Students’ adoption of Twitter as an information source: An exploratory study using the Technology Acceptance Model

Sultan, Mustafa; Al-Daihani, Sultan M.

doi:10.22452/mjlis.vol21no3.4

Cited by 16 publications

(28 citation statements)

References 16 publications

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“…The result suggests that the variables (PE, PEU, and PU) independently explain 72% of the variance of intention to use (R 2 = 0:724). This result is analogous with prior studies, in which R 2 = 0:506 [13], R 2 = 0:372 [18], R 2 = 0:67 [17], and R 2 = 0:53 [31]. Our result indicates that PU is in uenced by SI at = 0:298, thereby con rming H1.…”

Section: Structural Analysissupporting

confidence: 90%

“…Our result indicates that PU is in uenced by SI at = 0:298, thereby con rming H1. This result is similar to the results of [13]. Correspondingly, the path coe cient between SI and BI was determined to be signi cant at = 0:296.…”

Section: Structural Analysissupporting

confidence: 85%

“…Prior studies [11][12][13] have revealed that PU has a positive in uence on PEU. Thus, the easier, simpler, and more user-friendly the activities are for a social media user, the easier it is for him/her to adopt OSNs as a learning tool [26].…”

Section: Perceived Usefulness (Pu) and Perceivedmentioning

confidence: 99%

“…BI BI1 I intend to begin/continue use OSNs to interact with colleagues and lecturers. [11,13] BI2 I will continue to use OSNs as a learning tool. BI3 I will strongly recommend use of OSNs as a learning tool to others.…”

Section: Si3mentioning

confidence: 99%

“…Hence, the factors that in uence the acceptance of OSNs should be identi ed to facilitate the assessment and prediction of the success of adopting new OSNs in universities. Moreover, prior studies [11][12][13][14][15][16][17][18][19][20] have revealed that a limited number of research studies have analyzed the signi cance of the factors that in uence students' intention to use OSNs as learning tools.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

The Acceptance of Online Social Networks as a Technology-Based Education Tools among Higher Institutes Students: A Structural Equation Modeling Approach

et al. 2018

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Educational institutions are adopting Online Social Networks (OSNs) to support learning activities in university campuses. However, implementing a new technology requires identifying and assessing the factors that in uence users' acceptance of a new technology. Accordingly, this method enables the critical prediction of the success or failure of a new technology. This study aims to identify the factors that in uence a student's acceptance of OSNs as a learning tool by developing a research model based on the identi ed factors and on the technology acceptance model. The proposed model was further validated by employing online survey data collected from 537 students of the University Malaysia Pahang. Thereafter, structural equation modeling was utilized to analyze the collected data. Findings provide signi cant implications and considerable value for higher education institutions in adopting improved strategies for implementing OSNs as a learning tool.

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Section: Structural Analysissupporting

confidence: 90%

Section: Structural Analysissupporting

confidence: 85%

Section: Perceived Usefulness (Pu) and Perceivedmentioning

confidence: 99%

Section: Si3mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Acceptance of Online Social Networks as a Technology-Based Education Tools among Higher Institutes Students: A Structural Equation Modeling Approach

et al. 2018

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Citing criteria and its effects on researcher's intention to cite: A mixed‐method study

Xie

Kang

et al. 2022

Asso for Info Science & Tech

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This study explored users' criteria for citation decisions and investigated the effects on users' intention to cite using a mixed-method approach. A qualitative study was conducted first, where 16 citing criteria were identified based on interviews and inductive analysis. The findings were then used to develop hypotheses and extend the information adoption model. A questionnaire was designed to collect data from users in Chinese universities to test the research model. The findings indicated that pleasure, topicality, and functionality significantly increased users' perceived information usefulness, while familiarity and accessibility significantly enhanced users' perceived ease of use. Information usefulness and information ease of use further contributed to users' intention to cite with adjusted R 2 equaling 44.6%. It is also found that perceived academic quality based on 5 antecedents (i.e., reliability, comprehensiveness, novelty, author credibility, and source reputation) significantly increased users' pleasure. Implications and limitations were provided.

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Behavioral Intention of Students in Higher Education Institutions Towards Online Learning During COVID-19

Alajmi

Al-Sharafi

Yassin

2021

Studies in Systems, Decision and Control

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Across the world, Higher Education Institutions (HEIs) were mandatory to transform their teaching model from face-to-face interaction to online learning. Neither the faculty nor the students were ready for this sudden transformation, most of the HEIs were practicing online learning for the sake of changing or technology adoption. COVID-19 changes the HEIs standpoint towards online delivery, as of mid of March 2020, the only online learning come to be the reasonable solution for teaching in schools and HEIs. Therefore, this study aimed to develop a research model to explore the effect of perceived enjoinment, perceived ease of use, perceived usefulness, social influence on the students' intention and behavioral towards online learning during COVID-19 in Oman. The developed model was validated by employing Structural Equation Modeling (SEM) and the data collected via online questionnaire from 191 students whom have just completed the "Educational Technology" course on Spring 2020 at A'Sharqiyah University-Oman (ASU). The main finding of this study indicating that the identified factors; PEOU and SI significantly influenced students' Behavioral Intention (BI) towards online learning, where others; PE and PU were not supported in this study.

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Students’ adoption of Twitter as an information source: An exploratory study using the Technology Acceptance Model

Cited by 16 publications

References 16 publications

The Acceptance of Online Social Networks as a Technology-Based Education Tools among Higher Institutes Students: A Structural Equation Modeling Approach

The Acceptance of Online Social Networks as a Technology-Based Education Tools among Higher Institutes Students: A Structural Equation Modeling Approach

Citing criteria and its effects on researcher's intention to cite: A mixed‐method study

Behavioral Intention of Students in Higher Education Institutions Towards Online Learning During COVID-19

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