Collaborative knowledge building using the Design Principles Database

In this study we describe a mechanism for supporting a community of learning scientists who are exploring educational technologies by helping them to share and collaboratively build design knowledge. The Design Principles Database (DPD) is intended to be built and used by this community to provide an infrastructure for participants to publish, connect, discuss and review design ideas, and to use these ideas to create new designs. The potential of the DPD to serve as a collaborative knowledge-building endeavor is illustrated by analysis of a CSCL study focused on peer-evaluation. The analysis demonstrates how the DPD was used by the researchers of the peer-evaluation study in three phases. In the first phase, design principles were articulated based on a literature review and contributed to the DPD. In the second phase, a peer-evaluation activity was designed based on these principles, and was enacted and revised in a three-iteration study. In the third phase, lessons learned through these iterations were fed back to the DPD. The analysis indicates that such processes can contribute to collaborative development of design knowledge in a community of the learning sciences. Readers of ijCSCL are invited to take part in this endeavor and share their design knowledge with the community.     

Collaborative knowledge building with wikis: The impact of redundancy and polarity

Wikis as shared digital artifacts may enable users to participate in processes of knowledge building. To what extent and with which quality knowledge building can take place is assumed to depend on the interrelation between people’s prior knowledge and the information available in a wiki. In two experimental studies we examined the impact on learning and knowledge building of the redundancy (Study 1) and polarity (Study 2) between participants’ prior knowledge and information available in the wiki. Based on the co-evolution model of cognitive and social systems, external assimilation and accommodation were used as dependent variables to measure knowledge building. The results supported the hypotheses that a medium level of redundancy and a high level of polarity foster external accommodation processes. External assimilation was stimulated by low redundancy and a high level of polarity. Moreover, we found that individual learning was influenced by the degree of external assimilation.     

Mutual engagement and collocation with shared representations

In this paper we explore the use of shared representations to support creative activities, focussing on collaborative music making. We examine the effect that user interface features of shared representations have on mutual engagement and show that providing shared awareness mechanisms increases mutual engagement. In particular, we show through an empirical study of 78 participants that providing cues to identity and shared pointers increases mutual engagement between participants, but together these features can overwhelm users. We also demonstrate that support for free-form annotation and spatial interaction with shared representations mediates interaction and helps participants to manage their collaborative activity effectively. In this paper we develop several measures mutual engagement and demonstrate their use to assess the design of shared representations. A key contribution of this paper is the development of a measure of collocation of participant interaction which indicates mutual engagement. The findings of the study have implications beyond the domain of collaborative music making and we outline some design guidelines for mutually engaging shared representations.     

Propositional and terminological knowledge representations

Abstract

Formalisms based on a propositional representation demonstrate a high representational competence because of their flexibility, properties, and their great expression power, even if they often fail to represent the meaning of the nodes that make up the propositional networks. The presence of a network of definitions would make the representation richer, and would augment the expressiveness and the inferential capabilities of the whole system: the twofold architecture of the hybrid systems seems to be suitable to satisfy these prerequisites. Nevertheless, the hybrid systems fail to clearly define the intensional and extensional levels of knowledge. This paper proposes a different distribution of tasks between the two parts of a hybrid system on the ground of a precise distinction among intensional, mental extensional, and extensional aspects of knowledge. Moreover, it suggests employing a propositional approach also for arranging the abstract definitions of the terminological box. These principles have been tested in KRAM (Knowledge Representation for Agency Modelling), a hybrid system used as a component both of a cooperative interface and of a system able to model actions and minds of cognitive agents.     

