Optimising textual analysis in higher education studies through computer assisted qualitative data analysis (CAQDAS) with ATLAS.ti

  1. Ludovica Mastrobattista 1
  2. María Muñoz-Rico 1
  3. José Antonio Cordón-García 1
  1. 1 Universidad de Salamanca
    info

    Universidad de Salamanca

    Salamanca, España

    ROR https://ror.org/02f40zc51

Revista:
JOTSE

ISSN: 2013-6374

Año de publicación: 2024

Volumen: 14

Número: 2

Páginas: 622-632

Tipo: Artículo

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Otras publicaciones en: JOTSE

Resumen

The main objective of this article is to highlight the importance of training in digital tools at the university level to foster the development of innovative and efficient data analysis from a scientific perspective. In an increasingly digitised world, the acquisition of digital skills has become a fundamental requirement for success in various disciplines, especially in conducting academic studies and research. The implementation of Computer-Aided Qualitative Data Analysis (CAQDAS) software, such as the ATLAS.ti platform, for text analysis not only enriches the educational experience but also prepares students to excel in an ever-evolving digital environment and raise the quality of their research. We present here a practical example of textual analysis in ATLAS.ti that can serve as a reference guide for similar studies based on content analysis of interviews. Various qualitative and quantitative data analysis options and techniques are explored that allow researchers to identify patterns, trends and relationships in the texts analysed, which contributes to a deeper understanding of the topics under study by transcending traditional methods of text analysis.

Referencias bibliográficas

  • Al-Hail, M., Zguir, M.F., & Koç, M. (2023). University students’ and educators’ perceptions on the use of digital and social media platforms: A sentiment analysis and a multi-country review. iScience, 26 (8), 107322. https://doi.org/10.1016/j.isci.2023.107322
  • Baron, N.S. (2021). How we read now: Strategic choices for print, screen and audio. New York: Oxford University Press. https://doi.org/10.1093/oso/9780190084097.001.0001
  • Battershill, C., & Ross, S. (2022). Using Digital Humanities in the Classroom (2nd ed.). Bloomsbury Academy. https://doi.org/10.5040/9781350180932
  • Contreras, R.B. (2011). Examining the Context in Qualitative Analysis: The Role of the Co-Occurrence Tool in ATLAS.ti. ATLAS.ti Newsletter, 2(August), 5-6.
  • De Pablos, J.M., Colás, M.P., López-Gracia, A., & García-Lázaro, I. (2019). Los usos de las plataformas digitales en la enseñanza universitaria. Perspectivas desde la investigación educativa. REDU. Revista de Docencia Universitaria, 17(1), 61. https://doi.org/10.4995/redu.2019.11177
  • Esteve-Mon, F.M., Postigo-Fuentes, A.Y., & Castañeda, L. (2023). A strategic approach of the crucial elements for the implementation of digital tools and processes in higher education. Higher Education Quarterly, 77(3), 558-573. https://doi.org/10.1111/hequ.12411
  • Giraldo de López, M., Camargo-Toribio, I.A., Ortiz-Ordaz, F., & Martínez-Gil, L. (2019). Methodological perspective using data-based theory and ATLAS.ti to explain the culture towards work in higher education institutions. CISCI 2019 - Décima Octava Conferencia Iberoamericana en Sistemas, Cibernética e Informática, Décimo Sexto Simposium Iberoamericano en Educación, Cibernética e Informática - Memorias (2, 59-64).
  • Guetterman, T.C., & James, T.G. (2023). A software feature for mixed methods analysis: The MAXQDA Interactive Quote Matrix. Methods in Psychology, 8, 100116. https://doi.org/10.1016/j.metip.2023.100116
  • Hart, T., & Achterman, P. (2017). Qualitative Analysis Software. The International Encyclopedia of Communication Research Methods, 1-12. https://doi.org/10.1002/9781118901731.iecrm0194
  • Kapaniaris, A., & Dimitriou, A. (2023). Digital humanities and digital narrative. Research on E-Learning and ICT in Education (183-194). Springer. https://doi.org/10.1007/978-3-031-34291-2_11
  • Mastrobattista, L., & Merchán-Sánchez-Jara, J. (2022). Identificación y análisis de factores de desapego de la Lectura Digital en el entorno académico: una revisión crítica de la literatura. El Profesional de La Información, 31(2). https://doi.org/10.3145/epi.2022.mar.07
  • Mills, C.W. (2000). The sociological imagination. Oxford University Press.
  • Muñoz-Justicia, J., & Sahagún-Padilla, M.Á. (2011). Análisis Cualitativo Asistido Por Ordenador Con ATLAS.Ti. In Izquierdo, C., & Perinat, A. (Eds.), Investigar en Psicología de la Educación. Nuevas Perspectivas Conceptuales y Metodológicas (299-363).
  • Rahaman, V., & Haider, A. (2021). Deconstructive Big Data Analytics: Literary Texts Analysis Through Atlas.ti Software. In Sharma, S., Rahaman, V., & Sinha, G.R. (Eds.), Big Data Analytics in Cognitive Social Media and Literary Texts: Theory and Praxis (47-63). https://doi.org/10.1007/978-981-16-4729-1_3
  • Reyna-Mendoza, D.N. (2023). Herramientas digitales en entornos educativos de formación universitaria. Una Revisión sistemática. Revista de Climatología, 23, 318-327. https://doi.org/10.59427/rcli/2023/v23cs.318-327
  • Sabariego-Puig, M., Vilà-Baños, R., & Sandín-Esteban, M.P. (2014). El análisis cualitativo de datos con ATLAS.ti. REIRE. Revista d’Innovació i Recerca en Educació, 7(2), 119-133. https://doi.org/10.1344/reire2014.7.2728
  • San Martín-Cantero, D. (2014). Teoría fundamentada y Atlas.ti: recursos metodológicos para la investigación educativa (Grounded Theory and Atlas. ti: Methodological Resources for Educational Research). Revista Electrónica de Investigación Educativa, 16(1), 104-122.
  • Smit, B. (2021). Introduction to ATLAS.ti for mixed analysis. In Anthony, J., Onwuegbuzie, & Johnson, R.B. (Eds.), The Routledge Reviewer’s Guide to Mixed Methods Analysis (331-341), Routledge. https://doi.org/10.4324/9780203729434
  • Soratto, J., Pires, D.E.P. de, & Friese, S. (2020). Thematic content analysis using ATLAS.ti software: Potentialities for researchs in health. Revista Brasileira de Enfermagem, 73(3), e20190250. https://doi.org/10.1590/0034-7167-2019-0250
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