Research on moral judgment has been dominated by rationalist models, in which moral judgment is thought to be caused by moral reasoning. The author gives 4 reasons for considering the hypothesis that moral reasoning does not cause moral judgment; rather, moral reasoning is usually a post hoc construction, generated after a judgment has been reached. The social intuitionist model is presented as an alternative to rationalist models. The model is a social model in that it deemphasizes the private reasoning done (...) by individuals and emphasizes instead the importance of social and cultural influences. The model is an intuitionist model in that it states that moral judgment is generally the result of quick, automatic evaluations (intuitions). The model is more consistent than rationalist models with recent findings in social, cultural, evolutionary, and biological psychology, as well as in anthropology and primatology. (shrink)

The ability to recognize and correct errors in one's explanatory understanding is critically important for learning. However, little is known about the mechanisms that determine when and under what circumstances errors are detected and how they are corrected. The present study investigated thought experiments as a potential tool that can reveal errors and trigger belief revision in the service of error correction. Across two experiments, 1149 participants engaged in reasoning about force and motion (a domain with well‐documented misconceptions) in a (...) pre‐training—training—post‐training design. The two experiments manipulated the type of mental model manipulated in the thought experiments (i.e., whether participants reasoned about forces acting on their own bodies vs. on external objects), as well as the level of relational and argumentative reasoning about the outcomes of the thought experiments. The results showed that: (i) thought experiments can serve as a tool to elicit inconsistencies in one's representations; (ii) the level of relational and argumentative reasoning determines the level of belief revision in the service of error correction; and (iii) the type of mental model manipulated in a thought experiment determines its outcome and its potential to initiate belief revision. Thought experiments can serve as a valuable teaching and learning tool, and they can help us better understand the nature of error detection and correction systems. (shrink)

I examined the proposition that there are psychological limits on what scientific problems can be solved, and that these limits may be based on a failure to be able to produce imagable, observation-based models for any possible solution, a position suggested by philosopher Colin McGinn in an argument attempting to prove that the mind-body problem is unsolvable. I examined another likely candidate for an unsolvable problem -- the ultimate origin of the universe (i.e., what might have preceded the Big Bang (...) or any other starting point; why there should be something rather than nothing) -- by exploring the reasoning of physicists about this problem and measuring visual imagery frequency and vividness, with the expectation that those who most believed the problem unsolvable would be more frequent/vivid imagers and therefore more affected by the apparent impossibility of producing an imagable solution. Eight physicists were interviewed and imagery frequency and vividness measurements performed using Cohen & Saslona's IDQ-IHS and Marks's VVIQ, respectively. All subjects considered the problem unsolvable within today's physics and all but one thought the problem still meaningful, though none were optimistic about a solution. The one subject who dismissed the problem had the lowest imagery frequency score, and there was also a significant rank order correlation (r = 0.83, p < .02) between degree of belief in problem unsolvability (extended to include viewing the problem as meaningful and not already solved) and a composite imagery frequency/vividness score, though the sample was too small to control for some possible confounding factors. (shrink)

This paper is about guessing: how people respond to a question when they aren’t certain of the answer. Guesses show surprising and systematic patterns that the most obvious theories don’t explain. We argue that these patterns reveal that people aim to optimize a tradeoff between accuracy and informativity when forming their guess. After spelling out our theory, we use it to argue that guessing plays a central role in our cognitive lives. In particular, our account of guessing yields new theories (...) of belief, assertion, and the conjunction fallacy—the psychological finding that people sometimes rank a conjunction as more probable than one of its conjuncts. More generally, we suggest that guessing helps explain how boundedly rational agents like us navigate a complex, uncertain world. (shrink)

