An Empirical Study on Academic Commentary and Its Implications on Reading and Writing
This work addresses the challenge of measuring latent knowledge in RRW for learning science, though it is incremental as it applies an existing method to a new data context.
The study tackled the problem of understanding the relationship between reading and writing (RRW) in learning science by analyzing academic commentary using latent Dirichlet allocation (LDA) to visualize how it is influenced by target papers and authors' background knowledge, with results showing modulation by both factors.
The relationship between reading and writing (RRW) is one of the major themes in learning science. One of its obstacles is that it is difficult to define or measure the latent background knowledge of the individual. However, in an academic research setting, scholars are required to explicitly list their background knowledge in the citation sections of their manuscripts. This unique opportunity was taken advantage of to observe RRW, especially in the published academic commentary scenario. RRW was visualized under a proposed topic process model by using a state of the art version of latent Dirichlet allocation (LDA). The empirical study showed that the academic commentary is modulated both by its target paper and the author's background knowledge. Although this conclusion was obtained in a unique environment, we suggest its implications can also shed light on other similar interesting areas, such as dialog and conversation, group discussion, and social media.