Promoting academically productive talk with conversational agent interventions in collaborative learning settings

Research on computer-supported collaborative learning (CSCL) and conversational pedagogical agents has strongly emphasized the value of providing dynamic dialogue support for learners working together to accomplish a certain task. Recently, on the basis of the classroom discourse framework of Academically Productive Talk (APT), a flexible form of conversational agent support has emerged employing APT-based intervention methods so as to stimulate pedagogically beneficial conversational interactions among learning partners. This paper investigates the impact of an APT-based Linking Contributions (LC) intervention mode implemented by a conversational agent in the context of a collaborative activity in higher education. This type of agent interventions encourages students to explicitly externalize their reasoning on important domain concepts building upon the contributions of their partners. Forty-three (43) students collaborated in small groups using a prototype CSCL system to accomplish three different tasks in the domain of Multimedia Learning. Groups were randomly assigned to the treatment or the control condition. In the treatment condition, a conversational agent participated in students' dialogues making LC mode interventions. In the control condition, students discussed without the agent intervening. The results of the study illustrated that the students in the treatment condition engaged in a more productive dialogue demonstrating increased explicit reasoning throughout the collaborative activity. Furthermore, it was shown that the students in the treatment condition outperformed the control students in various measures on knowledge acquisition. Evidence also suggests that students' enhanced learning performance was mediated by the positive effect of the agent intervention mode on students' argumentation. Overall, this study provides insights into how the use of a configurable conversational agent displaying unsolicited LC interventions during students' discourse can be beneficial to collaborative learning.     

Unnormalized and normalized forms of gefura measures in directed and undirected networks

In some networks nodes belong to predefined groups(e.g.,authors belong to institutions).Common network centrality measures do not take this structure into account.Gefura measures are designed as indicators of a node’s brokerage role between such groups.They are defined as variants of betweenness centrality and consider to what extent a node belongs to shortest paths between nodes from different groups.In this article we make the following new contributions to their study:(1) We systematically study unnormalized gefura measures and show that,next to the ‘structural’ normalization that has hitherto been applied,a ‘basic’ normalization procedure is possible.While the former normalizes at the level of groups,the latter normalizes at the level of nodes.(2) Treating undirected networks as equivalent to symmetric directed networks,we expand the definition of gefura measures to the directed case.(3) It is shown how Brandes’ algorithm for betweenness centrality can be adjusted to cover these cases.     

iTalk–iSee: A participatory visual learning analytical tool for productive peer talk

International Journal of Computer-Supported Collaborative Learning - Productive peer talk moves have a fundamental role in structuring group discussions and promoting peer interactions. However,...     

Data mining for agent reasoning: A synergy for training intelligent agents

The task-oriented nature of data mining (DM) has already been dealt successfully with the employment of intelligent agent systems that distribute tasks, collaborate and synchronize in order to reach their ultimate goal, the extraction of knowledge. A number of sophisticated multi-agent systems (MAS) that perform DM have been developed, proving that agent technology can indeed be used in order to solve DM problems. Looking into the opposite direction though, knowledge extracted through DM has not yet been exploited on MASs. The inductive nature of DM imposes logic limitations and hinders the application of the extracted knowledge on such kind of deductive systems. This problem can be overcome, however, when certain conditions are satisfied a priori. In this paper, we present an approach that takes the relevant limitations and considerations into account and provides a gateway on the way DM techniques can be employed in order to augment agent intelligence. This work demonstrates how the extracted knowledge can be used for the formulation initially, and the improvement, in the long run, of agent reasoning.     

A distributed finite-time optimization algorithm for directed networks of continuous-time agents

This article proposes a new distributed finite-time optimization algorithm for agents under directed graphs. By employing the nonsmooth technique and graph theory, a distributed discontinuous algorithm for continuous-time agents subject to strongly convex local cost functions is first designed with a finite-time distributed estimator, where the gradients of the local cost functions are estimated in finite time. It is shown that for a strongly connected graph and arbitrary initial conditions, the proposed algorithms can achieve consensus, and the systems can converge to the optimal point in finite time. Then, a two-step approach is proposed to achieve finite-time optimization of high-order agents with disturbances under directed graphs. Finally, the validity of the proposed finite-time optimization algorithm is verified by two numerical examples.     

