Analyzing collaborative interactions: divergence,shared understanding and construction of knowledge

One of the most important facets of collaborative learning is the interaction between individual and collaborative learning activities – between divergent perspectives and shared knowledge building. Individuals bring divergent ideas into a collaborative environment. While individuals bring their own unique knowledge and perspectives, the second important aspect of collaborative learning is how they move from seemingly divergent perspectives to collaborative knowledge building. This is clearly a social process among group members who could adopt various strategies for resolving differences including asserting dominance, acquiescing, or some form of reciprocal sense making. An important aspect of collaborative learning is the move from assimilation to construction, i.e., creating new understandings based on the discussions that they have had. Documenting this change from divergence to collaborative knowledge building to possible construction is therefore important in understanding the nature the collaborative interactions. In this paper we discuss our analysis of the process of collaborative interactions based on three dimensions – divergence of ideas, collaborative knowledge building and construction. Our aim was to document as well as to understand how collaborative interactions develop over time: whether students raise new issues (ideas) more frequently as they become more familiar with the discussion and discussants, and whether shared knowledge building becomes richer over time, and subsequent evidence that students were able to construct their own understanding based on their interactions with others. Our analyses were conducted in the context of an online graduate course conducted using the learning environment that we designed, CoDE, (Constructivist, Distributed learning Environment). In this paper, we will first describe the design of CoDE. We will then describe a study in which CoDE was used to offer an online graduate course in learning theories. We then discuss our analyses of both individual and collaborative learning as it progressed through the duration of the course.     

Knowledge building in asynchronous discussion groups: Going beyond quantitative analysis

This contribution examines the methodological challenges involved in defining the collaborative knowledge-building processes occurring in asynchronous discussion and proposes an approach that could advance understanding of these processes. The written protocols that are available to the analyst provide an exact record of the instructional transactions at a given time in the online discussion. On the basis of a study of online discussion forums used in a higher education context, a model for the analysis of collaborative knowledge building in asynchronous discussion is presented. The model allows examination of the communication from the multiple perspectives of interaction, cognition and discourse analysis. The investigation was conducted using a qualitative case study approach and involved an in-depth examination of three cases. Content analysis of the discourse was done at a number of levels, focusing on the discussion forum itself, the discussion threads, the messages, and the exchanges and moves among the messages. As a result of correspondences found among the variables representing the different levels of the analysis, the most important being the relationship between type of interaction, phase of critical inquiry, and move in the exchange structure, it was possible to build a scheme for assessing knowledge building in asynchronous discussion groups. The scheme integrates the interactive, cognitive and discourse dimensions in computer-supported collaborative learning (CSCL). The study represents a merging of quantitative analysis within qualitative methodology and provides both an analytic and a holistic perspective on CSCL.     

Users’ attitudes toward Web-based collaborative learning systems for knowledge management

The Web-based technology is a potential tool for supported collaborative learning that may enrich learning performance, such as individual knowledge construction or group knowledge sharing. Thus, understanding Web-based collaborative learning for knowledge management is a critical issue. The present study is to investigate learners’ attitudes toward Web-based collaborative learning systems. Based on this research, the results of factor analysis show that five attitude factors (system functions, system satisfaction, collaborative activities, learners’ characteristics, and system acceptance) should be examined at the same time when building a Web-based collaborative learning system. The results also provide an acceptance model for understanding users’ behavioral intention of facilitating Web-based collaborative systems.     

Toward a classification of discourse patterns in asynchronous online discussions

The goal of this study was to develop a classification for a range of discourse patterns that occur in text-based asynchronous discussion forums, and that can aid in the distinction of three modes of discourse: knowledge sharing, knowledge construction, and knowledge building. The dataset was taken from Knowledge Forum® databases in the Knowledge Building Teacher Network in Hong Kong, and included three discussion views created for different classes: Grade 5 Science, Grade 10 Visual Arts, and Grade 10 Liberal Studies. We used a combination of qualitative coding and narrative analysis as well as teachers’ understanding of online discourse to analyze student discussions. Nine discourse patterns were identified. These patterns revealed a variety of ways in which students go about their collaborative interactions online and demonstrated how and why students succeed or fail in sustaining collaborative interactions. This study extended the three modes of online discourse and developed different discourse patterns, which are efforts to provide instructional guidance. The implications of supporting productive discourse and the enactment of CSCL innovations in classrooms are discussed.     

