A tutorial task and tertiary courseware model for collaborative learning communities

RAED provides a computerised infrastructure to support the development and administration of Vicarious Learning in collaborative learning communities spread across multiple universities and workplaces. The system is based on the OASIS middleware for Role-based Access Control. This paper describes the origins of the model and the approach to implementation and outlines some of its benefits to collaborative teachers and learners

Using contextual information to understand searching and browsing behavior

There is great imbalance in the richness of information on the web and the succinctness and poverty of search requests of web users, making their queries only a partial description of the underlying complex information needs. Finding ways to better leverage contextual information and make search context-aware holds the promise to dramatically improve the search experience of users. We conducted a series of studies to discover, model and utilize contextual information in order to understand and improve users' searching and browsing behavior on the web. Our results capture important aspects of context under the realistic conditions of different online search services, aiming to ensure that our scientific insights and solutions transfer to the operational settings of real world applications

The National Dialogue on the Quadrennial Homeland Security Review

Six years after its creation, the Department of Homeland Security (DHS) undertook the first Quadrennial Homeland Security Review (QHSR) to inform the design and implementation of actions to ensure the safety of the United States and its citizens. This review, mandated by the Implementing the 9/11 Commission Recommendations Act of 2007, represents the first comprehensive examination of the homeland security strategy of the nation. The QHSR includes recommendations addressing the long-term strategy and priorities of the nation for homeland security and guidance on the programs, assets, capabilities, budget, policies, and authorities of the department.Rather than set policy internally and implement it in a top-down fashion, DHS undertook the QHSR in a new and innovative way by engaging tens of thousands of stakeholders and soliciting their ideas and comments at the outset of the process. Through a series of three-week-long, web-based discussions, stakeholders reviewed materials developed by DHS study groups, submitted and discussed their own ideas and priorities, and rated or "tagged" others' feedback to surface the most relevant ideas and important themes deserving further consideration.Key FindingsThe recommendations included: (1) DHS should enhance its capacity for coordinating stakeholder engagement and consultation efforts across its component agencies, (2) DHS and other agencies should create special procurement and contracting guidance for acquisitions that involve creating or hosting such web-based engagement platforms as the National Dialogue, and (3) DHS should begin future stakeholder engagements by crafting quantitative metrics or indicators to measure such outcomes as transparency, community-building, and capacity

Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation

We introduce the multiresolution recurrent neural network, which extends the sequence-to-sequence framework to model natural language generation as two parallel discrete stochastic processes: a sequence of high-level coarse tokens, and a sequence of natural language tokens. There are many ways to estimate or learn the high-level coarse tokens, but we argue that a simple extraction procedure is sufficient to capture a wealth of high-level discourse semantics. Such procedure allows training the multiresolution recurrent neural network by maximizing the exact joint log-likelihood over both sequences. In contrast to the standard log- likelihood objective w.r.t. natural language tokens (word perplexity), optimizing the joint log-likelihood biases the model towards modeling high-level abstractions. We apply the proposed model to the task of dialogue response generation in two challenging domains: the Ubuntu technical support domain, and Twitter conversations. On Ubuntu, the model outperforms competing approaches by a substantial margin, achieving state-of-the-art results according to both automatic evaluation metrics and a human evaluation study. On Twitter, the model appears to generate more relevant and on-topic responses according to automatic evaluation metrics. Finally, our experiments demonstrate that the proposed model is more adept at overcoming the sparsity of natural language and is better able to capture long-term structure.Comment: 21 pages, 2 figures, 10 table

