Elke Kurz-Milcke

Bio: Elke Kurz-Milcke is an academic researcher from Georgia Institute of Technology. The author has contributed to research in topics: Scientific evidence & Declaration. The author has an hindex of 7, co-authored 15 publications receiving 255 citations. Previous affiliations of Elke Kurz-Milcke include University of Tübingen & University of Education, Winneba.

Transparency in risk communication : Graphical and analog tools

Abstract: Why is it that the public can read and write but only a few understand statistical information? Why are elementary distinctions, such as that between absolute and relative risks, not better known? In the absence of statistical literacy, key democratic ideals, such as informed consent and shared decision making in health care, will remain science fiction In this chapter, we deal with tools for transparency in risk communication The focus is on graphical and analog representations of risk Analog representations use a separate icon or sign for each individual in a population Like numerical representations, some graphical forms are transparent, whereas others indiscernibly mislead the reader We review cases of (1) tree diagrams for representing natural versus relative frequency,(2)decisiontreesfortherepresentationoffastandfrugaldecisionmaking,(3)bargraphs forrepresentingabsoluteversusrelativerisk,(4)populationdiagramsfortheanalogrepresentation of risk, and (5) a format of representation that employs colored tinker cubes for the encoding of informationaboutindividualsinapopulationGraphshavelongenjoyedthestatusofbeing“worth a thousand words” and hence of being more readily accessible to human understanding than longwinded symbolic representations This is both true and false Graphical tools can be just as well employed for transparent and nontransparent risk communications

Research Laboratories as Evolving Distributed Cognitive Systems

Abstract: We are carrying out a research project aimed at understanding reasoning and representational practices employed in problem solving in biomedical engineering (BME) laboratories. These laboratories are best construed as evolving distributed cognitive systems: the laboratory is not simply a physical space, but a problem space, the components of which change over time; cognition is distributed among people and artifacts; and the cognitive partnerships between the technological artifacts and the researchers in the system evolve. To investigate this evolving cognitive system we use both ethnography and cognitive-historical analysis. Understanding practices in innovative research laboratories requires in-depth observation of the lab as it presently exists, as well as research into the histories of the experimental devices used in it. We are aiming here for relational accounts (‘biographies’) of the distributed cognitive systems within the lab as they change in time. In this we find that one cannot divorce research from learning in the context of the laboratory, where learning involves building relationships with artifacts.

Experts in science and society

Abstract: Political Systems and the Experts They Support.- Scientists as Expert Advisors: Science Cultures Versus National Cultures?.- Experts' Discourses as Judicial Drama or Bureaucratic Coordination: Family Debate in the United States and Germany.- The Integration of Social Science Expertise Into the Political Process: Did It Actually Happen?.- Socialist Legal Experts: A New Profession?.- Who Is Called Upon as Expert?.- Folklore Protection in Australia: Who Is Expert in Aboriginal Tradition?.- The Humane Expert: The Crisis of Modern Medicine During the Weimar Republic.- Expertise Not Wanted: The Case of the Criminal Law.- Air Pollution Control: Who Are the Experts?.- Experts, Redefined.- The Philosopher as Coach.- Who Decides the Worth of an Arm and a Leg? Assessing the Monetary Value of Nonmonetary Damage.- The Expert in a Historical Context: The Case of Venetian Politics.- Innovative Representations.- Mapping Urban Nature: Bio-Ecological Expertise and Urban Planning.- How to Improve the Diagnostic Inferences of Medical Experts.- Statistical Scientific Evidence and Expertise in the Courtroom.- The Authority of Representations.

What Has History to Do with Cognition? Interactive Methods for Studying Research Laboratories ∗

Abstract: We have been studying cognition and learning in research laboratories in the field of biomedical engineering (Nersessian, Kurz-Milcke, Newstetter & Davies 2003; Newstetter, Kurz-Milcke & Nersessian, in press[a]). Through our combining of ethnography and cognitive-historical analysis in studying these settings we have been led to understand these labs as comprising evolving distributed cognitive systems and as furnishing agentive learning environments. For this paper we develop the theme of 'models-in-action,' a variant of what Knorr Cetina (1999) has called 'knowledge-in-action.' Among the epistemically most salient objects in these labs are so called "model systems," which are designs that blend engineering with the study and use of biological systems for purposes of simulative model-based reasoning. We portray the prevalent design-orientation in this engineering specialty and how the prevailing activity of cell-culturing in these labs transitions into a design activity for the bio-medical engineers, leading them to work with 'wet' devices. We discuss how devices, 'wet' and 'dry,' situate model-based understandings and how they participate in model systems in these labs. Models tend to come in clusters or configurations, and the model systems in these labs are epistemically salient junctures of interlocking models. Model systems in these labs evolve thereby consolidating what we want to call a 'fabric of interlocking models,' which functions as point of stability and departure in these labs. We convey a taste of such a 'fabric' for a tissue-engineering lab. We conjecture that through this 'fabric' extended developments in technology and methodology have a 'situated' presence in the workings of these labs.