Collaborative video searching on a tabletop

Almost all system and application design for multimedia systems is based around a single user working in isolation to perform some task yet much of the work for which we use computers to help us, is based on working collaboratively with colleagues. Groupware systems do support user collaboration but typically this is supported through software and users still physically work independently. Tabletop systems, such as the DiamondTouch from MERL, are interface devices which support direct user collaboration on a tabletop. When a tabletop is used as the interface for a multimedia system, such as a video search system, then this kind of direct collaboration raises many questions for system design. In this paper we present a tabletop system for supporting a pair of users in a video search task and we evaluate the system not only in terms of search performance but also in terms of user–user interaction and how different user personalities within each pair of searchers impacts search performance and user interaction. Incorporating the user into the system evaluation as we have done here reveals several interesting results and has important ramifications for the design of a multimedia search system.     

Using shared representations to improve coordination and intent inference

In groupware, users must communicate about their intentions and aintain common knowledge via communication channels that are explicitly designed into the system. Depending upon the task, generic communication tools like chat or a shared whiteboard may not be sufficient to support effective coordination. We have previously reported on a methodology that helps the designer develop task specific communication tools, called coordinating representations, for groupware systems. Coordinating representations lend structure and persistence to coordinating information. We have shown that coordinating representations are readily adopted by a user population, reduce coordination errors, and improve performance in a domain task. As we show in this article, coordinating representations present a unique opportunity to acquire user information in collaborative, user-adapted systems. Because coordinating representations support the exchange of coordinating information, they offer a window onto task and coordination-specific knowledge that is shared by users. Because they add structure to communication, the information that passes through them can be easily exploited by adaptive technology. This approach provides a simple technique for acquiring user knowledge in collaborative, user-adapted systems. We document our application of this approach to an existing groupware system. Several empirical results are provided. First, we show how information that is made available by a coordinating representation can be used to infer user intentions. We also show how this information can be used to mine free text chat for intent information, and show that this information further enhances intent inference. Empirical data shows that an automatic plan generation component, which is driven by information from a coordinating representation, reduces coordination errors and cognitive effort for its users. Finally, our methodology is summarized, and we present a framework for comparing our approach to other strategies for user knowledge acquisition in adaptive systems.     

Cross-community knowledge building with idea thread mapper

Research on computer-supported collaborative learning faces the challenge of extending student collaboration to higher social levels and enabling cross-boundary interaction. This study investigated collaborative knowledge building among four Grade 5 classroom communities that studied human body systems with the support of Idea Thread Mapper (ITM). While students in each classroom collaborated in their local (home) discourse space to investigate various human body functions, they generated reflective syntheses— “super notes”—to share knowledge progress and challenges in a cross-community meta-space. As a cross-community collaboration, students from the four classrooms further used the Super Talk feature of ITM to investigate a common problem: how do people grow? Data sources included classroom observations and videos, online discourse within each community, students’ super notes and records of Super Talk discussion shared across the classrooms, and student interviews. The results showed that the fifth-graders were able to generate high quality super notes to reflect on their inquiry progress for cross-classroom sharing. Detailed analysis of the cross-classroom Super Talk documented students’ multifaceted understanding constructed to understand how people grow, which built on the diverse ideas from each classroom and further contributed to enriching student discourse within each individual classroom. The findings are discussed focusing on how to approach cross-community collaboration as an expansive and dynamic context for high-level inquiry and continual knowledge building with technology support.

     

Practical representations of incomplete probabilistic knowledge

The compact representation of incomplete probabilistic knowledge which can be encountered in risk evaluation problems, for instance in environmental studies is considered. Various kinds of knowledge are considered such as expert opinions about characteristics of distributions or poor statistical information. The approach is based on probability families encoded by possibility distributions and belief functions. In each case, a technique for representing the available imprecise probabilistic information faithfully is proposed, using different uncertainty frameworks, such as possibility theory, probability theory, and belief functions, etc. Moreover the use of probability-possibility transformations enables confidence intervals to be encompassed by cuts of possibility distributions, thus making the representation stronger. The respective appropriateness of pairs of cumulative distributions, continuous possibility distributions or discrete random sets for representing information about the mean value, the mode, the median and other fractiles of ill-known probability distributions is discussed in detail.     

