Real-world Science Research Articles

Discovering interesting knowledge from a science and technology database with a genetic algorithm

Data mining consists of extracting interesting knowledge from data. This paper addresses the discovery of knowledge in the form of prediction IF-THEN rules, which are a popular form of knowledge representation in data mining. In this context, we propose a genetic algorithm (GA) designed specifically to discover interesting fuzzy prediction rules. The GA searches for prediction rules that are interesting in the sense of being new and surprising for the user. This is done adapting a technique little exploited in the literature, which is based on user-defined general impressions (subjective knowledge). More precisely, a prediction rule is considered interesting (or surprising) to the extent that it represents knowledge that not only was previously unknown by the user but also contradicts his original believes. In addition, the use of fuzzy logic helps to improve the comprehensibility of the rules discovered by the GA. This is due to the use of linguistic terms that are natural for the user. A prototype was implemented and applied to a real-world science & technology database, containing data about the scientific production of researchers. The GA implemented in this prototype was evaluated by comparing it with the J4.8 algorithm, a variant of the well-known C4.5 algorithm. Experiments were carried out to evaluate both the predictive accuracy and the degree of interestingness (or surprisingness) of the rules discovered by both algorithms. The predictive accuracy obtained by the proposed GA was similar to the one obtained by J4.8, but the former, in general, discovered rules with fewer conditions. In addition it works with natural linguistic terms, which leads to the discovery of more comprehensible knowledge. The rules discovered by the proposed GA and the best rules discovered by J4.8 were shown to a user (a University Director) in an interview who evaluated the degree of interestingness (surprisingness) of the rules to him. In general the user considered the rules discovered by the GA much more interesting than the rules discovered by J4.8.

Science to services: consumers need "real-world" science.

Over the past decade there has been a revolution in pharmacotherapy for schizophrenia and related disorders. The second generation, or atypical, antipsychotic medications have demonstrated efficacy and generally better side-effect profiles. However, from the perspective of policy makers the higher costs associated with these newer medications leads to tough decisions regarding their continued use in light of an escalating fiscal crisis. For consumers, both persons with the illness and their family caregivers, the budgetary cutbacks leave many scrambling for answers to questions that most treatment (efficacy) studies were never designed to answer. "Should we oppose formulary restrictions on principle alone, or is there scientific data that can be relied on to inform our position?" On a more personal note, many are asking whether or not to switch to one of the newer medications and which medication would be best for them. Unlike CATIE, efficacy studies were never designed to answer such questions. In this article, we start by highlighting how CATIE will fill important gaps in translating the results of efficacy studies to effectiveness in the real world. Both the development of the CATIE methodology and the study design itself reflect what we will refer to as "real-world science": i.e., science that sheds light on effectiveness in vivo and can inform decisions consumers, clinicians, and policy makers are faced with day-to-day. We discuss CATIE in the context of the fiscal crisis hitting MEDICAID programs leading many policy makers to take the more expensive, atypical antipsychotics off the list of medications made available to patients. We argue that studies like CATIE will be highly informative and ultimately vital to policy makers wishing to create mental health policies that will succeed. Throughout, we highlight how CATIE, and real-world science more generally, are vital to consumers striving to find the medication(s) that works best for them. Given the organic research design process, which arguably relies on a fuller range of stakeholders than any study of its kind before, we remain hopeful that CATIE can succeed in generating an unprecedented amount of real-world science that consumers can use.

