What's Fear Got to Do with It - It's Affect We Need to Worry About
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Critical Thinking and Debiasing: Experimentation in an Academic Writing Course
JAPAN ASSOCIATION FOR LANGUAGE TEACHING JALT2019 • TEACHER EFFICACY, LEARNER AGENCY NOVEMBER 1–4, 2019 • NAGOYA, JAPAN Critical Thinking and Debiasing: Experimentation in an Academic Writing Course esearch and interest in cognitive heuristics (shortcuts in thinking) and cognitive Guy Smith R biases (thinking predispositions or tendencies) has grown rapidly in the past 10 to 15 years. What is known about cognitive biases today owes much to work drawn from International Christian University behavioral economics, social psychology, decision making, and error studies. Recently, the cognitive bias discussion has found a much wider audience with the publication John Peloghitis of popular science books such as Nudge by Richard Thaler and Cass Sunstein (2008), International Christian University Predictably Irrational by Dan Ariely (2009), Daniel Kahneman’s Thinking, Fast and Slow (2011), and Robert Cialdini’s Pre-suasion (2016). These books provided the general public with a fascinating and, in some ways, unsettling look into how we think. The Reference Data: research demonstrated that judgments and decisions often emerge from taking thinking Smith, G., & Peloghitis, J. (2020). Critical thinking and debiasing: Experimentation in an academic shortcuts, relying on our intuitions and feelings, and attending to certain stimuli while writing course. In P. Clements, A. Krause, & R. Gentry (Eds.), Teacher efficacy, learner agency. ignoring others. Some of the biases that emerge from these cognitive processes include Tokyo: JALT. https://doi.org/10.37546/JALTPCP2019-51 confirmation bias (to look for or interpret information that confirms a previous belief), in- group bias (a tendency to favor members of your in-groups) and the aptly named ostrich In the last two decades, interest in cognitive biases has rapidly grown across various fields of effect (the tendency to ignore negative situations). -
The Influence of Emotional States on Short-Term Memory Retention by Using Electroencephalography (EEG) Measurements: a Case Study
The Influence of Emotional States on Short-term Memory Retention by using Electroencephalography (EEG) Measurements: A Case Study Ioana A. Badara1, Shobhitha Sarab2, Abhilash Medisetty2, Allen P. Cook1, Joyce Cook1 and Buket D. Barkana2 1School of Education, University of Bridgeport, 221 University Ave., Bridgeport, Connecticut, 06604, U.S.A. 2Department of Electrical Engineering, University of Bridgeport, 221 University Ave., Bridgeport, Connecticut, 06604, U.S.A. Keywords: Memory, Learning, Emotions, EEG, ERP, Neuroscience, Education. Abstract: This study explored how emotions can impact short-term memory retention, and thus the process of learning, by analyzing five mental tasks. EEG measurements were used to explore the effects of three emotional states (e.g., neutral, positive, and negative states) on memory retention. The ANT Neuro system with 625Hz sampling frequency was used for EEG recordings. A public-domain library with emotion-annotated images was used to evoke the three emotional states in study participants. EEG recordings were performed while each participant was asked to memorize a list of words and numbers, followed by exposure to images from the library corresponding to each of the three emotional states, and recall of the words and numbers from the list. The ASA software and EEGLab were utilized for the analysis of the data in five EEG bands, which were Alpha, Beta, Delta, Gamma, and Theta. The frequency of recalled event-related words and numbers after emotion arousal were found to be significantly different when compared to those following exposure to neutral emotions. The highest average energy for all tasks was observed in the Delta activity. Alpha, Beta, and Gamma activities were found to be slightly higher during the recall after positive emotion arousal. -
Contingent Reliance on the Affect Heuristic As a Function of Regulatory Focus
Contingent Reliance on the Affect Heuristic as a Function of Regulatory Focus Michel Tuan Pham Tamar Avnet Results from four studies show that the reliance on affect as a heuristic of judgment and decision-making is more pronounced under a promotion focus than under a prevent ion focus. Two different manifestations of this phenomenon were observed. Studies 1–3 show that different type s of affective inputs are weighted more heavily under promotion than under prevention in person-impression formation, product evaluations, and social recommendations. Study 4 additionally shows that valuations performed under promotion are more scope- insensitive—a characteristic of affect-based valuations—than valuations performed under prevention. The greater reliance on affect as a heuristic under promotion seems to arise because promotion-focused individuals tend to find affective inputs more diagnostic, not because promotion increases the reliance on peripheral information per se. Although decision research has historically focused affective responses to make judgments and decisions, on the cognitive processes underlying decision making, to begin with? a growing body of research from multiple disciplines The purpose of this research is to test the suggests that affective processes play an important role hypothesis that an important determinant of the as well. In particular, there is strong evidence that reliance on affect as a heuristic for evaluations and decisions are often based on subjective affective decisions is the self-regulatory orientation of the responses to the options, which appear to be seen as decision-maker. Building on recent findings by Pham indicative of the options’ values (Bechara, Damasio, and Avnet (2004), we propose that the reliance on Tranel, & Damasio, 1997; Loewenstein, Weber, Hsee, affect as an evaluation heuristic is more pronounced & Welch, 2001; Pham, 1998; Schwarz & Clore, 1983). -
