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The KJ Method: A Technique for Analyzing Data Derived from Japanese Ethnology

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Abstract

This essay is a discussion of the KJ method developed by a Japanese ethnologist, Jiro Kawakita. A brief biography of Kawakita and the history of the KJ method is described. The KJ method was developed as a result of having difficulties in interpreting ethnographic data in Nepal. The KJ method builds upon Charles Pierce's notions of abduction and relies upon intuitive non-logical thinking processes. Kawakita's methods were developed and diffused throughout Japanese management and educational circles. Kawakita believes that his methodology has the potential of liberating humanity from the mechanistic philosophy imposed by Western Civilization. The KJ mthod, according to Kawakita has universal applicability and does not only conform to Japanese culture and management decision-making processes which are generally based on the group-orientation model. This simplistic group-orientation model of Japanese society is being criticized by anthropologists such as Harumi Befu. Kawakita argues that human nature is universal, and that the KJ method, as a means of decision-making can be utilized in all societies throughout the world to implement social and economic development.
... REDCap (Research Electronic Data Capture) is a secure, web-based software platform designed to support data capture for research studies. We used content analysis, affinity mapping [14,25] and rapid qualitative data analysis methods [26] We summarized frequencies of the participant-preferred messages and modes at each study site. We analyzed ideal experience storyboards using affinity diagramming, a collaborative activity to organize related or similar storyboards into distinct, mutually exclusive clusters. ...
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Introduction: A traceback genetic testing program for ovarian cancer has the potential to identify individuals with hereditary breast and ovarian cancer and their relatives. Successful implementation depends on understanding and addressing the experiences, barriers, and preferences of the people served. Methods: We conducted a remote, human-centered design research study of people with ovarian, fallopian tube, or peritoneal cancer (probands) and people with a family history of ovarian cancer (relatives) at three integrated health systems between May and September 2021. Participants completed activities to elicit their preferences about ovarian cancer genetic testing messaging, and to design their ideal experience receiving an invitation to participate in genetic testing. Interview data were analyzed using a rapid thematic analysis approach. Results: We interviewed 70 participants and identified five preferred experiences for a traceback program. Participants strongly prefer discussing genetic testing with their doctor but are comfortable discussing with other clinicians. The most highly preferred experience for both probands and relatives was to discuss with a knowledgeable clinician who can answer questions, followed by directed (sent directly to specific people) or passive (shared in a public area) communication. Repeated contact was acceptable for reminders. Discussion/conclusion: Participants were open to receiving information about traceback genetic testing and recognized its value. Participants preferred discussing genetic testing with a trusted clinician. Directed communication was preferable to passive communication. Other valued information included how genetic tests help their family and the cost of genetic testing. These findings are informing traceback cascade genetic testing programs at all three sites.
... To merge the same or similar attribute items by the KJ simplification method [37], and repeat the step until no more grouping is possible, to obtain a clear attractive factor of the product. ...
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... We have considered the core categories as design influencing factors, found design opportunities from user needs and pain points, and translated them into specific design guidelines (see Table 1). Based on the design opportunities obtained from the above analysis, six design guidelines were summarized in an affinity way by the A-scheme diagramming method [45]. This approach collects linguistic information about the problem to be solved and uses the relationships inherent in the text to categorize and merge them hierarchically. ...
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With the rapid development of science and technology, the ability to creative thinking has become an essential criterion for measuring talents. Current creative thinking courses for college students are affected by COVID-19 and are challenging to conduct. This study aimed to explore practical ways to teach creative thinking knowledge online and explored design opportunities for working on this teaching activity online. Through qualitative interviews, we found that the factors that influenced the design of the online virtual simulation course platform were focused on five dimensions: information presentation, platform characteristics, course assessment, instruction design, and presentation format. Through the analysis of user requirements, we obtained six corresponding design guidelines. Based on the knowledge system of design thinking, we set up eight modules in the course platform and developed a prototype including 100 user interfaces. We invited three experts and 30 users to conduct cognitive walk-through sessions and made design iterations based on the feedback. After user evaluation, dimensions of attractiveness, efficiency, dependability, and novelty reached excellent rating and were recognized by users.
... The search results obtained from the survey were categorised by similar content following the KJ method (Kawakita, 1967) and focussing on each type of content. The KJ method is a qualitative analysis method developed by Jiro Kawakita, a Japanese cultural anthropologist, that creates groups through inductive categorisation and conceives new ideas from the relationships between the groups (Scupin, 1997). Regarding the specific procedures, the contents of each form of assistance were written as sticky notes. ...
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... This method can assist researchers in collecting the required data from respondents consisting of Community College students of TVET fashion programme. According to Raymond Scupin [7], the use of KJ's method can help researchers in obtaining information easily and effectively using keywords related to issues and problems faced by TVET fashion programme students. ...
... Coding was done through a pre-coded list and developed based on the rural livelihoods' analytical framework; however, codes also emerged in an inductive process (Miles & Huberman, 1994). After coding, all the information, structured with the K-J method (Scupin, 1997), allowed identifying patterns and triangulating information through networks. For a better treatment, organization, and reduction of the amount of information, the ATLAS.ti ...
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The affinity research approach also known as the Kawakita Jiro or KJ method, (also referred to as an “affinity diagram”) was created by Japanese anthropologist Jiro Kawakita in the 1960s. Kawakita, a cultural anthropologist, was searching for a method to organize data collected from various cultures.
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