An Empirical Investigation of Collaborative Web Search Tool on Novice\u27s Query Behavior

In the past decade, research efforts dedicated to studying the process of collaborative web search have been on the rise. Yet, a limited number of studies have examined the impact of collaborative information search processes on novices’ query behaviors. Studying and analyzing factors that influence web search behaviors, specifically users’ patterns of queries when using collaborative search systems can help with making query suggestions for group users. Improvements in user query behaviors and system query suggestions help in reducing search time and increasing query success rates for novices. This thesis investigates the influence of collaboration between experts and novices as well as the use of a collaborative web search tool on novices’ query behavior. We used SearchTeam as our collaborative search tool. This empirical study involves four collaborative team conditions: SearchTeam and expert-novice team, SearchTeam and novice-novice team, traditional and expert-novice team, and traditional and novice-novice team. We analyzed participants’ query behavior in two dimensions: quantitatively (e.g. the query success rate), and qualitatively (e.g. the query reformulation patterns). The findings of this study reveal that the successful query rate is higher in expert-novice collaborative teams, who used the collaborative search tools. Participants in expert-novice collaborative teams who used the collaborative search tools, required less time to finalize all tasks compared to expert-novice collaborative teams, who used the traditional search tools. Self-issued queries and chat logs were major sources of terms that novice participants in expert-novice collaborative teams who used the collaborative search tools used. Novices as part of expert-novice pairs who used the collaborative search tools, employed New and Specialization more often as query reformulation patterns. The results of this study contribute to the literature by providing detailed investigation regarding the influence of utilizing collaborative search tool (SearchTeam) in the context of software troubleshooting and development. This study highlights the possible collaborative information seeking (CIS) activities that may occur among software developers’ interns and their mentors. Furthermore, our study reveals that there are specific features, such as awareness and built-in instant messaging (IM), offered by SearchTeam that can promote the CIS activities among participants and help increase novices’ query success rates. Finally, we believe the use of CIS tools, designed to support collaborative search actions in big software development companies, has the potential to improve the overall novices’ query behavior and search strategies

Intelligent system for eliciting and explaining knowledge

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2005.Includes bibliographical references (leaves 97-100).We propose i-Seek, an Intelligent System for Eliciting and Explaining Knowledge that leverages the OpenMind [1] Commonsense knowledge base in conjunction with domain- specific knowledge in Personal Finance, Technical Help, and Health domains to act as an advisory system for novice users. Most of the interfaces are plagued by recurrent key problems: 1) elicitation - how to ask questions that enable the expert model to make decisions, and at the same time, are understandable to the novice, and 2) explanation - how to explain rationale behind expert decisions in terms that the user can understand. i- Seek maps the user's goals and expectations to the corresponding expert model's attributes as expressed in domain-specific terms. For example, instead of asking "What is your risk tolerance?", where the user might not comprehend the notion of risk tolerance, i-Seek tries to elicit the same information by asking a non-direct question such as "Do you usually buy lots of lottery tickets?". i-Seek constructs the novice user model by taking into account the user's personal information, interactions history, and the current context.by Ashwani Kumar.S.M

Grounding language in events

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 137-142).Broadcast video and virtual environments are just two of the growing number of domains in which language is embedded in multiple modalities of rich non-linguistic information. Applications for such multimodal domains are often based on traditional natural language processing techniques that ignore the connection between words and the non-linguistic context in which they are used. This thesis describes a methodology for representing these connections in models which ground the meaning of words in representations of events. Incorporating these grounded language models with text-based techniques significantly improves the performance of three multimodal applications: natural language understanding in videogames, sports video search and automatic speech recognition. Two approaches to representing the structure of events are presented and used to model the meaning of words. In the domain of virtual game worlds, a hand-designed hierarchical behavior grammar is used to explicitly represent all the various actions that an agent can take in a virtual world. This grammar is used to interpret events by parsing sequences of observed actions in order to generate hierarchical event structures. In the noisier and more open -ended domain of broadcast sports video, hierarchical temporal patterns are automatically mined from large corpora of unlabeled video data. The structure of events in video is represented by vectors of these hierarchical patterns.(cont.) Grounded language models are encoded using Hierarchical Bayesian models to represent the probability of words given elements of these event structures. These grounded language models are used to incorporate non-linguistic information into text-based approaches to multimodal applications. In the virtual game domain, this non-linguistic information improves natural language understanding for a virtual agent by nearly 10% and cuts in half the negative effects of noise caused by automatic speech recognition. For broadcast video of baseball and American football, video search systems that incorporate grounded language models are shown to perform up to 33% better than text-based systems. Further, systems for recognizing speech in baseball video that use grounded language models show 25% greater word accuracy than traditional systems.by Michael Ben Fleischman.Ph.D

Becoming an engineering communicator : a study of novices' trajectories in learning genres of their profession