Multisource surveillance video data coding with hierarchical knowledge library

The rapidly increasing surveillance video data has challenged the existing video coding standards. Even though knowledge based video coding scheme has been proposed to remove redundancy of moving objects across multiple videos and achieved great coding efficiency improvement, it still has difficulties to cope with complicated visual changes of objects resulting from various factors. In this paper, a novel hierarchical knowledge extraction method is proposed. Common knowledge on three coarse-to-fine levels, namely category level, object level and video level, are extracted from history data to model the initial appearance, stable changes and temporal changes respectively for better object representation and redundancy removal. In addition, we apply the extracted hierarchical knowledge to surveillance video coding tasks and establish a hybrid prediction based coding framework. On the one hand, hierarchical knowledge is projected to the image plane to generate reference for I frames to achieve better prediction performance. On the other hand, we develop a transform based prediction for P/B frames to reduce the computational complexity while improve the coding efficiency. Experimental results demonstrate the effectiveness of our proposed method.

     

Set-based representations of conjunctive and disjunctive knowledge

We look at the use of sets as a method of representing information. We study the use of different set operators to implement different semantic operations. Careful distinction is made between conjunctive and disjunctive type information.     

Community knowledge assessment in a knowledge building environment

This study investigates ways of using key terms to represent and assess community knowledge in an online knowledge building environment. Knowledge Forum – an environment specially designed to support advances in community knowledge – incorporates key-term analytic tools. In the current study these tools were used to determine if key-term measures complement conventional online behavioral measures in assessing community knowledge advances. Discourse rated as more reflective and depth-oriented showed higher percentages of shared key terms and higher frequency use of shared key terms than less reflective, shallower discourse. Limitations and possibilities for using key terms for automated assessment and visual representation of community knowledge are discussed.     

On building cyclic and shared structures in Haskell

We demonstrate how to build certain cyclic and other multi-linked structures in the lazy functional programming language Haskell. No explicit pointers are used in these constructions. Each task is accomplished by starting with a suitable specification and then calculating the required program.     

融合时空多特征表示的无监督视频分割算法

针对视频分割的难点在于分割目标的无规则运动、快速变换的背景、目标外观的任意变化与形变等,提出了一种基于时空多特征表示的无监督视频分割算法,通过融合像素级、超像素级以及显著性三类特征设计由细粒度到粗粒度的稳健特征表示。首先,采用超像素分割对视频序列进行处理以提高运算效率,并设计图割算法进行快速求解;其次,利用光流法对相邻帧信息进行匹配,并通过K-D树算法实现最近邻搜索以引入各超像素的非局部时空颜色特征,从而增强分割的鲁棒性;然后,对采用超像素计算得到的分割结果,设计混合高斯模型进行完善;最后,引入图像的显著性特征,协同超像素分割与混合高斯模型的分割结果,设计投票获得更加准确的视频分割结果。实验结果表明,所提算法是一种稳健且有效的分割算法,其结果优于当前大部分无监督视频分割算法及部分半监督视频分割算法。     

A persistent store for large shared knowledge bases

A knowledge-base management system (KBMS) with the following goals is proposed: (1) to allow a knowledge engineer to update a knowledge base and have these updates persist on secondary storage, (2) to allow multiple knowledge engineers to have shared access to a knowledge base and modify the knowledge base concurrently, and (3) to maintain consistency of the shared knowledge base as it evolves. At the heart of the KBMS is the version store, which is a persistent storage structure that maintains multiple versions of a knowledge base. Retrieve and update operations are defined on the version store to efficiently access and modify any version. Objects in the version store are clustered to support efficient access of an entire version or some subparts of it. To store the effects of an update requires space proportional to the size of the update and which is independent of the size of the knowledge base. The additional cost of maintaining multiple versions is within a small constant factor of maintaining a single version     

