Meta-Reasoning: The Challenge of Effective Reasoning Regulation
Technion—IsraelInstitute of Technology, Haifa, Israel
The metacognitive framework (Nelson & Narens, 1990) deals with effort regulation while performing cognitive tasks, such as learning. To date, this framework was examined empirically mainly by studies involving memorization tasks. As a result, it is often referred to as Meta-Memory. The Meta-Reasoning framework (Ackerman & Thompson, 2014) deals with effort regulation while solving reasoning problems. It suggests that in some respects there are analogies between meta-memory and meta-reasoning, while in others, alternative theoretical approaches are needed. For instance, while isolated words are clearly memorable by healthy adults, a reasoning problem may be unsolvable in general or for the particular person (e.g., lack of math knowledge). Thus, while investing a lot of effort in memorization is likely to be valuable, waste of time is a likely outcome when one cannot solve a problem. Can people identify unsolvable problems in the first place? When are they willing to give up a problem after engaging in solving it? Can they adjust their efforts to work effectively under time pressure? What are the predictable biases in judgments and effort regulation while solving problems? Theoretical and practical aspects will be discussed.
The credibility of psychological science at stake: Lessons to be learned from low reproducibility of psychological studies
Department of Psychology, University of Ljubljana, Ljubljana, Slovenia
Many psychology papers fail replication test was one of the most frequent and loudest headlines in scientific and popular press reporting a study entitled Estimating the reproducibility of psychological science published in Science in 2015 by 270 authors – researchers in psychology from different parts of the world. The authors tried to replicate 100 empirical studies, published in three prominent American psychological journals from 2008. Namely, modern science understands scientific findings as reproducible, replicable, and generalizable. The results of the study were sobering and presented a clear challenge to the field, as the reproducibility turned up to be surprisingly low. In general, reproducibility seems undervalued because scientists prioritize novelty over replication. Innovation is the engine of discovery; researchers are usually driven by searching for the barriers of science; when a topic seems covered, they tend to rush forward but forget to stop and check the stability of the outcomes. However, reproducibility and cross-validation also help to establish a firm nomological network and a high validity of scientific theories. We need to talk about it and include the topic in the academic curricula for studying psychology because science can learn from replication studies, critically pointing to important issues in planning and performing research of good quality. It will also help prevent the manipulations and the poorly supported reproaches of psychology. In public debate there are occurrences of misuse of the Science replicability study such as erroneous and malicious interpretations of the results that more than two thirds of psychological studies are falsified, faked, or fraudulent with clear intention to discredit psychology as a science and profession by simply stating that it is not trustworthy enough to be taken seriously. As one of the after-effects of the Science study we can expect that journals will most likely publish more replications in the future. They are already launching new policies that will encourage authors, editors, and reviewers to re-examine and recalibrate the basic notions about what constitutes a good research. Editorial boards will advance the acceptance culture of the submitted articles such as sharing data, the analysis code, and study materials, disclosing all data exclusions, requiring authors to discuss sample sizes and statistical power, report effect size, etc. There are at least two heartening lessons that can be learned from the Science study: (i) that the project was conducted with concern about the health of the discipline, believing in its promise for accumulating knowledge about human behaviour that can advance the quality of the human condition and (ii) that many will be tempted to conclude that psychology is a bad apple in the basket. However, this is not the case: this is a problem shared with natural sciences, medical sciences, and biomedicine, as well as behavioural or social sciences, because the replication efforts in other fields are similarly low.
Novel contributions of Anderson’s theory of information integration to intuitive physics
Sergio C. Masin
Department of General Psychology, University of Padova, Padova, Italy
The research methodology based on Anderson’s theory of information integration represents one of the most fruitful techniques for investigating mental processes. This methodology is briefly described with examples of application in various fields of psychology. Its power in unraveling hidden information is more specifically demonstrated in the field of knowledge assessment. A striking example of this is the assessment of people’s intuitive knowledge of the laws of the ordinary physical world, which has led to the unprecedented finding that lay people generally have correct intuitive knowledge of these laws.
Social Comparisons – How other people influence who we are and what we want
Department of Psychology, University of Graz, Graz, Austria
People are social beings. We seek affiliations, work in groups, and strive for long lasting personal relationships. But other people do not only comfort us, support us and help us, they also influence our own understanding of our self. Social information based on comparisons between the self and others is a crucial building block of our self-knowledge. Furthermore, social comparison could make us feel good or bad and might have a motivating function. In this talk, I will present our understanding of how social comparison unfolds. Social comparison is a very flexible process. The outcome of a comparison process does not only depend on the person one compares with, but also on the comparison process itself. Sometimes we assimilate to a standard and at other times we contrast away. Thus, if people want to profit from the comparison and use it to feel good or to be motivated, one has to understand in more detail the complex mechanisms of social comparisons.
