Level Of Domain Knowledge Research Articles

Differences between experts and novices when reading with navigational table of contents

PurposeThe purpose of this paper is to examine the difference between experts and novices when reading with navigational table of contents (N-TOC). Experts refer to readers with high level of domain knowledge; novices refer to readers with low level of domain knowledge.Design/methodology/approachThe authors performed a controlled experiment of three reading tasks (including fact finding task, partial understanding task, and full-text understanding task) on an N-TOC system for 35 post-graduates of Wuhan University who have rich experience in reading with N-TOC. Participants’ domain knowledge was measured by pre-experiment questionnaires; reading performance data including score, time, navigation use, and evaluation of N-TOC were collected.FindingsThe results showed that there was significant difference in neither navigation use nor participants’ evaluation, but domain experts performed significantly better in both score and time of all tasks than domain novices, which revealed an “illusion of control” phenomenon that rich experience in reading with N-TOC enabled domain novices to achieve the same performance as domain experts. In addition, this research found that N-TOC was not suitable for domain novices to solve full-text understanding task because of “cognitive overload” phenomenon.Originality/valueThis study makes a good contribution to the literature on the effect of domain knowledge on reading performance during N-TOC reading and how to provide better digital reading service in the field of library science and information science.

How Text Presentation and Financial Literacy Affect Pension Communication Success

This study examined the effects of (a) text presentation and (b) prior knowledge and language skill on finding information in financial documents. First, the participants filled out tests that measured their levels of vocabulary, reading skill, domain knowledge, and topic knowledge. Subsequently, they read an on-screen text on pension information in either a linear structure (“nonlayered”) or a hypertext structure (“layered”). Readers’ performance was measured by verbal scenario questions. No difference was found for text presentation. Language skill and domain knowledge were both important predictors for finding, whereas topic knowledge was not associated with readers’ performance at all. When differentiating between text presentation conditions, we found that domain knowledge only plays a role in the nonlayered condition, not in the layered condition. These results indicate that the set of skills needed to successfully read a document varies with both type of task and type of reading, confirming prior research.

Intelligent Learning Model Based On Significant Weight Of Domain Knowledge Concept For Adaptive E-Learning

In order to support personalized learning, an adaptive learning system should have a capability to provide each student with a suitable learning material regarding his profile. However, the issue of student varieties in acquiring every Domain Knowledge Concept (DKC), and a range of DKC important variations in a particular learning material produced a complex dependency that causes a difficulty in the learning material selection process. Existing rule-based learning material selection approach requires the definition of a huge set adaptation rules. However, this approach usually results in inaccurate and incorrect selection due to the inconsistent, insufficient and confluence of the defined rules. Consequently, the process of learning material selection is hard to be algorithmized, therefore, intelligent methods are applied to handle the complexity challenges. This research proposes a significance weight approach that represents the complex dependency of learning material selection problem to substitute the rules definition in the selection process. In addition, this research proposes an intelligent learning model that combines unsupervised and supervised machine learning techniques to accurately select the learning material for a particular student adaptively. The unsupervised machine learning technique is vital in obtaining a learning material classification and labelling based on the proposed significance weight. Meanwhile, the supervised machine learning technique, the Multilayer Perceptron Artificial Neural Networks conducts the adaptation process that will assign the student to suitable learning materials regarding his performance upon specific DKC. With 98% achievement of classification accuracies, this model can be considered as highly accurate in selecting a correct and suitable learning material based on student’s domain knowledge level.

Training peer-feedback skills on geometric construction tasks: role of domain knowledge and peer-feedback levels

Peer feedback is widely used to train assessment skills and to support collaborative learning of various learning tasks, but research on peer feedback in the domain of mathematics is limited. Although domain knowledge seems to be a prerequisite for peer-feedback provision, it only recently received attention in the peer-feedback literature. In this study, preservice mathematics teachers (N = 43) were involved in a peer-feedback training in which they evaluated geometric construction tasks and were (a) trained to provide peer feedback on different levels (i.e. task, process and self-regulation) and (b) scaffolded with worked examples, feedback provision prompts and evaluation rubrics during the training. A quasi-experimental mixed design was implemented with domain knowledge as the between-subject factor and measurement occasion as the within-subject factor. Students’ peer-feedback provision skills and their beliefs about peer-feedback provision were measured before and after the training. Students with high and medium domain knowledge provided more peer feedback at the self-regulation level, whereas those low in domain knowledge provided more peer feedback at the task-level after the training. Students’ beliefs about peer-feedback provision became less positive after the training, regardless of the level of their domain knowledge.