The topic of my thesis is individual and collective responsibility for collectively caused systemic harms, with climate change as the case study. Can an individual be responsible for these harms, and if so, how? Furthermore, what does it mean to say that a collective is responsible? A related question, and the second main theme, is how ignorance and knowledge affect our responsibility. -/- My aim is to show that despite the various complexities involved, an individual can have responsibility to address (...) climate change. I argue that climate change is not a problem just for states and international bodies, but also for individuals. There are three possible sources of moral responsibility for individuals in relation to climate change harms: direct responsibility (individuals qua individuals), shared responsibility as members (individuals qua members of collective agents), and shared responsibility as constituents (individuals qua constituents of unorganised collectives). -/- Accounts that deny individual responsibility fail to either take our interdependent reality seriously or fail to understand marginal participation (or in the case direct responsibility, fail to appreciate the nature of the climate change phenomenon). Individuals can be complicit in climate change harms, either as members of collective agents (e.g. as citizens of states or employees of a corporation) or as constituents of unorganised collectives (e.g. as consumers or polluters). -/- Although I focus on individual complicity, I do not deny the obligations of collective agents. However, nation-states, governments, and international bodies are not the only relevant collective agents in climate ethics: other collective agents, such as corporations, matter also and can have obligations concerning making sure that their activities are as carbon-neutral as possible. In addition, those corporations that have engaged in lobbying against climate regulation through creating and disseminating misleading information have acquired themselves additional obligations to mitigate climate change and compensate for the harm they have caused. Even so, the ethical claims can only be understood by individual members of these collective agents because only they can feel the pull of moral claims. I suggest that we could distinguish between what one must possess in order to be capable of making moral claims (i.e. moral agency conditions), and what it means to have the ability to exhibit such claims through one’s conduct. -/- Individual direct responsibility is to not to increase the probable risk of serious harm to other people, at least as long as we can do so at a less than significant cost to ourselves. It is limited to relatively wealthy individuals. Offsetting is not a reliable way to meet this duty; we need to look at the emissions from our lifestyle choices (within the available infrastructure). Shared responsibility qua members of collective agents is the key individual responsibility, and it presses especially on those occupying key positions within key collective agents. Saying that, our shared responsibility qua constituents of unorganised collectives has the potential to be decisive in whether some action is taken or not, either through a set of actions that can signal certain acceptance or support, or as a form of political support from the grass roots. (shrink)

The rise of conspiracy culture and the growing influence of conspiracy theories have attracted the attention of scholars from a range of fields. In recent years, Daniel Jolley, Asbjørn Dyrendal, and others have noted the prevalence of conspiracy theories amongst adolescent schoolchildren in Scandinavia and the UK. This article draws on Paulo Freire’s concept of the ‘banking model’ of education to make the case against a ‘debunking’ approach to anticonspiracist education. It argues that conspiracism should be understood as a feature (...) of our culture and as such it should be interrogated rather than dismissed by educators who are engaged in the process of educating for democracy. (shrink)

Can the output of human cognition be predicted from the assumption that it is an optimal response to the information-processing demands of the environment? A methodology called rational analysis is described for deriving predictions about cognitive phenomena using optimization assumptions. The predictions flow from the statistical structure of the environment and not the assumed structure of the mind. Bayesian inference is used, assuming that people start with a weak prior model of the world which they integrate with experience to develop (...) stronger models of specific aspects of the world. Cognitive performance maximizes the difference between the expected gain and cost of mental effort. Memory performance can be predicted on the assumption that retrieval seeks a maximal trade-off between the probability of finding the relevant memories and the effort required to do so; in categorization performance there is a similar trade-off between accuracy in predicting object features and the cost of hypothesis formation; in casual inference the trade-off is between accuracy in predicting future events and the cost of hypothesis formation; and in problem solving it is between the probability of achieving goals and the cost of both external and mental problem-solving search. The implemention of these rational prescriptions in neurally plausible architecture is also discussed. (shrink)