Is metacognition “hot”? The role of affect in metacognition and self-regulated learning
School of Psychology, Aristotle University of Thessaloniki, Thessaloniki, Greece
The term “hot cognition” has been used in the past to denote that cognition and affect interact in cognitive processing to support intuition, creative thinking, decision making, or analytic thinking. I propose that if we look at metacognition in the broader context of self-regulated learning (SRL) metacognition is also “hot”. Specifically, metacognitive experiences, namely feelings and judgments as one works on a task, are closely connected to positive and negative affect as well as emotions. Neuropsychological evidence shows that metacognitive experiences and affect share brain mechanisms (i.e., the Anterior Cingulate Cortex). Moreover, fluency or making progress in cognitive processing elicits positive affect and metacognitive experiences such as ease of processing whereas disfluency elicits negative affect and feeling of difficulty as well as awareness of effort exertion. Also, cognitive events such as cognitive interruption increase feeling of difficulty and elicit surprise. Moreover, there is evidence suggesting that one’s mood state has effects on metacognitive experiences such as feeling of difficulty or judgment of effort exertion, and metacognitive experiences, in their turn, have effects on affect. For example, metacognitive experiences have reciprocal relations with self-concept, contribute to attributions regarding competence or effort (that underlie the formation of achievement emotions), and feeling of confidence is part of the mechanism that triggers curiosity. Conceptualizing metacognition as hot can explain the complex relations between monitoring and control in SRL, and particularly why metacognitive experiences do not often suffice to activate effective metacognitive and cognitive control strategies.
To understand intergroup relations: the socially embedded Self and Other in play
Institute of Psychology, University of Pécs, Pécs, Hungary
The aim of science is to understand reality. When we try to understand a social phenomenon we think about causes, effects, and what makes a contribution or not, to a „supposed” progress. We think about how to produce change and with witch derivatives. More than focus on the myth of generalisation, it’s important to care about predictability of phenomena (Tajfel, 1981). Social psychology in this way has the responsibility to contribute to the understanding of negative social phenomena (e.g. intergroup conflicts, wars, terrorism, Holocaust) and to designate the conditions of what it thinks to be directions of “progress” (e.g. recognition of diversity in knowledge production, process of cooperation, community development, inclusiveness). Its main contribution in understanding reality is to highlight the importance of how individuals create and maintain their point of view and “knowledge” is strictly related to the social context in which they live and act according to their own psychological perspective. To explain these considerations different theoretical approaches are taken into account. The theory of social identity (Tajfel, 1981) will help to understand the point of view of the individuals; the theory of social representation (Moscovici, 1973, 1981, 1984) frames the social creation and negotiation of “knowledge”, thus even cultural diversities; and finally the theory of Narrative Social Psychology (László, 2001, 2007, 2013) explains the psychological organisation of both identity and worldview and how these constructions and reconstructions can be captured. I will present the results of different research that explores self/other construction as possible causes of intergroup conflicts, such as: how prejudice is related to threat (refugees, migrants, Gypsies), how majority identification influences the way people think about Minorities (collective victimhood and its dynamic), and how being a member of a threatened Minority group delimits an individual’s cognitive alternatives (Bokrétás, Bigazzi & Péley, 2007; Bigazzi & Csertő, 2016; Bigazzi & Serdült, in press).
Deductive Reasoning: Why People Are Not Always Logical
Department of Psychology, University of Zadar, Zadar, Croatia
Research on reasoning deals with the processes of deductive, inductive and analogical reasoning. Since the theoretical frame of cognitive psychology considers thinking as a process of mental representation manipulation, the traditional intelligence-test approach is not enough. A psychological experimental approach is needed to gain insight into the mental processes of thought. Systematic research on deduction originated in the 1960’s when the British psychologist Peter Wason investigated this subject. These experiments demonstrated that there were significant and systematic deviations in human deduction when related to traditional and formal logic. For example, the paradigm of the Wason selection task reveals the biases in human reasoning such as the confirmation and matching bias, among others. These biases are connected to specific reasoning heuristics and are usually the cause of the characteristic fallacies in specific reasoning situations. A change in reasoning conditions (e.g. the use of abstract or concrete content) can change the activation of the specific bias and drastically change the reasoning outcome. Therefore, these situations encourage a strong and confusing impression of people being limitedly logical or even non-logical. However, these observations nicely fit into the modern Dual process theory. Dual process theory explains that there are two types of processes involved in thinking: Type 1 which is rapid, automatic and based on the activation of heuristics and biases, and Type 2 which is slow, demands mental effort and is based on mental skills (e.g. mathematical or logical skills). Theories of deductive reasoning are usually divided into three classes: deduction as the process of factual knowledge connecting; deduction as the syntactic process based on the rules of formal logic; and deduction as the sematic process based on representations called mental models. The third theory describes mental models as crucial representations that are related to systems of long-term and working memory and offers explanations of a broad set of phenomena which includes reasoning with syllogisms, conditionals, inductive reasoning, and representation of discourse, probabilities and mental simulations. The information that models include cannot only be abstract, but also based on perceptive and motor systems which can be a link that relates reasoning studies with embodied cognition. Finally, the reasoning constraints described by mental models theory contribute to the explanation of characteristic logical fallacies and reasoners as limited in logical problem solving.