The importance of assessment can be seen in various fields, including employment and healthcare because evaluating a person’s skills and abilities is what assessments are designed for. Fairness and objectivity in assessments may not always prevail due to the influence of biases, which could skew the results. The presence of biases in assessments can result in inaccuracies that could lead to serious consequences of job rejection or lower IQ levels of social inequality. This report will discuss in-depth ways to avoid assessment biases, and the objective of my study is to scrutinize the predispositions in IQ tests—a popular measurement tool for evaluating one’s general mental aptitude.
Bias in IQ Testing
IQ testing is a common way to assess general intelligence, and for decades IQ testing has been a controversial subject, with numerous concerns raised regarding its validity and fairness. The presence of bias in IQ tests is a significant concern because IQ tests measure specific cognitive capabilities that play a significant role in achieving academic and professional success. There is an argument among some individuals that the tests could be culturally biased and, therefore, may not accurately represent the abilities of people with varying cultural and socioeconomic backgrounds.
A primary worry with IQ testing is cultural bias within its test items because knowledge of Western history, literature, and art is often required in IQ tests due to their association with the dominant culture. This problem can lead to variations in the average test performance of diverse ethnic groups and growth in a non-Western culture can lead to different knowledge and experiences compared to growth in a Western culture. Even with equivalent levels of cognitive ability to their Western counterparts, individuals from non-Western backgrounds may still receive lower test scores.
According to Cambridge University Press (2020), bias is present in the testing if two people with similar skills but come from diverse demographic backgrounds get distinct results on an exam because of their association with that particular group. Henceforth, detecting bias in examinations necessitates examining differences that manifest themselves amongst these comparable groups who communicate using their first language and have become accustomed to living in this nation. The relevance of average score differences should not be dismissed. Psychologists must look into possible test biases when presented with such indicators because these elements cannot demonstrate whether a test has any partiality.
IQ testing has the potential for the test items to show a linguistic bias because IQ exams will frequently assess a person’s vocabulary, reading comprehension, and verbal reasoning. Even though they possess the same level of cognitive ability as native English speakers, individuals from non-native backgrounds might encounter difficulties in mastering these skills; however, lower test scores are possible for individuals from non-native English-speaking backgrounds despite having similar cognitive abilities to native English speakers.
Avoiding Bias in IQ Testing
To guarantee fairness in IQ testing, it is crucial to develop tests that do not show cultural or linguistic bias. Utilizing a diverse group of individuals to create and take tests can help achieve this. Cultural and linguistic fairness of test items can be ensured by having a diverse group of test creators from different cultural and linguistic backgrounds, and the representation of the population in the test results can be ensured by having test takers from various cultural and linguistic backgrounds.
One can also avoid bias in IQ testing by using alternative assessment tools that are less culturally and linguistically biased. Moreover, The Assessment of Children’s Thinking (ACT) and other performance-based evaluations measure cognitive abilities by utilizing problem-solving tasks minimally dependent on language skills. One must consider using performance-based assessments to obtain a less biased measurement of cognitive abilities than what an IQ test provides.
Another way to prevent bias is to provide a testing environment that is both fair and free from any potential distractions that could impact the test taker’s performance, and a level playing field must be established in the testing environment so as not to put any particular group at a disadvantage due to cultural or linguistic biases. To achieve this goal, avoiding using unfamiliar vocabulary and making cultural references is necessary. Also, the guidelines provided for the examination ought to be precise and easy to comprehend, and individuals who take the test must be given proper assistance to achieve their highest potential.
To guarantee the cultural and linguistic impartiality of IQ tests is still necessary, and the performance of validation studies can help ascertain if there is any bias in the test toward certain cultural or linguistic groups and furnish substantiation for its validity across different cultures and languages. The use of validation studies can aid in identifying any culturally or linguistically biased test items that need to be revised or removed to ensure a fair assessment.
Training and education are crucial for test administrators to avoid bias in IQ testing. Providing thorough training for administrators is crucial as it enables them to recognize and prevent cultural and linguistic biases while offering clear and concise directions. Moreover, they must remain sensitive to the cultural differences of the test takers. Administrators must recognize and minimize their biases to ensure fair testing practices.