The influence of domain expertise on visual overviews of spatiotemporal data

ABSTRACTOverviews of spatiotemporal data are acknowledged to play an important role in visualization in initiating and supporting geovisualization and exploratory data analysis (EDA). However, relatively little research has focused on the visual overviews themselves, and their potential impacts on EDA outcomes. In a user study, we evaluated the influence of different levels of domain knowledge on the usefulness of four distinct types of static visual overview of spatiotemporal data. Beyond simply orienting users, our results indicate that visual overviews can be important in gaining insights into a data set, for example, in learning about metadata. Although subjects without domain knowledge struggled to judge the quality of their findings, they were as successful at identifying interesting patterns in the data as those with domain expertise. Our results suggest that detailed background knowledge of a data set can actively hinder EDA. Being already familiar with their own data sets, our results highlight the tendency of data experts to disregard findings that do not match their pre-existing domain knowledge. Based on these findings, our conclusions identify a range of potential avenues for future work, including the use of visual overviews that deliberately do not, from first view, reveal the context of the data they show. This later approach could help in cases where domain experts need to see their data with ‘fresh eyes’, and detect interesting patterns in spatiotemporal data before relating the findings to specific knowledge about the data sets and the domain.

Reduce, reuse, recycle: Acceptance of CO2-utilization for plastic products

Global warming is a central threat for today's society caused by greenhouse gas emissions, mostly carbon dioxide emissions. Carbon dioxide capture and utilization (CCU) is a promising approach to reduce emissions and the use of expensive and limited fossil resources. Applying CCU, carbon dioxide (CO2) can be incorporated as raw material during the manufacture of plastic products. While most of the studies address technical feasibilities, hardly any systematic research on public perception and acceptance of those specific products exists so far. This study empirically investigates the acceptance of CCU plastic products (mattress as example). First, interviews with experts and lay people revealed critical acceptance factors (CO2 proportion, saving of fossil resources, disposal conditions, perceived health complaints). Their relative importance was detailed in two consecutive conjoint studies. Study 1 revealed disposal conditions and saving of fossil resources as essential for product selection, while the products’ CO2 proportion was less important. In study 2, potential health complaints were integrated as well as individual levels of domain knowledge and risk perception, which significantly affected acceptance of CCU products. Recommendations concerning communication strategies for policy and industry were derived.

Students’ silence and identity in small group interactions

Problem-based learning (PBL) has been increasingly employed as a teaching and learning approach in many disciplines in higher education. In English medium of instruction (EMI) universities in Asia, PBL can further enhance knowledge construction as well as development of disciplinary language and communicative skills. It is necessary to explore how learners participate in PBL, especially considering PBL requires high level of both domain knowledge and language skills. The issue of silence in small group collaborative learning such as PBL tutorials has received very limited attention. More factors such as identity need to be considered in fully exploring small group interactions in higher education. Thus, this study aims to investigate undergraduate students’ silence and identity in small group interactions for PBL in EMI universities in Asia. Eight PBL tutorials in the Faculty of Dentistry were video recorded. Three extracts of PBL interactions and the accompanying stimulated recall interviews were selected for case analysis. The analysis provides in-depth insights into the significant instances of students’ silence and identity construction in the learning process. Such a study offers opportunities to rethink the issue of silence and provides facilitators and curriculum developers with useful information about small group collaborative learning in higher education.

