Journal ArticleDOI
The impact of knowledge management practices on the acceptance of Massive Open Online Courses (MOOCs) by engineering students: A cross-cultural comparison
TLDR
A cross-cultural analysis of the impact of knowledge management (KM) practices on the acceptance of Massive Open Online Courses (MOOCs) suggested cultural differences in patterns between acceptance behaviors of engineering students in Malaysia and Turkey.About:
This article is published in Telematics and Informatics.The article was published on 2020-07-14. It has received 63 citations till now. The article focuses on the topics: Knowledge sharing & Technology acceptance model.read more
Citations
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Journal ArticleDOI
Knowledge management in two universities before and during the COVID-19 effect in Peru
TL;DR: In this article, a case study has been developed in Lima, associated to two universities with 271 teachers and 5928 students; with this model could be used for knowledge management assessment in all university in Peru.
Journal ArticleDOI
Key factors in MOOC pedagogy based on NLP sentiment analysis of learner reviews: What makes a hit
TL;DR: In this paper, the authors apply a crowdsourcing approach and interpret the semantics of reviews for the top-rated courses on Coursera.org to explore the answers of what makes a great MOOC? What makes a hit?
Journal ArticleDOI
Key factors in MOOC pedagogy based on NLP sentiment analysis of learner reviews: What makes a hit
TL;DR: In this paper , the authors apply a crowdsourcing approach and interpret the semantics of reviews for the top-rated courses on Coursera.org to explore the answers of what makes a great MOOC? What makes a hit?
Journal ArticleDOI
Massive Open Online Course (MOOCs) Acceptance: The Role of Task-Technology Fit (TTF) for Higher Education Sustainability
TL;DR: In this paper, the authors explored the role of task-technology fit (TTF) as a mediating variable in evaluating education sustainability, which had a positive impact on student satisfaction, academic performance, and long-term viability of MOOCs in higher education.
Journal ArticleDOI
Understanding the impact of knowledge management factors on the sustainable use of AI-based chatbots for educational purposes using a hybrid SEM-ANN approach
Mohammed R. A. AL-Sharafi,Mostafa Al-Emran,Mohammad Iranmanesh,Noor Al-Qaysi,Noorminshah A. Iahad,Ibrahim Arpaci +5 more
TL;DR: In this article , the authors developed a theoretical model based on extracting constructs from the expectation confirmation model (ECM) (expectation confirmation, perceived usefulness, and satisfaction), combined with knowledge management (KM) factors (knowledge sharing, knowledge acquisition, and knowledge application) to understand the sustainable use of chatbots.
References
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Journal ArticleDOI
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Claes Fornell,David F. Larcker +1 more
TL;DR: In this paper, the statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined, and a drawback of the commonly applied chi square test, in additit...
Perceived Usefulness, Perceived Ease of Use, and User
TL;DR: Regression analyses suggest that perceived ease of use may actually be a causal antecdent to perceived usefulness, as opposed to a parallel, direct determinant of system usage.
Journal ArticleDOI
Perceived usefulness, perceived ease of use, and user acceptance of information technology
TL;DR: In this article, the authors developed and validated new scales for two specific variables, perceived usefulness and perceived ease of use, which are hypothesized to be fundamental determinants of user acceptance.
Book
Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research
Martin Fishbein,Icek Ajzen +1 more
Journal ArticleDOI
User acceptance of information technology: toward a unified view
TL;DR: The Unified Theory of Acceptance and Use of Technology (UTAUT) as mentioned in this paper is a unified model that integrates elements across the eight models, and empirically validate the unified model.
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