Identifying and Reducing Cognitive Biases in Research
Feature article by David D. Perrodin, King Mongkut’s University of Technology Thonburi
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The primary role of a PhD student is to develop as an academic researcher. In doing so, the PhD student builds credibility and trustworthiness as a specialist in their field. It is likely that most doctoral students are genuinely interested in their chosen discipline, as was the case for the participants in Hribar and Dolinšek’s (2015) study in Slovenia. Despite this interest, the possibility of gaining better employment in their current careers was the most significant factor in deciding to pursue a doctorate. However, in the United States, Bowen and Rudenstine (2014) found that over half of the PhD students at ten leading universities failed to complete their doctoral studies. Bowen and Rudenstine, among others, have discussed fundamental issues that may interfere with pursuing a doctorate, such as anxiety, conflict with PhD supervisors, funding issues, inadequate work/life balance, lack of institutional or personal support, loneliness, problems with motivation, and time management (Naylor et al., 2016; Pyhältö et al., 2012; Wan, 2016). Although most studies have focused on the abovementioned emotional and physical challenges in the academic pursuit of a doctorate, few studies have focused on the challenging influences of biases on up-and-coming researchers.
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Biases are subtle yet ubiquitous and may emerge from internal and/or external influences. They are a faulty manner of interpreting the weight or value of information according to one’s preconceived association as an insider within a community or social unit, such as with customs, identity, norms, religion, or values (Psychology Today, 2022). Wan (2016) found that one of the most challenging aspects for developing PhD researchers is identifying and overcoming biases in research. Moreover, Pannucci and Wilkins determined that biases can appear in all stages of research, from the planning, data collection, and analysis to the final writing phases.
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One type of bias that a PhD student will encounter in their doctoral journey is cognitive bias, or our brain’s ability to recognize and favor natural processing patterns within various stimuli (Wilke & Mata, 2012). An illustration of cognitive bias is confirmation bias, or the irrational processing of information where an individual is emotionally connected to an issue or has a personal stake in a belief, faith, or opinion (Nickerson, 1998). For example, a researcher may profile certain extralocal (see below) teachers as privileged and others as marginalized due to their appearance, nationality, or ethnicity.
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My Own Experience With Research Biases
Although quite grueling, identifying and reducing cognitive biases is a rite of passage for developing PhD scholars. Take my current doctoral study, for instance. I am looking at privilege and marginalization in the working contexts, social perceptions, and self-image of ‘extralocal’ English teachers in Thailand (see Perrodin 2020, 2021a, 2021b). I define extralocal teachers as non-local teachers of English who are not citizens of the country in which they teach. They may be “native” or “non-native” speakers of English—or, to use another popular description, L1 or LX English users (see Thomas & Osment, 2019). To adequately examine privilege and marginalization within the three aspects above, I had to carefully identify biases in each phase before analyzing the data sets and then choose the most appropriate methodology to reduce biases within each. Consequently, carefully selecting the most appropriate methods will help reduce, although not eliminate, biases within the analysis of each data set.
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Firstly, identifying and reducing biases in examining specific working contexts of different positions affiliated with teaching English in Thailand required a thorough literature review. I had several discussions with extralocal teachers from diverse backgrounds about what websites they use when looking for teaching jobs in Thailand. I ventured into a three-month undertaking examining hundreds of job advertisements from the most predominantly mentioned website catering to English teachers in Thailand. The landing page promoting job advertisements for this website displayed the job title, the school's name, whether the institute was government or private, the location of the job, and the minimum salary. A careful reading of the job advertisements provided additional information concerning the desired nationality, language proficiency, gender, educational qualifications, and/or experience. Utilizing the most preferred website mentioned by the majority of extralocal teachers for information related to teaching English in Thailand reduced bias in examining working contexts of extralocal English teachers in Thailand.
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Next, identifying and reducing biases in social perceptions within the Thai society about extralocal teachers of English within Thailand was more challenging. Seeing as I am an outsider, both not Thai and not fully proficient in the Thai language, I elicited assistance in examining the opinions of Thai education stakeholders in Thai social settings. Upon completing a thorough literature review and several discussions with Thai education stakeholders (e.g., school directors, parents, students, teachers), I realized that certain Thai customs and traditions would not allow the stakeholders to offer constructive criticism of extralocal teachers straightforwardly. To overcome this obstacle, my Thai associates and I reviewed open conversations (in the Thai language) on social media platforms about extralocal teachers of English. As one of the most widely used social networks in Thailand when it comes to sharing and criticizing relevant topics, Twitter appeared to be the best platform to review social perceptions of extralocal teachers of English within Thailand.
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To reduce bias in analyzing criticisms written in Thai about extralocal teachers of English in Thailand, I elicited the services of qualified Thai academics and language translators for the over 20,000 words I accumulated while building the corpus. In reviewing other studies of this nature, I found that researchers read through translated texts and ‘discovered’ themes related to their research focus. To safeguard against my own bias in analyzing criticisms, I employed a corpus analysis application, AntConc, for concordancing and text analysis to identify themes in the Twitter messages (Anthony, 2022). The application provided the frequency of occurrences of certain content words within the Twitter messages. The basic assumption was that by analyzing the frequency of lexical words (i.e., nouns, verbs, adjectives, adverbs) within the text, a relationship between the keywords and themes within the text could be identified (Popping, 2000).