People are adept at inferring novel causal relations, even from only a few observations. Prior knowledge about the probability of encountering causal relations of various types and the nature of the mechanisms relating causes and effects plays a crucial role in these inferences. We test a formal account of how this knowledge can be used and acquired, based on analyzing causal induction as Bayesian inference. Five studies explored the predictions of this account with adults and 4-year-olds, using tasks in which (...) participants learned about the causal properties of a set of objects. The studies varied the two factors that our Bayesian approach predicted should be relevant to causal induction: the prior probability with which causal relations exist, and the assumption of a deterministic or a probabilistic relation between cause and effect. Adults’ judgments (Experiments 1, 2, and 4) were in close correspondence with the quantitative predictions of the model, and children’s judgments (Experiments 3 and 5) agreed qualitatively with this account. (shrink)

Recent experimental philosophy arguments have raised trouble for philosophers' reliance on armchair intuitions. One popular line of response has been the expertise defense: philosophers are highly-trained experts, whereas the subjects in the experimental philosophy studies have generally been ordinary undergraduates, and so there's no reason to think philosophers will make the same mistakes. But this deploys a substantive empirical claim, that philosophers' training indeed inculcates sufficient protection from such mistakes. We canvass the psychological literature on expertise, which indicates that people (...) are not generally very good at reckoning who will develop expertise under what circumstances. We consider three promising hypotheses concerning what philosophical expertise might consist in: (i) better conceptual schemata; (ii) mastery of entrenched theories; and (iii) general practical know-how with the entertaining of hypotheticals. On inspection, none seem to provide us with good reason to endorse this key empirical premise of the expertise defense. (shrink)

Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Without our ability to discover and empirically test causal theories, we would not have made progress in various empirical sciences. In the past decades, the important role of causal knowledge has been discovered in many areas of cognitive (...) psychology. Despite the ubiquity of causal reasoning, textbooks of cognitive psychology have neglected this growing field. The goal of The Oxford Handbook of Causal Reasoning is to fill this gap. The handbook brings together the leading researchers in the field of causal reasoning and offers state-of-the-art presentations of theories and research. It provides introductions of competing theories of causal reasoning, and discusses its role in various cognitive functions and domains. The final section presents research from neighboring fields. 1. Causal Reasoning: An Introduction Michael R. Waldmann Part I: Theories of Causal Cognition 2. Associative Accounts of Causal Cognition Mike E. Le Pelley, Oren Griffiths, and Tom Beesley 3. Rules of Causal Judgment: Mapping Statistical Information Onto Causal Beliefs José C. Perales, Andrés Catena, Antonio Cándido, and Antonio Maldonado 4. The Inferential Reasoning Theory of Causal Learning: Toward a Multi- Process Propositional Account Yannick Boddez, Jan De Houwer, and Tom Beckers 5. Causal Invariance as an Essential Constraint for Creating a Causal Representation of the World: Generalizing the Invariance of Causal Power Patricia W. Cheng and Hongjing Lu 6. The Acquisition and Use of Causal Structure Knowledge Benjamin Margolin Rottman 7. Formalizing Prior Knowledge in Causal Induction Thomas L. Griffiths 8. Causal Mechanisms Samuel G. B. Johnson and Woo-kyoung Ahn 9. Force Dynamics and Causation Phillip Wolff and Robert Thorstad 10. Mental Models and Causation P. N. Johnson- Laird and Sangeet S. Khemlani 11. Pseudocontingencies Klaus Fiedler and Florian Kutzner 12. Singular Causation David Danks 13. Cognitive Neuroscience of Causal Reasoning Joachim T. Operskalski and Aron K. Barbey Part II: Basic Cognitive Functions 14. Visual Impressions of Causality Peter White 15. Goal-Directed Actions Bernhard Hommel 16. Planning and Control Magda Osman 17. Reinforcement Learning and Causal Models Samuel J. Gershman 18. Causation and the Probability of Causal Conditionals David E. Over 19. Causal Models and Conditional Reasoning Mike Oaksford and Nick Chater 20. Concepts as Causal Models: Categorization Bob Rehder 21. Concepts as Causal Models: Induction Bob Rehder 22. Causal Explanation Tania Lombrozo and Nadya Vasilyeva 23. Diagnostic Reasoning Björn Meder and Ralf Mayrhofer 24. Inferring Causal Relations by Analogy Keith J. Holyoak and Hee-Seung Lee 25. Causal Argument Ulrike Hahn, Roland Bluhm, and Frank Zenker 26. Causality in Decision- Making York Hagmayer and Philip M. Fernbach Part III: Domains of Causal Reasoning 27. Intuitive Theories Tobias Gerstenberg and Joshua B. Tenenbaum 28. Space, Time, and Causality Marc J. Buehner 29. Causation in Legal and Moral Reasoning David A. Lagnado and Tobias Gerstenberg 30. The Role of Causal Knowledge in Reasoning About Mental Disorders Woo-kyoung Ahn, Nancy S. Kim, and Matthew S. Lebowitz 31. Causality and Causal Reasoning in Natural Language Torgrim Solstad and Oliver Bott 32. Social Attribution and Explanation Denis Hilton Part IV: Development, Phylogeny, and Culture 33. The Development of Causal Reasoning Paul Muentener and Elizabeth Bonawitz 34. Causal Reasoning in Non-Human Animals Christian Schloegl and Julia Fischer 35. Causal Cognition and Culture Andrea Bender, Sieghard Beller, and Douglas L. Medin. (shrink)

