Data commentary is an important text type in research articles; however, its discourse model is often challenging to access because it is embedded in the upper genres such as textbook, weather forecast, and journal article. This study aims to establish a discourse model of data commentary, with a focus on academic research papers in Economics and Business administration journals. To accomplish this, this study employs Move analysis and SF-MDA(Systemic Functional-Multimodal Discourse Analysis) to investigate the moves of data commentaries and the metafunctional meanings of each step. The results indicate that the data commentary discourse model consists of three moves: (1) summarizing the topic and methodology, (2) representing figure and numbers, and (3) analyzing and commenting on results. Additionally, 22 steps are identified for each move that creates metafunctional meaning: ideational, interpersonal, and textual.

This study aims to analyze the process of how Chinese students practice collaborative writing and to figure out whether collaborative writing is useful to Korean language learners for academic purposes. In total, 15 Chinese students of Korean language for academic purposes participated in the research and they were divided into Groups A and B, respectively. Five participants of Group A were individually assigned with writing tasks while ten participants of Group B conducted collaborative writing tasks in pairs. Groups A and B conducted both tasks of a data commentary and an argumentative essay. The result was that fluency and complexity were not significantly different between Groups A and B. However, accuracy was higher in Group B. Accordingly, for students of Korean language in an advanced level, collaborative writing activities did not result in longer texts or more complex linguistic practices but led to more accurate texts. Whether this accuracy will strengthen grammatical knowledge of language students in an advanced level in the long-term is unknown, so follow-up studies are needed.