The Impacts of Mutual Collaboration Experience and Domain Knowledge Levels on CAIS Behavior: An Experimental Study

AbstractSome studies have investigated participants’ information-seeking practices from the perspective of mutual collaboration experience and level of domain knowledge. This study provides insights into collaborative academic information-seeking (CAIS) behaviour. The article explores whether groups with different levels of domain knowledge and mutual collaboration experiences had different CAIS behaviour. It also asked whether domain knowledge level or mutual collaboration experience had an impact on CAIS behaviour. We describe a user study with 18 participants in nine pairs with an experimental collaborative information-seeking tool, the participants categorized into three types of groups: high domain knowledge level and few mutual collaboration experiences (Group 1), low domain knowledge level and many mutual collaboration experiences (Group 2), and no domain knowledge level and no mutual collaboration experience (Group 3). Quantitative and qualitative data analysis were used to analyse the user data collected. The results showed that compared with members of Group 3, participants in Groups 1 and 2 had a better understanding of search tasks and were aware of the ways of completing the tasks successfully. They did not depend on the information-retrieval system when constructing search queries, and adopted diverse cooperation strategies. They were more likely to recommend information to their partners. Domain knowledge had greater impact on CAIS behaviour than collaboration experience. The findings help us to understand social interactions among community members and help CAIS researchers to understand user interactions and inform information system designers as they design collaborative systems to facilitate social communication in the information-seeking process. Our work was limited by the group types we chose and the small group size, which could affect the generalizability of our findings and should be addressed in future studies.

번역가의 ‘전문성’ 개념 변화의 필요성 — 디지털 시대 ‘비전문가’ 번역을 중심으로

This paper starts from questioning whether it is appropriate to describe a newly emerging group of user-translators as “non-professionals” just because they do not receive formal training in translation. Unlike traditional non-professional translators, these volunteer translators participating in translation of webtoons, free open-source softwares(FOSS), games, educational contents, news articles and subtitles for dramas, have domain knowledge and high level of digital proficiency. They work online in collaboration with other like-minded people with the help of computer aided translation tools and hold online discussion forums on translation related topics. In commercialized cases, quality control and evaluation are done through peer-reviews, voting, and revision by professionals. Through collaboration, discussions, usage of CAT tools and division of works, their lack of professional competence is compensated. With a dramatic increase in the volume of online contents which need linguistic mediation, these volunteers contribute a lot in helping people enjoy the cultural and intellectual contents over language barriers. Considering the strength of these translators characterized by strong interest, genre knowledge, online collaboration, digital literacy, and language proficiency, the term “non-professional” referring to these volunteer translators is not quite appropriate; and the traditional concept of professionalism in the translation community largely based on translation education needs to be reevaluated.

The exploration of objective task difficulty and domain knowledge effects on users' query formulation

ABSTRACTIn this paper, we explore the effects of objective task difficulty and domain knowledge on users' query formulation behaviors. The dataset from a user experiment was used in this research, which focused on the medical domain. The objective difficulty was measured by the precision level of search topics (as queries) in the search system, and searchers' domain knowledge was assessed by a self‐reported rating on the familiarity with MeSH terms that were related to the search topics in the study. We compared expert searchers' and novice searchers' query similarity and query features between easy and difficult tasks. The results showed that there was no significant difference between domain experts and novices in query similarity, but there existed an opposite pattern of task difficulty effects on query similarity for searchers with different domain knowledge levels. Domain expert searchers had more diverse vocabulary in difficult tasks than in easy tasks, whereas novice searchers had to rely heavily on task descriptions to formulate their queries. Task difficulty had also influenced searchers' performance, especially the precision measure. Novice searchers' recall was relatively low in both easy and difficult tasks. The findings in this study help us further understand users' query formulation process, and have implication for the design of query suggestion functions in search systems.

Business knowledge requirements and onsite offshore work division in Indian software outsourcing projects

Purpose – The purpose of the paper is to find out the knowledge requirements and its effect on both onsite and offshore project work division for development, re-engineering and maintenance projects in Indian outsourcing software industry in different phases of software development. Design/methodology/approach – This study employs an expert interview approach in Indian software industry to find out knowledge requirement for project execution and division of work between onsite and offshore locations. The requisite data were collected through expert interviews and direct observations. Findings – The study found that the development projects require higher level of domain, strategic, business process and operation process knowledge in comparison to re-engineering and maintenance projects. So there is a need of higher onsite presence in development projects. The maintenance work is taken up at the offshore location in a phase-wise manner. Research limitations/implications – The implication of the study is in the development of a broad framework of knowledge requirements and work division in on-shore and offshore locations for Indian software outsourcing projects. As the study is based on expert opinion in the context of India, it cannot be generalized for outsourcing scenarios elsewhere. Practical implications – The software project manager can use the findings to get more insight into the project and divide the software team between onsite and offshore location. Originality/value – The study is novel, as there is little attempt at finding the knowledge requirement to execute various kinds of business software development in outsourcing environment in the context of India.

