• Journal of The Korean Association For Science Education
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• v.33 no.4
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• pp.840-862
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• 2013

This study undertook a methodological investigation on previous research that had proposed alternative methods for analyzing argumentative discourse in science classes in terms of collaborative construction and epistemic enactments of argumentation. The study also proposed a new way of analyzing argumentation discourse based on the achievements and limitations of previous research. The new method was applied to actual argumentation discourse episodes to examine its feasibility. For these purposes, we chose the studies employing Toulmin's argument layout, seeking for a method to analyze comprehensively the structure, content, and justification of arguments, or emphasizing evidence-based reasoning processes of argumentation discourse. In addition, we contrived an alternative method of analyzing argumentative discourse, Discourse Register on the Evidence-Explanation Continuum (DREEC), and applied DREEC to an argumentative discourse episode that occurred in an actual science classroom. The advanced methods of analyzing argumentative discourse used in previous research usually examined argument structure by the presence and absence of the elements of Toulmin's argument layout or its extension. Those methods, however, had some problems in describing and comparing the quality of argumentation based on the justification and epistemic enactments of the arguments, while they could analyze and compare argumentative discourse quantitatively. Also, those methods had limitations on showing participants' collaborative construction during the argumentative discourse. In contrast, DREEC could describe collaborative construction through the relationships between THEMEs and RHEMEs and the links of data, evidence, pattern, and explanation in the discourse, as well as the justification of arguments based on the flow of epistemic enactments of the argumentative discourse.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.1-17
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• 2012

Personalized smart devices such as smartphones and smart pads are widely used. Unlike traditional feature phones, theses smart devices allow users to choose a variety of functions, which support not only daily experiences but also business operations. Actually, there exist a huge number of applications accessible by smart device users in online and mobile application markets. Users can choose apps that fit their own tastes and needs, which is impossible for conventional phone users. With the increase in app demand, the tastes and needs of app users are becoming more diverse. To meet these requirements, numerous apps with diverse functions are being released on the market, which leads to fierce competition. Unlike offline markets, online markets have a limitation in that purchasing decisions should be made without experiencing the items. Therefore, online customers rely more on item-related information that can be seen on the item page in which online markets commonly provide details about each item. Customers can feel confident about the quality of an item through the online information and decide whether to purchase it. The same is true of online app markets. To win the sales competition against other apps that perform similar functions, app developers need to focus on writing app descriptions to attract the attention of customers. If we can measure the effect of app descriptions on sales without regard to the app's price and quality, app descriptions that facilitate the sale of apps can be identified. This study intends to provide such a quantitative result for app developers who want to promote the sales of their apps. For this purpose, we collected app details including the descriptions written in Korean from one of the largest app markets in Korea, and then extracted keywords from the descriptions. Next, the impact of the keywords on sales performance was measured through our econometric model. Through this analysis, we were able to analyze the impact of each keyword itself, apart from that of the design or quality. The keywords, comprised of the attribute and evaluation of each app, are extracted by a morpheme analyzer. Our model with the keywords as its input variables was established to analyze their impact on sales performance. A regression analysis was conducted for each category in which apps are included. This analysis was required because we found the keywords, which are emphasized in app descriptions, different category-by-category. The analysis conducted not only for free apps but also for paid apps showed which keywords have more impact on sales performance for each type of app. In the analysis of paid apps in the education category, keywords such as 'search+easy' and 'words+abundant' showed higher effectiveness. In the same category, free apps whose keywords emphasize the quality of apps showed higher sales performance. One interesting fact is that keywords describing not only the app but also the need for the app have asignificant impact. Language learning apps, regardless of whether they are sold free or paid, showed higher sales performance by including the keywords 'foreign language study+important'. This result shows that motivation for the purchase affected sales. While item reviews are widely researched in online markets, item descriptions are not very actively studied. In the case of the mobile app markets, newly introduced apps may not have many item reviews because of the low quantity sold. In such cases, item descriptions can be regarded more important when customers make a decision about purchasing items. This study is the first trial to quantitatively analyze the relationship between an item description and its impact on sales performance. The results show that our research framework successfully provides a list of the most effective sales key terms with the estimates of their effectiveness. Although this study is performed for a specified type of item (i.e., mobile apps), our model can be applied to almost all of the items traded in online markets.