Anger in Negotiations: a Review of Causes, Effects, and Unanswered Questions David A
Negotiation and Conflict Management Research Anger in Negotiations: A Review of Causes, Effects, and Unanswered Questions David A. Hunsaker Department of Management, University of Utah, Salt Lake City, UT, U.S.A. Keywords Abstract anger, negotiation, emotion, attribution. This article reviews the literature on the emotion of anger in the negotia- tion context. I discuss the known antecedents of anger in negotiation, as Correspondence well as its positive and negative inter- and intrapersonal effects. I pay par- David Hunsaker, David Eccles ticular attention to the apparent disagreements within the literature con- School of Business, Spencer Fox cerning the benefits and drawbacks of using anger to gain advantage in Eccles Business Building, negotiations and employ Attribution Theory as a unifying mechanism to University of Utah, 1655 East Campus Center Drive, Salt Lake help explain these diverse findings. I call attention to the weaknesses evi- City, UT 84112, U.S.A.; e-mail: dent in current research questions and methodologies and end with sug- david.hunsaker@eccles. gestions for future research in this important area. utah.edu. What role does anger play in the negotiation context? Can this emotion be harnessed and manipulated to increase negotiating power and improve negotiation outcomes, or does it have inevitable downsides? The purpose of this article is to review the work of scholars that have focused on the emotion of anger within the negotiation context. I begin by offering some background on the field of research to be reviewed. I then explain why Attri- bution Theory is particularly helpful in making sense of diverse findings in the field. -
1 the Development of Empathy: How, When, and Why Nicole M. Mcdonald & Daniel S. Messinger University of Miami Department Of
1 The Development of Empathy: How, When, and Why Nicole M. McDonald & Daniel S. Messinger University of Miami Department of Psychology 5665 Ponce de Leon Dr. Coral Gables, FL 33146, USA 2 Empathy is a potential psychological motivator for helping others in distress. Empathy can be defined as the ability to feel or imagine another person’s emotional experience. The ability to empathize is an important part of social and emotional development, affecting an individual’s behavior toward others and the quality of social relationships. In this chapter, we begin by describing the development of empathy in children as they move toward becoming empathic adults. We then discuss biological and environmental processes that facilitate the development of empathy. Next, we discuss important social outcomes associated with empathic ability. Finally, we describe atypical empathy development, exploring the disorders of autism and psychopathy in an attempt to learn about the consequences of not having an intact ability to empathize. Development of Empathy in Children Early theorists suggested that young children were too egocentric or otherwise not cognitively able to experience empathy (Freud 1958; Piaget 1965). However, a multitude of studies have provided evidence that very young children are, in fact, capable of displaying a variety of rather sophisticated empathy related behaviors (Zahn-Waxler et al. 1979; Zahn-Waxler et al. 1992a; Zahn-Waxler et al. 1992b). Measuring constructs such as empathy in very young children does involve special challenges because of their limited verbal expressiveness. Nevertheless, young children also present a special opportunity to measure constructs such as empathy behaviorally, with less interference from concepts such as social desirability or skepticism. -
The Somatic Marker Hypothesis: a Neural Theory of Economic Decision
Games and Economic Behavior 52 (2005) 336–372 www.elsevier.com/locate/geb The somatic marker hypothesis: A neural theory of economic decision Antoine Bechara ∗, Antonio R. Damasio Department of Neurology, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA Received 8 June 2004 Available online 23 September 2004 Abstract Modern economic theory ignores the influence of emotions on decision-making. Emerging neuro- science evidence suggests that sound and rational decision making, in fact, depends on prior accurate emotional processing. The somatic marker hypothesis provides a systems-level neuroanatomical and cognitive framework for decision-making and its influence by emotion. The key idea of this hypothe- sis is that decision-making is a process that is influenced by marker signals that arise in bioregulatory processes, including those that express themselves in emotions and feelings. This influence can oc- cur at multiple levels of operation, some of which occur consciously, and some of which occur non-consciously. Here we review studies that confirm various predictions from the hypothesis, and propose a neural model for economic decision, in which emotions are a major factor in the interac- tion between environmental conditions and human decision processes, with these emotional systems providing valuable implicit or explicit knowledge for making fast and advantageous decisions. 2004 Elsevier Inc. All rights reserved. Introduction Modern economic theory assumes that human decision-making involves rational Bayesian maximization of expected utility, as if humans were equipped with unlim- ited knowledge, time, and information-processing power. The influence of emotions on * Corresponding author. E-mail address: [email protected] (A. -