Reaching a consensus in networks of high-order integral agents under switching directed topologies

Consensus problem of high-order integral multi-agent systems under switching directed topology is considered in this study. Depending on whether the agent’s full state is available or not, two distributed protocols are proposed to ensure that states of all agents can be convergent to a same stationary value. In the proposed protocols, the gain vector associated with the agent’s (estimated) state and the gain vector associated with the relative (estimated) states between agents are designed in a sophisticated way. By this particular design, the high-order integral multi-agent system can be transformed into a first-order integral multi-agent system. Also, the convergence of the transformed first-order integral agent’s state indicates the convergence of the original high-order integral agent’s state, if and only if all roots of the polynomial, whose coefficients are the entries of the gain vector associated with the relative (estimated) states between agents, are in the open left-half complex plane. Therefore, many analysis techniques in the first-order integral multi-agent system can be directly borrowed to solve the problems in the high-order integral multi-agent system. Due to this property, it is proved that to reach a consensus, the switching directed topology of multi-agent system is only required to be ‘uniformly jointly quasi-strongly connected’, which seems the mildest connectivity condition in the literature. In addition, the consensus problem of discrete-time high-order integral multi-agent systems is studied. The corresponding consensus protocol and performance analysis are presented. Finally, three simulation examples are provided to show the effectiveness of the proposed approach.     

NP-Click: a productive software development approach for network processors

Application-specific integrated circuit (ASIC) design is too risky and prohibitively expensive for many applications. This trend, combined with increasing silicon capability on a die, is fueling the emergence of application-specific programmable architectures. This focus on architecture design for network processors has made programming them an arduous task. Current network processors require in-depth knowledge of the architecture just to begin programming the device. However, for network processors to succeed, programmers must efficiently implement high-performance applications on them. Writing high-performance code for modern network processors is difficult because of their complexity. NP-Click is a simple programming model that permits programmers to reap the benefits of a domain specific language while still allowing for target-specific optimizations. Results for the Intel IXP1200 indicate that NP-Click delivers a large productivity gain at a slight performance expense.     

‘It''s just like you talk to a friend’ relational agents for older adults

Relational agents—computational artifacts designed to build and maintain long-term social–emotional relationships with users—may provide an effective interface modality for older adults. This is especially true when the agents use simulated face-to-face conversation as the primary communication medium, and for applications in which repeated interactions over long time periods are required, such as in health behavior change. In this article, we discuss the design of a relational agent for older adults that plays the role of an exercise advisor, and report on the results of a longitudinal study involving 21 adults aged 62–84, half of whom interacted with the agent daily for 2 months in their homes and half who served as a standard-of-care control. Results indicate the agent was accepted and liked, and was significantly more efficacious at increasing physical activity (daily steps walked) than the control.     

Pedagogical agents as learning companions: the impact of agent emotion and gender

Abstract  The potential of emotional interaction between human and computer has recently interested researchers in human–computer interaction. The instructional impact of this interaction in learning environments has not been established, however. This study examined the impact of emotion and gender of a pedagogical agent as a learning companion (PAL) on social judgements, interest, self-efficacy, and learning. Two experiments investigated separately the effects of a PAL's emotional expression and empathetic response. Experiment 1 focused on emotional expression (positive vs. negative vs. neutral) and gender (male vs. female) with a sample of 142 male and female college students in a computer literacy course. Experiment 2 investigated the impact of empathetic response (responsive vs. non-responsive) and gender with 56 pre-service teachers. Overall, the results yielded main and interaction effects of PAL emotion and gender on the dependent variables. In particular, the PAL's empathetic response had a positive impact on learner interest and self-efficacy; PAL gender had a positive impact on recall. The findings imply that the emotion and the gender of the digital learning companion could be utilized to optimize college students' motivation and learning.     

Systematic Review: Trust-Building Factors and Implications for Conversational Agent Design

ABSTRACT

Off-the-shelf conversational agents are permeating people’s everyday lives. In these artificial intelligence devices, trust plays a key role in users’ initial adoption and successful utilization. Factors enhancing trust toward conversational agents include appearances, voice features, and communication styles. Synthesizing such work will be useful in designing evidence-based, trustworthy conversational agents appropriate for various contexts. We conducted a systematic review of the experimental studies that investigated the effect of conversational agents’ and users’ characteristics on trust. From a full-text review of 29 articles, we identified five agent design-themes affecting trust toward conversational agents: social intelligence of the agent, voice characteristics and communication style, look of the agent, non-verbal communication, and performance quality. We also found that participants’ demographic, personality, or use context moderate the effect of these themes. We discuss implications for designing trustworthy conversational agents and responsibilities around on stereotypes and social norm building through agent design.     

