Expansive Visibilization of Work: An Activity-Theoretical Perspective

Work is commonly made visible along two dimensions: the linear and the socio-spatial. Both are limited to depicting work in terms of relatively discrete actions. Activity theory introduces the crucial distinction between collective activity systems and individual actions. Expansive visibilization of collective activity systems offers a powerful intervention methodology for dealing with major transformations of work. The linear and the socio-spatial dimensions of work actions are seen in the broader perspective of a third, developmental dimension of work activity. Four steps are identified in a cycle of expansive visibilization, combining activity-level visions and action-level concretizations. The cycle is examined in detail as it unfolded in an intervention study at a children's hospital in Finland. It is concluded that expansive visibilization, driven by contradictions and seeking to reconceptualize the object and motive of work, is not a straightforward process which can be neatly controlled from above. Coherent analytical explanation and goal-setting may come only after the creation and practical implementation of innovative solutions.     

Understanding organizational learning by focusing on “activity systems”

This paper suggests that in order to understand relations between different aspects of organizational learning, an appropriate unit of analysis and a concrete, historical approach is needed. The units of analysis used in representative theories of organizational learning are first reviewed and evaluated. “Activity system”, a concept that is based on Cultural Historical Activity Theory, is then introduced as a potential candidate for a unit of analysis that makes it possible to analyze the specific historical, local challenges and problems of organizational learning and to direct a collective learning process. A case of organizational learning is then presented by using a model of the activity system and Activity Theory-based intervention methodology. Theoretical implications of the case are pointed out in discussion.     

Repositories and communities at cross-purposes: issues in sharing and reuse of digital learning resources

Abstract   Globally, institutions are setting up digital repositories to support the sharing of resources for teaching and learning. The educational rationale is that a single set of resources can be restructured to support different pedagogical approaches and to achieve economies of scale. A key problem is that these learning object repositories (LORs), like many other learning technology innovations, are often designed to exploit the capabilities of technology rather than to meet learners' needs. The premise of this study is that the nature and organization of a community is likely to impact the way an LOR is used. Key dimensions of repositories and communities are discussed. Three repository systems are analysed to identify how communities use repositories. Guided by Activity Theory, the LORs and user communities are analysed as activity systems. These activity systems are compared and contradictions between them are identified. From the analysis, barriers and enablers for the use of LORs to support learning are discussed and a framework for addressing the key issues in the repository development stage is proposed.     

Activity Theory as a conceptual framework for understanding teacher approaches to Information and Communication Technologies

While the issue of teachers’ perspectives on the barriers to technology use has received considerable attention, teacher concerns have not been studied in a systematic and holistic way. The present paper examines teacher concerns regarding a proposed technology-based innovation using Activity Theory as a theoretical framework. Fifty-one teachers participated in an inservice blended learning course in which a real-life Computer Supported Collaborative Learning example was presented and subsequently discussed in the online forum. The teachers were asked under which conditions they thought Computer Supported Collaborative Learning could be incorporated into their daily practices. Teacher concerns were identified through their online posts. Time and curriculum constraints were reported by teachers as the main obstacles to the proposed technological innovation. The examination of these obstacles using Activity Theory helped to identify three major contradictions in teachers’ activity system: (a) within the object of activity, (b) between the mediational means and the object of activity and (c) between the current and the proposed object. These contradictions are discussed from the perspective of Activity Theory and their implications for the design and implementation of technology are drawn.     

A View on Human Goal-Directed Activity and the Construction of Artificial Intelligence

Although activity aimed at the construction of artificial intelligence started about 60 years ago however, contemporary intelligent systems are effective in very narrow domains only. One of the reasons for this situation appears to be serious problems in the theory of intelligence. Intelligence is a characteristic of goal-directed systems and two classes of goal-directed systems can be derived from observations on animals and humans, one class is systems with innately and jointly determined goals and means. The other class contains systems that are able to construct arbitrary goals and means. It is suggested that the classes (that implicitly underlie most models of artificial intelligence) are insufficient to explain human goal-directed activity. A broader approach to goal-directed systems is considered. This approach suggests that humans are goal-directed systems that jointly synthesize arbitrary goals and means. Neural and psychological data favoring this hypothesis and its experimental validation are considered. A simple computer model based on the idea of joint synthesis to simulate goal-directed activity is presented. The usage of the idea of joint synthesis for the construction of artificial intelligence is discussed.     

Information Systems Development as an Activity

Information systems development (ISD) is analysed in this paper as asystemic work activity, using Activity Analysis and Development (ActAD)as the theoretical framework. ISD is regarded here as the process bywhich some collective work activity is facilitated by newinformation-technological means through analysis, design, implementation,introduction and sustained support, as well as process management. Itis a temporary, boundary-crossing activity which draws its actors,means, rules, etc. from two sides – typically a software companyand the IS user organization. ISD is analysed as a part of a networkof activities, too, around software development and a computer-supporteduse activity. A theoretical framework and a pragmatic checklist arepresented for studying ISD activities. It is argued that the activity-theoretical framework provides a theoretically foundedbut detailed and practicable procedure for studying ISD as a workactivity in context.     