Effect of supportive supervision on routine immunization service delivery-a randomized post-test study in Odisha.

Introduction:Routine immunization is a key child survival intervention. Issues related to quality of service delivery pose operational challenges in delivering effective immunization services. Accumulated evidences suggest that “supportive supervision” improves the quality of health care services. During 2009-10, Govt. of Odisha (GoO) and UNICEF jointly piloted this strategy in four districts to improve routine immunization. The present study aims to assess the effect of supportive supervision strategy on improvement of knowledge and practices on routine immunization among service providers.Materials and Methods:We adopted a ‘post-test only’ study design to compare the knowledge and practices of frontline health workers and their supervisors in four intervention districts with that of two control districts. Altogether we interviewed 170 supervisors and supervisees (health workers), each, using semi-structured interview schedules. We also directly observed 25 ice lined refrigerator (ILR) points in both groups of districts. The findings were compared with the baseline information, available only for the intervention districts.Results:The health workers in the intervention districts displayed a higher knowledge score in selected items than in the control group. No significant difference in knowledge was observed between control and intervention supervisors. The management practices at ILR points on key routine immunization components were found to have improved significantly in intervention districts.Conclusion and Recommendations:The observed improvements in the ILR management practices indicate positive influence of supportive supervision. Higher level of domain knowledge among intervention health workers on specific items related to routine immunization could be due to successful transfer of knowledge from supervisors. A ‘pre-post’ study design should be undertaken to gain insights into the effectiveness of supportive supervision in improving routine immunization services.

Predicting users' domain knowledge in information retrieval using multiple regression analysis of search behaviors

User domain knowledge affects search behaviors and search success. Predicting a user's knowledge level from implicit evidence such as search behaviors could allow an adaptive information retrieval system to better personalize its interaction with users. This study examines whether user domain knowledge can be predicted from search behaviors by applying a regression modeling analysis method. We identify behavioral features that contribute most to a successful prediction model. A user experiment was conducted with 40 participants searching on task topics in the domain of genomics. Participant domain knowledge level was assessed based on the users' familiarity with and expertise in the search topics and their knowledge of MeSH (Medical Subject Headings) terms in the categories that corresponded to the search topics. Users' search behaviors were captured by logging software, which includes querying behaviors, document selection behaviors, and general task interaction behaviors. Multiple regression analysis was run on the behavioral data using different variable selection methods. Four successful predictive models were identified, each involving a slightly different set of behavioral variables. The models were compared for the best on model fit, significance of the model, and contributions of individual predictors in each model. Each model was validated using the split sampling method. The final model highlights three behavioral variables as domain knowledge level predictors: the number of documents saved, the average query length, and the average ranking position of the documents opened. The results are discussed, study limitations are addressed, and future research directions are suggested.

Building digital collections in a public university library in Ghana: priority-setting and user needs assessment

Purpose – Although user needs assessment is an intrinsic element of service quality delivery in digital libraries (DLs), not much has been written on this topic in the context of African universities. This is understandable as academic digital libraries in Africa are rather nascent. Even so, the most frequently-used needs assessment methods do not directly involve the users. This study aims to assess priority setting by academic library administrators and the needs of patrons of digital collections of a public university library in Ghana. Design/methodology/approach – Analysis of official university documents and interviews with digital library patrons at the University of Cape Coast (UCC) in Ghana were carried out between September, 2011 and January, 2012. Five research questions were asked: what are the current conditions of the UCC digital library project, the user communities and their needs, what are the priorities set by the university administrators and library leaders at the UCC and the state of technological readiness in place and what are needed by the UCCDL. Also, what is the extent of collaboration by interested parties in the UCCDL? Findings – Three general digital library user communities were identified, that is, UCCDL staff- this community was composed of experts in both digital library systems and content, characterized as heavy users of the existing systems, as knowledgeable about articulated (formalized) user needs, and able to devote short (usually less than two hours) amounts of time to individual's needs. Next, are scholars and other visitors to the UCCDL – this community was characterized as having high levels of domain expertise and knowledge of library systems. They are also able to devote large but specific amounts of time (days or weeks) to their individual information needs. Visitors/Prospective users- this community was characterized as having varied levels of domain expertise and low levels of library systems knowledge. They are able to devote only short periods of time to their information needs or explorations. These user communities are influenced by diverse preferences, experiences, and knowledge structures. Practical implications – Academic libraries are increasingly advocating local user studies as a way to provide the digital library services that are relevant to the culture and user population of the academic institution. Replicating digital library user studies at the local level can provide information for improving existing services or developing new ones. Originality/value – In African public universities, there is little earlier research on digital library user needs assessments or DL priority-setting by academic library administrators.

