Roadblocks to Scientific Thinking in Educational Decision Making

2008 ◽  
Vol 32 (1) ◽  
pp. 125-137 ◽  
Author(s):  
Gregory C. R. Yates
Keyword(s):  
Decision Making ◽  
Scientific Reasoning ◽  
Cognitive Biases ◽  
Theory Change ◽  
Scientific Data ◽  
Evidence Based Practices ◽  
Research Findings ◽  
Secured Data ◽  
The Relationship ◽  
Biases And Heuristics

Principles of scientific data accumulation and evidence‐based practices are vehicles of professional enhancement. In this article, the author argues that a scientific knowledge base exists descriptive of the relationship between teachers’ activities and student learning. This database appears barely recognised however, for reasons including (a) the scientific tradition may not be seen as an appropriate basis for humanistic decision making; (b) personal observations can override impersonal statistics; (c) alternative frames, such as postmodernism, may contribute towards an anti‐science stance; (d) qualitative research may be viewed as representing a sampled universe; (e) educational theorising thrives upon dichotomisations which cannot be mapped against objectively‐secured data; and (f) individuals are relatively unable to undertake the mental processes demanded of theory change. The author also discusses the distinction between scientific reasoning and everyday cognition, as illustrated by research findings into cognitive biases and heuristics.

Cognitive Bias and its Relationship to Decision Making: the Case of Talented Secondary Students in Jeddah: الانحياز المعرفي وعلاقته باتخاذ القرار لدى عينة من طالبات المرحلة الثانوية الموهوبات بمدينة جدة

2020 ◽  
Vol 4 (45) ◽  
Author(s):  
Dalal Hamid Al-Dhahri, Arwa Abdullah Al-Ghamdi, Mogeda El-Sa
Keyword(s):  
Decision Making ◽  
Secondary Students ◽  
Cognitive Bias ◽  
Random Sampling ◽  
Cognitive Biases ◽  
School Administration ◽  
High Level ◽  
The Relationship ◽  
Descriptive Method

This study aims at investigating the relationship between cognitive biases and decision making from a sample of gifted secondary students. It also aims at identifying the level of students’ cognitive biases and decision making and the differences in these two areas based on different classrooms. Random sampling was used to collect data from 139 female secondary students from the gifted group. Their age ranged between (16-18) with an average of (16.6), A descriptive method was adopted in the study. The research tools used consisted of DACOBS David Assessment of Cognitive biases Scale (Vander Gaag. et al., 2000), translated and standardized by the present researchers, and Tuistra’s decision making scale for teenagers (Tuinstra, et al., 2000). The findings of the study show a negative correlation between cognitive biases and decision making. Also, there were no differences between cognitive biases and decision making scores based on different classrooms. The study also shows a low level of students’ cognitive biases and a high level of decision making. The study recommends activating the role of mentors and students' counseling, planning for the values and behaviors that need to be acquired by students by including them in the annual goals of the school administration and participating in societal awareness and education.

scholarly journals Why Does Privacy Paradox Exist?

2022 ◽  
Vol 20 (1) ◽  
pp. 1-20
Author(s):  
Sakhhi Chhabra
Keyword(s):  
Decision Making ◽  
Grounded Theory ◽  
Mobile Computing ◽  
Learned Helplessness ◽  
Exploratory Study ◽  
Cognitive Biases ◽  
Mobile Users ◽  
Privacy Paradox ◽  
Biases And Heuristics ◽  
Depth Interviews

In this exploratory study, the main aim was to find, ‘why do people disclose information when they are concerned about their privacy?’. The reasons that provide a plausible explanation to the privacy paradox have been conjectural. From the analysis of the eighteen in-depth interviews using grounded theory, themes were then conceptualized. We found rational and irrational explanations in terms of cognitive biases and heuristics that explain the privacy paradox among mobile users. We figured out some reasons in this context of mobile computing which were not emphasized earlier in the privacy paradox literature such as Peanut Effect, Fear of Missing Out- FoMo, Learned Helplessness, and Neophiliac Personality. These results add to the privacy paradox discourse and provide implications for smartphone users for making privacy-related decisions more consciously rather than inconsiderately disclosing information. Also, the results would help marketers and policymakers design nudges and choice architectures that consider privacy decision-making hurdles.