Interactive innovation of technology for mobile work

Despite the increasing popularity of mobile information systems, the actual processes leading to the innovation of mobile technologies remain largely unexplored. This study uses Action Research to examine the innovation of a mobile RFID technology. Working from Activity Theory, it departs from the prevalent product-oriented view of innovation and treats technology-in-the-making as a complex activity, made possible through the interaction of manufacturers, their organisational clients and their respective mobile workers. The lens of a normative Interactive Innovation Framework reveals distinctive interaction problems that bear on the innovation activity. In addition to difficulties emerging from dissimilar motivations for the innovation project, the mobile setting presents unique contradictions based on the geographical distribution of its participants, the diverse role of mobile technology, the complexity of interacting through representations and the importance of the discretion with which mobile work activities are carried out today.     

Organisational learning—a critical systems thinking discipline

This paper deals with the application of critical systems thinking in the domain of organisational learning and knowledge management. Its viewpoint is that deep organisational learning only takes place when the business systems' stakeholders reflect on their actions and thus inquire about their purpose(s) in relation to the business system and the other stakeholders they perceive to exist. This is done by reflecting both on the sources of motivation and/or deception that are contained in their purpose, and also on the sources of collective motivation and/or deception that are contained in the business system's purpose. The development of an organisational information system that captures, manages and institutionalises meaningful information—a knowledge management system—cannot be separated from organisational learning practices, since it should be the result of these very practices. Although Senge's five disciplines provide a useful starting-point in looking at organisational learning, we argue for a critical systems approach, instead of an uncritical Systems Dynamics one that concentrates only on the organisational learning practices.We proceed to outline a methodology called Business Systems Purpose Analysis (BSPA) that offers a participatory structure for team and organisational learning, upon which the stakeholders can take legitimate action that is based on the force of the better argument. In addition, the organisational learning process in BSPA leads to the development of an intrinsically motivated information organisational system that allows for the institutionalisation of the learning process itself in the form of an organisational knowledge management system. This could be a specific application, or something as wide-ranging as an Enterprise Resource Planning (ERP) implementation. Examples of the use of BSPA in two ERP implementations are presented.     

Concept-based learning of human behavior for customer relationship management

In this paper, we apply concept learning techniques to solve a number of problems in the customer relationship management (CRM) domain. We present a concept learning technique to tackle common scenarios of interaction between conflicting human agents (such as customers and customer support representatives). Scenarios are represented by directed graphs with labeled vertices (for communicative actions) and arcs (for temporal and causal relationships between these actions and their parameters). The classification of a scenario is performed by comparing a partial matching of its graph with graphs of positive and negative examples. We illustrate machine learning of graph structures using the Nearest Neighbor approach and then proceed to JSM-based concept learning, which minimizes the number of false negatives and takes advantage of a more accurate way of matching sequences of communicative actions. Scenario representation and comparative analysis techniques developed herein are applied to the classification of textual customer complaints as a CRM component. In order to estimate complaint validity, we take advantage of the observation [19] that analyzing the structure of communicative actions without context information is frequently sufficient to judge how humans explain their behavior, in a plausible way or not. This paper demonstrates the superiority of concept learning in tackling human attitudes. Therefore, because human attitudes are domain-independent, the proposed concept learning approach is a good compliment to a wide range of CRM technologies where a formal treatment of inter-human interactions is required.     

教与学——巧用通道“合成图片”

本文主要通过对学习内容、学习目标、学习重点和难点的分析,迎合社会需求,并结合学生实际进行知识解读采取相应的教法、学法一在Photoshop中如何利用选区与通道合成图片的方法。主要采用任务引领教学法引导学生进行主动式学习,首先采用资讯的方式进行自主式学习,逐步摸索出自主学习的方法;然后采用工作页方式指导学生完成任务,在完整的工作过程中进行理论实践一体化的学习;最后,展示作品、集体进行点评,充分发展学生的创造性思维!     

Learning in groups of traffic signals

Computer science in general, and artificial intelligence and multiagent systems in particular, are part of an effort to build intelligent transportation systems. An efficient use of the existing infrastructure relates closely to multiagent systems as many problems in traffic management and control are inherently distributed. In particular, traffic signal controllers located at intersections can be seen as autonomous agents. However, challenging issues are involved in this kind of modeling: the number of agents is high; in general agents must be highly adaptive; they must react to changes in the environment at individual level while also causing an unpredictable collective pattern, as they act in a highly coupled environment. Therefore, traffic signal control poses many challenges for standard techniques from multiagent systems such as learning. Despite the progress in multiagent reinforcement learning via formalisms based on stochastic games, these cannot cope with a high number of agents due to the combinatorial explosion in the number of joint actions. One possible way to reduce the complexity of the problem is to have agents organized in groups of limited size so that the number of joint actions is reduced. These groups are then coordinated by another agent, a tutor or supervisor. Thus, this paper investigates the task of multiagent reinforcement learning for control of traffic signals in two situations: agents act individually (individual learners) and agents can be “tutored”, meaning that another agent with a broader sight will recommend a joint action.     

