The definition of metrics capable of reporting on quality issues is a difficult task in the health care sector. This thesis proposes a goal-driven methodology for the development, collection, and analysis of health care quality metrics that expose in a quantifiable way the progress of measurement goals stated by interested stakeholders. In other words, this methodology produces reports containing metrics that enable the understanding of information out of health care data. The resulting Health Care Goal Question Metric (HC-GQM) methodology is based on the Goal Question Metric (GQM) approach, a methodology originally created for the software development industry and adapted to the context and specificities of the health care sector. HC-GQM benefits from a double loop validation process where the methodology is first implemented, then analysed, and finally improved. The validation process takes place in the context of adverse event management and incident reporting initiatives at a Canadian teaching hospital, where the HC-GQM provides a set of meaningful metrics and reports on the occurrence of adverse events and incidents to the stakeholders involved. The results of a survey suggest that the users of HC-GQM have found it beneficial and would use it again.

For learners engaging in senior-level courses, tutors in many cases would like to pick some articles as supplementary reading materials for them each week. Unlike researchers Googling papers from the Internet, tutors, when making recommendations, should consider course syllabus and their assessment of learners along many dimensions. As such, simply Googling articles from the Internet is far from enough. That is, learner models of each individual, including their learning interest, knowledge, goals, etc. should be considered when making paper recommendations, since the recommendation should be carried out so as to ensure that the suitability of a paper for a learner is calculated as the summation of the fitness of the appropriateness of it to help the learner in general. This type of the recommendation is called a Pedagogical Paper Recommender.<p>In this thesis, we propose a set of recommendation methods for a Pedagogical Paper Recommender and study the various important issues surrounding it. Experimental studies confirm that making recommendations to learners in social learning environments is not the same as making recommendation to users in commercial environments such as Amazon.com. In such learning environments, learners are willing to accept items that are not interesting, yet meet their learning goals in some way or another; learners overall impression towards each paper is not solely dependent on the interestingness of the paper, but also other factors, such as the degree to which the paper can help to meet their cognitive goals.<p>It is also observed that most of the recommendation methods are scalable. Although the degree of this scalability is still unclear, we conjecture that those methods are consistent to up to 50 papers in terms of recommendation accuracy. <p>The experiments conducted so far and suggestions made on the adoption of recommendation methods are based on the data we have collected during one semester of a course. Therefore, the generality of results needs to undergo further validation before more certain conclusion can be drawn. These follow up studies should be performed (ideally) in more semesters on the same course or related courses with more newly added papers. Then, some open issues can be further investigated. <p>Despite these weaknesses, this study has been able to reach the research goals set out in the proposed pedagogical paper recommender which, although sounding intuitive, unfortunately has been largely ignored in the research community. <p>Finding a good paper is not trivial: it is not about the simple fact that the user will either accept the recommended items, or not; rather, it is a multiple step process that typically entails the users navigating the paper collections, understanding the recommended items, seeing what others like/dislike, and making decisions. Therefore, a future research goal to proceed from the study here is to design for different kinds of social navigation in order to study their respective impacts on user behavior, and how over time, user behavior feeds back to influence the system performance.

Record matching is a fundamental and ubiquitous part of today?s society. Anything from typing in a password in order to access your email to connecting existing health records in California with new health records in New York requires matching records together. In general, there are two types of record matching algorithms: deterministic, a more rules-based approach, and probabilistic, a model-based approach. Both types have their advantages and disadvantages. If the amount of data is relatively small, deterministic algorithms yield very high success rates. However, the number of common mistakes, and subsequent rules, becomes astronomically large as the sizes of the datasets increase. This leads to a highly labor-intensive process updating and maintaining the matching algorithm. On the other hand, probabilistic record matching implements a mathematical model that can take into account keying mistakes, does not require as much maintenance and over- head, and provides a probability that two particular entities should be linked. At the same time, as a model, assumptions need to be met, fitness has to be assessed, and predictions can be incorrect. Regardless of the type of algorithm, nearly all utilize a 0/1 field-matching structure, including the Fellegi-Sunter algorithm from 1969. That is to say that either the fields match entirely, or they do not match at all. As a result, typographical errors can get lost and false negatives can result. My research has yielded that using Jaro-Winkler string comparator scores as predictors to a Bayesian logistic regression model in lieu of a restrictive binary structure yields marginal improvement over current methodologies.

