Investigating Safety Awareness in Assembly Operations via Mixed Reality Technology DOI
Israa Azzam, Souvik Das, Gaurav Nanda

et al.

IISE Transactions on Occupational Ergonomics and Human Factors, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 17

Published: Dec. 4, 2024

We investigated the impact of using Mixed Reality (MR) technology as a training tool to help trainees identify safety risks during machine assembly tasks, by analyzing their task completion efficiency and risk estimation capabilities. As proof-of-concept, an interactive MR module on hydraulic gripper was designed incorporated in fluid power laboratories be tested with mechanical engineering students. The developed environment evaluated accident causation models. An analysis revealed smooth operation minimal challenges. Incorporating modules into programs allows practitioners provide hands-on experience simulated while identifying potential risks. Addressing limitations, such simulating physical feedback more accurately, will crucial for optimizing future effectiveness technology.

Language: Английский

Text Mining and Multi-Attribute Decision-Making-Based Course Improvement in Massive Open Online Courses DOI Creative Commons
Yang Pei, Liu Ying, Yuyan Luo

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(9), P. 3654 - 3654

Published: April 25, 2024

As the leading platform of online education, MOOCs provide learners with rich course resources, but designers are still faced challenge how to accurately improve quality courses. Current research mainly focuses on learners’ emotional feedback different attributes, neglecting non-emotional content as well costs required these attributes. This limitation makes it difficult for fully grasp real needs and locate key issues in course. To overcome above challenges, this study proposes an MOOC improvement method based text mining multi-attribute decision-making. Firstly, we utilize word vectors clustering techniques extract attributes that focus from their comments. Secondly, help some deep learning methods BERT, conduct a sentiment analysis comments reveal tendencies towards Finally, adopt decision-making TOPSIS comprehensively consider score, attention, content, providing priority ranking attribute improvement. We applied two typical programming courses—C language Java language. The experimental findings demonstrate our approach effectively identifies reviews, assesses satisfaction, cost improvement, ultimately generates prioritized list provides new improving courses contributes sustainable development quality.

Language: Английский

Citations

4
Evaluating the quality of digital education resources based on learners’ online reviews through topic modeling and opinion mining DOI
Lin Zhang, Qi Li, Weiyan Xiong

et al.

Education and Information Technologies, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 6, 2025

Language: Английский

Citations

0
Nexus between generative AI engagement, quality and expectation formation: an application of expectation–confirmation theory DOI
Mai Nguyen, Ankit Mehrotra,

Ashish Malik

et al.

Journal of Enterprise Information Management, Journal Year: 2025, Volume and Issue: unknown

Published: March 4, 2025

Purpose Generative Artificial Intelligence (Gen-AI) has provided new opportunities and challenges in using educational environments for students’ interaction knowledge acquisition. Based on the expectation–confirmation theory, this paper aims to investigate effect of different constructs associated with Gen-AI engagement, satisfaction word-of-mouth. Design/methodology/approach We collected data from 508 students UK Qualtrics, a prominent online collection platform. The conceptual framework was analysed through structural equation modelling. Findings findings show that expectation formation quality help boost engagement. Further, we found active engagement positively affects positive word mouth. mediating role confirmation between two outcomes, mouth, also confirmed. moderating cognitive processing relationship found. Originality/value This extends Expectation-Confirmation Theory how can enhance satisfaction. Suggestions future research are derived advance beyond confines current study capture development use AI education.

Language: Английский

Citations

0
Effects of sentiment discreteness on MOOCs’ disconfirmation: text analytics in online reviews DOI
Wei Wang, Haiwang Liu, Yenchun Jim Wu

et al.

Interactive Learning Environments, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 18

Published: Aug. 20, 2024

In Massive Open Online Courses (MOOCs), online reviews serve as a basis for teachers to improve their courses. The disconfirmation effect of reviews, i.e. the inconsistency between level attention paid course factor and actual weight that factor's influence on learner satisfaction, leads erroneous judgments by teachers. Based two-factor theory emotion, 4,070 courses 165,705 are adopted corpus identify sentiment effect. empirical results show there is significant negative but not positive ones. A fine-grained analysis finds containing more sadness anger sentiments have stronger comparison types reveals instrument-based than knowledge-based practice-based addition, word-of-mouth weakens enhances reviews. Further, learner's reputation

Language: Английский

Citations

0
Investigating Safety Awareness in Assembly Operations via Mixed Reality Technology DOI
Israa Azzam, Souvik Das, Gaurav Nanda

et al.

IISE Transactions on Occupational Ergonomics and Human Factors, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 17

Published: Dec. 4, 2024

We investigated the impact of using Mixed Reality (MR) technology as a training tool to help trainees identify safety risks during machine assembly tasks, by analyzing their task completion efficiency and risk estimation capabilities. As proof-of-concept, an interactive MR module on hydraulic gripper was designed incorporated in fluid power laboratories be tested with mechanical engineering students. The developed environment evaluated accident causation models. An analysis revealed smooth operation minimal challenges. Incorporating modules into programs allows practitioners provide hands-on experience simulated while identifying potential risks. Addressing limitations, such simulating physical feedback more accurately, will crucial for optimizing future effectiveness technology.

Language: Английский

Citations

0