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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
Lingbo Tong; Wen Qu; Zhiyong Zhang – Grantee Submission, 2025
Factor analysis is widely utilized to identify latent factors underlying the observed variables. This paper presents a comprehensive comparative study of two widely used methods for determining the optimal number of factors in factor analysis, the K1 rule, and parallel analysis, along with a more recently developed method, the bass-ackward method.…
Descriptors: Factor Analysis, Monte Carlo Methods, Statistical Analysis, Sample Size
Zhaoyang Liu; Wenlan Zhang; Liangliang Hu – Innovations in Education and Teaching International, 2025
Virtual Reality (VR) is gradually integrating into classroom teaching, emerging as a new trend in educational development in the era of artificial intelligence. Desktop virtual reality stands out due to its lower cost and greater convenience. To elucidate the effectiveness of desktop virtual reality in learning, this paper employs a meta-analysis…
Descriptors: Computer Simulation, Meta Analysis, Teaching Methods, Instructional Effectiveness