Innovation, Ethics, and Consumer Protection

2021 ◽  
pp. 208-224
Author(s):  
Sandrine Prom Tep ◽  
Maya Cachecho ◽  
Évelyne Jean-Bouchard
Keyword(s):  
Decision Making ◽  
Social Networks ◽  
Cognitive Biases ◽  
Law And Economics ◽  
Legal Issues ◽  
Minimum Requirements ◽  
Decision Making Processes ◽  
Ethical And Legal Issues ◽  
Behavioral Law And Economics ◽  
The Relationship

In recent years, firms that rely on fintech to develop and deliver financial products and services have become increasingly important in the banking and financial sector. Nevertheless, fintech products raise various ethical and legal issues, particularly relating to consumer rights. These issues can be analyzed in the light of behavioral law and economics which suggest that prevalent cognitive biases systematically affect the judgment of individuals. To mitigate this bounded rationality, it is possible to guide the decision-making processes through the use of nudges and configured sets of choices. A good example is fintech gamification, defined as the use of game-related mechanisms in other areas, particularly websites or social networks. However, the use of nudges for commercial purposes is often associated with some form of manipulative tactics explicitly aimed at exploiting individuals' biases without their consent. In this context, recourse to the law is useful as it provides for the minimum requirements needed to regulate the relationship between a firm and its customers.

scholarly journals CUSTOMER BEHAVIOR AND DECISION MAKING IN THE REFURBISHMENT INDUSTRY‐A DATA MINING APPROACH

2010 ◽  
Vol 16 (1) ◽  
pp. 75-84 ◽  
Author(s):  
Chung-Fah Huang ◽  
Sung-Lin Hsueh
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Consumer Behavior ◽  
Customer Behavior ◽  
Business Operation ◽  
Data Mining Approach ◽  
Selection Behavior ◽  
Research Findings ◽  
Firm Selection ◽  
The Relationship

The study of consumer behavior in the refurbishment industry is crucial to the business operation of firms, but there is a lack of research in this regard. With reference to the EKB model specific to consumer behavior, this paper discusses the relationship among consumption characteristics, firm selection behavior and satisfaction degree of refurbishment customers. 242 valid questionnaire copies were collected from refurbishment customers, and analyzed using Decision Tree Analysis and Association Rules in Data Mining. The research results show that, over half of the customers tend to entrust the refurbishment to well‐reputed firms. Moreover, the integrity of refurbishment equipment, response of refurbishment personnel, professionalism and confidence are key elements in service quality (SQ). The best marketing policy for the customers is one which provides more attractive services. These research findings may provide a useful reference for innovative refurbishment firms in their decision‐making. Santrauka Vartotoju elgsena, tiriant atnaujinima, yra labai svarbi verslo imoniu veiklai, tačiau stinga šiuo klausimu atliktu tyrimu. Remiantis EKB (Engel‐Kollat‐Blackwell) konkrečiu vartotoju elgsenos modeliu, straipsnyje aptariami ryšiai tarp vartojimo charakteristiku, imones pasirinkimo elgsenos ir atnaujinimo vartotoju ivertinimo laipsnio. Surinktos 242 galiojančios atsinaujinančiu vartotoju apklausos, kurios buvo nagrinejamos taikant sprendimu priemimo medi ir ryšiu taisykles gaunant duomenis. Tyrimu rezultatai rodo, kad daugiau kaip puse vartotojuyra linke patiketi atnaujinima žinomoms imonems. Dar daugiau, pagrindiniai elementai, užtikrinantys paslaugu kokybe (PK) ir atnaujinimo vientisuma, yra atnaujinančio personalo reakcija, jo profesionalumas ir pasitikejimas juo. Geriausia vartotoju rinkodaros politika ta, kuri suteikia daugiau patraukliu paslaugu. Šiu tyrimu rezultatai gali suteikti naudingos informacijos novatoriškoms atnaujinimo imonems ir ju sprendimams.

scholarly journals Initial evidence for biased decision-making despite human-centered AI explanations

2021 ◽  
Author(s):  
Nicolas Scharowski ◽  
Florian Brühlmann
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Cognitive Biases ◽  
Ongoing Debate ◽  
Explainable Artificial Intelligence ◽  
Decision Making Processes ◽  
Financial Decision ◽  
Biases And Heuristics ◽  
User Trust ◽  
Initial Price