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Finally, identifying and reducing biases in the self-image of extralocal teachers of English from various nationalities was as challenging as analyzing the social perceptions within Thai society. Seeing as I am both an insider and outsider within the different social groups of extralocal teachers in Thailand, I chose to use similar methodologies for analysis of the ‘keyness’ (i.e., the degree of being ‘key’ or significant within a text) of content words from in-depth interviews to identify themes (Bondi & Scott, 2010; Graham, 2021). As with examining the social perceptions, by utilizing the above application (Anthony, 2022), I reduced my potential bias in determining themes in the transcribed text from interviews about the self-image of extralocal teachers.
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In Essence
Although studies have shown that the attrition rate for some doctorate programs is as high as 70%, these studies have mainly concentrated on the mental and physical challenges influencing the continued pursuit of a doctorate. Yet, according to several studies, acknowledging research biases is one of the most demanding elements of an emerging PhD researcher. Pursuing a costly doctorate monopolizes four or more years of a doctoral student’s time. So failing to perceive and lessen biases in research may legitimately jeopardize a student's reputation and trustworthiness in their pursuit of a career in their field of study. Therefore, along with the demand to develop as an academic researcher and build credibility and trustworthiness as a specialist in a chosen field, identifying and reducing cognitive biases should be of equal importance in developing as a PhD graduate.
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References
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Anthony, L. (2022). AntConc (Version 4.0.3) [Computer Software]. Waseda University. https://www.laurenceanthony.net/software
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Bondi, M., & Scott, M. (2010). Keyness in texts. John Benjamins Publishing Company.
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Bowen, W. & Rudenstine, N. (2014). In pursuit of the PhD. Princeton University Press. https://doi.org/10.1515/9781400862474
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Graham, D. (2021). Key-BNC (Version 2.4.0) [Computer Software]. King Mongkut’s University of Technology Thonburi. https://key-bnc.tfiaa.com
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Hribar T., & Dolinšek, S. (2015). Choice Patterns of PhD Students: Why should I pursue a PhD? In E. Henriksen, J. Dillon, & L. Ryder (Eds)., Understanding student participation and choice in science and technology education. Springer. https://doi.org/10.1007/978-94-007-7793-4_11
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Naylor, R., Chakravarti, S., & Baik, C. (2016). Differing motivations and requirements in PhD student cohorts: A case study. Issues in Educational Research, 26(2), 351–367. https://www.iier.org.au/iier26/naylor.pdf
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Nickerson, R. S. (1998). Confirmation Bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175–220. https://doi.org/10.1037/1089-2680.2.2.175
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Pannucci, C. J., & Wilkins, E. G. (2010). Identifying and avoiding bias in research. Plastic and Reconstructive Surgery, 126(2), 619–625. https://doi.org/10.1097/prs.0b013e3181de24bc
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Perrodin, D. D. (2020). The constructs of privilege and marginalization subjectively experienced by extralocal teachers of English in Thailand. Mahidol Migration Center Newsletter, 7, 16. http://www.migrationcenter.mahidol.ac.th/download_newsletter/MMC_Newsletter_Vol.7.pdf
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Perrodin, D. D. (2021a). Aspirations of creating one homogenous group of extralocal teachers of English. The Educators' Link, 1(4), 226.
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Perrodin, D. D. (2021b). Extralocal! Extralocal! Read All About It! EFL Magazine. https://eflmagazine.com/extralocal-extralocal-read-all-about-it/
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Popping, R. (2000). Thematic text analysis. In Computer-assisted text analysis (pp. 39-66). SAGE Publications, Ltd, https://www.doi.org/10.4135/9781849208741
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Psychology Today. (2022). Bias. https://www.psychologytoday.com/us/basics/bias
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Pyhältö, K., Toom, A., Stubb, J., & Lonka, K. (2012). Challenges of becoming a scholar: A study of doctoral students’ problems and well-being. ISRN Education, 2012, 1–12. https://doi.org/10.5402/2012/934941
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Thomas, N., & Osment, C. (2019). Building on Dewaele’s (2018) L1 versus LX Dichotomy: The Language-Usage-Identity State Model. Applied Linguistics, 41(6), 1005–1010. https://doi.org/10.1093/applin/amz010
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Wan, C. D. (2016). Positional challenges and advantages of a PhD student researching the PhD. The Qualitative Report, 21(7), 1193–1202. https://doi.org/10.46743/2160-3715/2016.2411
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Wilke, A., & Mata, R. (2012). Cognitive Bias. In V. S. Ramachandran (Ed.), Encyclopedia of Human Behavior (2nd ed., pp. 531–535). Academic Press. https://doi.org/10.1016/B978-0-12-375000-6.00094-X
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David D. Perrodin is a Foreign Expert, and Journal Manager for the Journal of Population and Social Studies (JPSS), with the Institute for Population and Social Research (IPSR), Mahidol University. He is pursuing a Ph.D. in Applied Linguistics for English Language Teaching at King Mongkut’s University of Technology Thonburi.