Indigo: user-level support for building distributed shared abstractions

Distributed systems that consist of workstations connected by high performance interconnects offer computational power comparable to moderate size parallel machines. Middleware like distributed shared memory (DSM) or distributed shared objects (DSO) attempts to improve the programmability of such hardware by presenting to application programmers interfaces similar to those offered by shared memory machines. This paper presents the portable Indigo data sharing library which provides a small set of primitives with which arbitrary shared abstractions are easily and efficiently implemented across distributed hardware platforms. Sample shared abstractions implemented with Indigo include DSM as well as fragmented objects, where the object state is split across different machines and where interfragment communications may be customized to application-specific consistency needs. The Indigo library's design and implementation are evaluated on two different target platforms: a workstation cluster and an IBM SP2 machine. As part of this evaluation, a novel DSM system and consistency protocol are implemented and evaluated with several high performance applications. Application performance attained with the DSM system is compared to the performance experienced when utilizing the underlying basic message-passing facilities or when employing Indigo to construct customized fragmented objects implementing the application's shared state. Such experimentation results in insights concerning the efficient implementation of DSM systems (e.g. how to deal with false sharing). It also leads to the conclusion that Indigo provides a sufficiently rich set of abstractions for efficient implementation of the next generation of parallel programming models for high performance machines. © 1998 John Wiley & Sons, Ltd.     

Collaborative intelligence in knowledge based service planning

E-services are provided by several web-enabled companies. While some of them are competitive in nature, others are collaborative. There are few methodologies currently existing for measuring the value of e-collaboration among these e-service providers. The objective of this research is to measure collaborative intelligence (CI) in the knowledge based service (KBS) industry and to identify measures for finding the best collaborators during the formation and functioning stages of collaborative networks. The model developed in this research, CIMK (collaborative intelligence measure of KBS), measures CI by multi-objective optimization on parameters for collaboration, and suggests optimal operating points for various clients with greater flexibility. CIMK allows decision makers to customize the model based on their knowledge of the industry. Then, the CNOA (Collaborative Network Optimization Algorithm) is applied to select the best providers for requests based on their CI levels. CNOA has been implemented over a HUB-CI (HUB with CI) platform, which is a next generation collaboration support system developed at Purdue University. Three analytic experiments are designed and performed to validate the models (1) in terms of usability, (2) to compare the CIMK with alternative methods, and (3) to find the relative advantages of the CIMK model. The results of the experiments indicate that the average service cost can decrease by close to 50% when operating points with high CI, suggested by CIMK model, are implemented. The CI level computed by CIMK is successfully used as a decision parameter for on-going matching e-service providers to different requests.     

深浅层表示融合的半监督视频目标分割

为了解决半监督视频目标分割任务中,分割精度与分割速度难以兼顾以及无法对视频中与前景相似的背景目标做出有效区分的问题,提出一种基于深浅层特征融合的半监督视频目标分割算法。首先,利用预先生成的粗糙掩膜对图像特征进行处理,以获取更鲁棒的特征;然后,通过注意力模型提取深层语义信息;最后,将深层语义信息与浅层位置信息进行融合,从而得到更加精确的分割结果。在多个流行的数据集上进行了实验,实验结果表明：在分割运行速度基本不变的情况下,所提算法在DAVIS 2016数据集上的雅卡尔（J）指标相较于学习快速鲁棒目标模型的视频目标分割（FRTM）算法提高了1.8个百分点,综合评价指标为J和F得分的均值J&F相较于FRTM提高了2.3个百分点;同时,在DAVIS 2017数据集上,所提算法的J指标比FRTM提升了1.2个百分点,综合评价指标J&F比FRTM提升了1.1个百分点。以上结果充分说明所提算法能够在保持较快分割速度的情况下实现更高的分割精度,并且能够有效区别相似的前景与背景目标,具有较强的鲁棒性。可见所提算法在平衡速度与精度以及有效区分前景背景方面的优越性能。