Factors driving the adoption of m-learning: An empirical study

By Yong Liu, Hongxiu Li, Christer Carlsson. Comput. Educ., 2010

481 citations recorded by the source corpus.

Subfields: Information Systems and Management, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/cfeed5a4b5c4a54c9333298ab0809e0f3f0433d1

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In Information Systems and Management

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Citations in the corpus

Understanding the Blockchain technology adoption in supply chains-Indian context (2018, background): “Perceived ease of use refers to the degree to which a person believes that using a particular system would be free of effort (Davis 1989; Liu, Li, and Carlsson 2010).”
An empirical examination of continuous intention to use m-learning: An integrated model (2020, background): “In another study, Liu et al. (2010) suggested that personal innovativeness significantly predicts students ’ behavioral intention to use mobile technology.”
Factors influencing students’ acceptance of m-learning: An investigation in higher education (2013, background): “This could suggest an effective strategy to motivate students with high innovativeness at the early stage of the adoption of m-learning, as it has a positive affect on performance expectancy and effort expectancy (Zampou et al., 2012; Liu et al., 2010).”
An investigation of mobile learning readiness in higher education based on the theory of planned behavior (2012, methodology): “For example, instructional content for m-learning should be adapted to the small screen size (Lowenthal, 2010).”
Developing a General Extended Technology Acceptance Model for E-Learning (GETAMEL) by analysing commonly used external factors (2016, result): “…the results of previous e-learning studies (including Ifinedo, 2006, p.12; Lee, Hsiao & Purnomo, 2014, p.572; Lee, Hsieh & Chen, 2013, p.182; Liu, Li & Carlsson, 2010, p.1217; Shen & Chuang, 2010, p.205) show that extended TAM models provided good explanatory power, with total variance,…”
A model of acceptance of augmented-reality interactive technology: the moderating role of cognitive innovativeness (2014, background): “Liu et al. [43] added personal innovativeness [1] to their model, with the construct being deﬁned as an individual’s disposition toward trying any new information technology.”
Investigating users' perspectives on e-learning: An integration of TAM and IS success model (2015, background): “Liu, Li, and Carlsson (2010) indicated that perceived near-term/long-term usefulness and personal innovativeness significantly affect intention towards m-learning adoption, while perceived long-term usefulness had a significant influence on near-term usefulness.”
NFC mobile credit card: The next frontier of mobile payment? (2014, background): “Future studies could include age, experience, education, income (Loke et al., 2011; Amin, 2012) and so on in furthering their exploration on MCC. Lastly, this is a cross-sectional research.”
A meta-analysis of e-learning technology acceptance: The role of user types and e-learning technology types (2011, unknown): “…363 Students E-learning System TAM + TPB + ECM Liu, Chen, Sun, Wible, and Kuo (2010) 436 Students E-learning Technology/Tool (On-line community) TAM Liu, Li, and Carlsson (2010) 220 Students E-learning Technology/Tool (Mobile Learning Tool) TAM Lee, Hsieh, and Ma (2011) 357 Employees…”