Many political theorists, philosophers, social scientists, and other academics engage in political activism. And many think this is how things ought to be. In this essay, I challenge the ideal of the politically engaged academic. I argue that, quite to the contrary, political theorists, philosophers, and other political thinkers have a prima facie duty to refrain from political activism. This argument is based on a commonsense moral principle, a claim about the point of political thought, and findings in cognitive psychology.

Previous research suggests that children can infer causal relations from patterns of events. However, what appear to be cases of causal inference may simply reduce to children recognizing relevant associations among events, and responding based on those associations. To examine this claim, in Experiments 1 and 2, children were introduced to a “blicket detector,” a machine that lit up and played music when certain objects were placed upon it. Children observed patterns of contingency between objects and the machine's activation that (...) required them to use indirect evidence to make causal inferences. Critically, associative models either made no predictions, or made incorrect predictions about these inferences. In general, children were able to make these inferences, but some developmental differences between 3- and 4-year-olds were found. We suggest that children's causal inferences are not based on recognizing associations, but rather that children develop a mechanism for Bayesian structure learning. Experiment 3 explicitly tests a prediction of this account. Children were asked to make an inference about ambiguous data based on the base rate of certain events occurring. Four-year-olds, but not 3-year-olds were able to make this inference. (shrink)

This article presents the results of an experiment which investigated elementary school children's explanations of the day/night cycle. First, third, and fifth grade children were asked to explain certain phenomena, such as the disappearance of the sun during the night, the disappearance of stars during the day, the apparent movement of the moon, and the alteration of day and night. The results showed that the majority of the children in our sample used in a consistent fashion a small number of (...) relatively well‐defined mental models of the earth, the sun, and the moon to explain the day/night cycle. These mental models of the day/night cycle were empirically accurate, logically consistent and revealed some sensitivity on the part of the children to issues of simplicity of explanation. The younger children formed Initial mental models which provided explanations of the day/night cycle based on everyday experience (e.g., the sun goes down behind mountains, clouds cover up the sun). The older children constructed synthetic mental models (e.g., the sun and the moon revolve around the stationary earth every 24 hours; the earth rotates in an up/down direction and the sun and moon are fixed on opposite sides) which represented attempts to synthesize the culturally accepted view with aspects of their Initial models. A few of the older children appeared to have constructed a mental model of the day/night cycle similar to the scientific one. A theoretical framework is outlined which explains the formation of initial, synthetic, and scientific models of the day/night cycle in terms of the reinterpretation of a hierarchy of constraints, some of which are present early in the child's life, and others which emerge later out of the structure of the acquired knowledge. (shrink)