In explainable artificial intelligence (XAI) research, explainability is widely regarded as crucial for user trust in artificial intelligence (AI). However, empirical investigations of this assumption are still lacking. There are several proposals as to how explainability might be achieved and it is an ongoing debate what ramifications explanations actually have on humans. In our work-in-progress we explored two posthoc explanation approaches presented in natural language as a means for explainable AI. We examined the effects of human-centered explanations on trust behavior in a financial decision-making experiment (N = 387), captured by weight of advice (WOA). Results showed that AI explanations lead to higher trust behavior if participants were advised to decrease an initial price estimate. However, explanations had no effect if the AI recommended to increase the initial price estimate. We argue that these differences in trust behavior may be caused by cognitive biases and heuristics that people retain in their decision-making processes involving AI. So far, XAI has primarily focused on biased data and prejudice due to incorrect assumptions in the machine learning process. The implications of potential biases and heuristics that humans exhibit when being presented an explanation by AI have received little attention in the current XAI debate. Both researchers and practitioners need to be aware of such human biases and heuristics in order to develop truly human-centered AI.

scholarly journals Womens Education and Empowerment in Islamabad, Pakistan

2020 ◽  
Vol V (I) ◽  
pp. 50-62
Author(s):  
Sarfraz Khan ◽  
Syed Imran Haider ◽  
Saadia
Keyword(s):  
Decision Making ◽  
Research Study ◽  
Daily Life ◽  
University Graduates ◽  
University Teachers ◽  
Freedom Of Movement ◽  
The Family ◽  
Research Findings ◽  
The Relationship ◽  
Selection Of

The present research study was conducted in two public sector universities in Islamabad, Pakistan to explore the relationship between womens education and empowerment. In this research we have looked at the five major dimensions of the womens empowerment in conjunction with education i.e. (1) freedom of movement, (2) economic activism, familial and social affairs (3) freedom from domination and support by the family, (4) decision-making in daily life, and (5) political participation and community engagement. The data was collected from 30 female respondents (15 university teachers and 15 recently passed-out university graduates). The selection of the respondents was made through purposive sampling but with a special inclusion criterion. Based on the research findings, we can suggest that higher levels of education could positively be associated with the higher levels of womens empowerment.

Personality Traits and Cognitive Biases

2018 ◽  
pp. 133-163
Keyword(s):  
Decision Making ◽  
Personality Traits ◽  
Cognitive Style ◽  
Big Five ◽  
Cognitive Biases ◽  
The Other ◽  
Personality Theory ◽  
Strong Impact ◽  
Other Hand ◽  
The Relationship

Personality plays an important role in determining one's cognitive style, having a strong impact on the decision making of each person. Personality is a set of traits and qualities that form how somebody is, and it distinguishes us from others. At present, the most widely accepted personality theory is the big five factor, where personality is divided into five large traits: openness, conscientiousness, extraversion, agreeableness, and neuroticism. These traits are independent of each other. On the other hand, several personality traits have been more strongly associated with psychopathology. Therefore, personality traits would be related to the production of several cognitive biases in all people because personality influences our own beliefs, and these can guide us to display certain types of biases. This chapter delves into the relationship between personality traits (especially openness, neuroticism, extroversion, and schizotypy) and cognitive biases.

scholarly journals Confirmation Bias Estimation from Electroencephalography with Machine Learning

2019 ◽  
Vol 63 (1) ◽  
pp. 73-77
Author(s):  
Micah N. Villarreal ◽  
Alexander J. Kamrud ◽  
Brett J. Borghetti
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Cognitive Biases ◽  
Confirmation Bias ◽  
Supervised Machine Learning ◽  
Bias Estimation ◽  
Human Decision ◽  
Behavioral Evidence ◽  
Post Hoc ◽  
The Relationship

Cognitive biases are known to affect human decision making and can have disastrous effects in the fast-paced environments of military operators. Traditionally, post-hoc behavioral analysis is used to measure the level of bias in a decision. However, these techniques can be hindered by subjective factors and cannot be collected in real-time. This pilot study collects behavior patterns and physiological signals present during biased and unbiased decision-making. Supervised machine learning models are trained to find the relationship between Electroencephalography (EEG) signals and behavioral evidence of cognitive bias. Once trained, the models should infer the presence of confirmation bias during decision-making using only EEG - without the interruptions or the subjective nature of traditional confirmation bias estimation techniques.

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