Using NVivo to Answer the Challenges of Qualitative Research in Professional Communication: Benefits and Best Practices Tutorial

Hoover, Ryan; Koerber, Amy

doi:10.1109/tpc.2009.2036896

Cited by 119 publications

(74 citation statements)

References 17 publications

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“…Since, qualitative analysis can be significantly facilitated by the use of Computer-Assisted Qualitative Data Analysis Software (CAQDAS), in this research Nvivo was selected to perform the analysis and coding of the interviews. Nvivo is one of the most popular CAQDAS (Hoover & Koerber, 2011;Ozkan, 2004). One of the advantages of using Nvivo is that it allows the coding scheme to be viewed hierarchically.…”

Section: Methodsmentioning

confidence: 99%

Validation of an e-Learning 3.0 Critical Success Factors Framework: A Qualitative Research

et al. 2017

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Aim/PurposeAs e-Learning 3.0 evolves from a theoretical construct into an actual solution for online learning, it becomes crucial to accompany this progress by scrutinising the elements that are at the origin of its success. Background This paper outlines a framework of e-Learning 3.0's critical success factors and its empirical validation. MethodologyThe framework is the result of an extensive literature review and its empirical substantiation derives from semi-structured interviews with e-Learning experts. ContributionThe viewpoints of the experts enable the confirmation and the refinement of the original framework and serve as a foundation for the prospective implementation of e-Learning 3.0. FindingsThe analysis of the interviews demonstrates that e-Learning 3.0 remains in its early stages with a reticent dissemination. Nonetheless, the interviewees invoked factors related to technology, content and stakeholders as being critical for the success of this new phase of e-Learning. Recommendations for PractitionersPractitioners can use the framework as a guide for promoting and implementing effective e-Learning 3.0 initiatives. Validation of an e-Learning 3.0 Critical Success Factors Framework 340 Recommendation for ResearchersAs a new phenomenon with uncharted potential, e-Learning 3.0 should be placed at the centre of educational research. Impact on Society The understanding of what drives the success of e-Learning 3.0 is fundamental for its implementation and for the progress of online education in this new stage of its evolution. Future ResearchFuture research ventures can include the design of quantitative and selfadministered data collection instruments that can provide further insight into the elements of the framework.

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Section: Methodsmentioning

confidence: 99%

Validation of an e-Learning 3.0 Critical Success Factors Framework: A Qualitative Research

et al. 2017

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“…Verbatim transcriptions of the audiotaped session were generated and the researcher read all the transcriptions to familiarize herself with the data. The focus group transcriptions were imported into Nvivo 11.0 for thematic analysis [15]. NVivo helps a researcher to manage and organize the data and facilitates the process of analysis, identification of themes, collecting insights and developing conclusions [16].…”

Section: Data Analysis Thematic Analysismentioning

confidence: 99%

Multidisciplinary Smartphone-Based Interventions to Empower Patients With Acute Coronary Syndromes: Qualitative Study on Health Care Providers’ Perspectives (Preprint)

Bashi¹,

Hassanzadeh²,

Varnfield³

et al. 2018

Preprint

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“…Social network analysis offers a method for mapping group interactions, communication, and dynamics. The methods are usually implemented using computer-assisted qualitative data analysis software such as NVivo (Hoover & Koerber, 2011). This method codes the contributions into units of meaning which are assigned to parts of messages based on semantic features.…”

Section: Related Work About Forum Analysismentioning

confidence: 99%

A Computational Method for Enabling Teaching-Learning Process in Huge Online Courses and Communities

Mora

Ferrández

Gil

et al. 2017

IRRODL

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Massive Open Online Courses and e-learning represent the future of the teaching-learning processes through the development of Information and Communication Technologies. They are the response to the new education needs of society. However, this future also presents many challenges such as the processing of online forums when a huge number of messages are generated. These forums provide an excellent platform for learning and connecting students of the subject, but the difficulties in following and searching the vast volume of information that they generate may produce the opposite effect. In this paper, we propose a computational method for enabling the educational process in huge online learning communities. This method analyses the forum information through Natural Language Processing techniques and extract the main topics discussed. The results generated improves the management of the forums, increases the effectiveness of the teachers' explanations and reduces the time spent by students to follow the course. The proposal has been complemented with a real case study that shows promising results.Keywords: natural language processing, topic detection, distance learning, online forum, mooc managing, However, there are still challenges that should be specifically addressed in order to achieve the effective ODL provision and to maintain excellent educational standards. One of the most powerful and popular tools are online forums (Mora, Signes Pont, DeMiguel Casado, & Gilart Iglesias, 2015). Online forums are a communication technology tool in education and provide an excellent platform for learning and connecting students to the subject. The expected roles of the forums are to increase engagement of students in the subject, promote deep learning, and maintain motivation (Onah et al., 2014).Technological advances and computing methods may provide tools for enhancing these roles and facilitating the educational process. In this way, artificial intelligence approaches based on NaturalLanguage Processing (NLP) should deliver tools specifically aimed at students and teachers to make the assimilation of content and course tracking easier for students, and to provide mechanisms to manage the learning platforms by teachers. The working hypothesis of our research is that this kind of solution can be used to better engage the students and teachers in online platforms with huge forums by enabling the knowledge management and learning-teaching processes. Under our approach, the main objective of our work is to provide automatic tools and applications to facilitate tracking and monitoring online learning communities through the automatic processing of forums of lexical, syntactic, and semantic analysis; clustering; and information retrieval techniques. A Computational Method for Enabling Teaching-Learning Process in Huge Online Courses and Communities Mora, Ferrández, Gil, and Peral 227The remainder of the paper is structured as follows: Section 2 describes the problem of management and monitoring forums in huge online ...

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Using NVivo to Answer the Challenges of Qualitative Research in Professional Communication: Benefits and Best Practices Tutorial

Cited by 119 publications

References 17 publications

Validation of an e-Learning 3.0 Critical Success Factors Framework: A Qualitative Research

Validation of an e-Learning 3.0 Critical Success Factors Framework: A Qualitative Research

Multidisciplinary Smartphone-Based Interventions to Empower Patients With Acute Coronary Syndromes: Qualitative Study on Health Care Providers’ Perspectives (Preprint)

A Computational Method for Enabling Teaching-Learning Process in Huge Online Courses and Communities

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