The history of ethics often presupposes rationalist thinking on moral issues. An alternative to rationalism has been proposed by the social intuitionist model. This model suggests the bulk of our moral decisions are ‘gut reactions’ or intuitions. Unlike the rationalists, which support reasons and deliberation to draw moral conclusions, intuitionists argue such reasoning is used to support preconceived ethical decisions. This paper provides the first investigation to determine if intuitionism has any validity within business ethics. Using data from the Defining (...) Issues Test and individual journal entries, results indicate discussion-based pedagogy improved the moral reasoning of participants but had very little influence over their beliefs. In short, the social intuitionist model is supported by this study. Most importantly, ethics education that focuses on peer-to-peer discussion can change how students’ reason about moral problems and should be heavily incorporated into classrooms. (shrink)

Unlike behaviorism, cognitive psychology relies on mental concepts to explain behavior. Yet mental processes are not directly observable and multiple explanations are possible, which poses a challenge for finding a useful framework. In this article, I distinguish three new frameworks for explanations that emerged after the cognitive revolution. The first is called tools‐to‐theories: Psychologists' new tools for data analysis, such as computers and statistics, are turned into theories of mind. The second proposes as‐if theories: Expected utility theory and Bayesian statistics (...) are turned into theories of mind, describing an optimal solution of a problem but not its psychological process. The third studies the adaptive toolbox (formal models of heuristics) that describes mental processes in situations of uncertainty where an optimal solution is unknown. Depending on which framework researchers choose, they will model behavior in either situations of risk or of uncertainty, and construct models of cognitive processes or not. The frameworks also determine what questions are asked and what kind of data are generated. What all three frameworks have in common, however, is a clear preference for formal models rather than explanations by general dichotomies or mere verbal concepts. The frameworks have considerable potential to inform each other and to generate points of integration. (shrink)

Mathematics educators suggest that students of all ages need to participate in productive forms of mathematical argument (NCTM, 2000). Accordingly, we developed two complementary frameworks for analyzing the emergence of mathematical argumentation in one second‐grade classroom. Children attempted to resolve contesting claims about the “space covered” by three different‐looking rectangles of equal area measure. Our first analysis renders the topology of the semantic structure of the classroom conversation as a directed graph. The graph affords clear “at a glance” visualization of (...) how various senses of mathematics—as imagined, as performed, and as historically rooted—were interrelated. The graph represents the emergence and intercoordination between conceptual and procedural knowledge in the ebb and flow of classroom conversation. The graph has not just descriptive, but also predictive power: Interconnectedness among the nodes of the graph representing the first 40 min of conversation predicted the structure of recall in the final ten minutes by children who had played little overt role in the conversation up to that point. The second, complementary framework draws upon Goffman's expanded repertoire of roles in speech to demonstrate how the teacher orchestrated this classroom conversation to establish coherent argument. In this second analysis, we establish how the teacher mediated between the everyday talk of her students and the discourse of mathematics. Her revoicing of student talk created interstices for identity and participation in the formation of the argument. Together, the two forms of analysis illuminate the emergence of mathematical argument at two levels: as collective structure and concurrently, as individual activity. (shrink)

The concept of innateness appears in systematic research within cognitive science, but it also appears in less systematic modes of thought that long predate the scientific study of the mind. The present studies therefore explore the relationship between the properly scientific uses of this concept and its role in ordinary folk understanding. Studies 1-4 examined the judgments of people with no specific training in cognitive science. Results showed (a) that judgments about whether a trait was innate were not affected by (...) whether or not the trait was learned, but (b) such judgments were impacted by moral considerations. Study 5 looked at the judgments of both non-scientists and scientists, in conditions that encouraged either thinking about individual cases or thinking about certain general principles. In the case-based condition, both non-scientists and scientists showed an impact of moral considerations but little impact of learning. In the principled condition, both non-scientists and scientists showed an impact of learning but little impact of moral considerations. These results suggest that both non-scientists and scientists are drawn to a conception of innateness that differs from the one at work in contemporary scientific research but that they are also both capable of 'filtering out' their initial intuitions and using a more scientific approach. (shrink)