Emotion Classification Based on Biophysical Signals and Machine Learning Techniques
S S symmetry Article Emotion Classification Based on Biophysical Signals and Machine Learning Techniques Oana Bălan 1,* , Gabriela Moise 2 , Livia Petrescu 3 , Alin Moldoveanu 1 , Marius Leordeanu 1 and Florica Moldoveanu 1 1 Faculty of Automatic Control and Computers, University POLITEHNICA of Bucharest, Bucharest 060042, Romania; [email protected] (A.M.); [email protected] (M.L.); fl[email protected] (F.M.) 2 Department of Computer Science, Information Technology, Mathematics and Physics (ITIMF), Petroleum-Gas University of Ploiesti, Ploiesti 100680, Romania; [email protected] 3 Faculty of Biology, University of Bucharest, Bucharest 030014, Romania; [email protected] * Correspondence: [email protected]; Tel.: +40722276571 Received: 12 November 2019; Accepted: 18 December 2019; Published: 20 December 2019 Abstract: Emotions constitute an indispensable component of our everyday life. They consist of conscious mental reactions towards objects or situations and are associated with various physiological, behavioral, and cognitive changes. In this paper, we propose a comparative analysis between different machine learning and deep learning techniques, with and without feature selection, for binarily classifying the six basic emotions, namely anger, disgust, fear, joy, sadness, and surprise, into two symmetrical categorical classes (emotion and no emotion), using the physiological recordings and subjective ratings of valence, arousal, and dominance from the DEAP (Dataset for Emotion Analysis using EEG, Physiological and Video Signals) database. The results showed that the maximum classification accuracies for each emotion were: anger: 98.02%, joy:100%, surprise: 96%, disgust: 95%, fear: 90.75%, and sadness: 90.08%. In the case of four emotions (anger, disgust, fear, and sadness), the classification accuracies were higher without feature selection. -
Mechanisms in Risky Choice Framing
Mechanisms in Risky Choice Framing Affective Responses and Deliberative Processing Liva Jenny Martinussen Master of Philosophy in Psychology, Cognitive Neuroscience Department of Psychology University of Oslo April 2016 II Mechanisms in Risky Choice Framing: Affective Responses and Deliberative Processing By Liva Jenny Martinussen Department of Psychology UNIVERSITY OF OSLO III © Liva Jenny Martinussen 2016 Mechanisms in Risky Choice Framing: Affective responses and Deliberative Processing Author: Live Jenny Martinussen http://www.duo.uio.no/ IV Summary Author: Liva Jenny Martinussen Supervisors: Anine Riege (Supervisor) and Unni Sulutvedt (Co-Supervisor) Title: Mechanisms in Risky Choice Framing: Affective Responses and Deliberative Processing Background: The risky choice framing effect is a decision making bias, where people tend to be risk-averse when options are presented as gains and risk-seeking when options are presented as losses, although the outcomes are objectively equivalent. The mechanisms involved in risky choice framing effects are still not fully understood. Several individual differences are assumed to moderate the processing of framing tasks and the magnitude of framing effects. Objectives: The aim of the current study was to investigate the framing effect across six framing task in a within-subject design, and explore whether gain and loss frames were associated with different levels of affective responses and deliberative processing. An additional aim was to investigate how individual differences in emotion management ability and numeracy affected performance and processing of framing tasks. Method: The study was an independent research project and the author collected all the data. Eye-tracking technology was employed; number of fixations, duration of fixations, repeated inspections of options and pupil dilations were recorded from 80 predominantly young adults while performing on six framing tasks. -
Somatic Markers, Working Memory, and Decision Making
Cognitive, Affective, & Behavioral Neuroscience 2002, 2 (4), 341-353 Somatic markers, working memory, and decision making JOHN M. HINSON, TINA L. JAMESON, and PAUL WHITNEY Washington State University, Pullman, Washington The somatic marker hypothesis formulated by Damasio (e.g., 1994; Damasio, Tranel, & Damasio, 1991)argues that affectivereactions ordinarily guide and simplify decision making. Although originally intended to explain decision-making deficits in people with specific frontal lobe damage, the hypothe- sis also applies to decision-making problems in populations without brain injury. Subsequently, the gambling task was developed by Bechara (Bechara, Damasio, Damasio, & Anderson, 1994) as a diag- nostic test of decision-making deficit in neurological populations. More recently, the gambling task has been used to explore implications of the somatic marker hypothesis, as well as to study suboptimal de- cision making in a variety of domains. We examined relations among gambling task decision making, working memory (WM) load, and somatic markers in a modified version of the gambling task. In- creased WM load produced by secondary tasks led to poorer gambling performance. Declines in gam- bling performance were associated with the absence of the affective reactions that anticipate choice outcomes and guide future decision making. Our experiments provide evidence that WM processes contribute to the development of somatic markers. If WM functioning is taxed, somatic markers may not develop, and decision making may thereby suffer. One of the most consistent challenges of daily life is & Damasio, 2000). That is, decision making is guided by the management of information in order to continually the immediate outcomes of actions, without regard to what make decisions about courses of action. -