The study presented in this dissertation focusses on the analysis of novices' trajectories in learning genres of their profession, engineering. The goals of the study are: (a) to refine the current understanding of what constitutes professional genre knowledge and of how novices learn and use genres of professional communication, and (b) to test the effectiveness of the suggested pedagogy for an Engineering Communication course. This qualitative longitudinal exploration includes ten case studies that span eight years and trace the participants' trajectories through the university and workplaces. I use a combination of three theoretical perspectives---Rhetorical Genre Studies, Activity Theory, and situated learning---as a lens for the analysis of novices' learning trajectories on their way to becoming professional communicators. The study demonstrates that in addition to the knowledge of genre conventions and understanding of an audience's expectations, genre knowledge is a result of a summative effect of such ingredients accumulated from different sources at different time periods as (a) cultural capital, (b) domain content expertise, (c) the novice's understanding of the improvisational qualities of genre, (d) agency, as reflected in the novice's ability to both seize and create kairotic moments in the chronological flux of time and enact genres in the ways that are recognizable by the community of practice, (e) formal education, (f) workplace experiences, and (g) private intention. The study indicates that the ingredients of genre knowledge accumulated in one context may be used in another, that is, that rhetorical strategy may be portable, thus allowing novices to adapt genres learned elsewhere to a new rhetorical situation. The study also shows that communication practices can be successfully taught outside of local contexts, for example, in the academic classroom. In addition I draw pedagogical implications of the inquiry for the communication classroom; for example, that communication instructors need to extend their pedagogies beyond teaching genre conventions and audience awareness and provide classroom contexts that would allow students to develop the understanding of genre as allowing for flexibility and educated intervention. The study also shows that the timing of the offering of domain-specific communication courses is crucial for the students to be able to develop the sense of connections among communication courses, subject matter courses, and professional practice

The Role of Geospatial Thinking and Geographic Skills in Effective Problem Solving with GIS: K-16 Education

Effective use of a Geographic Information System (GIS) is hampered by the limited geospatial reasoning abilities of students. The ability to reason with spatial relations, more specifically apply geospatial concepts, including the identification of spatial patterns and spatial associations, is important to geographic problem solving in a GIS context. This dissertation examines the broad influence of three factors on GIS problem solving: 1) affection towards computers, geography, and mathematics, 2) geospatial thinking, as well as 3) geographic skills. The research was conducted with 104 students in Waterloo, Ontario, Canada. Students were drawn from four educational levels: grade 9 students, 13 to 14 years of age; 1st year undergraduate university students, 3rd and 4th year undergraduate geography majors; and geography students at the graduate level ranging from 22 to 32 years of age. The level of affection is measured with modified scales borrowed from psychology. Results show that students in general exhibit positive sentiments toward computers and geography but less so towards mathematics. Spatial thinking and knowledge of geospatial concepts are measured by a 30-item scale differentiating among spatial thinkers along a novice-expert continuum. Scores on the scale showed an increase in spatial reasoning ability with age, grade, and level of education, such that grade 9 students averaged 7.5 out of 30 while the mean score of graduate students was 20.6. The final exercise assessed pertinent skills to geography namely inquiry, data collection, and analysis. In general, there was a positive correlation in the scores such that the skill proficiency increased with grade. Related analysis found three factors that affect problem-solving performance with a GIS. These include age, geographic skills (inquiry and analysis), and geospatial thinking (subscales analysis, representation, comprehension, and application). As well, the relationship(s) between performance on the geospatial scale and the observed problem-solving sequences and strategies applied on a GIS was examined. In general, students with lower scores were more apt to use basic visualization (zoom/measure tools) or buffer operations, while those with higher scores used a combination of buffers, intersection, and spatial queries. There were, however, exceptions as some advanced students used strategies that overly complicated the problem while others used visualization tools alone. The study concludes with a discussion on future research directions, followed by a series of pencil and paper games aimed to develop spatial thinking within a geographic setting

Motivational and metacognitive feedback in an ITS: linking past states and experiences to current problems

Feedback is an important element in learning as it can provide learners with both information about progress as well as external motivational stimuli, providing them with an opportunity for reflection. Motivation and metacognition are strongly intertwined, with learners high in self-efficacy more likely to use a variety of self-regulatory learning strategies, as well as to persist longer on challenging tasks. Learning from past experience involves metacognitive processes as an act of reflecting upon one’s own experience and, coupled with existing knowledge, aids the acquisition and construction of further knowledge. The aim of the research was to improve the learner’s focus on the process and experience of problem solving while using an Intelligent Tutoring System (ITS), by addressing the primary question: what are the effects of including motivational and metacognitive feedback based on the learner’s past states and experiences? An existing ITS, SQL-Tutor, was used in a study with participants from first year undergraduate degrees studying a database module. The study used two versions of SQL-Tutor: the Control group used a base version providing domain feedback and the Study group used an extended version that also provided motivational and metacognitive feedback. Three sources of data collection were used: module summative assessments, ITS log files and a post-study questionnaire. The analysis included both pre-post comparisons and how the participants interacted with the system, for example their persistence in problem-solving and the degree to which they referred to past learning. Comparisons between groups showed some differing trends both in learning and behaviour in favour of the Study group, though these trends were not significantly different. The study findings showed promise for the use of motivational and metacognitive feedback based on the learners’ past states and experiences that could be used as a basis for future research work and refinement