Experimental design heuristics for scientific discovery: the use of “baseline” and “known standard” controls

What type of heuristics do scientists use when they design experiments? In this paper, we analysed the ways biological scientists designed complex experiments at their weekly laboratory meetings. In two studies, we found that one of the key components of experimental design is that specific types of control conditions are used in the service of different goals that are important in scientific discovery. “Baseline” control conditions are identical to the experimental manipulation, except that a key feature, such as a reagent, is absent from the control condition and present in the experimental condition. “Known standard” control conditions involve performing the experimental technique on materials where the expected result is already well known; if the expected result is obtained, the scientist can have confidence that the procedure is working. In Study 1, which analysed transcripts of real-world biology laboratory meetings, we found that scientists used baseline controls when testing hypotheses and known standard controls when focusing on possible error. In Study 2, undergraduate science students were asked to address the goals of hypothesis testing and dealing with potential error as they designed experiments. Like the real-world scientists, science majors proposed baseline controls to test hypotheses and known standard controls to deal with potential error. We argue that baseline control conditions play an important role in hypothesis testing: unexpected results obtained on baseline control conditions can alert scientists that their hypotheses are incorrect, and hence should encourage the scientists to reformulate their hypotheses. We further argue that use of known standard controls is a heuristic that enables scientists to solve an important problem in real-world science: when to trust their data. Both of these heuristics can be incorporated into experimental design programs, thus making it more likely that scientific discoveries will be made.

Influences of Concept-Oriented Reading Instruction on Strategy Use and Conceptual Learning from Text

We define reading engagement as the mutual support of motivations, strategies, and conceptual knowledge during reading. To increase reading engagement, a collaborative team of teachers, reading specialists, and university faculty implemented a year-long integration of reading/language arts and science instruction known as Concept-Oriented Reading Instruction (CORI). This instruction contained conceptual themes, real world science interactions, self-directed learning, strategy instruction situated within conceptual contexts, peer collaborations, self-expression of knowledge through portfolios and exhibits, and coherence of the curriculum. Five teachers provided CORI to 53 grade 5 and 67 grade 3 students. 5 teachers provided traditionally organized instruction aimed toward the same objectives to 53 grade 5 and 66 grade 3 students. Students were from 2 low-income schools. The CORI context increased strategy use, conceptual learning, and text comprehension more than traditional instruction, when background wa...

Economic Modeling and Sensitivity Analysis

The field of pharmacoeconomics (PE) faces serious concerns of research credibility and bias. The failure of researchers to reproduce similar results in similar settings, the inappropriate use of clinical data in economic models, the lack of transparency, and the inability of readers to make meaningful comparisons across published studies have greatly contributed to skepticism about the validity, reliability, and relevance of these studies to healthcare decision-makers. Using a case study in the field of lipid PE, two suggestions are presented for generally applicable reporting standards that will improve the credibility of PE. Health economists and researchers should be expected to provide either the software used to create their PE model or a multivariate sensitivity analysis of their PE model. Software distribution would allow other users to validate the assumptions and calculations of a particular model and apply it to their own circumstances. Multivariate sensitivity analysis can also be used to present results in a consistent and meaningful way that will facilitate comparisons across the PE literature. Using these methods, broader acceptance and application of PE results by policy-makers would become possible. To reduce the uncertainty about what is being accomplished with PE studies, it is recommended that these guidelines become requirements of both scientific journals and healthcare plan decision-makers. The standardization of economic modeling in this manner will increase the acceptability of pharmacoeconomics as a practical, real-world science.

Moving Real-World Science Into High School

Moving Real-World Science Into High School

Pharmacoeconomics: from ‘marketing fluff’ to ‘real-world science’

Despite the ever-increasing importance of economic issues in the field of healthcare and the boom in the development of this type of research over recent years, many clinical and healthcare policy decision-makers still view pharmacoeconomic studies with suspicion and are confused as to how to apply the results of these studies to the particular circumstances of their health practice or plan. This is especially true of studies that employ pharmacoeconomic models, since these models are perceived as ‘black boxes’ that yield different results depending on clever manipulation by experts. At the recent APOR* Lipid Conference [Florida, US; November 1997], leaders in the field discussed various ways to improve the credibility and usefulness of pharmacoeconomic studies to the healthcare industry.

