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Collating Student Learning Information: Ethical Considerations Part 1

“Bias is any trend or deviation from the truth in data collection, data analysis, interpretation and publication which can cause false conclusions. Bias can occur either intentionally or unintentionally. Intention to introduce bias into someone’s research is immoral.” Simundic, 2013.

In educational assessments, bias can have significant implications for the fairness, accuracy and effectiveness of the evaluation process. Educators must remain impartial and not let their preconceptions influence the results or, indeed, the delivery of assessments.  An assessment method can be biased towards a particular socioeconomic, cultural or linguistic background, particularly where access is not equitable.  The way that children whose first language is other than English, for example, are assessed is important. If the assessment is conducted in English, the results may differ from if it was conducted in their first language, thus, providing a misleading picture of their actual skills.

Campbell, 2015, found that teacher’s stereotypes of primary-aged childrenexist and that the resulting bias affects the child’s assessment results.

KneoWorld supports all students. Their curriculum’s data-driven analytics provide insights to easily implement learning experiences as unique as each student. You can see how KneoWorld can support your school in this way by booking a demonstration.

Educators must consider the needs of their students They must make a professional decision on which assessment tools to use that are appropriate for the individual child to ensure that every child has an equitable opportunity to demonstrate their skills.. 

Assessment tools that are influenced by any form of bias can ultimately compromise the validity of the results, resulting in misinterpretation and misclassification of a child’s abilities, skills and knowledge. By actively addressing and mitigating bias in learning assessments, educators and policymakers can contribute to creating a more inclusive and equitable educational environment.

 

References

American Psychological Association (no date) Children, youth, families and socioeconomic status, American Psychological Association. Available at: https://www.apa.org/pi/ses/resources/publications/children-families (Accessed: 23 December 2023).

Campbell, T. (2015) Stereotyped at Seven? Biases in Teacher Judgement of Pupils’ Ability and Attainment. Journal of Social Policy, 44:3, pp 517-547. http://dx.doi.org/10.1017/S0047279415000227

 DeCarlo Santiago, C., Wadsworth, M. E., & Stump, J. (2011). Socioeconomic status, neighborhood disadvantage, and poverty-related stress: Prospective effects on psychological syndromes among diverse low-income families. Journal of Economic Psychology, 32, 218-230. https://doi.org/10.1016/j.joep.2009.10.008

Porath, Marion. (1996). Affective and motivational considerations in the assessment of gifted learners. Roeper Review. 19. 13-17. 10.1080/02783199609553775.

Russell, A. E., Ford, T., Williams, R., & Russell, G. (2016). The association between socioeconomic disadvantage and attention deficit/hyperactivity disorder (ADHD): A systematic review. Child Psychiatry and Human Development, 47, 440-458. doi:10.1007/s10578-015-0578-3

Simundić, A.-M. (2013) Bias in research, Biochemia medica. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3900086/#:~:text=Definition%20of%20bias,intentionally%20or%20unintentionally%20(1). (Accessed: 22 December 2023).

Spencer, M. S., Kohn L. P., & Woods J. R. (2002). Labeling vs. early identification: The dilemma of mental health services under-utilization among low-income African American children. African American Perspectives, 8, 1–14.