Previous research suggests that children can infer causal relations from patterns of events. However, what appear to be cases of causal inference may simply reduce to children recognizing relevant associations among events, and responding based on those associations. To examine this claim, in Experiments 1 and 2, children were introduced to a “blicket detector”, a machine that lit up and played music when certain objects were placed upon it. Children observed patterns of contingency between objects and the machine’s activation that (...) required them to use indirect evidence to make causal inferences. Critically, associative models either made no predictions, or made incorrect predictions about these inferences. In general, children were able to make these inferences, but some developmental differences between 3- and 4- year-olds were found. We suggest that children’s causal inferences are not based on recognizing associations, but rather that children develop a mechanism for Bayesian structure learning. Experiment 3 explicitly tests a prediction of this account. Children were asked to make an inference about ambiguous data based on the base-rate of certain events occurring. Fouryear-olds, but not 3-year-olds were able to make this inference. (shrink)

A novel experimental paradigm that measured theory change and confidence in participants' theories was used in three experiments to test the effects of anomalous evidence. Experiment 1 varied the amount of anomalous evidence to see if “dose size” made incremental changes in confidence toward theory change. Experiment 2 varied whether anomalous evidence was convergent or replicating. Experiment 3 varied whether participants were provided with an alternative theory that explained the anomalous evidence. All experiments showed that participants' confidence changes were commensurate (...) with the amount of anomalous evidence presented, and that larger decreases in confidence predicted theory changes. Convergent evidence and the presentation of an alternative theory led to larger confidence change. Convergent evidence also caused more theory changes. Even when people do not change theories, factors pertinent to the evidence and alternative theories decrease their confidence in their current theory and move them incrementally closer to theory change. (shrink)

A familiar adage in the philosophy of science is that general hypotheses are better supported by varied evidence than by uniform evidence. Several studies suggest that young children do not respect this principle, and thus suffer from a defect in their inductive methodology. We argue that the diversity principle does not have the normative status that psychologists attribute to it, and should be replaced by a simple rule of probability. We then report experiments designed to detect conformity to the latter (...) rule in children's inductive judgment. The results suggest that young children in both the United States and Taiwan are sensitive to the constraints imposed by the rule on judgments of probability and evidential strength. We conclude with a suggested reinterpretation of the thesis that children's inductive methodology qualifies them as “little scientists.”. (shrink)

Data are presented that focus on the nature and development of argumentative reasoning. In particular our study describes how support for or against an issue affects memory for critical parts of an argumentative interaction, judgments of argument goodness, and the content of the reasons given in support of one view versus another. Two other factors were examined: developmental differences in argumentation skill and the conditional nature of supporting one side of an argument across varying contexts. Our results show that even (...) seven year old children can recognize, identify, and use the basic components of an argument to provide evidence for and make judgements about their favored position. Moreover, if position support is held constant across all age groups of students, seven year old children were found to give reasons and explanations that were highly similar in content and principle to college students. The same similarities held across age with respect to biases in memory and judgements of argument goodness. The primary difference between children's and college students' argument behavior lay in the side of an argument the students chose to support. Seven year old children and some eleven yearold children supported positions that impute more value to friendship and social consequences than to the maintenance and advancement of individual rights, as specified in a contract agreement. The similarities and differences across development are discussed with respect to a theory of argumentation that speaks to the importance of understanding the nature of goal conflict and a theory of intentionality in predicting how arguments will be represented and resolved. (shrink)

(2013). Rational argument, rational inference. Argument & Computation: Vol. 4, Formal Models of Reasoning in Cognitive Psychology, pp. 21-35. doi: 10.1080/19462166.2012.689327.