Achieving Green and Healthy Homes and Communities in America

In the Fall of 2010, the National Coalition to End Childhood Lead Poisioning contracted with the National Academy to develop and execute an online dialogue that would examine ways to increase the health, safety, and energy efficiency of low- to moderate-income homes. Since 1999, the National Coalition had worked to improve low- to moderate-income housing through the support and execution of home interventions that addressed multiple issues within a home at one time; an approach that often did not align with other traditional, single-issue housing assistance programs. By 2010, the National Coalition had taken on the leadership of the Green and Healthy Homes Initiative, a public-private partnership focused on integrating funding streams to improve low- to middle-income homes across the country.With plans to expand the GHHI's operations, the National Coalition partnered with the National Academy to conduct the National Dialogue on Green and Healthy Homes, a collaborative online dailogue in which participants were asked to identify challenges to, and innovative practices for, improving the health, safety and energy-efficiency of low- to moderate- income homes. The Dialogue was live from November 4-November 22, 2010, and collected 100 hundred ideas and 362 comments from 320 registered users. Over the course of its two and a half week duration, the Dialogue received more than 2,500 visits from over 1,100 people in 48 states and territories. Key FindingsBy reviewing the feedback received in the Dialogue, the Panel was able to make a number of recommendations on how the green and healthy homes community of practice could increase the health, safety and energy efficiency of homes across the country. These recommendations included: Conduct an evaluation of current housing standards to determine if they meet the Nation's health, safety, and energy efficiency needs; Develop a tiered performance standard for healthy, safe and energy efficient homes; Group government funding streams to better align programs with the comprehensive intervention approach; Develop a long-term funding strategy to support efforts after Recovery Act funding ends; and Educate government decisionmakers and the public on the importance of developing green and healthy homes and communities, and the work that supports that development

Formalisation and evaluation of focus theories for requirements elicitation dialogues in natural language

Requirements engineering is an important part of software engineering. It consists in defining the needs of users when building a new system. These needs may be functional, i.e., what service should the system be able to provide, as well as non-functional, i.e., under which constraints should the system operate. Errors in requirements may have disastrous effects in the rest of the software engineering process (Brooks 1995, p.199), since they would lead to the construction of a system of little interest to its users or would require expensive modifications to correct. Because requirements documents may be very large, errors are usually hard to detect manually. Computer support is therefore often beneficial for their analysis. This is made easier if requirements are expressed formally. However, this support must also be adapted to and be usable by people who are expressing their requirements. These people are usually not computer specialists and are not accustomed to use formal languages. It is therefore necessary to help them express their requirements. Numerous approaches, have been suggested as aids to the acquisition of requirements (Reubenstein 1990). Much less attention has been paid to the control of the dialogue taking place between the users and the system whilst using such frameworks (Bubenko et al. 1994). Frameworks for requirements acquisition are not normally accompanied by theories of the types of dialogue which they support. Our ability to develop sophisticated formal frameworks to analyse requirements makes this deficiency more acutely felt, since increases in formality are often accompanied by greater difficulty in understanding and using the frameworks (Robertson et al. 1989).Users write their requirements in more or less natural language. This is then translated into a formal language that can be interpreted by the elicitation module. This module works on the requirements and provide feedback. The translation process is then applied to convert feedback into more or less natural language. Different systems put different emphasis on the parts of that general architecture. Some are very good at natural language interpretation while others put more emphasis on analysing the requirements and providing feedback.Natural language approaches to requirements elicitation, put an emphasis on natural language interpretation (see section 1.2.1). In these approaches, users write their specifica¬ tion in a subset of natural language. The system then translates it into a formal notation. The main benefit provided by these approaches is the improvement in the ease of use of the system: natural language is the main means of communication for human beings and does not need to be learned. However, most of these approaches do not provide a dialogue well suited for the requirements elicitation process. Because they translate the natural lan¬ guage specification into a formal notation but do not provide guidance on how to write the specification in the first place, users are left in charge of writing correct requirements. If a mistake is made while writing the specification, it will simply be translated into the formal notation.In order to actively help users in the process of writing the requirements, the elicit¬ ation system must interact with them. The emphasis, here, is no longer on translating requirements, but on actively extracting them through a dialogue with users. This is useful, since the requirements elicitation process is complex, and offering guidance is a big help for users. Unfortunately, most of the approaches providing guidance expose their formal underlying frameworks directly to users (see section 1.2.2). In order to benefit from the guidance provided, users have to learn the idiosyncrasies of the system they use. The task of providing guidance is complicated by the fact that there are numerous ways of carrying out the requirements elicitation. Very little research has been done on how to organise best the elicitation process to provide effective guidance. An arbitrary choice could be made, but forcing users to adopt a predefined method is usually not possible as it would make the elicitation process very difficult to follow and understand. The system must therefore be able to adapt itself to various elicitation methods. On the other hand, it is necessary for the system to make choices in order to provide active guidance. A "least-commitment" strategy, such as asking users at every choice point what to do next, is not a useful approach (Ferguson et al. 1996).One way of offering guidance without restricting users too much is by communicating with them in natural language, and by using natural language constraints to inform the choices made by the system to select a guidance strategy. These constraints ensure that the system adopts a strategy that will guide users in a natural and understandable manner, by taking into account the current state of the dialogue. In other words, the system takes into account the current state of the specification to help users complete it, but the current state of the dialogue is the principal factor constraining what will be spoken about next. Using such an approach reduces some of the problems discussed above. The specification does not need to be immediately correct as it will be checked and reworked by the system. The formal framework is hidden from users but is still there to ensure the correctness of the specifications. Guidance is continuously offered through dialogue, which is influenced by but does not directly follow the steps of construction of the specification.The natural language constraints we use in this thesis are theories of dialogue coherence, called "focus" theories. They define what can be spoken about next in a dialogue based on what has already been discussed and the subject under discussion. The theories take into account what participants in a dialogue pay attention to and try to ensure that the rest of the dialogue is related to it. The systems tries to help its users define how a research group WWW site should look like. The way the dialogue evolves from discussing the research group, to discussing the site and its associated home page, to discussing the set of publication can quite easily be followed. The use of pronouns helps in making the text fell natural. It would have been difficult to achieve the same result without using focus rules.Other techniques for organising dialogues, such as those based on the intentions under¬ lying the dialogue (Cohen et al. 1990), would require the dialogue manager to know what the elicitation system is trying to achieve and what its plan is. For some elicitation systems, this knowledge may not be available. Similarly, techniques based on the content of the communications exchanged and how they relate, e.g., based on RST (Mann and Thompson 1987), usually require a lot of domain knowledge. They are therefore time-consumming to code. Focus theories require less information from the elicitation module while enabling the dialogue manager to structure the dialogue. However, in some cases, focus theories are not sufficient to organise a dialogue. We use a theory based on speech act (see section 3.4.1) and some ideas from Grice's work on conversation (see section 5.2.1) to deal with these cases. More generally, although we tried to minimise the impact of other theories to study in detail focus theories, it would be interesting to know whether and how we can integrate them with the work presented in this thesis. In particular, the notion of dialog act and its application to dialog grammar could be of interest. General frameworks developped to study various aspects of dialogue, including dialog acts and focus, have started to appear but work is still at an early stage (C-Star Consortium 1998; Allen and Core 1997).Organising a dialogue based on attention requires a lot of domain knowledge in order to know how things mentioned in the dialogue relate to each other. Therefore, the amount of knowledge engineering needed to build natural language applications is also an important issue. We have tried to limit the engineering difficulties by clearly separating the domain knowledge needed by our dialogue manager from its management capabilities, and by provid¬ ing a way of re-using the existing domain knowledge as far as possible. This is done by using rules which enable us to re-use part of the domain knowledge already used by the elicitation module.The contribution of this thesis is therefore the formalisation and evaluation of focus theories for requirements elicitation dialogues in natural language. The main questions we deal with are the following: • Which focus theories should we use? • What are the relations between the constraints imposed by the focus theories and the constraints inherent to the requirements elicitation process? • Does this approach improve the perceived quality of the dialogue between the elicita¬ tion tool and its users?A prototype system has been developed. This system mainly operates in the WWW site design domain. It has also been applied in other domains as an initial demonstration of the range of problems that can be tackled by our approach