When you are assigned a research paper, you will spend many hours searching the library and the Internet for materials relevant to your topic. It is important to develop a system to organize and save the information you wish to use for your paper. After completing this interactive tutorial you will be able to create a research log to organize and save the information from a web site. This flash tutorial requires a screen resolution of 1024 x 768 or higher.

The definition of metrics capable of reporting on quality issues is a difficult task in the health care sector. This thesis proposes a goal-driven methodology for the development, collection, and analysis of health care quality metrics that expose in a quantifiable way the progress of measurement goals stated by interested stakeholders. In other words, this methodology produces reports containing metrics that enable the understanding of information out of health care data. The resulting Health Care Goal Question Metric (HC-GQM) methodology is based on the Goal Question Metric (GQM) approach, a methodology originally created for the software development industry and adapted to the context and specificities of the health care sector. HC-GQM benefits from a double loop validation process where the methodology is first implemented, then analysed, and finally improved. The validation process takes place in the context of adverse event management and incident reporting initiatives at a Canadian teaching hospital, where the HC-GQM provides a set of meaningful metrics and reports on the occurrence of adverse events and incidents to the stakeholders involved. The results of a survey suggest that the users of HC-GQM have found it beneficial and would use it again.

For learners engaging in senior-level courses, tutors in many cases would like to pick some articles as supplementary reading materials for them each week. Unlike researchers Googling papers from the Internet, tutors, when making recommendations, should consider course syllabus and their assessment of learners along many dimensions. As such, simply Googling articles from the Internet is far from enough. That is, learner models of each individual, including their learning interest, knowledge, goals, etc. should be considered when making paper recommendations, since the recommendation should be carried out so as to ensure that the suitability of a paper for a learner is calculated as the summation of the fitness of the appropriateness of it to help the learner in general. This type of the recommendation is called a Pedagogical Paper Recommender.<p>In this thesis, we propose a set of recommendation methods for a Pedagogical Paper Recommender and study the various important issues surrounding it. Experimental studies confirm that making recommendations to learners in social learning environments is not the same as making recommendation to users in commercial environments such as Amazon.com. In such learning environments, learners are willing to accept items that are not interesting, yet meet their learning goals in some way or another; learners overall impression towards each paper is not solely dependent on the interestingness of the paper, but also other factors, such as the degree to which the paper can help to meet their cognitive goals.<p>It is also observed that most of the recommendation methods are scalable. Although the degree of this scalability is still unclear, we conjecture that those methods are consistent to up to 50 papers in terms of recommendation accuracy. <p>The experiments conducted so far and suggestions made on the adoption of recommendation methods are based on the data we have collected during one semester of a course. Therefore, the generality of results needs to undergo further validation before more certain conclusion can be drawn. These follow up studies should be performed (ideally) in more semesters on the same course or related courses with more newly added papers. Then, some open issues can be further investigated. <p>Despite these weaknesses, this study has been able to reach the research goals set out in the proposed pedagogical paper recommender which, although sounding intuitive, unfortunately has been largely ignored in the research community. <p>Finding a good paper is not trivial: it is not about the simple fact that the user will either accept the recommended items, or not; rather, it is a multiple step process that typically entails the users navigating the paper collections, understanding the recommended items, seeing what others like/dislike, and making decisions. Therefore, a future research goal to proceed from the study here is to design for different kinds of social navigation in order to study their respective impacts on user behavior, and how over time, user behavior feeds back to influence the system performance.

Metacognition involves different evaluations of your own thinking- and learning process. Ease of learning (EOL) means judging how difficult for example a word is to learn. When researching about EOLs, different methods have been used in the past. In an experiment that tested glossaries, the methodology for measuring EOLs was investigated in this study. In the experiment, a comparison was made between making a sequential or simultaneous judgement of the difficulty of the words. A simultaneous judgement means judging one item while seeing the other items on the list, and a sequential judgement means judging while only seeing the word pair you are to judge. The result of this experiment was in line with previous research in that EOL judgments significantly, but only moderately so, predict the actual learnability of the items. However, the difference between a sequential and simultaneous judgement and their correlation with recall was not significant. There was a tendency towards better EOLs being made with simultaneous judgements, having a 30 % higher correlation with recall than sequential judgements.

