Exploring University Students’ Adoption of ChatGPT Using the Diffusion of Innovation Theory and Sentiment Analysis With Gender Dimension

Human Behavior and Emerging Technologies, Journal Year: 2024, Volume and Issue: 2024(1)

Published: Jan. 1, 2024

This study explores the adoption and societal implications of an emerging technology such as Chat Generative Pre‐Trained Transformer (ChatGPT) in higher education students. By utilizing a mixed‐method framework, this research combines Rogers’ diffusion innovation theory with sentiment analysis, offering innovative methodological approach for examining educational settings. It five attributes—relative advantage, compatibility, ease use, observability, trialability—shaping students’ behavioral intentions toward ChatGPT. Sentiment analysis offers qualitative depth, revealing emotional perceptual aspects, introduces gender‐based perspective. The results suggest that attributes significantly impact rates perceptions ChatGPT, indicating its potential transformative social change within sector. Gen Zs viewed ChatGPT innovative, compatible, user‐friendly, enabling independent pursuit goals. Consequently, benefits provided by motivate students to use tool. Gender differences were observed prioritization attributes, male favoring while female emphasized relative trialability. findings have understanding how technological innovations could be strategically diffused across different segments, especially academic context where ethical considerations integrity are paramount. underscores need demographic‐sensitive, user‐centric design generative artificial intelligence (AI) technologies.

Language: Английский

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Equity across the educational spectrum: innovations in educational access crosswise all levels

Frontiers in Education, Journal Year: 2025, Volume and Issue: 9

Published: Jan. 10, 2025

Introduction Educational equity remains a critical issue in the U.S., where disparities access and outcomes exist across socioeconomic, racial, gender, geographical areas. These inequities influence student success at all levels, from general education to higher education. The study aims explore these disparities, identify their root causes, examine effects on educational opportunities outcomes. Current addresses gaps resources, tuition affordability, support mechanisms, this research highlights urgent need for innovative solutions bridge inequities. study’s focus importance of creating an inclusive accessible framework that can benefit learners. Research methods This utilizes quantitative approach investigate various levels U.S. Data sources include national databases, university records, standardized test scores, financial aid statistics, providing comprehensive view disparities. Regression analysis is employed key indicators assess relationships between factors By analyzing data diverse contexts demographics, methodology ensures clear understanding patterns dynamics inequality. provides data-driven groundwork identifying effective strategies enhance Results findings reveal significant outcomes, with socioeconomic status, race, geography emerging as prominent factors. General marked by unequal resource distribution, while faces challenges high costs limited marginalized groups. how hinder achievement perpetuate systemic barriers. However, also identifies successful interventions, such targeted scholarships, teaching practices, systems. initiatives demonstrate tangible progress mitigating pathways more equitable experience spectrum. Discussion emphasizes implications results, linking observed issues policy practice. It suggests scalable solutions, funding models, affordable policies, curricula, address persistent advocates expanding programs like scholarships services under-served communities. While has been made, work ensure concludes recommendations policymakers educators adopt evidence-based promote inclusion, fostering fairer system all.

Language: Английский

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The Transformative Power of Generative Artificial Intelligence for Achieving the Sustainable Development Goal of Quality Education

Sustainability, Journal Year: 2024, Volume and Issue: 16(22), P. 9779 - 9779

Published: Nov. 9, 2024

This study explored the transformative potential of generative artificial intelligence (GAI) for achieving UN Sustainable Development Goal on Quality Education (SDG4), emphasizing its interconnectedness with other SDGs. A proprietary algorithm and cocitation network analysis were used to identify analyze SDG features in GAI research publications (n = 1501). By examining GAI’s implications ten SDG4 targets, findings advocate a collaborative, ethical approach integrating GAI, policy practice developments that ensure technological advancements align overarching goals SDG4. The results highlight multifaceted impact First, this paper outlines framework leverages enhance educational equity, quality, lifelong learning opportunities. highlighting synergy between SDGs, such as reducing inequalities (SDG10) promoting gender equality (SDG5), underscores need an integrated utilizing GAI. Moreover, it advocates personalized learning, equitable technology access, adherence AI principles, fostering global citizenship, proposing strategic alignment applications broader agenda. Next, introduces significant challenges, including concerns, data privacy, risk exacerbating digital divide. Overall, our underscore critical role reforms innovative practices navigating challenges harnessing opportunities presented by education, thereby contributing comprehensive discourse technology’s advancing education sustainable development.

Language: Английский

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Exploring large language models as an integrated tool for learning, teaching, and research through the Fogg Behavior Model: a comprehensive mixed-methods analysis

Cogent Engineering, Journal Year: 2024, Volume and Issue: 11(1)

Published: June 1, 2024

Large language models (LLMs) are a recent advancement in artificial intelligence that has the potential to revolutionize learning, teaching, and research. Still, there is room for improvement regarding how effectively LLMs could be incorporated into these environments. This study investigated role of LLMs, specifically ChatGPT, research contexts. To understand motivation, ability, triggers influence behavior undergraduate students, teachers, scholars toward Fogg Behavior Model (FBM) adopted. The revealed students researchers apply their respective domains was greatly influenced by motivation ability. However, teachers exhibited little interest incorporating any pedagogical strategies. In addition results, participants identified limitations ChatGPT fields. These insights contribute valuable perspectives on practical implementation effectiveness diverse academic sheds light benefits challenges integrating educational findings emphasize importance accounting motivational factors individual abilities when applying such models. study's offer invaluable educators harness environments while mitigating limitations.

Language: Английский

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