For a comparison to be meaningful, tests available in different languages must measure the same construct. Difficulty in comparing both scores may arise due to non-equivalent constructs between the two test forms caused by a poor translation leading to a compromise in the validity of the test (Cecilio-Fernandes et al., 2019). Mitigating the loss of content validity through effectively reducing language barriers in assessment can lead to a fair assessment for all students. Studies have indicated that non-native English speakers may perform poorly on knowledge tests in English due to inadequate English proficiency. This can result in the test becoming a language assessment.
Students’ knowledge cannot be assessed adequately without understanding the vocabulary and linguistic structures. Therefore knowledge and English proficiency become the main factors affecting the test score. The test’s content validity is in jeopardy, according to (Cecilio-Fernandes et al., 2019). Item language bias is a specific source of item bias in research. However, blaming this bias solely on language factors may be unjustified. An additional source of bias that often accompanies different languages is cultural differences.
Consequences of Test Bias
Severe consequences can arise from test bias, leading to social inequality and discrimination. Lower test scores can result from biased assessments for individuals from certain cultural and socioeconomic backgrounds leading to job denial and social inequality. For instance, if a job needs an IQ test for employment and the test leans towards a certain cultural or linguistic group, this could lead to job rejection for individuals from other backgrounds who might possess similar cognitive abilities to those from the dominant culture.
In educational settings, biased assessments can have severe consequences. Underprivileged students may face disadvantages because they lack exposure to cultural and educational experiences reflected in assessments. Their abilities may be inaccurately assessed, reducing educational opportunities and limiting academic and career advancement.
According to Shi & Zhu’s (2021) research findings, the supposedly advantageous “positive” stereotype may have negative outcomes. Stereotyping can lead to individuals in certain groups being held to unrealistically high expectations and experiencing hindered performance. Certain academic and career paths may be restricted for stereotyped group members. Reinforcing the notion of fundamental differences across groups or bolstering negative stereotypes for under-represented minorities can cause negative effects on other minority groups through the positive stereotypes of Asians.
In addition, faulty appraisals may lead to adverse opinions of specific groups based on their exam scores, ultimately causing prejudice and inequality in society. Suppose a particular group consistently receives lower marks on an assessment due to cultural or linguistic prejudices; they can be perceived as inferior or less smart, leading to negative stereotypes and bias (Schünemann et al., 2020).
In healthcare settings, inaccurate diagnoses and treatment test bias can lead to bias in tests. If a healthcare professional uses a culturally biased assessment as an example, they may diagnose patients from certain backgrounds inaccurately or mistreat them, resulting in care that is not appropriate (Schünemann et al., 2020).
Conclusion
Evaluating an individual’s skills and knowledge necessitates using assessments. However, biases when administering assessments may cause errors in the results, leading to significant consequences of job denial or lower IQ levels and social inequality. IQ testing is a tool frequently used to assess general intelligence that has sparked controversy for decades. Lower test scores on IQ tests are frequently observed among individuals from non-Western cultures and non-native English-speaking backgrounds due to cultural and linguistic biases.
References
Cambridge University Press. (2020, October 1). Understanding bias in intelligence, academic, and cognitive tests. Cambridge Core Blog. https://www.cambridgeblog.org/2020/10/understanding-bias-in-intelligence-academic-and-cognitive-tests/#:~:text=For%20the%20testing%20industry%2C%20bias,of%20their%20demographic%20group%20membership.
Cecilio-Fernandes, D., Bremers, A., Collares, C. F., Nieuwland, W., van der Vleuten, C., & Tio, R. A. (2019). Investigating possible causes of bias in a progress test translation: a one-edged sword. Korean Journal of medical education, 31(3), 193.
Shi, Y., & Zhu, M. (2021). Model Minorities in the Classroom? Positive Bias Towards Asian Students and its Consequences. Working Paper.
Schünemann, H. J., Mustafa, R. A., Brozek, J., Steingart, K. R., Leeflang, M., Murad, M. H., … & GRADE Working Group. (2020). GRADE guidelines: 21 part 1. Study design, risk of bias, and indirectness in rating the certainty across a body of evidence for test accuracy. Journal of Clinical Epidemiology, 122, 129-141.
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