Grading vs Assessing: Is it a Meaningful Difference?
Updated: Aug 5
Grading student work has long been an integral task for teachers in the education system. For generations, teachers have spent countless hours score-marking assignments, exams, essays, and other student work, assigning letter grades or percentages based on performance. However, as discussed in this article on grading smarter from Edutopia, in recent years, there has been a major shift in focus towards prioritizing assessment over traditional paper grading.
With the rise of advanced AI solutions that enable automated grading and feedback, educators now have powerful tools to assess students in much more meaningful, multidimensional ways.
But is there truly a significant difference between grading and assessment? In this comprehensive blog post, we’ll dive deep into the key distinctions, analyze the limitations of paper grading, discuss how AI assessment tools are transforming the landscape, and make the case for why the difference is indeed meaningful in the modern digital era.
Defining Grading and Assessment
Grading is the process of a teacher examining students’ work, most commonly written assignments and tests, and assigning a numeric score or letter grade based on accuracy, completion and formatting. Once a grade is assigned, the work is handed back to the students. Grading focuses solely on the final output.
In contrast, assessment refers to systematically evaluating students’ knowledge, skill levels, mindsets and ongoing progress or learning. As explained in Carnegie Mellon University's overview of formative vs summative assessments, effective assessments incorporate diverse methods, tools and activities - not just written work.
Limitations of Over-Reliance on Traditional Paper Grading
While grading has purposes, over-reliance on paper grading has limitations:
Teachers spend significant time outside of instruction grading lengthy assignments. This Forbes article on AI grading notes it's not uncommon to spend 8-12 hours on a single class set.
Grades give no nuanced feedback on how students can improve. Students are left unsure of problem areas, as discussed in this paper on automated essay scoring from IEEE.
How AI Assessment Tools Resolve Grading Issues
Advanced AI grading and assessment platforms automate evaluation using machine learning:
They deliver instant, personalized feedback identifying students' strengths, gaps, and areas needing improvement.
AI applies consistent rules, eliminating human bias and errors.
Benefits of AI-Enabled Student Assessment
Intelligently implemented AI assessment delivers numerous benefits
Automating grading and feedback reduces teachers’ after-hours workloads, per this article on how AI saves teachers grading time.
Students receive specific feedback to focus improvement efforts, rather than just a letter grade.
AI systems provide grading recommendations, but teachers determine final grades based on their assessment.
In summary, while grading and assessment both evaluate student learning, the latter goes deeper by providing meaningful multidimensional feedback. AI solutions automate dreary grading while enhancing personalized feedback.
As this study on AI grading's impact notes, these benefits will continue growing as the technology advances. The difference between grading and AI-enhanced assessment is indeed meaningful.