Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

Automatic coding of dialogue acts in collaboration protocols

Although protocol analysis can be an important tool for researchers to investigate the process of collaboration and communication, the use of this method of analysis can be time consuming. Hence, an automatic coding procedure for coding dialogue acts was developed. This procedure helps to determine the communicative function of messages in online discussions by recognizing discourse markers and cue phrases in the utterances. Five main communicative functions are distinguished: argumentative, responsive, informative, elicitative, and imperative. A total of 29 different dialogue acts are specified and recognized automatically in collaboration protocols. The reliability of the automatic coding procedure was determined by comparing automatically coded dialogue acts to hand-coded dialogue acts by a human rater. The validity of the automatic coding procedure was examined using three different types of analyses. First, an examination of group differences was used (dialogue acts used by female versus male students). Ideally, the coding procedure should be able to distinguish between groups who are likely to communicate differently. Second, to examine the validity of the automatic coding procedure through examination of experimental intervention, the results of the automatic coding procedure of students, with access to a tool that visualizes the degree of participation of each student, were compared to students who did not have access to this tool. Finally, the validity of the automatic coding procedure of dialogue acts was examined using correlation analyses. Results of the automatic coding procedure of dialogue acts of utterances (form) were related to results of a manual coding procedure of the collaborative activities to which the utterances refer (content). The analyses presented in this paper indicate promising results concerning the reliability and validity of the automatic coding procedure for dialogue acts. However, limitations of the procedure were also found and discussed.     

Measuring and analyzing agents’ uncertainty in argumentation-based negotiation dialogue games

Nowadays, multiagent systems have become a widely used technology in everyday life, and many authors have adopted the view of communication or interaction between agents as a joint activity regulated by means of dialogue games. Dialogue games are a set of communication rules that agents can combine in their complex interactions. In these games, uncertainty is an important problem that each agent faces when making decisions, especially in the absence of enough information. This paper focuses on the uncertainty in a particular type of dialogue games, namely argumentation-based negotiation. There exist several proposals on this type of dialogue games in the literature, and most of them are concerned with proposing protocols to show how agents can communicate with each other, and how arguments and offers can be generated, evaluated and exchanged. Nevertheless, none of them is directly targeting the agents’ uncertainty about the exchanged arguments and how this uncertainty could be measured at each dialogue step to assist those agents make better decisions. The aim of this paper is to tackle this problem by defining a new set of uncertainty measures in negotiation dialogue games from an external agent’s point of view. In particular, we introduce two types of uncertainty: Type I and Type II. Type I is about the uncertainty index of playing the right move. For this, we use Shannon entropy to measure: (i) the uncertainty index of the agent that he is selecting the right move at each dialogue step; and (ii) the uncertainty index of participating agents in the negotiation about the whole dialogue. This is done in two different ways; the first is by taking the average of the uncertainty index of all moves, and the second is by determining all possible dialogues and applying the general formula of Shannon entropy. Type II is about the uncertainty degree of the agent that the move will be accepted by the addressee. In this context, we introduce a new classification for the arguments based on their certainty to be accepted by the addressee.     

Public Displays of Play: Studying Online Games in Physical Settings

As research on virtual worlds gains increasing attention in educational, commercial, and military domains, a consideration of how player populations are ‘reassembled’ through social scientific data is a timely matter for communication scholars. This paper describes a large‐scale study of virtual worlds in which participants were recruited at public gaming events, as opposed to through online means, and explores the dynamic relationships between players and contexts of play that this approach makes visible. Challenging conventional approaches to quantitatively driven virtual worlds research, which categorizes players based on their involvement in an online game at a particular point in time, this account demonstrates how players' networked gaming activities are contingent on who they are playing with, where, and when.     

