Effects and acceptance of precision education in an AI-supported smart learning environment

Hu, Yung-Hsiang

doi:10.1007/s10639-021-10664-3

Cited by 29 publications

(15 citation statements)

References 68 publications

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“…A questionnaire completed by 662 students evaluated their attitudes toward AI virtual teachers, offering insights into how these technologies could support self‐directed learning in higher education. Furthermore, education in AI‐supported learning environments was assessed (Hu, 2022). This research evaluated the effects and acceptance of an AI‐supported smart learning environment in education, focusing on students' learning behaviors through a learning analytics dashboard.…”

Section: Literature Reviewmentioning

confidence: 99%

Are skepticism and moderation dominating attitudes toward AI‐based technologies?

Oprea,

Nica,

Bâra

et al. 2024

American J Econ Sociol

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AI advancements are poised to substantially modify human abilities in the foreseeable future. They include the integration of Brain–Computer Interfaces (BCIs) to augment cognitive functions, the application of gene editing, and the utilization of AI‐powered robotic exoskeletons to enhance physical strength. This study employs a comprehensive analytical framework combining factor analysis, clustering, ANOVA, and logistic regression to investigate public attitudes toward these transformative technologies. Our findings reveal three distinct clusters of public opinion reflecting varying optimism and concern toward AI technologies. Cluster 1 (1574 participants) held a positive view with high excitement while Cluster 2 (1334 participants) showed a balanced stance. Cluster 3 (2199 participants) expressed heightened concern despite some excitement. Notably, regional disparities, particularly between urban and rural participants, emerge as a prominent factor influencing these attitudes (ANOVA, F = 15.2, p < 0.001). Furthermore, logistic regression identifies key influencers of public perception, highlighting the significant roles played by religion and regional factors. The implications of these findings extend beyond understanding public sentiment. They underscore the need for informed policies that promote education and awareness about AI technologies, address ethical concerns, and engage the public in decision‐making processes. As society navigates this transformative technological landscape, a nuanced understanding of public attitudes becomes paramount, guiding ethical regulation, innovation, and public engagement strategies. This study provides valuable insights into the intricate dynamics surrounding AI acceptance and highlights the importance of adapting measures to evolving perceptions and attitudes among the general public.

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Section: Literature Reviewmentioning

confidence: 99%

Are skepticism and moderation dominating attitudes toward AI‐based technologies?

Oprea,

Nica,

Bâra

et al. 2024

American J Econ Sociol

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show abstract

“…However, some students also expressed concerns about the lack of human interaction and the potential for errors or technical glitches. Another example is Hu's (2022) study that examined the factors affecting students' use of an AI-supported smart learning environment system and found that perceived ease of use and perceived usefulness influenced students' behavioural intention. Bonsu and Baffour-Koduah (2023) explored the perceptions and intentions of Ghanaian higher education students towards using ChatGPT, using a mixed-method approach guided by the Technology Acceptance Model (TAM) with a sample size of 107 students.…”

Section: Literature On Student's Perception Of Ai and Genaimentioning

confidence: 99%

An expectancy value theory (EVT) based instrument for measuring student perceptions of generative AI

Chan,

Zhou

2023

Smart Learn. Environ.

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This study examines the relationship between student perceptions and their intention to use generative artificial intelligence (GenAI) in higher education. With a sample of 405 students participating in the study, their knowledge, perceived value, and perceived cost of using the technology were measured by an Expectancy-Value Theory (EVT) instrument. The scales were first validated and the correlations between the different components were subsequently estimated. The results indicate a strong positive correlation between perceived value and intention to use generative AI, and a weak negative correlation between perceived cost and intention to use. As we continue to explore the implications of GenAI in education and other domains, it is crucial to carefully consider the potential long-term consequences and the ethical dilemmas that may arise from widespread adoption.

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“…Recently, improvements in image and video processing have allowed for the use of AI in learning environments to track student behaviour using facial recognition, recognize gestures, and identify social interactions and emotional states (Hu, 2022). Natural language processing technologies specifically have been of interest in education, primarily for automated writing evaluation (Wilson et al, 2021).…”

Section: Causes Technological Driversmentioning

confidence: 99%

A Scenario for the Future of AI and Technology in Public Education

Garza¹,

Farrow²,

Lam³

et al. 2022

iJournal

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Using narrative writing techniques, four authors use a “what if” approach to explore a future possible scenario, set in the year 2037, to reflect on looming changes in an increasingly technological human environment. The purpose of this imaginative exercise is not to pinpoint or predict future events, but to highlight large-scale forces that could push the future of learning in key directions. In this story, we follow a young student through a technology-me- diated experience of daily life. As they navigate their learning environment, we observe some of the challenges and opportunities that this student may face including personalized learning technologies, data tracking, and automated decision systems—all tools which come to firmly define this student’s envi- ronment and potential prospects. The authors follow the scenario by breaking down the major influences and forces behind this possible future reality. This analysis provides a view of the ethical dilemmas raised in such a future world and concludes with a series of proposed solutions: proactive governmental in- volvement, a reimagining of industry best practices, and an emphasis on con- text-aware, community-led, future-building initiatives.

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Effects and acceptance of precision education in an AI-supported smart learning environment

Cited by 29 publications

References 68 publications

Are skepticism and moderation dominating attitudes toward AI‐based technologies?

Are skepticism and moderation dominating attitudes toward AI‐based technologies?

An expectancy value theory (EVT) based instrument for measuring student perceptions of generative AI

A Scenario for the Future of AI and Technology in Public Education

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