Investigating the user experience of customer service chatbot interaction: a framework for qualitative analysis of chatbot dialogues

The uptake of chatbots for customer service depends on the user experience. For such chatbots, user experience in particular concerns whether the user is provided relevant answers to their queries and the chatbot interaction brings them closer to resolving their problem. Dialogue data from interactions between users and chatbots represents a potentially valuable source of insight into user experience. However, there is a need for knowledge of how to make use of these data. Motivated by this, we present a framework for qualitative analysis of chatbot dialogues in the customer service domain. The framework has been developed across several studies involving two chatbots for customer service, in collaboration with the chatbot hosts. We present the framework and illustrate its application with insights from three case examples. Through the case findings, we show how the framework may provide insight into key drivers of user experience, including response relevance and dialogue helpfulness (Case 1), insight to drive chatbot improvement in practice (Case 2), and insight of theoretical and practical relevance for understanding chatbot user types and interaction patterns (Case 3). On the basis of the findings, we discuss the strengths and limitations of the framework, its theoretical and practical implications, and directions for future work.publishedVersio

Sustaining Public Engagement: Embedded Deliberation in Local Communities

Describes nine communities using organized deliberation to consider public issues over several years and their accomplishments and analyzes how public deliberation addresses deficits in local democratic governance. Includes benchmarks and strategies