How to Do Things With Words

http://science.sciencemag.org/content/sci/201/4359/899.2.full.pdf

Phenomenology of perception.

DBpedia is a community effort to extract structured information from Wikipedia and to make this information available on the Web. DBpedia allows you to ask sophisticated queries against datasets derived from Wikipedia and to link other datasets on the Web to Wikipedia data. We describe the extraction of the DBpedia datasets, and how the resulting information is published on the Web for human-andmachine-consumption. We describe some emerging applications from the DBpedia community and show how website authors can facilitate DBpedia content within their sites. Finally, we present the current status of interlinking DBpedia with other open datasets on the Web and outline how DBpedia could serve as a nucleus for an emerging Web of open data.

/pdf/dbpedia-a-nucleus-for-a-web-of-open-data-64wla3p0zr.pdf

DBpedia: a nucleus for a web of open data

語用論(Pragmatics)を考える

미국의 “전국 수학 교사 협의회”(National Council of Teachers of Mathematics, NCTM)는 1989년부터 〈학교 수학의 교육과정과 평가 규준〉(1989), 〈수학 가르침(교수)의 전문성 규준〉(1991), 〈학교 수학의 평가(시험) 규준〉(NCTM, 1995), 〈학교 수학의 원리와 규준〉(2000)을 출판하여 미국의 수학 교육 의 전망(목표, 나아갈 길)과 규준(실행 지침)을 제시하였다. 수학 교사들로 구성된 미국의 NCTM은 학생, 학부모, 학교 행정가 등 많은 사람들과 힘을 합하여 모든 학생들에게 수준 높은 수학 교육을 받을 수 있는 여건(환경, 기회)을 조성하는 데 구심점의 역할을 하였다. 한편 많은 관련 단체들은 여러 배경과 능력을 가진 학생들이 전문성을 지닌 교사(특수 교사를 일컫는 밀이 아니다. 수학 교과를 이해하고 수학의 전문성과 특수성을 가르칠 수 있는 일반 교사를 일컫는 말이다.)로부터 미래를 대비해 평등하고, 진취적이며, 지원이 잘 이루어지고, 공학 도구(IT)가 잘 갖춰진 환경에서 중요한 수학적 아이디어를 이해하면서 학습할 수 있는 수학 교실(미국에서는 우리나라처럼 수학 교사가 수학 시간에 학생의 방(교실: Homeroom)에 찾아가지 않고 학생들이 선생의 방(수학 교실: Classroom)을 찾아온다. 전형적인 수학 교실의 사진은 2쪽에 나와 있다.)을 만들기 위해 함께 힘썼다. NCTM에서 출간한 여러 규준들은 우리나라의 제6차와 제7차 교육과정에도 큰 영향을 미쳤다. 이 글에서는 NCTM(2000)에서 제시한 학습 원리를 간단히 살펴본 다음 이를 중심으로 현재 미국 수학 교육의 교수ㆍ학습 이론의 동향을 살펴본다.

미국 NCTM의 Principles and Standards for School Mathematics에 나타난 수학과 교수,학습의 이론

In order to collaborate effectively in group discourse on a topic like mathematical patterns, group participants must organize their activities in ways that share the significance of their utterances, inscriptions, and behaviors. Here, we report the results of a ethnomethodological case study of collaborative math problem-solving activities mediated by a synchronous multimodal online environment. We investigate the moment-by-moment details of the interaction practices through which participants organize their chat utterances and whiteboard actions as a coherent whole. This approach to analysis foregrounds the sequentiality of action and the implicit referencing of meaning making—fundamental features of interaction. In particular, we observe that the sequential construction of shared drawings and the deictic references that link chat messages to features of those drawings and to prior chat content are instrumental in the achievement of intersubjectivity among group members’ understandings. We characterize this precondition of collaboration as the co-construction of an indexical field that functions as a common ground for group cognition. Our analysis reveals methods by which the group co-constructs meaningful inscriptions in the dual-interaction spaces of its CSCL environment. The integration of graphical, narrative, and symbolic semiotic modalities in this manner also facilitates joint problem solving. It allows group members to invoke and operate with multiple realizations of their mathematical artifacts, a characteristic of deep learning of mathematics.