There is common agreement that preschool-level science education affects children’s curiosity, their positive approach towards science, and their desire to engage with the subject. Children’s natural curiosity drives them to engage enthusiastically in all forms of exploration. Engaging in scientific exploration necessitates self-regulation capabilities and a wide repertoire of cognitive and metacognitive strategies. The purpose of this study was to examine to what extent preschoolers (aged 5‒6 years) implement nascent inquiry skills, metacognitive awareness, and self-regulation capabilities during play-based scientific exploration (...) tasks. An additional purpose was to investigate the relationships between these capabilities, a relationship not yet investigated in the context of play-based, scientific exploration among young children. The study consisted of 215 preschoolers, from 10 preschools. For this study, we developed two scientific exploration tasks—structured and open-ended. Our motivation was to examine whether preschoolers’ capabilities will differ in the context of structured task which is aligned with the view that young children need guidance and explicit instructions compared to the context of open-ended, play-based task–allowing the children to apply and test their intuitive theories and skills. During performance participants were videotaped. Their verbal and non-verbal responses were analyzed by means of a scoring scheme. The results of a micro-analysis of about 100 hours of video showed that given the opportunity, even without setting explicit goals and instructions, children exhibit inquiry capabilities: they ask questions, plan, hypothesize, use tools, draw conclusions. Asking questions and planning were better manifested during the structured task. Children also manifested higher levels of attention, persistence, and autonomy during the structured task. However, significant higher scores of self-regulation indications were revealed in the context of the open-ended, play-based, exploration task. Moreover, results indicate significant correlations between the five measures of preschoolers’ inquiry capabilities and measures of metacognitive strategic awareness and self-regulation. The results of the present study suggest the importance of combining various learning environments and experiences in early science education that encourage children to engage in structured exploration alongside play-based, open-ended, exploration. (shrink)

Within the last ten to fifteen years, models emerged for describing and developing undergraduate research and inquiry. This article discusses four examples of modelling didactical issues around undergraduate research and inquiry. The aim of the first part of this article is to scrutinize the epistemological and the didactical purpose of these models. As essential dimensions of undergraduate research and inquiry are neglected, two new models are developed. The first puts the coordination of theory and evidence in the centre and determines (...) three different horizons of significance in the field of science. In relation to these horizons, the second model highlights the broader societal context of scientific practices. The role of research and science in society is recognized here on the one hand as an affirmative process of institutionalization of approved knowledge, and on the other, as practices of criticizing and breaking away from established forms of knowing, testing, evaluating, and approving. Concomitantly, the education of students through and within scientific practices of research and inquiry is interpreted against the backdrop of two opposite trajectories influencing students’ ambitions to engage with problems of science. Didactics of higher education therefore need to distinguish between long-term and short-term goals. It is argued that the latter concretizes the former. This understanding of teaching is corroborated against the backdrop of the concept of learning as ‘enculturation’ in science. The argumentation refers back to insights by Lev S. Vygotsky, Ludwik Fleck and Michael Polanyi. (shrink)

A substantial body of evidence shows that people tend to rely too heavily on explanations when trying to justify an opinion. Some research suggests these errors may arise from an inability to distinguish between explanations and the evidence that bears upon them. We examine an alternative account, that many people do distinguish between explanations and evidence, but rely more heavily on unsubstantiated explanations when evidence is scarce or absent. We examine the philosophical and psychological distinctions between explanation and evidence, and (...) show that participants use explanations as a substitute for missing evidence. Experiment 1 replicates the results of other researchers, but further shows that participants generate more evidence when they are not constrained by their lack of data. Merely mentioning a source of data can alter both their evaluation (Experiment 2) and their production (Experiment 3) of explanations and evidence. In Experiment 4, we show that participants can explicitly consider the availability of evidence and other pragmatic factors when evaluating arguments. Finally, we consider the implications of using explanations to replace missing evidence as a strategy in argument. (shrink)