Socio-Cognitive Constructs and Characteristics of Classroom Communities: An Exploration of Relationships

In our Cultures Connect project, students engaged in interactions with local and remote audiences in a telecommunication, constructivist-based learning environment with an emphasis on writing about real-world science. The sample consisted of fourth and fifth grade students from a predominantly Hispanic school. They were part of a larger learning community with six other school sites connected through telecommunications. Participants at our site worked in cooperative groups toward the development of a research writing project on real-world science topics. Interactions with their distant peers about their research and other topics consistently occurred over the project's course.Data collected for the current study targeted the status of relationships among socio-cognitive factors with selected group dynamic features of task structure preference and audience awareness. The task structure preference variable divided the students into two groups: (1a) preference to work in teams or (1b) preference to work independently. For another analysis, students were divided into two groups on the basis of expressing an (2a) audience awareness or (2b) lack of an audience awareness in their written communications. Sociocognitive factors included confidence in writing, metacognition, academic motivation, and self-efficacy measures. A group-comparison design was used to compare the mean scores on these constructs for each group factor.The group reporting an audience awareness demonstrated a higher orientation to engaging in group interactions and in using metacognitive strategies in writing. A lack of confidence in writing was more prevalent among the students expressing less awareness to different audiences in their writing.Students with a preference to work by themselves showed statistically significant higher ratings in self-efficacy and a marginal significance on the use of metacognitive skills. Those with a group work preference enjoyed interacting with and receiving input from their peers. Other questions assessed students' perceptions of the benefits accrued as a Cultures Connect participant.The study and discussion of results are situated in the constructivist principles of instruction and learning. In addition, the research addresses related concepts of communities of learners, with implications for designing student-directed environments.

Managing the Fruit Fly Experiment

Today's biology student dips a toe into the waters of biotechnology, sometimes even before learning to swim in basic Mendelian genetics. Back to basics could mean growing Wisconsin FastPlants3'!, the modern equivalent of Mendel's pea plants. But even fast plants have a relatively long generation time. Back to basics can also mean a return to the classic fruit fly experiment-the crossing of homozygous flies of different types to achieve the Fl and F2 generations-to introduce general biology students to genetics. A sophisticated version of the fruit fly experiment is used by AP biology students. I suggest that the historical experiment is a natural for all biology students. First, the experiment is relatively inexpensive. Reusable equipment consists of vials and plugs. Consumable supplies are flies, fly food and anesthetic. Second, the generation time of the fruit fly is a short two weeks. And finally, the experiment affords students the opportunity to work with live animals over an extended period. Students replicate the work of Nobel Prize winners. In doing so they experience the mishaps and frustrations that accompany real world science, but also have the thrill of success when achieving a predicted-or surpriseend! Teachers cite two reasons for putting off the experiment: lack of time and too burdensome a task to manage. Managing the fruit fly experiment for 140 students does sound like an overwhelming, unmanageable task that would take up a disproportionate amount of class time. It's possible, though, to carry off the experiment with a maximum of three class periods plus student work before and after school. This management plan uses three days of class time. The rest of the

Rationality and the psychology of inference

Recent advances in the cognitive psychology of inference have been of great interest to philosophers of science. The present paper reviews one such area, namely studies based upon Wason's “4-card” selection task. It is argued that interpretation of the results of the experiments is complex, because a variety of inference strategies may be used by subjects to select evidence needed to confirm or disconfirm a hypothesis. Empirical evidence suggests that which strategy is used depends in part on the semantic, syntactic, and pragmatic context of the inference problem at hand. Since the factors of importance are also present in real-world science, and similarly complicate its interpretation, the selection task, though it does not present a “quick fix”, represents a kind of microcosm of great utility for the understanding of science. Several studies which have examined selection strategies in more complex problem-solving environments are also reviewed, in an attempt to determine the limits of generalizability of the simpler selection tasks. Certain interpretational misuses of laboratory research are described, and a claim made that the issue of whether or not scientists are rational should be approached by philosophers and psychologists with appropriate respect for the complexities of the issue.