Educating children in stochastic modeling: games with stochastic urns and colored tinker-cubes

Abstract: It is an established opinion that young children have good probabilistic intuitions although their mental framework for reasoning probabilistically may be fragmentary and even contain inconsistencies. We join the camp of mathematics educators who advocate an early training in stochastic thinking. We recognize, however, that such early training can only be based on a heuristic approach to stochastics. The heuristic approach that we propose here is implemented by guiding children to actively construct stochastic situations by means of plastic tinker-cubes and stochastic urns. The aim of this enactive training is to foster the development of a dynamic mental imagery for representing stochastic situations. INTRODUCTION Due mostly to historical factors, the pace at which stochastics has been integrated as a component of mathematics school curricula has been comparatively slow: The debate on how early and to what extent children should be taught statistics and probability is far from being concluded. Probability is one of the core concepts in stochastics and aspects of it are being grasped by a child of seven (Piaget, 1952; Wollring, 1994; Falk, 1982, Martignon and Wassner, 2005). Yet its philosophical and mathematical complexity, involving either notions of infinity and convergence in the classical approach, or notions of sets and measures in the modern formalization, has led mathematics educators to think that the inception of probabilistic concepts should be confined to the last years of secondary school. In countries like Germany this late inception had, until 2003, seldom been implemented with real enthusiasm by teachers, although most did acknowledge that stochastics is more useful than other branches of mathematics for everyday life. The influence of the NCTM Standards and the effects PISA Studies 2000 and 2003 operated a change in the attitudes both of teachers and of ministerial organizations towards statistics and probability in schools: After all, 25% of all questions in the PISA 2003 tests dealt with probabilistic or statistical situations. In most of the Lander special recommendations have also been formulated in the programs for primary school to encourage teachers to introduce first notions of descriptive statistics and probabilities.

Helping Doctors and Patients Make Sense of Health Statistics

Abstract: Many doctors, patients, journalists, and politicians alike do not understand what health statistics mean or draw wrong conclusions without noticing. Collective statistical illiteracy refers to the widespread inability to understand the meaning of numbers. For instance, many citizens are unaware that higher survival rates with cancer screening do not imply longer life, or that the statement that mammography screening reduces the risk of dying from breast cancer by 25% in fact means that 1 less woman out of 1,000 will die of the disease. We provide evidence that statistical illiteracy (a) is common to patients, journalists, and physicians; (b) is created by nontransparent framing of information that is sometimes an unintentional result of lack of understanding but can also be a result of intentional efforts to manipulate or persuade people; and (c) can have serious consequences for health. The causes of statistical illiteracy should not be attributed to cognitive biases alone, but to the emotional nature of the doctor-patient relationship and conflicts of interest in the healthcare system. The classic doctor-patient relation is based on (the physician's) paternalism and (the patient's) trust in authority, which make statistical literacy seem unnecessary; so does the traditional combination of determinism (physicians who seek causes, not chances) and the illusion of certainty (patients who seek certainty when there is none). We show that information pamphlets, Web sites, leaflets distributed to doctors by the pharmaceutical industry, and even medical journals often report evidence in nontransparent forms that suggest big benefits of featured interventions and small harms. Without understanding the numbers involved, the public is susceptible to political and commercial manipulation of their anxieties and hopes, which undermines the goals of informed consent and shared decision making. What can be done? We discuss the importance of teaching statistical thinking and transparent representations in primary and secondary education as well as in medical school. Yet this requires familiarizing children early on with the concept of probability and teaching statistical literacy as the art of solving real-world problems rather than applying formulas to toy problems about coins and dice. A major precondition for statistical literacy is transparent risk communication. We recommend using frequency statements instead of single-event probabilities, absolute risks instead of relative risks, mortality rates instead of survival rates, and natural frequencies instead of conditional probabilities. Psychological research on transparent visual and numerical forms of risk communication, as well as training of physicians in their use, is called for. Statistical literacy is a necessary precondition for an educated citizenship in a technological democracy. Understanding risks and asking critical questions can also shape the emotional climate in a society so that hopes and anxieties are no longer as easily manipulated from outside and citizens can develop a better-informed and more relaxed attitude toward their health.

