agenda facilitating implementation effective safe AIED.

Язык: Английский

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