Function allocation: a perspective from studies of work practice

Function allocation is a central component of systems engineering and its main aim is to provide a rational means of determining which system-level functions should be carried out by humans and which by machines. Such allocation, it is assumed, can take place early in design life cycle. Such a rational approach to work design sits uneasily with studies of work practice reported in the ACI and CSCW literature. In this paper we present two case studies of work in practice. The first highlights the difference between functional abstractions used for function allocation decision making and what is required to make those functions work in practice. The second highlights how practice and technology can co-evolve in ways that change the meanings of functions allocated early in design. The case studies raise a number of implications for function allocation. One implication is that there is a need for richer representations of the work context in function allocation methods. Although some progress has been made in function allocation methodologies, it is suggested that the method of Contextual Design might offer useful insights. A second implication is that there is a need for better theories of work to inform function allocation decision making. Activity Theory is considered as a possible candidate since it incorporates a cultural-historical view of work evolution. Both Contextual Design and Activity Theory challenge assumptions that are deeply embedded in the human factors and systems engineering communities. In particular, that functions and tasks are an appropriate unit of analysis for function allocation.     

Autonomous online generation of a motor representation of the workspace for intelligent whole-body reaching

We describe a learning strategy that allows a humanoid robot to autonomously build a representation of its workspace: we call this representation Reachable Space Map. Interestingly, the robot can use this map to: (i) estimate the Reachability of a visually detected object (i.e. judge whether the object can be reached for, and how well, according to some performance metric) and (ii) modify its body posture or its position with respect to the object to achieve better reaching. The robot learns this map incrementally during the execution of goal-directed reaching movements; reaching control employs kinematic models that are updated online as well. Our solution is innovative with respect to previous works in three aspects: the robot workspace is described using a gaze-centered motor representation, the map is built incrementally during the execution of goal-directed actions, learning is autonomous and online. We implement our strategy on the 48-DOFs humanoid robot Kobian and we show how the Reachable Space Map can support intelligent reaching behavior with the whole-body (i.e. head, eyes, arm, waist, legs).     

Exploring the antecedents of team performance in collaborative learning of computer software

As teamwork becomes common in computer software learning, there is an increasing need to study factors contributing to team performance. To this pursuit, the concept of collective efficacy offers great potential to researchers of information systems (IS). Drawing upon social cognitive theory (SCT), this study examines the relationships among computer collective efficacy (CCE), outcome expectations and team performance in the context of collaborative learning. Computer collective efficacy is further divided into two constructs, general CCE and specific CCE. Their causal relationships with two other constructs, performance and outcome expectations, are then investigated using longitudinal data collected from 188 groups of students of an 18-week computer software course. The results indicate that a team’s software learning performance is strongly influenced by specific CCE and outcome expectations, which in turn are influenced by prior performance and general CCE. Finally, prior performance of a group has no direct impact on its subsequent performance.     

Bacterial colonies as complex adaptive systems

The present work explores bacterial colonies and their individual and social behaviours under the lens of complex adaptive systems. We initially provide a background on the biology of bacteria to describe important phenomena, such as quorum-sensing, individual and collective behaviours, adaptation, evolution and self-organization over the influence of mechanical effects on bacterial systems and connecting scales. We then explore some associations between bacterial colonies and complex adaptive systems by considering components and ownerships of self-organization. The main contribution of this paper places emphasis on individual decision-making and behaviour as a cause of bacterial colonies’ actions, i.e., how self-organization and collective behaviours impact the ability of a bacterial colony to address an environmental stimulus and maintain itself as an open biological and fault-tolerant system. Finally, we conclude the work and provide some comments regarding future research.     

基于多级深度网络架构的群体行为分析模型研究

群体行为的多层次深度分析是行为识别领域亟待解决的重要问题。在深度神经网络研究的基础上,提出了群体行为识别的层级性分析模型。基于调控网络的迁移学习,实现了行为群体中多人体的时序一致性检测;通过融合时空特征学习,完成了群体行为中时长无约束的个体行为识别;通过场景中个体行为类别、交互场景上下文信息的融合,实现了对群体行为稳定有效的识别。在公用数据集上进行的大量实验表明,与现有方法相比,该模型在群体行为分析识别方面具有良好的效果。     

Activity Theory and Higher Education: evaluating learning technologies

Abstract This paper examines current practice in the evaluation of learning technology in the UK and proposes a new approach informed by Activity Theory. It is based on our experiences of using Activity Theory to understand students' and lecturers' experiences of technology-based teaching environments. We discuss the activity of evaluating learning technologies in higher education, and some frameworks currently in use that assume an efficiency criteria for their evaluations. We use the evaluation criteria proposed by Breen et al . (2001) as a starting point for alternative criteria to review a number of examples of technology based teaching in Higher Education. We identify a need for a broader view of the outcomes and value of using learning technologies and relate this activity to a new approach based on an Activity Theory augmented view of evaluation.