A goal-oriented user interface for personalized semantic search

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, February 2006.Includes bibliographical references (v. 2, leaves 280-288).Users have high-level goals when they browse the Web or perform searches. However, the two primary user interfaces positioned between users and the Web, Web browsers and search engines, have very little interest in users' goals. Present-day Web browsers provide only a thin interface between users and the Web, and present-day search engines rely solely on keyword matching. This thesis leverages large knowledge bases of semantic information to provide users with a goal-oriented Web browsing experience. By understanding the meaning of Web pages and search queries, this thesis demonstrates how Web browsers and search engines can proactively suggest content and services to users that are both contextually relevant and personalized. This thesis presents (1) Creo, a Programming by Example system that allows users to teach their computers how to automate interactions with their favorite Web sites by providing a single demonstration, (2) Miro, a Data Detector that matches the content of a Web page to high-level user goals, and allows users to perform semantic searches, and (3) Adeo, an application that streamlines browsing the Web on mobile devices, allowing users to complete actions with a minimal amount of input and output.(cont.) An evaluation with 34 subjects found that they were more effective at completing tasks when using these applications, and that the subjects would use these applications if they had access to them. Beyond these three user interfaces, this thesis also explores a number of underlying issues, including (1) automatically providing semantics to unstructured text, (2) building robust applications on top of messy knowledge bases, (3) leveraging surrounding context to disambiguate concepts that have multiple meanings, and (4) learning new knowledge by reading the Web.by Alexander James Faaborg.S.M

The use of images and descriptive words for the development of an image database for product designers

This research aims to understand the role images currently play within the design process, in order to develop a classification of image types and reference keywords to construct an electronic image database for professional use in product design. Images play an important role in the design process, both in defining the context for designs and in informing the creation of individual design. They are also used to communicate with clients, to understand consumers, to assist in expressing the themes of the project, to understand the related environments, or to search for inspiration or functional solutions. Designers usually have their own collections of images, however for each project they still spend a significant amount of time searching images, either looking within their own collection or searching for new images. This study is based on the assumption that there is a structure that can show the relationship between the image itself and the information it conveys and can be used to develop the database. A product-image database will enable designers to consult images more easily and this will also facilitate communication of visual ideas among designers or between designers and their clients, thus augmenting its potential value in the professional design process. Also, the value of an image may be enhanced by applying its linguistic associations through descriptions and keywords which identify and interpret its content. Through a series of interviews, workshops, and understanding relevant issues, such as design method, linguistic theory, perception psychology and so on, a prototype database system was developed. It was developed based on three information divisions: SPECIFICATION, CHARACTERISTIC, and EMOTION. The three divisions construct a model of the information which an image conveys. The database prototype was tested and evaluated by groups of students and professional designers. The results showed that users understand the concept and working of the database and appreciated its value. They also indicated that the CHARACTERISTIC division was most valuable as it allows users to record images through their recollection of feelings

An investigation into tacit knowledge management at the supervisory level.

An investigation into tacit knowledge management at the supervisory level Objective: The purpose of this study was to investigate how supervisors managed tacit knowledge. Aims: The aims were to understand what tacit knowledge looked like on the shop floor, to understand "experience‟ in terms of tacit knowledge, and to describe the methods and techniques that supervisors used to manage this elusive resource as they went about the task of achieving organisational goals. Method: Qualitative data was collected using a novel iterative participant observation method, where the researcher-as-instrument was embedded as a novice (but privileged) employee for extended periods in four different case study sites. Over the course of the study, the researcher took on the role of laboratory technician, electrical engineer, manufacturing process worker, and aircraft maintenance engineer. A grounded theory approach was taken to the analysis of the various field notes, photographs, video, audio, and found objects. The methodology was augmented with specialist qualitative research software to manage the data. Results: It was found that supervisors' tacit knowledge management activities can be classified according to formal and informal behaviours that correspond with Nonaka and Takeuchi's SECI knowledge life cycle. It was also found that a worker's task related tacit knowledge has seven aspects in five levels of competency, and their experience can be described in terms of 10 categories of tacit knowledge working capital. Insights attributed to the novel method of data collection produced an unexpected finding – the Home Guard model, which describes how the value of an individual's knowledge sharing activities is related to their power distance and self-confidence. Conclusions: The findings provide empirical support for existing knowledge management theory, identify specific supervisory behaviours that support tacit knowledge management on the shop floor, and extend the knowledge management discourse with new theories about knowledge sharing behaviours that have direct application to the supervisory role