Apply design pattern in software analysis and design can reduce time and cost by reuse proven and validated solution to avoid redesign. Design pattern provide general solution to specific problem domain, it is best to adopt design pattern in Platform Intendant Model (PIM). Model Driven Architecture (MDA) lack of methodology to judge problem domain from UML Diagram like sequential diagram, timing diagram or class diagram and how to apply design pattern in PIM mode. To alleviate the forgoing problem, this study proposed methodology to describe rule and step to apply design pattern, and present the difference between adopt design pattern by UML diagram. The research methodology is articulated using the design science research methodology. A usability study evaluation is performed to demonstrate its applicability with test case. With this proposed method, system analyst will improve software system flexibility and accuracy by design pattern after first phase PIM modeling, and object designed in software system will be low cohesion and high coupling .

Wind power is a fast growing alternative energy source. Since 2000, wind energy capacity has increased 24 percent per year with Texas leading the U.S. in installed wind turbine capacity. Most socioeconomic research in wind energy has focused on understanding local opposition, especially aesthetic impacts on the surrounding landscape. Recent studies have addressed reasons for social acceptance of wind farms, suggesting that positions both favorable and unfavorable to wind power are subtle and intricate, rather than monolithic, and rooted in place-specific issues. In the case of Texas, scholars have reported that the minimal permitting process is the dominant variable that explains the rapid rise of wind power in the state?s western region. However, scholars have yet to study the place-based local or regional factors that structure and inform acceptance of wind energy by key actors who negotiate with wind-energy firms. This thesis presents empirically determined, statistically significant social perspectives regarding socioeconomic wind energy impacts. I determined social perspectives by using Q-Method in Nolan County, Texas, a major site of wind-power development. Q-Method allows researchers to generalize about social perspectives, but not about how widely or deeply populations ascribe to social perspectives. Q-Method combines qualitative and quantitative techniques beginning with semi-structured interviews to collect statements on wind power, followed by participant ranking of statements on a ?most disagree? to ?most agree? scale. Key actors surveyed included landowners with wind turbines, elected and civilservice government officials, and prominent local business and community leaders. My findings identified five significant clusters of opinion, two of which shared strong support for wind energy on the basis of perceived positive economic impacts. Three clusters of opinion were less favorable to wind energy; these arguments were based upon opposition to tax abatements, support of tax abatements, and concerns over negative impacts to the community. Consensus emerged over the idea that positive views toward wind-energy development were unrelated to broader commitments to renewable energy. The support of key actors in favor of wind energy is contingent upon direct financial benefits from wind-energy royalties, political views on taxes, notions of landscape aesthetics, and sense of community.

The aim of this dissertation is to reflect on economic methodology. To reflect means to think about the relationship between researcher and the object of research. The object in mainstream economics is fixed in market realm. When the object is fixed then the focus in economic study is the method. Mainstream economics used equilibrium analysis method in order to make the research outcome be certainty. In the process of pursuing certainty the ontology of the object is neglected. The de-centering strategy we applied is deconstruction concept. My main reason for taking Derrida¡¦s deconstruction as a starting point is to de-center the fixed center which operating mechanism is the invisible hand. In this dissertation the logic of deconstruction is ¡§neither..or..¡¨ form and the steps are to undo and displace. In order to emphasize the multiples means and the relation of knowledge and power we use the term discourse. In chapter four we undo ¡§the invisible hand¡¨ metaphor that is the center of market. The direct consequence of the undo process is the finding of the ontological implication. In chapter five we displace ¡§the invisible hand¡¨ metaphor. Through rereading Adam Smith¡¦s methodology we interpret invisible hand as causal relation and find the same ontological implication. Together with these two processes above we find out the inspiration for reflection of economic methodology that is to answer the most fundamental question about what is the economic object. In chapter six we call for discussion to bringing the ontology back into economics. We believe the study of economic ontology is a prerequisite for understanding economics as a scientific discipline. It is thus intended and hoped that this reflection will help to beyond the opposite between positivism and post-positivism. For the defined goal to coordinate the opposite we introduce philosopher Quine¡¦s ontological method called ontological commitment. After the reflection we claim ¡Gthe method such as formation and econometric is important, but if we can emphasize the ontology of research object then the study will be activity. The defense of this claim is the main subject of this dissertation. Finally we just point out that if the claim is accepted, then something along this line of the attention is essential to the practice researcher. That is to take more time to think the nature of the research object when he construes a model.