In the article, Beyond analytics: using computer-aided methods in educational research to extend qualitative data analysis, Vieira and colleagues identified a gap within educational research by looking at using computer-aided methods as a means to quantify qualitative data. The authors provided guidelines as to how this translation should be completed through the form of the assessment triangle, a framework used to “design valid assessments” within the field of education (Vieira et. al, 2024). This includes three corners/pillars: cognition, observation and interpretation. Through the cognition corner, individuals should align their research with theories or conceptual hypotheses that explain how learners develop knowledge or how individuals perceive specific issues within the field of education. The observation corner describes identifying and characterizing topics such as student performance and behaviors as well as identifying evidence of learning. Finally, the interpretation corner allows for the individual to then translate the findings of the observation corner to understand, analyze, and present the results found through the other corners. To support these guidelines, Vieira and colleagues provided three examples through studies which, when using this framework, display a quantifiable view of the qualitative results. The authors conclude based on these examples, in addition to the framework, that the assessment triangle is an effective means to using a principle-based approach in ,”to integrate these methods in a meaningful manner,” (Vieira et. al, 2024). This framework allows for an extension of qualitative data through the use of computer-aided methods. 

Vieira et. al (2024)’s proposal is backed by three various studies that collected qualitative research. The presentation of each study’s results, while they could be challenging to interpret at first, do allow for the individual to visualize the qualitative data. Each study was explicitly explained through the lens of the framework mentioned and provided tangible means of applying this framework to educational studies. Further, the authors’ organization of this information was presentable and varying. This allows for the reader to see a myriad of presentations of qualitative data, with 5-6 examples. This organization and clear presentation of the article allows the reader to not only clearly identify how this framework is applied, but also address a major concern in qualitative research which is in presenting clear and concise results using computer-aided programs to do so.

One of the major topics we had discussed previously in our course is the optimal need for quantitative and qualitative research in many educational research topics. While data can present statistics that are easy to digest and interpret for the common figure, what is often missing is the context surrounding these data measures to understand why this study yielded specific results. Vieira et. al’s work is applicable to any research but it is certainly most applicable to educational research in that it highlights that qualitative can be represented and quantified quantitatively by following the proposed guidelines. I have noticed a trend specifically for myself in that while I am intrigued in these articles the last four weeks, I have found nothing that has jumped out at me as a research topic. That said, this article continues to add to my understanding and perspective of the type of research I want to be mindful of and do moving forward. What I think this article has certainly done for me is press forward my desire to include various methods of research in whatever I chose to research throughout my doctorate. It will obviously be determined by my research question, but in that, I want to be open and aware of the possible angles and methods I can use to approach my question. These articles have helped to develop a picture for me of how I view the work and research and what parameters I want to set for myself along this journey. 

Sources
C. Vieira, J. D. Ortega-Alvarez, A. J. Magana, and M. Boutin, Beyond analytics: using computer-aided methods in educational research to extend qualitative data analysis, Comput. Appl. Eng. Educ. 32, (2024), e22749. https://doi.org/10.1002/cae.22749

Link to the article