Technology-Facilitated Contribution Behavior: An Experimental Investigation

ABSTRACT: Contribution behavior is described as voluntarily providing assistance or sharing knowledge when a colleague makes a request for assistance (Olivera, Goodman, and Tan 2008). The purpose of this paper is to investigate factors that lead to contribution behavior through collaboration technology. We engaged 183 participants over a collaboration platform to work on an accounting task and interrupted them with a request for help on a similar task. The participants could respond to the request using communication tools embedded in the collaboration application if they wanted to help. Post-experimental survey data were collected to measure the participants' motivations to contribute and analyze the quality of their contributions. The results indicate that participants are more motivated to contribute when they know the individual requesting assistance and have positive prior experience with the individual. Furthermore, having a higher level of domain knowledge in the area of the request and specificity of the request are associated with higher contribution quality. We discuss implications to accounting firms for providing an environment conducive to contribution behavior. Data Availability: Data are available from the first author.

The effects of decision aid structural restrictiveness on cognitive load, perceived usefulness, and reuse intentions

As accounting environments become increasingly automated through information technology support systems, the underlying systems are increasingly restrictive in an effort to direct user behavior and decision making. However, consistent with the theory of technology dominance, restrictive systems have been found to dominate users' decision processes and to have a detrimental effect when decisions require knowledge from outside the system's capability. This study expands upon this research through an examination of users' preferences for more (less) restrictive systems based on their own level of domain knowledge. Incorporating theory on task technology fit, we theorize that users with less knowledge will prefer to be dominated by the system, while users with greater levels of knowledge will prefer a system that provides the user with a level of control over the decision process rather than submitting entirely to the decision aid's control. These theorizations are empirically tested through an experimental design that varies the level of systems restrictiveness across groups of novice and experienced participants. The results confirm that novice (experienced) participants find a highly restrictive system substantially (minimally) reduces cognitive load, increases (decreases) usefulness of the decision aid, and strengthens (weakens) the intention to reuse the system in the future. The results add an important piece to understanding the effect of restrictive systems in that the users that are most susceptible to dominance by decision aids are the users most willing to adopt a restrictive system that reduces the effort they must put forth and in turn reduces the knowledge they accrue from using the system.

Collectively figuring it out : foreign-trained health professionals and labor market integration

