Controlled language and readability

Controlled Language (CL) rules specify constraints on lexicon, grammar and style with the objective of improving text translatability, comprehensibility, readability and usability. A significant body of research exists demonstrating the positive effects CL rules can have on machine translation quality (e.g. Mitamura and Nyberg 1995; Kamprath et al 1998; Bernth 1999; Nyberg et al 2003), acceptability (Roturier 2006), and post-editing effort (O’Brien 2006). Since CL rules aim to reduce complexity and ambiguity, claims have been made that they consequently improve the readability of text (e.g., Spaggiari, Beaujard and Cannesson 2003; Reuther 2003). Little work, however, has been done on the effects of CL on readability. This paper represents an attempt to investigate the relationship in an empirical manner using both qualitative and quantitative methods

Nutrition Labeling in the United States and the Role of Consumer Processing, Message Structure, and Moderating Conditions

It has been since 1990 that the landmark Nutritional Labeling Education Act (NLEA) was passed in the United States, and since 1969 that the first White House Conference on Food, Nutrition and Health occurred. In the time since these important events, considerable research has been conducted on how U.S. consumers process and use nutritional labeling. An up-to-date review of nutritional labeling research must address key findings on the processing and use of nutrition facts panels (NFPs), restaurant labeling, front-of-pack (FOP) symbols, health and nutrient content claims, new labeling efforts (e.g., for meat products), and claims not regulated by the U.S. Food and Drug Administration (FDA). Message structure mediates the ways in which consumers process nutritional labeling while moderating conditions affect research outcomes associated with labeling efforts. The most recent policy issues and problems to be considered (e.g., by the FDA) include nutritional labeling as well as identifying opportunities for consumer research in helping to promote healthy lifestyles and reducing obesity in the United States and throughout the world. For example, several unanswered research questions remain regarding how the proposed changes to the NFPs—beef, poultry, and seafood labeling; restaurant chain calorie labeling; alternative FOP formats; and regulated and unregulated health and nutrient content claims—will affect consumers. Researchers have yet to examine not only these different labeling and nutrition information formats, but also how they might interact with one another and the role of key moderating conditions (e.g., one’s motivation, ability opportunity to process nutrition information) in affecting consumer processing and behavior

Adaptive intermittent control: A computational model explaining motor intermittency observed in human behavior

It is a fundamental question how our brain performs a given motor task in a real-time fashion with the slow sensorimotor system. Computational theory proposed an influential idea of feed-forward control, but it has mainly treated the case that the movement is ballistic (such as reaching) because the motor commands should be calculated in advance of movement execution. As a possible mechanism for operating feed-forward control in continuous motor tasks (such as target tracking), we propose a control model called "adaptive intermittent control" or "segmented control," that brain adaptively divides the continuous time axis into discrete segments and executes feed-forward control in each segment. The idea of intermittent control has been proposed in the fields of control theory, biological modeling and nonlinear dynamical system. Compared with these previous models, the key of the proposed model is that the system speculatively determines the segmentation based on the future prediction and its uncertainty. The result of computer simulation showed that the proposed model realized faithful visuo-manual tracking with realistic sensorimotor delays and with less computational costs (i.e., with fewer number of segments). Furthermore, it replicated "motor intermittency", that is, intermittent discontinuities commonly observed in human movement trajectories. We discuss that the temporally segmented control is an inevitable strategy for brain which has to achieve a given task with small computational (or cognitive) cost, using a slow control system in an uncertain variable environment, and the motor intermittency is the side-effect of this strategy

Freeform User Interfaces for Graphical Computing

報告番号: 甲15222 ; 学位授与年月日: 2000-03-29 ; 学位の種別: 課程博士 ; 学位の種類: 博士(工学) ; 学位記番号: 博工第4717号 ; 研究科・専攻: 工学系研究科情報工学専

Dialogue as Data in Learning Analytics for Productive Educational Dialogue

This paper provides a novel, conceptually driven stance on the state of the contemporary analytic challenges faced in the treatment of dialogue as a form of data across on- and offline sites of learning. In prior research, preliminary steps have been taken to detect occurrences of such dialogue using automated analysis techniques. Such advances have the potential to foster effective dialogue using learning analytic techniques that scaffold, give feedback on, and provide pedagogic contexts promoting such dialogue. However, the translation of much prior learning science research to online contexts is complex, requiring the operationalization of constructs theorized in different contexts (often face-to-face), and based on different datasets and structures (often spoken dialogue). In this paper, we explore what could constitute the effective analysis of productive online dialogues, arguing that it requires consideration of three key facets of the dialogue: features indicative of productive dialogue; the unit of segmentation; and the interplay of features and segmentation with the temporal underpinning of learning contexts. The paper thus foregrounds key considerations regarding the analysis of dialogue data in emerging learning analytics environments, both for learning-science and for computationally oriented researchers