When data are collected in native language and translated into English language, the underlying sociocultural meaning of participants' speech can be missed. This paper discusses a new contextual coding approach and illustrates its application in research. The technique was used in ...
While there is widespread concern within the community about the use of AI tools (van Dis et al., 2023), our focus in this perspective is on the positive opportunities for responsibly using AI, specifically large language models (LLMs), to assist with coding, both for research and in the...
You can also code to gather content at nodes that represent the subjects of your research, such as people or places. For example, if you have survey responses from a class of students, you can create a case node to represent each student, and then code their opinions at their case node....
The vastity of histological, neurophysiological, and behavioral data collected during the last century, together with new technological advancements, including genetic tools, confirm the honeybee as an attractive research model for understanding olfactory coding and learning....
(Shute et al.,2017; Voogt et al.,2015), much research investigating computational thinking for coding in schools is devoid of ‘critical thinking’, as understood in the humanities more broadly. With this, there is an absence of discussion around the political philosophy framing the society and...
The process of coding can generate ideas and help you to identify patterns and theories in your research material. For example, you could gather all the negative opinions about a policy and examine them together in a node—from there, you could tease out common threads and ask questions like...
Automated clinical coding (ACC) has emerged as a promising alternative to manual coding. This study proposes a novel human-in-the-loop (HITL) framework, CliniCoCo. Using deep learning capacities, CliniCoCo focuses on how such ACC systems and human coders
comparison and computation with other sentences. These embedders have been trained on large corpora of textual data to learn highly generic semantic relations between sentences. The goal is to encode the sentence so that similar sentences (in terms of meaning) are close in the embedding space, ...
Go beyond text, find meaning. Rapid Insight, Real Impact: The Role of Thematic Analysis in Crisis Research The Language of Change: A Qualitative Look at Evolving Themes The Unspoken Word: Analysing Silence and Absence in Qualitative Data
This is a bold value proposition and one that deserves in-depth analysis. If coding bootcamps are successfully bridging the technology talent gap, the model could have a major impact on the post-secondary training market.For Career Karma’s most up-to-date research into the state of the ...