Assessing Creative Projects in K-12 Education: Embracing Teacher Collaboration and Comparative Judgement

Lubna Khan
2 min readJun 17, 2024

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In today’s rapidly evolving educational landscape, fostering creativity and innovation has become a paramount goal. Encouraging students to engage in creative projects not only nurtures their imagination and critical thinking skills but also prepares them for the challenges of the 21st century. However, assessing these projects poses unique challenges, and traditional assessment methods, such as rubrics, often fall short.

Rubrics can be overly prescriptive, subjective, and fail to promote consistency across classrooms and educators. Through moderation, educators can engage in meaningful discussions, share perspectives, and calibrate their understanding of what constitutes high-quality creative work. Collaboration between teachers fosters a shared understanding of assessment criteria and promotes consistency in evaluation.

Comparative judgement, an emerging assessment method, involves comparing two pieces of student work side-by-side and making a holistic judgement about which one better demonstrates the desired qualities. By repeatedly making these comparisons, a rank order of student work emerges, providing a fair and reliable assessment of creative projects. This is an emerging assessment technique particularly suited for the assessment of hard-to-assess subjects and skills. Comparative Judgement encourages holistic evaluation of creative work by minimising biases and subjectivity and promoting consistent assessment across educators.

Embracing a collaborative mindset and adopting newer approaches to assessment , such as the comparative judgement approach to assessing creative projects not only enhances the fairness and reliability of the assessment process but also creates opportunities for professional growth and shared understanding among educators.

References:

[1] Pollitt, A. (2012). Comparative judgement for assessment. International Journal of Technology and Design Education, 22(2), 157–170.

[2] Wiliam, D. (2018). Embedded formative assessment. Solution Tree Press.

[3]Wyatt-Smith, C. M., & Klenowski, V. (2013). Explicit, inferred, and invisible criteria: Implications for assessment. Curriculum Studies, 45(1), 16–33.

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Lubna Khan

Data Specialist, Educationalist, AI enthusiast, lifelong learner.