Interaction between tool and talk: how instruction and tools support consensus building in collaborative inquiry-learning environments

The process of collaborative inquiry learning requires maintaining a mutual understanding of the task, along with reaching consensus on strategies, plans and domain knowledge. In this study, we explore how different supportive measures affect students' consensus-building process, based on a re-analysis of data from four studies. We distinguish between scaffolds that aim at supporting students' collaborative processes and scaffolds that aim primarily at supporting the inquiry learning process. The overall picture that emerges from the re-analysis is that integration-oriented consensus-building activities are facilitated by scaffolds that provide explicit instruction in rules for effective collaboration and by scaffolds that encourage students to collaboratively construct a representation. Scaffolds that display inter-individual differences between students' opinions resulted primarily in quick consensus-building activities.     

Designing collaborative knowledge building environments accessible to all learners: Impacts and design challenges

The present study attempted to investigate whether young learners who were new to knowledge building approaches could work towards advancing both individual and collective knowledge, and whether knowledge building could be beneficial to both high-achieving and low-achieving students. Findings reported in this paper are from one and a half-year design research for science learning in one primary school in Singapore. In this study, we closely examined the design and enactment of the Knowledge Building Community model in one class with high-achieving students and two classes with mixed-ability students. The research consists of two phases: Phase I Cultivating a collaborative knowledge building culture and Phase II Progressive Knowledge Building using Knowledge Forum. Data were collected from multiple sources, including knowledge assessment, conceptual understanding tasks, and the content analysis of Knowledge Forum postings. The results in Phase I show that while it is critical for students to monitor and build knowledge for their own understanding, they had difficulties developing such skills. In both phases, we found positive impacts on academic achievements showing improvement of student understanding in the course of reflective thinking and progressive inquiry. Overall, quantitative data suggest that the collaborative knowledge building environment was beneficial for both high-achieving and low-achieving students. We conclude by discussing some of challenges and issues in designing collaborative knowledge building environments for young learners with diverse abilities.     

Understanding knowledge-sharing breakdowns: a meeting of the quantitative and qualitative minds

Abstract The rapid advance of distance learning and networking technology has enabled universities and corporations to reach out and educate students across time and space barriers. Although this technology enables structured collaborative learning activities, online groups often do not enjoy the same benefits as face‐to‐face learners, and their instructors often do not have time to actively support and mediate the online collaboration. This article demonstrates our capacity to computationally model, analyse, and support online student interaction, in particular knowledge sharing. A unique combination of qualitative analysis and artificial intelligence methods was designed to (a) recognize when students are having trouble learning the new concepts they share with each other, and (b) understand why they are having trouble, so that we might assist an instructor or intelligent coach in mediating group knowledge‐sharing activities.     

面向链接预测的知识图谱表示学习方法综述

作为人工智能的重要基石, 知识图谱能够从互联网海量数据中抽取并表达先验知识, 极大程度解决了智能系统认知决策可解释性差的瓶颈问题, 对智能系统的构建与应用起关键作用. 随着知识图谱技术应用的不断深化, 旨在解决图谱欠完整性问题的知识图谱补全工作迫在眉睫. 链接预测是针对知识图谱中缺失的实体与关系进行预测的任务, 是知识图谱构建与补全中不可或缺的一环. 要充分挖掘知识图谱中的隐藏关系, 利用海量的实体与关系进行计算, 就需要将符号化表示的信息转换为数值形式, 即进行知识图谱表示学习. 基于此, 面向链接预测的知识图谱表示学习成为知识图谱领域的研究热点. 从链接预测与表示学习的基本概念出发, 系统性地介绍面向链接预测的知识图谱表示学习方法最新研究进展. 具体从知识表示形式、算法建模方式两种维度对研究进展进行详细论述. 以知识表示形式的发展历程为线索, 分别介绍二元关系、多元关系和超关系知识表示形式下链接预测任务的数学建模. 基于表示学习建模方式, 将现有方法细化为4类模型: 平移距离模型、张量分解模型、传统神经网络模型和图神经网络模型, 并详细描述每类模型的实现方式与解决不同关系元数链接预测任务的代表模型. 在介绍链接预测的常用的数据集与评判标准基础上, 分别对比分析二元关系、多元关系和超关系3类知识表示形式下, 4类知识表示学习模型的链接预测效果, 并从模型优化、知识表示形式和问题作用域3个方面展望未来发展趋势.     

Combining qualitative evaluation and social network analysis for the study of classroom social interactions

Studying and evaluating real experiences that promote active and collaborative learning is a crucial field in CSCL. Major issues that remain unsolved deal with the merging of qualitative and quantitative methods and data, especially in educational settings that involve both physical and computer-supported collaboration. In this paper we present a mixed evaluation method that combines traditional sources of data with computer logs, and integrates quantitative statistics, qualitative data analysis and social network analysis in an overall interpretative approach. Several computer tools have been developed to assist in this process, integrated with generic software for qualitative analysis. The evaluation method and tools have been incrementally applied and validated in the context of an educational and research project that has been going on during the last three years. The use of the method is illustrated in this paper by an example consisting of the evaluation of a particular category within this project. The proposed method and tools aim at giving an answer to the need of innovative techniques for the study of new forms of interaction emerging in CSCL; at increasing the efficiency of the traditionally demanding qualitative methods, so that they can be used by teachers in curriculum-based experiences; and at the definition of a set of guidelines for bridging different data sources and analysis perspectives.     