Do Men Advance Faster Than Women? Debunking the Gender Performance Gap in Two Massively Multiplayer Online Games

Prior research on digital games illustrates a perceived gender gap in participation and performance, suggesting men as playing more and better than women. This article challenges the gender gap using longitudinal behavioral data of men and women in 2 MMOs in the United States and China. Results show that women advance at least as fast as men do in both games. Thus, perceived gender‐based performance disparities seem to result from factors that are confounded with gender (i.e., amount of play), not player gender itself. We conclude that the stereotype of female players as inferior is not only false, but also a potential cause for unequal participation in digital gaming.     

Retracted: Antecedents and Consequences of Gender Swapping in Online Games

This study examines the reasons underlying gender swapping and its impacts on online gaming behavior. While previous studies considered gender swapping to be an abnormal or rare exception in one's self‐presentation, this study hypothesized that people swap genders as a rational choice based on practical benefits. An online survey was conducted with 318 male players of MMORPGs in Korea. Players swapped gender in games to gain benefits from other players under the condition of anonymity rather than to represent their own gender identity. Men playing female avatars displayed more socially amiable behaviors conventionally characterized as more feminine. Moreover, players were more willing to purchase virtual goods to decorate their gender swapped avatars, mediated by their emotional attachment to their avatar.     

Gaming Social Capital: Exploring Civic Value in Multiplayer Video Games

Recent research suggests that social interactions in video games may lead to the development of community bonding and prosocial attitudes. Building on this line of research, a national survey of U.S. adults finds that gamers who develop ties with a community of fellow gamers possess gaming social capital, a new gaming‐related community construct that is shown to be a positive antecedent in predicting both face‐to‐face social capital and civic participation.     

Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition

The automatic recognition of dialogue act is a task of crucial importance for the processing of natural language dialogue at discourse level. It is also one of the most challenging problems as most often the dialogue act is not expressed directly in speaker’s utterance. In this paper, a new cue-based model for dialogue act recognition is presented. The model is, essentially, a dynamic Bayesian network induced from manually annotated dialogue corpus via dynamic Bayesian machine learning algorithms. Furthermore, the dynamic Bayesian network’s random variables are constituted from sets of lexical cues selected automatically by means of a variable length genetic algorithm, developed specifically for this purpose. To evaluate the proposed approaches of design, three stages of experiments have been conducted. In the initial stage, the dynamic Bayesian network model is constructed using sets of lexical cues selected manually from the dialogue corpus. The model is evaluated against two previously proposed models and the results confirm the potentiality of dynamic Bayesian networks for dialogue act recognition. In the second stage, the developed variable length genetic algorithm is used to select different sets of lexical cues to constitute the dynamic Bayesian networks’ random variables. The developed approach is evaluated against some of the previously used ranking approaches and the results provide experimental evidences on its ability to avoid the drawbacks of the ranking approaches. In the third stage, the dynamic Bayesian networks model is constructed using random variables constituted from the sets of lexical cues generated in the second stage and the results confirm the effectiveness of the proposed approaches for designing dialogue act recognition model.     

Plans, Actions and Dialogues Using Linear Logic

We describe how Intuitionistic Linear Logic can be used to provide a unified logical account for agents to find and execute plans. This account supports the modelling of agent interaction, including dialogue; allows agents to be robust to unexpected events and failures; and supports significant reuse of agent specifications. The framework has been implemented and several case studies have been considered. Further applications include human–computer interfaces as well as agent interaction in the semantic web.     

Digital Game Dynamics Preferences and Player Types

In this study, we examine digital game preferences by identifying game dynamics, i.e. player–game interaction modes, of 700 contemporary digital games, and players' (N = 1717) desire to play games with specific types of dynamics. Based on statistical analysis of the data, 5 game dynamics preference categories (“assault,” “manage,” “journey,” “care,” and “coordinate”) and 7 player types were revealed. The results show that identifying player types requires including both preferred and undesired game dynamics categories in the analysis. The findings unveil digital gaming as a more multifaceted phenomenon than common stereotypes suggest. The original game preferences model we present in this study can be conceptualized as a complementary approach for motivations to play and player behavior studies.