Do we just "Google" it?
The United Kingdom's Department for Education (DoFE) has been advocating for a knowledge-rich national curriculum (NC) in recent years, an increased shift known to be specifically championed by former Education Secretary Michael Gove. This focus on long-term memory and the accumulation of factual knowledge continues to spark discussions about assessment practices, educational equality, and its dichotomy against modern day information access in the world of "just Google it". Do we really need to remember all these facts if we can access them just as quickly without knowing them?
Proponents argue that acquiring a broad base of factual knowledge across various subjects is essential for building a strong foundation for future learning and critical thinking. Ian Warwick from London GTi points out,
the knowledge-rich curriculum has a stable base of generalised knowledge for learning that has to be prior to learning complex skills as an adult.
Cognitive psychology research supports this idea, emphasising the importance of prior knowledge in facilitating the acquisition of new information and skills (Willingham, 2009).
However, the emphasis on a knowledge-rich curriculum has also raised concerns about assessments that feed off these practices in schools, potentially causing increased stress and anxiety in students, which is among the highest it's ever been for decades. If not handled with proper care, this could be further negatively fuelled by AI marking that can mark assessments on-demand at low cost, virtually instantly formulating the use of continuous high-stakes assessment. While this could accumulate vast data assessment sets on students and more efficiently design relevant modular courses, even at the GCSE level, it's hard to imagine students being happy with this constant high-stakes testing, even if it's for the better of their future selves.
Discussing the curriculum
The Rt Hon Michael Gove served as Secretary of State for Education from May 2010 until July 2014.
Critics of high-stakes knowledge-rich standardised testing argue that an overemphasis on standardised assessment may neglect the importance of skills-based learning and in-person assessment, limiting students' potential to showcase their merit in all forms, free from guidelines fostering creativity and purpose. These forms of assessment, while more challenging and costly to implement, provide valuable insights into a student's ability to apply knowledge in practical settings.
Having AI (Artificial Intelligence) in assessment could also be the holy grail as well as the reaper of assessment, delivering the potential for mass holistic assessment like gamified assessment or video-based assessments where students can upload a video of them explaining a subject instead of relying on anxiety-inducing exam halls. Gamification in assessment has been shown to increase student engagement and motivation (Dicheva et al., 2015), while video-based assessments can provide a more authentic and contextualised evaluation of student understanding (Shute et al., 2016).
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The DoFE's push for more reliable and objective knowledge-based assessment methods, like keyword tracking in science questions or key fact recall in history, is partly to increase accountability for schools and the spread of students' grade scores. This negatively impacts their mental health and doesn't necessarily result in better assessment, only more effort and practices designed around how to take exams.
Addressing educational equality requires a comprehensive approach that considers factors beyond the classroom, such as access to quality early childhood education, family support, and community resources. Research has consistently shown that early childhood education plays a crucial role in laying the foundation for future academic success (Heckman, 2011), while family and community support can help mitigate the effects of socio-economic disadvantage (Epstein, 2011).
As the debate continues, it is crucial to strike a balance between the acquisition of knowledge, the development of skills, and the use and deployment of technology in assessment. Standardised assessment tools should not come at the expense of fostering critical thinking, creativity, and practical application. Instead of standardising tests, we should standardise the AI that assesses the test and variabilise the tests, making them more engaging than the lessons with dynamic questions, videos, 3D modeling, and access to certain resources with a table of every possible weighted keywords relevant to the question that can be mapped so that there is no more "losing" of marks due to not using the right keyword. This idea of consistent holistic AI assessment aligns well if used iteratively with the right concept called "assessment for learning" (Black & Wiliam, 1998), which emphasises the use of assessment to support student learning and provide meaningful feedback in a tight iterative loop to maximise progression in students.
In conclusion, the knowledge-rich curriculum and its associated assessment practices have sparked a complex debate about the future of education and related qualification infrastructure in the UK. By engaging in open and constructive dialogue, educators, policymakers, and stakeholders can work together to develop a curriculum and assessment framework that prepares students for success while promoting fairness and inclusivity in the education system. Ultimately, the goal should be to create an education system that nurtures the potential of all students, regardless of their background, and equips them with the knowledge, skills, and values needed to thrive in an increasingly complex and interconnected world.
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References
- Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5(1), 7–74.
- Dicheva, D., Dichev, C., Agre, G., & Angelova, G. (2015). Gamification in education: A systematic mapping study. Journal of Educational Technology & Society, 18(3), 75–88.
- Epstein, J. L. (2011). School, family, and community partnerships: Preparing educators and improving schools. Routledge.
- Heckman, J. J. (2011). The economics of inequality: The value of early childhood education. American Educator, 35(1), 31.
- Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson Education.
- Shute, V. J., Leighton, J. P., Jang, E. E., & Chu, M. W. (2016). Advances in the science of assessment. Educational Assessment, 21(1), 34–59.
- Sirin, S. R. (2005). Socioeconomic status and academic achievement: A meta-analytic review of research. Review of Educational Research, 75(3), 417–453.
- Willingham, D. T. (2009). Why don't students like school? A cognitive scientist answers questions about how the mind works and what it means for the classroom. John Wiley & Sons.