In this paper, I present a framework where possible relations between learning and mental models are explored. In particular, I’ll be concerned with non-symbolic gestures accompanying discourse and their role in inducing the construction of models and therefore deep comprehension and learning in the listener. Also, I’ll be concerned with cognitive and socio-cognitive conflicts and their roles in inducing construction of alternative models of a problem and therefore in learning to reason. Human ability to learn is of great importance for (...) individuals interested in change. Indeed, to learn both declarative and procedural knowledge means to change, and in order to be able to intervene on change in a desired way it is necessary to have a theory of the mental representations and processes involved in learning and a theory of the communication and contexts that favour learning. (shrink)

Future professionals should be prepared for scientific reasoning, i.e., to construct and apply scientific knowledge, in order to analyze and solve problems in their professional practice. Yet, future practitioners’ scientific reasoning skills often seem to be deficient when solving practical problems. This dissertation explores to what extent collaboration may foster the engagement of future practitioners in scientific reasoning: i.e., in epistemic processes and in referring to scientific content knowledge. Therefore, two studies were conducted to compare collaborative and individual problem solving (...) of pre-service teachers regarding their scientific reasoning. Study 1 investigates the effect of group heterogeneity with respect to problem solving scripts on scientific reasoning. Study 2 explores to what extent Epistemic Network Analysis can serve as a methodological approach for measuring scientific reasoning. As part of Study 1, pre-service teachers solved an educational problem either as individuals or as pairs. Collaboration showed a mixed effect on scientific reasoning processes: pairs engaged more in explaining and reasoning about the problem and drew more conclusions, while individuals engaged more in generating solutions. Additional analyses showed that the more heterogeneous pairs were regarding their members’ problem solving scripts the more they engaged in hypothesizing and evaluating evidence and the less they engaged in generating solutions. Finally, pairs less often referred to scientific content than individuals did during problem solving. Study 2 further analyzed the data by applying Epistemic Network Analysis. This method has the advantage of analyzing patterns of connections between epistemic processes, i.e., epistemic networks of scientific reasoning. The central epistemic process for pairs was evidence evaluation, which they frequently used in combination with hypothesizing and communicating and scrutinizing. On the other hand, the most characteristic process in individuals’ scientific reasoning was solution generation, which very often co-occurred with hypothesizing and evidence evaluation. The overall results indicate that if the aim is to develop a more reflective understanding of the problem, future practitioners should collaborate with each other, especially in heterogeneous settings. However, they should be supported to share knowledge regarding scientific theories and evidence as well as to reach a mutual understanding on the problem after a certain time so as to be able to have the capacity of generating solutions. Moreover, the different effects of collaboration on the process and content aspects of scientific reasoning imply that scientific reasoning might not be a unidimensional construct, and its process and content levels should be differentiated in future research. A further important methodological implication is that the process aspect of scientific reasoning can be analyzed as a network of interconnected skills and such analysis might bring more explanatory value than the mere reliance on frequencies of occurrences of isolated activities. (shrink)

Constructing an intuitive theory from data confronts learners with a “chicken‐and‐egg” problem: The laws can only be expressed in terms of the theory's core concepts, but these concepts are only meaningful in terms of the role they play in the theory's laws; how can a learner discover appropriate concepts and laws simultaneously, knowing neither to begin with? We explore how children can solve this chicken‐and‐egg problem in the domain of magnetism, drawing on perspectives from computational modeling and behavioral experiments. We (...) present 4‐ and 5‐year‐olds with two different simplified magnet‐learning tasks. Children appropriately constrain their beliefs to two hypotheses following ambiguous but informative evidence. Following a critical intervention, they learn the correct theory. In the second study, children infer the correct number of categories given no information about the possible causal laws. Children's hypotheses in these tasks are explained as rational inferences within a Bayesian computational framework. (shrink)