Technoliteracy and learning: An analysis of the quality of knowledge in electronic representations of understanding

Recent educational research from a socio-cognitive perspective has validated students’ collaborative engagement with new technologies and heightened understanding of influential factors shaping the effectiveness of peer interactions, learning contexts and computer interfaces for enhancing learning. This paper focuses on an analysis of the complexity of knowledge in student-designed, electronically created texts for what they might reveal about learning with technology. It reports on a study with 17-year-old female students whose collaborative learning process in subject English was mediated by the creation of electronic concept maps and Web files to represent their developing understanding. To analyse these electronic texts, evaluative criteria templates were developed from the Structure of Observed Learning Outcomes (SOLO) taxonomy, integrating levels of understanding with the distinctive characteristics of multimodal text production. Findings indicated not just the incremental acquisition of conceptual understanding equated with cognitive change but that the level of understanding might also be positively influenced by the students’ length of exposure to computer-mediated learning practices. As well, the criteria templates have emerged as useful evaluative tools for classroom assessment or further research when analysis of the level of complexity of student-created, electronic artefacts is required.     

Enacting artifact-based activities for social technologies in language learning using a design-based research approach

This paper presents the results of a three-year design-based research (DBR) study on the use of social technologies for collaborative construction of shareable artifacts by groups of learners. The study builds on the learning theory of constructionism which assumes that knowledge is better gained when students find this knowledge for themselves while engaging in the making of concrete and public artifacts. In an attempt to infuse elements of constructionism in the use of social technologies, we tasked groups of learners in language learning courses with collaborative construction of an artifact using social technologies. A unique characteristic of our approach is that the process that students adopted and the way technology and context fostered this procedure was analyzed. The cycle of DBR fueled deep insights into the learning processes that emerged through the construction of an artifact, thus deepening our understanding of the multimode and multi-trajectory relationship between theory, artifact construction and social technologies. For sustaining and orchestrating social construction of artifacts by groups of learners, a set of instructional elements emerged, as well as implications for enacting social technology innovations in real-life classrooms.     

医学文本表示学习方法与质量评测研究综述

为了及时掌握医学文本表示学习的研究现状,对其现有研究进行系统全面综述.首先,基于技术范式对现有技术进行分类,分别从基于统计学习的方法、基于知识图谱表示的方法和基于图表示的方法,对医学文本表示学习主流方法和相应的代表性成果进行总结.然后,提出了运用定量和定性的质量评测体系,系统地梳理和总结了医学文本表示学习的质量评测方法.最后,对医学文本表示学习的研究趋势进行了展望.     

SECOL: a semantic environment based on social media to support organisational learning

Organisational learning (OL) helps companies to significantly improve their processes through the reuse of experiences, making knowledge accessible to the whole organisation. However, establishing learning in software development companies is not a trivial task, since it is an area in which processes and knowledge are usually hidden inside the employees’ mind. Generally, employees prefer to look for knowledge via Internet search engines rather than using the knowledge produced inside the company. Hence, we explored how better organising content produced within the company may minimise this problem. We investigated how a semantic collaborative environment, titled semantic collaborative environment for organisational learning (SECOL), based on social software, learning objects (LOs), and units of learning (UL) may assist to improve OL for software development companies. We defined an approach to generate LOs and UL from social software’s content used by companies. The environment was implemented based on ontologies in order to represent and organise acquired knowledge. Furthermore, an experiment was conducted using qualitative data analysis. The results indicated that the use of the environment is appropriate to improve OL in software development teams and the use of SECOL is efficient, particularly in order to acquire new knowledge, assisting the promotion of the use of organisational patterns and minimising repeated solutions.     

PROLEGOMENA TO ANY FUTURE QUALITATIVE PHYSICS

We evaluate the success of the qualitative physics enterprise in automating expert reasoning about physical systems. The field has agreed, in essentials, upon a modeling language for dynamical systems, a representation for behavior, and an analysis method. The modeling language consists of generalized ordinary differential equations containing unspecified constants and monotonic functions; the behavioral representation decomposes the state space described by the equations into discrete cells; and the analysis method traces the transitory response using sign arithmetic and calculus. The field has developed several reasoners based on these choices over some 15 years. We demonstrate that these reasoners exhibit severe limitations in comparison with experts and can analyze only a handful of simple systems. We trace the limitations to inappropriate assumptions about expert needs and methods. Experts ordinarily seek to determine asymptotic behavior rather than transient response, and use extensive mathematical knowledge and numerical analysis to derive this information. Standard mathematics provides complete qualitative understanding of many systems, including those addressed so far in qualitative physics. Preliminary evidence suggests that expert knowledge and reasoning methods can be automated directly, without restriction to the accepted language, representation, and algorithm. We conclude that expert knowledge and methods provide the most promising basis for automating qualitative reasoning about physical systems.     