Engineering in K-12 Education: Understanding the Status and Improving the Prospects.

Abstract: Engineering education in K-12 classrooms is a small but growing phenomenon that may have implications for engineering and also for the other STEM subjects--science, technology, and mathematics. Specifically, engineering education may improve student learning and achievement in science and mathematics, increase awareness of engineering and the work of engineers, boost youth interest in pursuing engineering as a career, and increase the technological literacy of all students. The teaching of STEM subjects in U.S. schools must be improved in order to retain U.S. competitiveness in the global economy and to develop a workforce with the knowledge and skills to address technical and technological issues. Engineering in K-12 Education reviews the scope and impact of engineering education today and makes several recommendations to address curriculum, policy, and funding issues. The book also analyzes a number of K-12 engineering curricula in depth and discusses what is known from the cognitive sciences about how children learn engineering-related concepts and skills. Engineering in K-12 Education will serve as a reference for science, technology, engineering, and math educators, policy makers, employers, and others concerned about the development of the country's technical workforce. The book will also prove useful to educational researchers, cognitive scientists, advocates for greater public understanding of engineering, and those working to boost technological and scientific literacy.

Numeric, Verbal, and Visual Formats of Conveying Health Risks: Suggested Best Practices and Future Recommendations

Abstract: Perception of health risk can affect medical decisions and health behavior change Yet the concept of risk is a difficult one for the public to grasp Whether perceptions of risk affect decisions and behaviors often relies on how messages of risk magnitudes (ie, likelihood) are conveyed Based on expert opinion, this article offers, when possible, best practices for conveying magnitude of health risks using numeric, verbal, and visual formats This expert opinion is based on existing empirical evidence, review of papers and books, and consultations with experts in risk communication This article also discusses formats to use pertaining to unique risk communication challenges (eg, conveying small-probability events, interactions) Several recommendations are suggested for enhancing precision in perception of risk by presenting risk magnitudes numerically and visually Overall, there are little data to suggest best practices for verbal communication of risk magnitudes Across the 3 formats, few overall recommendations could be suggested because of 1) lack of consistency in testing formats using the same outcomes in the domain of interest, 2) lack of critical tests using randomized controlled studies pitting formats against one another, and 3) lack of theoretical progress detailing and testing mechanisms why one format should be more efficacious in a specific context to affect risk magnitudes than others Areas of future research are provided that it is hoped will help illuminate future best practices

Learning in Activity

Abstract: This chapter discusses a program of research in the learning sciences that I call “situative.” The defining characteristic of a situative approach is that instead of focusing on individual learners, the main focus of analysis is on activity systems : complex social organizations containing learners, teachers, curriculum materials, software tools, and the physical environment. Over the decades, many psychologists have advocated a study of these larger systems (Dewey, 1896, 1929/1958; Lewin, 1935, 1946/1997; Mead, 1934; Vygotsky, 1987), although they remained outside the mainstream of psychology, which instead focused on individuals. Situative analyses include hypotheses about principles of coordination that support communication and reasoning in activity systems, including construction of meaning and understanding. Other terms for the perspective I refer to as situative include sociocultural psychology (Cole, 1996; Rogoff, 1995), activity theory (Engestrom, 1993; 1999), distributed cognition (Hutchins, 1995a), and ecological psychology (Gibson, 1979; Reed, 1996). I use the term “situative” because I was introduced to the perspective by scholars who referred to their perspective as situated action (Suchman, 1985), situated cognition (Lave, 1988), or situated learning (Lave & Wenger, 1991). I prefer the term “situative,” a modifier of “perspective,” “analysis,” or “theory,” to “situated,” used to modify “action,” “cognition,” or “learning,” because the latter adjective invites a misconception: that some instances of action, cognition, or learning are situated and others are not. During the 1980s and 1990s these scholars and others provided analyses in which concepts of cognition and learning are relocated at the level of activity systems.