Time Pressure and System Delays in Information Search

We report preliminary results of the impact of time pres- sure and system delays on search behavior from a laboratory study with forty-three participants. To induce time pres- sure, we randomly assigned half of our study participants to a treatment condition where they were only allowed five minutes to search for each of four ad-hoc search topics. The other half of the participants were given no task time limits. For half of participants’ search tasks (n=2), five second de- lays were introduced after queries were submitted and SERP results were clicked. Results showed that participants in the time pressure condition queried at a significantly higher rate, viewed significantly fewer documents per query, had significantly shallower hover and view depths, and spent sig- nificantly less time examining documents and SERPs. We found few significant differences in search behavior for sys- tem delay or interaction effects between time pressure and system delay. These initial results show time pressure has a significant impact on search behavior and suggest the de- sign of search interfaces and features that support people who are searching under time pressure

Follow-up question handling in the IMIX and Ritel systems: A comparative study

One of the basic topics of question answering (QA) dialogue systems is how follow-up questions should be interpreted by a QA system. In this paper, we shall discuss our experience with the IMIX and Ritel systems, for both of which a follow-up question handling scheme has been developed, and corpora have been collected. These two systems are each other's opposites in many respects: IMIX is multimodal, non-factoid, black-box QA, while Ritel is speech, factoid, keyword-based QA. Nevertheless, we will show that they are quite comparable, and that it is fruitful to examine the similarities and differences. We shall look at how the systems are composed, and how real, non-expert, users interact with the systems. We shall also provide comparisons with systems from the literature where possible, and indicate where open issues lie and in what areas existing systems may be improved. We conclude that most systems have a common architecture with a set of common subtasks, in particular detecting follow-up questions and finding referents for them. We characterise these tasks using the typical techniques used for performing them, and data from our corpora. We also identify a special type of follow-up question, the discourse question, which is asked when the user is trying to understand an answer, and propose some basic methods for handling it

Stemming the flow: improving retention for distance learning students

Though concern about student attrition and failure is not a new phenomenon, higher education institutions (HEIs) have struggled to significantly reduce the revolving door syndrome. Open distance learning higher education is particularly susceptible to high student attrition. Despite a great deal of research into the student journey and factors impacting on likely success, we are not necessarily closer to understanding and being able to mitigate against student attrition. Learning analytics as emerging discipline and practice promises to help penetrate the fog… This case study describes work undertaken at the Open University in the UK to investigate how a learning analytics approach allows the University to provide timely and appropriate student support in a cost-effective manner. It includes a summary of the establishment of curriculum-based student support teams and a framework which defines more standardised student support informed by both student data and an enhanced knowledge of the curriculum. The primary aim of student support teams is to proactively support students through their study journey and to optimise their chances of reaching their declared study goals. Higher education institutions (HEIs) are making increasing use of learning analytics to support delivery of timely and relevant student support. The Open University in the UK, like other HEIs, knows a great deal about its students before they start to study and is able to track student behaviours once study has begun. Until recently, the university has not taken full advantage of the additional insight offered by such information. This paper describes the framework of support interventions established for all student support teams and describes the learning analytics approach used to support that framework

Semantics and Conversations for an Agent Communication Language

We address the issues of semantics and conversations for agent communication languages and the Knowledge Query Manipulation Language (KQML) in particular. Based on ideas from speech act theory, we present a semantic description for KQML that associates ``cognitive'' states of the agent with the use of the language's primitives (performatives). We have used this approach to describe the semantics for the whole set of reserved KQML performatives. Building on the semantics, we devise the conversation policies, i.e., a formal description of how KQML performatives may be combined into KQML exchanges (conversations), using a Definite Clause Grammar. Our research offers methods for a speech act theory-based semantic description of a language of communication acts and for the specification of the protocols associated with these acts. Languages of communication acts address the issue of communication among software applications at a level of abstraction that is useful to the emerging software agents paradigm.Comment: Also in in "Readings in Agents", Michael Huhns and Munindar Singh (eds), Morgan Kaufmann Publishers, In