What does it mean? Students’ procedural and conceptual problem solving in a CSCL environment designed within the field of science education

This article discusses the relationship between procedural and conceptual problem solving in a computer-supported collaborative learning (CSCL) environment designed within the field of science education. The contribution of this article, and our understanding of this phenomenon, is anchored in our socio-cultural interpretation, and that implies distinctive inputs for the design and re-design of these kinds of learning environments. We discuss institutional aspects linked to the school as a curriculum deliverer, as well as to the presentation of the knowledge domain and the construction of the CSCL environment. The data is gathered from a design experiment in a science setting in a secondary school, and video data is used to perform an interaction analysis. More specifically, we follow a group of four secondary school students who solve a biological problem in a computer-based 3D model supported by a website. Our findings are clear in the sense that the procedural types of problem solving tend to dominate the students’ interactions, while conceptual knowledge construction is only present where it is strictly necessary to carry out the problem solving. Based on our analyses, we conclude that this can be explained partly by how the knowledge domain is presented and how the CSCL environment is designed, but that the main reason is linked to the institutional aspects related to the school as curriculum deliverer where its target is to secure that the students actually solve problems that are predefined in the syllabus list. We argue that this affords some particular challenges, linked to making conceptual knowledge constructions in science education explicit in the CSCL environment, and to encouraging the teachers and the school as a curriculum deliverer to give this kind of knowledge construction a prioritised value.     

Tacit guidance for collaborative multimedia learning

Collaborative multimedia learning is a scenario placing various demands on the learners that go beyond understanding complex issues and coordinating a learning discourse. On the one hand, individuals have to mentally interrelate multiple external representations in order to understand the learning material and the underlying concepts; on the other hand, during collaboration, learners have to use the differently coded information in order to exchange conceptual knowledge. In this paper, the development and experimental evaluation of a group awareness tool (collaborative integration tool) is presented that is intended to simultaneously support both individual and collaborative learning processes during dyadic collaborative multimedia learning. The tool was experimentally compared with an integration task that already proved to foster meaningful individual learning processes. The results suggest that providing group awareness can lead to better individual learning gains by reducing demanding processes and by tacitly guiding learner interactions.     

Comparing the effects of representational tools in collaborative and individual inquiry learning

Constructing a representation in which students express their domain understanding can help them improve their knowledge. Many different representational formats can be used to express one’s domain understanding (e.g., concept maps, textual summaries, mathematical equations). The format can direct students’ attention to specific aspects of the subject matter. For example, creating a concept map can emphasize domain concepts and forming equations can stress arithmetical aspects. The focus of the current study was to examine the role of tools for constructing domain representations in collaborative inquiry learning. The study was driven by three questions. First, what are the effects of collaborative inquiry learning with representational tools on learning outcomes? Second, does format have differential effects on domain understanding? And third, does format have differential effects on students’ inclination to construct a representation? A pre-test post-test design was applied with 61 dyads in a (face-to-face) collaborative learning setting and 95 students in an individual setting. The participants worked on a learning task in a simulation-based learning environment equipped with a representational tool. The format of the tool was either conceptual or arithmetical or textual. Our results show that collaborative learners outperform individuals, in particular with regard to intuitive knowledge and situational knowledge. In the case of individuals a positive relation was observed between constructing a representation and learning outcomes, in particular situational knowledge. In general, the effects of format could not be linked directly to learning outcomes, but marked differences were found regarding students’ inclination to use or not use specific formats.     

Online collaboration: Collaborative behavior patterns and factors affecting globally distributed team performance

Studying the collaborative behavior of online learning teams and how this behavior is related to communication mode and task type is a complex process. Research about small group learning suggests that a higher percentage of social interactions occur in synchronous rather than asynchronous mode, and that students spend more time in task-oriented interaction in asynchronous discussions than in synchronous mode. This study analyzed the collaborative interaction patterns of global software development learning teams composed of students from Turkey, US, and Panama. Data collected from students’ chat histories and forum discussions from three global software development projects were collected and compared. Both qualitative and quantitative analysis methods were used to determine the differences between a group’s communication patterns in asynchronous versus synchronous communication mode. K-means clustering with the Ward method was used to investigate the patterns of behaviors in distributed teams. The results show that communication patterns are related to communication mode, the nature of the task, and the experience level of the leader. The paper also includes recommendations for building effective online collaborative teams and describes future research possibilities.