Hybrid Approach for Emotion Classification of Audio Conversation Based on Text and Speech Mining
Available online at www.sciencedirect.com ScienceDirect Procedia Computer Science 46 ( 2015 ) 635 – 643 International Conference on Information and Communication Technologies (ICICT 2014) Hybrid Approach for Emotion Classification of Audio Conversation Based on Text and Speech Mining a, a b Jasmine Bhaskar * ,Sruthi K , Prema Nedungadi aDepartment of Compute science , Amrita University, Amrita School of Engineering, Amritapuri, 690525, India bAmrita Create, Amrita University, Amrita School of Engineering, Amritapuri, 690525, India Abstract One of the greatest challenges in speech technology is estimating the speaker’s emotion. Most of the existing approaches concentrate either on audio or text features. In this work, we propose a novel approach for emotion classification of audio conversation based on both speech and text. The novelty in this approach is in the choice of features and the generation of a single feature vector for classification. Our main intention is to increase the accuracy of emotion classification of speech by considering both audio and text features. In this work we use standard methods such as Natural Language Processing, Support Vector Machines, WordNet Affect and SentiWordNet. The dataset for this work have been taken from Semval -2007 and eNTERFACE'05 EMOTION Database. © 20152014 PublishedThe Authors. by ElsevierPublished B.V. by ElsevierThis is an B.V. open access article under the CC BY-NC-ND license (Peer-reviewhttp://creativecommons.org/licenses/by-nc-nd/4.0/ under responsibility of organizing committee). of the International Conference on Information and Communication PeerTechnologies-review under (ICICT responsibility 2014). of organizing committee of the International Conference on Information and Communication Technologies (ICICT 2014) Keywords: Emotion classification;text mining;speech mining;hybrid approach 1. -
The Law of Implicit Bias
The Law of Implicit Bias Christine Jolls† Cass R. Sunstein†† Considerable attention has been given to the Implicit Association Test (IAT), which finds that most people have an implicit and unconscious bias against members of traditionally disadvantaged groups. Implicit bias poses a special challenge for antidiscrimination law because it suggests the pos- sibility that people are treating others differently even when they are un- aware that they are doing so. Some aspects of current law operate, whether intentionally or not, as controls on implicit bias; it is possible to imagine other efforts in that vein. An underlying suggestion is that implicit bias might be controlled through a general strategy of “debiasing through law.” Introduction Consider two pairs of problems: 1A. A regulatory agency is deciding whether to impose new restric- tions on cloning mammals for use as food. Most people within the agency believe that the issue is an exceedingly difficult one, but in the end they support the restrictions on the basis of a study suggesting that cloned mammals are likely to prove unhealthy for human consumption. The study turns out to be based on palpable errors. 1B. A regulatory agency is deciding whether to impose new restric- tions on cloning mammals for use as food. Most people within the agency believe that the issue is an exceedingly difficult one, but in the end they support the restrictions on the basis of a “gut feeling” that cloned mammals are likely to be unhealthy to eat. It turns out that the “gut feeling,” spurred Copyright © 2006 California Law Review, Inc. -
It's Complicated: a Literature Review of Happiness and the Big Five
Bengtson 1 Lilly Bengtson PSYC330 It’s Complicated: A Review of Literature on Happiness and the Big Five One of the great quests of an individual’s life is often to find happiness. But what does “happiness” mean? Can it even be “found?” These questions and more have been addressed with the growth of the positive psychology movement, a modern attempt to examine happiness from a scientific perspective. A natural first step in the study of happiness is evaluating exactly who is happy, and why. While a great many factors influence one’s satisfaction with life, personality is an especially relevant contributor to consider. Personality factors influence how people see the world, how they behave, and how they move through life, so it follows that these same factors would strongly influence one’s ultimate failure or success in achieving happiness. The Five Factor model of personality is a tried-and-true trait model which breaks personality down into five basic components: extraversion, openness, conscientiousness, agreeableness, and neuroticism. This empirically-validated model has been combined with the relatively recent positive psychology movement to study how personality traits affect individuals’ overall happiness. The Big Five traits of neuroticism and extraversion have been shown to correlate strongly with measures of individual happiness, but this effect is moderated by both internal and external factors of an individual’s life circumstances. In order to study the relationship between personality traits and happiness, one must first establish exactly how to evaluate this concept. A common measure for happiness is subjective well-being, which can be broken down into individual scales of life satisfaction, positive affect, and negative affect.