A comparison study of 12 paradigms for developing embodied agents

We report on a study in which 12 different paradigms were used to implement agents acting in an environment which borrows elements from artificial life and multi‐player strategy games. In choosing the paradigms we strived to maintain a balance between high‐level, logic‐based approaches and low‐level, physics‐oriented models; between imperative programming, declarative approaches and ‘learning from basics’; between anthropomorphic or biologically inspired models on one hand and pragmatic, performance‐oriented approaches on the other. We have found that the choice of the paradigm determines the software development process and requires a different set of skills from the developers. In terms of raw performance, we found that the best performing paradigms were those which (a) allowed the knowledge of human experts to be explicitly transferred to the agent and (b) allowed the integration of well‐known, high‐performance algorithms. We have found that maintaining a commitment to the chosen paradigm can be difficult; there is a strong temptation to offer shallow fixes to perceived performance problems through a ‘flight into heuristics’. Our experience is that a development process without the discipline enforced by a central paradigm leads to agents which are a random collection of heuristics whose interactions are not clearly understood. Although far from providing a definitive verdict on the benefits of the different paradigms, our study provided a good insight into what kind of conceptual, technical or organizational problems would a development team face depending on their choice of agent paradigm. Copyright © 2007 John Wiley & Sons, Ltd.     

Empathic agents to reduce user frustration: The effects of varying agent characteristics

There is now growing interest in the development of computer systems which respond to users' emotion and affect. We report three small-scale studies (with a total of 42 participants), which investigate the extent to which affective agents, using strategies derived from human–human interaction, can reduce user frustration within human–computer interaction. The results confirm the previous findings of Klein et al. [Klein, J., Moon, Y., Picard, R.W., 2002. This computer responds to user frustration: theory, design and results. Interacting with Computers 142, 119–140] that such interventions can be effective. We also obtained results that suggest that embodied agents can be more effective at reducing frustration than non-embodied agents, and that female embodied agents may be more effective than male embodied agents. These results are discussed in light of the existing research literature.     

On average consensus in directed networks of agents with switching topology and time delay

In this article, the average consensus problem in directed networks of agents with both switching topology and coupling delay is investigated. First, based on a specific orthogonal transformation of the Laplacian matrix, an important proposition for verifying the positive definiteness of a class of quadratic forms is provided, which is of independent interest in matrix theory. And the relation between weakly connected and strongly connected digraphs is also investigated. Then, it is proved that all the agents reach the average consensus asymptotically for appropriate time delay if the communication topology keeps weakly connected and balanced. Finally, a numerical example is given to demonstrate the effectiveness and advantage of the new result.     

A backstepping design for directed formation control of three‐coleader agents in the plane

This paper deals with a directed formation control problem of three agents moving in the plane, where the agents have a cyclic ordering with each one required to maintain a nominated distance from its neighbor, and each agent is described by a double integrator. Firstly, a directed formation control law based on the knowledge only of the neighbor's direction is designed by using the integrator backstepping technique, which can not only accomplish the desired triangle formation but also ensure that speeds of all agents converge to a common value without collision between each other during the motion. Then, with the purpose of relaxing and even overcoming the restriction of initial conditions of the agents owing to collision avoidance, we introduce the inter‐agent potential functions into the design. The convergence of the proposed control algorithms is proved by using tools from LaSalle's invariance principle. Simulation results are provided to illustrate the effectiveness of the control laws. Copyright © 2008 John Wiley & Sons, Ltd.     

KLAIM: a kernel language for agents interaction and mobility

We investigate the issue of designing a kernel programming language for mobile computing and describe KLAIM, a language that supports a programming paradigm where processes, like data, can be moved from one computing environment to another. The language consists of a core Linda with multiple tuple spaces and of a set of operators for building processes. KLAIM naturally supports programming with explicit localities. Localities are first-class data (they can be manipulated like any other data), but the language provides coordination mechanisms to control the interaction protocols among located processes. The formal operational semantics is useful for discussing the design of the language and provides guidelines for implementations. KLAIM is equipped with a type system that statically checks access right violations of mobile agents. Types are used to describe the intentions (read, write, execute, etc.) of processes in relation to the various localities. The type system is used to determine the operations that processes want to perform at each locality, and to check whether they comply with the declared intentions and whether they have the necessary rights to perform the intended operations at the specific localities. Via a series of examples, we show that many mobile code programming paradigms can be naturally implemented in our kernel language. We also present a prototype implementation of KLAIM in Java     

Gaze awareness and metacognitive suggestions by a pedagogical conversational agent: an experimental investigation on interventions to support collaborative learning process and performance

International Journal of Computer-Supported Collaborative Learning - Research on collaborative learning has revealed that peer-collaboration explanation activities facilitate reflection and...     

Design and Evaluation of a Conversational Agent for Facilitating Idea Generation in Organizational Innovation Processes

Information Systems Frontiers - Large numbers of incomplete, unclear, and unspecific submissions on idea platforms hinder organizations to exploit the full potential of open innovation initiatives...