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Judith Glaesser – Field Methods, 2025
In qualitative comparative analysis, as with all methods, there is a question about how many cases are needed to make an analysis robust. In deciding on the number of cases, a key consideration is the number of conditions to be analyzed. I suggest that adding cases is preferable to dropping conditions if there are too many conditions relative to…
Descriptors: Comparative Analysis, Robustness (Statistics), Sampling, Case Studies
Jane M. Watson; Zalman Usiskin – For the Learning of Mathematics, 2025
A newspaper article about the availability of guns in Chicago, presented at a mathematics education conference in that city in 1998, is linked to a tragic shooting near that city in 2022. The article was used in Australia for many years in research with teachers and students to assess statistical literacy in relation to sampling, until ethics…
Descriptors: News Reporting, Weapons, Mathematics Education, Conferences (Gatherings)
Tamara Broderick; Andrew Gelman; Rachael Meager; Anna L. Smith; Tian Zheng – Grantee Submission, 2022
Probabilistic machine learning increasingly informs critical decisions in medicine, economics, politics, and beyond. To aid the development of trust in these decisions, we develop a taxonomy delineating where trust in an analysis can break down: (1) in the translation of real-world goals to goals on a particular set of training data, (2) in the…
Descriptors: Taxonomy, Trust (Psychology), Algorithms, Probability
Vimala Judy Kamalodeen – Sage Research Methods Cases, 2022
This case study focuses on issues and dilemmas I faced when collecting data on a social networking site that enabled sociability, communication, and collaboration among teachers. To understand teacher online participation, I used an eclectic mixed-methods design with three phases to collect qualitative and quantitative data. This design allowed me…
Descriptors: Mixed Methods Research, Research Methodology, Social Networks, Computer Mediated Communication
Misato Hiraga – ProQuest LLC, 2024
This dissertation developed a new learner corpus of Japanese and introduced an error and linguistic annotation scheme specifically designed for Japanese particles. The corpus contains texts written by learners who are in the first year to fourth year university level Japanese courses. The texts in the corpus were tagged with part-of-speech and…
Descriptors: Japanese, Computational Linguistics, Form Classes (Languages), Error Analysis (Language)