ABSTRACTBackground. Foreign-trained health professionals arrive in the United States and Canada to find a professional environment that is often unwelcoming and complex.Objectives. We examine the nature of information in foreign-trained health professionals' lives as they attempt to integrate into the North American labor market. We focus on the role that online discussion forums play in channeling the discussions: what functions do these online spaces support (e.g., informational, emotional, instrumental and phatic) and how information is shared (e.g., sharing stories, linking to/reposting resources, contextualizing and critiquing).Methods. Content analysis was carried out on a sample of postings directed at foreign-trained health professionals in five online forums: AllNurses and Trackitt in the United States; and Canadian Desi, LoonLounge and CanadaVisa in Canada.Results. The interactions in these forums include requesting guidance and clarification about the North American system, sharing experiences and stories, expressing visceral or affective reactions, offering opinions, and negotiating the norms and etiquette of the forum. The content of the postings mostly revolve around issues relating to the immigration process, certification and employability. Other issues identified can be grouped into three categories: information preparedness, information as support and informational practices.Conclusion. Foreign-trained health professionals are faced with a combination of unfamiliar healthcare system, terminology, information sources and informationseeking practices. Online communities supported by online discussion forums help these health professionals integrate into the local healthcare system.BACKGROUND AND CONTEXTIn an era of global migration, recruiting and retaining highly qualified professionals is critical. Indeed, immigration plays a key role in the workforce and economic development of many countries, with some professions facing a higher demand than others. In countries such as the United States or Canada, the demand for health professionals, in particular, has significantly increased in the past decades. The Organization for Economic Co-operation and Development (OECD) has estimated that more than one-third of physicians in the United States and Canada (34 and 32%, respectively) are over the age of 55 years, and are expected to retire over the next 10 years (OECD, 2013). Despite the demands for health professionals (and the associated ethical issue of brain drain that it raises (Lofters, Slater, Fumakia & Thulien, 2014), there is increased evidence that foreign-trained health professionals are facing significant challenges as they attempt to integrate into the labor market in their new country.Although information is increasingly available before one migrates to the new country (thanks to the Internet), finding career-related information, such as foreign credential recognition, recertification, bridging programs, and employability in the labor market remains a challenge. Buried under layers of challenges is the fact that even though highly educated, these individuals have to search for information in English (or French), which is often a second or foreign language for them. While high levels of domain knowledge have been shown to mitigate language-based difficulties in second- and foreign-language searching (Kralisch & Berendt, 2005), it remains an obstacle for many foreign-trained health professionals, along with a lack of familiarity with the information environment of the new country.The purpose of this study is to examine how foreign-trained (also known as internationally-educated) health professionals seek, use, and share health- and career-related information as they attempt to migrate and prepare for integrating the labor market in their new country. Despite demonstrated credentials, a large knowledge base, and a command of foreign language(s), foreign-trained health professionals in the US and Canada face numerous challenges when trying to gain work as health professionals after immigrating. …

Ontological modeling of spatial shaft-position knowledge for steam turbine rotor

Large business enterprises rely heavily on their human capital. The human capital consists of domain knowledge, experience, analytical and creativity levels. It is recognized that, creativity levels and analytical skills are traits of individuals. All these need to be captured by the use of suitable knowledge capturing techniques, particularly due to exponential knowledge growth in all domains of technology. Ontological modeling has the potential to capture such knowledge, and organize it in a structured format based on the concepts and their mutual relations. It can capture the analytical and creative rationale of design and troubleshooting, besides incorporating specific design sub-routines for tasks. This paper discusses an ontology based model, which stores knowledge for the positioning-system of steam turbine rotor. The efficacy of the model has been demonstrated in capturing this domain knowledge, which can be used by the design and the maintenance personnel and thereby, increase their efficiency.

Individual Differences in Learning with Hypermedia: Effects of Students’ Cognitive Styles, Computer Competency Levels, and Prior Knowledge Levels on Learning Strategies

This study examines the effects of cognitive styles, computer competency levels, and prior domain knowledge levels on students’ learning strategies in an instructional hypermedia program. Sixteen students were selected out of 111 students from a Web-enhanced course, based on their cognitive style, computer competency, and prior domain knowledge test scores. In order to reveal students’ learning strategies, interviews and observations were conducted. Results indicated that cognitive styles may be important in terms of study management strategies of the students, and computer competency and prior knowledge levels may affect the patterns of using the hypermedia program.

Inferring user knowledge level from eye movement patterns

The acquisition of information and the search interaction process is influenced strongly by a person’s use of their knowledge of the domain and the task. In this paper we show that a user’s level of domain knowledge can be inferred from their interactive search behaviors without considering the content of queries or documents. A technique is presented to model a user’s information acquisition process during search using only measurements of eye movement patterns. In a user study (n=40) of search in the domain of genomics, a representation of the participant’s domain knowledge was constructed using self-ratings of knowledge of genomics-related terms (n=409). Cognitive effort features associated with reading eye movement patterns were calculated for each reading instance during the search tasks. The results show correlations between the cognitive effort due to reading and an individual’s level of domain knowledge. We construct exploratory regression models that suggest it is possible to build models that can make predictions of the user’s level of knowledge based on real-time measurements of eye movement patterns during a task session.