Exploring Cognitive Biases Limiting Rational Problem Solving and Debiasing Methods Using Science Education

Abstract

This study aims to explore cognitive biases relating the core competences of science and instructional strategy in reducing the level of cognitive biases. The literature review method was used to explore cognitive biases and science education experts discussed the relevance of cognitive biases to science education. Twenty nine cognitive biases were categorized into five groups (limiting rational causal inference, limiting diverse information search, limiting self-regulated learning, limiting self-directed decision making, and category-limited thinking). The cognitive biases in limiting rational causal inference group are teleological thinking, availability heuristic, illusory correlation, and clustering illusion. The cognitive biases in limiting diverse information search group are selective perception, experimenter bias, confirmation bias, mere thought effect, attentional bias, belief bias, pragmatic fallacy, functional fixedness, and framing effect. The cognitive biases in limiting self-regulated learning group are overconfidence bias, better-than-average bias, planning fallacy, fundamental attribution error, Dunning-Kruger effect, hindsight bias, and blind-spot bias. The cognitive biases in limiting self-directed decision-making group are acquiescence effect, bandwagon effect, group-think, appeal to authority bias, and information bias. Lastly, the cognitive biases in category-limited thinking group are psychological essentialism, stereotyping, anthropomorphism, and outgroup homogeneity bias. The instructional strategy to reduce the level of cognitive biases is disused based on the psychological characters of cognitive biases reviewed in this study and related science education methods.

The new ecological paradigm and attitudes towards sustainable business practices – a Mexican case study

“…Human behaviour and ways of thinking are influenced by various cultural, genetic, and neurological factors (Sapolsky, 2023). Appreciation of complexity (Sterman, 2000) and non-linearity (Lambrechts et al, 2018) and understanding cognitive biases (Ha, 2016) may be more relevant than changing mindsets. The confirmation of hypothesis 2 that the teaching intervention impacts the appreciation of substantive reasoning may indicate that the existing program possesses the potential for more intensively developing analytical skills and fostering a substantial reasoning approach for addressing sustainability challenges.…”

Assessing Cognitive Bias in Korean and Indonesian Scientists: Considering Sociocultural Factors in Judgment and Choice

“…In addition, science education also has an important role in understanding how scientists think and reason systematically (Dunbar, 2000), through scientific method. Educational programs have been suggested to reduce a potential cognitive bias among future scientists (Ha, 2016;Aini et al, 2021). This study attempts to evaluate the magnitude and consistency of cross-cultural differences in cognitive bias with a focus on two different countries in Asia with different sociocultural factors.…”

“…Benson (2016) has listed more than 150 cognitive biases that are commonly found in the research area of behavioral economics, social psychology, and cognitive science. Ha (2016) explored biases that are potentially correlated with core competencies of science and suggested instructional practice to reduce the cognitive bias. This study documented five categories of problems in science learning due to cognitive biases: limiting rational causal inference, limiting diverse information search, limiting self-regulated learning, limiting self-directed decision making, and category-limited thinking.…”

“…In general, cognitive bias related to probability and decision making ASIA-PACIFIC SCIENCE EDUCATION 8 (2022) 222-255 might significantly affect scientific activities (Aini et al, 2021). Cognitive bias is naturally formed and is a psychological attribute that interferes with rational human decision making, and cognitive bias has been shown difficult to correct in a short period of time through education (Ha, 2016;Rusmana et al, 2020).…”

“…Instrument We extended our previous work to measure cognitive biases in scientists (Aini et al, 2021;Ha, 2016;Hwang et al, 2021). First, more than 150 lists of cognitive biases and their definitions from Benson (2021) were collected.…”