/pdf/the-joint-organization-of-interaction-within-a-multimodal-4dk19s506c.pdf

The Joint Organization of Interaction within a Multimodal CSCL Medium.

Conventional data integration techniques employ a “top-down” design philosophy, starting by assessing requirements and defining a global schema, and then mapping data sources to that schema. This works well if the problem domain is well-understood and relatively static, as with enterprise data. However, it is fundamentally mismatched with the “bottom-up”model of scientific data sharing, in which new data needs to be rapidly developed, published, and then assessed, filtered, and revised by others. We address the need for bottom-up collaborative data sharing, in which independent researchers or groups with different goals, schemas, and data can share information in the absence of global agreement. Each group independently curates, revises, and extends its data; eventually the groups compare and reconcile their changes, but they are not required to agree. This paper describes our initial design and prototype of the ORCHESTRA system, which focuses on managing disagreement among multiple data representations and instances. Our work represents an important evolution of the concepts of peer-to-peer data sharing [23], which considers revision, disagreement, authority, and intermittent participation.

/pdf/orchestra-rapid-collaborative-sharing-of-dynamic-data-8r51vnxh7o.pdf

ORCHESTRA : Rapid, collaborative sharing of dynamic data

Recent interest towards university rankings has led to the development of several ranking systems at national and global levels. Global ranking systems tend to rely on internationally accessible bibliometric databases and reputation surveys to develop league tables at a global level. Given their access and in-depth knowledge about local institutions, national ranking systems tend to include a more comprehensive set of indicators. The purpose of this study is to conduct a systematic comparison of national and global university ranking systems in terms of their indicators, coverage and ranking results. Our findings indicate that national rankings tend to include a larger number of indicators that primarily focus on educational and institutional parameters, whereas global ranking systems tend to have fewer indicators mainly focusing on research performance. Rank similarity analysis between national rankings and global rankings filtered for each country suggest that with the exception of a few instances global rankings do not strongly predict the national rankings.

A comparative analysis of global and national university ranking systems

An accurate assessment of mental workload and expertise level would help improve operational safety and efficacy of human computer interaction for aerospace applications. The current study utilized functional near-infrared spectroscopy (fNIR) to investigate the relationship of the hemodynamic response in the anterior prefrontal cortex to changes in mental workload, level of expertise, and task performance during learning of simulated unmanned aerial vehicle (UAV) piloting tasks. Results indicated that fNIR measures are correlated to task performance and subjective self-reported measures; and contained additional information that allowed categorizing learning phases. Level of expertise does appear to influence the hemodynamic response in the dorsolateral/ventrolateral prefrontal cortices. Since fNIR allows development of portable and wearable instruments, it has the potential to be deployed in future learning environments to personalize the training regimen and/or assess the effort of human operators in critical multitasking settings.

Monitoring expertise development during simulated UAV piloting tasks using optical brain imaging

In this work we present a thread-based approach for analyzing synchronous collaborative math problem solving activities. Thread information is shown to be an important resource for analyzing collaborative activities, especially for conducting sequential analysis of interaction among participants of a small group. We propose a computational model based on thread information which allows us to identify patterns of interaction and their sequential organization in computer-supported collaborative environments. This approach enables us to understand important features of collaborative math problem solving in a chat environment and to envisage several useful implications for educational and design purposes.

/pdf/thread-based-analysis-of-patterns-of-collaborative-48xwgwt5fs.pdf

Murat Cakir

Papers

The Joint Organization of Interaction within a Multimodal CSCL Medium.

ORCHESTRA : Rapid, collaborative sharing of dynamic data

A comparative analysis of global and national university ranking systems

Monitoring expertise development during simulated UAV piloting tasks using optical brain imaging

Thread-based analysis of patterns of collaborative interaction in chat