RESEARCH ARTICLE
Development of a Personalized Web-based Educational Program for Scientific Researchers’ Cognitive bias Regulation
Sangwoo Bae1 , Eunju Park2 , Minsu Ha2*
1Seogang University
2Kangwon National University
Correspondence to msha@kangwon.ac.kr
Brain, Digital, & Learning. Volume 12, Number 3, 387–402, September 2022. https://doi.org/10.31216/BDL.20220024
Received on September 2, 2022, Revised on September 16, 2022, Accepted on September 19, 2022, Published on September 30, 2022.
Copyright © 2022. Institute of Brain based Education, Korea National University of Education This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Cognitive bias, which is habitual thinking resulting from human experience, has a variety of implications on scientific study. In the meanwhile, several ways for correcting cognitive bias have been investigated, but there is a limit to eliciting a change in long-held beliefs by a unilateral delivery mechanism, typically a one-time group education or training session. Therefore, the purpose of this study is to design a web-based application that focuses on cognitive biases that can influence the thought processes and scientific research of scientists by addressing the shortcomings of the existing de-cognitive bias correction approach. To this purpose, cognitive biases that can influence scientific thought and research are divided into categories such as “identifying ideas”, “selecting ideas”, “generating ideas”, “evaluating ideas”, and “transforming ideas”, and a self-assessment questionnaire was created. After logging into the website program and completing a survey, participants can receive data that has been designed for they based on the survey findings, monitor their own learning progress with regular notifications, and modify their way of thinking naturally by submitting feedback. For this program, the ‘nudge’ technique was used. This program’s front end was made with Next.js and distributed with vecel, while the back end was created with Firebase. After a pilot test, the viability of the program will be demonstrated, and scientists will be informed.
Keywords
Cognitive bias, cognitive bias regulation, KAAR model, nudge effect, personalized web-based program