As school systems prioritize 21st-century skills like problem-solving, critical thinking, and experimentation, educators are stepping up their assessment game. To accurately measure performance on higher-order thinking tasks, teachers are relying increasingly on complex subjective assessments, including essays, presentations, and capstone projects.
However, many find that automating the grading of subjective assessments is far more difficult than scoring objective assessments like multiple-choice tests. Educators may worry that artificial intelligence (AI)-powered scoring systems won’t be able to handle the nuances of expression found in more open-ended assessments. As a result, teachers are often left with a hefty manual grading burden that takes time away from preparing lesson plans or reaching out to families.
But it doesn’t have to be that way. In this article, we’ll show how it’s possible to automate grading, even for subjective assessments, and save school systems time and money.
Key Takeaways
- Efficiency boost: Automated grading significantly reduces the time educators spend on assessments, especially for large-scale tasks.
- AI-human balance: While AI can handle objective grading and some aspects of subjective tasks, human oversight is crucial for nuanced assessments.
- Flexibility is key: Flexible algorithms and hybrid models enhance the ability to fairly evaluate creativity, originality, and diverse perspectives.
- Teacher support: Intuitive EdTech tools and proper training empower educators to seamlessly integrate automated grading into their workflow without sacrificing quality.
What Is Automated Grading?
Automated grading refers to using technology, such as AI and machine learning (ML), to evaluate and score student assessments. This is particularly useful for large-scale educational settings, where manually grading hundreds or thousands of assignments can be time-consuming and prone to inconsistencies.
Contrary to popular opinion, automated grading systems can assess a variety of formats, including multiple-choice, true/false, short-answer, and even more complex text-based responses like essays. The goal is to enhance efficiency and provide quick feedback while maintaining grading fairness and reliability.
EdTech platforms such as TAO put automated grading tools in teachers’ hands. For example, TAO can grade objective questions like multiple choice using predefined answer keys, while for more subjective or complex answers, it employs a technology-assisted human scoring system, TAO Grader, that increases the efficiency of manual grading. The AI assistant within TAO Grader uses advanced algorithms like natural language processing (NLP) to analyze written responses and recommend a score, along with the reasoning behind the score, based on the grading rubric.
4 Challenges (and Solutions) When Using Automated Grading for Subjective Assessments
Many educators and administrators feel that automated grading systems can’t appreciate the full depth and breadth of student learning. The truth is a bit more nuanced. While these systems aren’t perfect subjective assessors, they can provide invaluable assistance to human graders when used correctly.
1. Grading long-form essays
Perhaps the most enduring form of subjective assessment, long-form essays are notoriously time-consuming to grade. When educators have to mark up writing for grammatical errors, catch logical inconsistencies, and evaluate evidence, it can take dozens of hours to finish grading a set of essays. Can AI really help with this highly complex challenge?
Solution: AI-assisted grading
Yes, it most certainly can. While automated grading systems can’t do 100% of the work, they can substantially reduce the time teachers devote to assessing long-form essays.
Thanks to the kind of advanced NLP capabilities evident in chatbots such as ChatGPT and Gemini, AI grading assistants can spot grammar and spelling issues and evaluate essays for logical consistency. This frees teachers to focus on writing targeted feedback and spotting issues with factual evidence and analysis.
With AI-assisted grading, educators still play an important role in defining scoring standards. A flexible EdTech platform will even let educators define scoring strategies for distinct items to ensure scoring fairness. In TAO, educators can assign fellow teachers who excel in a certain subject—the politics of the Roman Republic, for example—to grade questions on that topic while blinding them to student identity.
2. Assessing creativity
A significant challenge in automated grading for subjective assessments is the difficulty of assessing creativity and innovation. The originality of response often expected in essay writing, oral presentations, and problem-solving tasks poses a problem for automated systems that rely on pattern recognition and standardization.
For example, a student might present a unique perspective or structure in an essay that defies traditional formats, but the automated system may penalize the response for deviating from patterns it was trained to recognize as “correct.”
In contrast, formulaic, repetitive responses that stick closely to the expected patterns might score higher, even if they lack depth or creativity. This limitation can stifle innovation in students’ work, as they may focus on writing for the algorithm rather than expressing fresh ideas.
Solution: Flexible grading
To overcome the challenge of assessing creativity, automated grading systems can be designed with flexibility in mind. One solution is to use a platform like TAO that integrates algorithms for analyzing complex and nuanced language. The algorithms can be trained to identify not just patterns but also the use of original arguments, new perspectives, or diverse approaches to problem-solving.
A hybrid model, where AI flags potentially creative work for human review, would help preserve the balance between automation and subjective human judgment, ensuring that originality and innovation are properly rewarded.
3. Teacher training
Educators need support as they transition from fully manual to automated and assisted grading. To ensure they get the most out of their EdTech tools, administrators may have to plan training sessions. Naturally, the time and financial costs of this may be a barrier to implementation.
Solution: Intuitive tooling
While digital literacy training is critical, intuitive EdTech platforms can greatly reduce the need to hold lengthy workshops. When educators can log on to a single hub to issue assessments, upload rubrics, carry out automated grading, and conduct manual scoring, they won’t have to devote time and energy to managing several distinct educational assessment packages.
One element of intuitive EdTech software is entirely behind the scenes, but it’s incredibly important: interoperability. Interoperable EdTech solutions follow open-source standards such as those set by the IMS Global Learning Consortium (IMS), so they can be seamlessly integrated with other learning tools. This eliminates the need for costly custom integrations, reduces the training burden, and allows educators to choose the solutions they want to use without additional administrative headaches.
4. Preventing plagiarism
Automated grading systems face significant challenges in detecting plagiarism, especially in subjective assessments where students may use subtle forms of academic dishonesty. Plagiarism isn’t limited to straightforward copy-pasting: it can involve paraphrasing, idea theft, or using AI-generated content, making detection harder for algorithms that rely only on surface-level matching techniques.
Solution: Integration of advanced plagiarism detection tools
To address this challenge, plagiarism detection solutions should be integrated into grading systems. These tools can go beyond simple text matching by employing semantic analysis. This identifies similarities in meaning, even when the wording is different.
Additionally, AI models should be trained to detect common patterns of plagiarism across various sources. Automated grading systems can also be connected to large academic databases and the web for real-time comparisons and increased trust in academic integrity.
Conclusion
While automated grading systems present unique challenges, particularly in assessing subjective, long-form, and creative work, they also offer immense potential to streamline grading processes and improve efficiency. By leveraging advanced AI tools like NLP, educators can significantly reduce the time spent on grading, while still ensuring fairness and accuracy.
Solutions such as hybrid grading models, flexible algorithms, and intuitive, interoperable platforms make it easier for teachers to integrate automated systems without losing the human element crucial for subjective assessments. With the right balance of technology and human oversight, automated grading can enhance the educational experience for both students and teachers.
To learn more about automating the grading of subjective assessments, take a look at these helpful resources on the TAO blog:
- Breaking from Convention: 3 Types of Alternative Assessments Explained
- How to Reduce Cheating Risks in Online Testing
- Podcast: The Future of Language and Literacy Assessment in NYC Schools
FAQs
- Can AI fully replace teachers in grading subjective assessments?
No, AI can’t fully replace teachers for subjective assessments. While AI can handle tasks like grammar checks and identifying logical consistency, human oversight is needed for nuanced judgments, such as assessing creativity, originality, and the depth of arguments.
- How accurate is automated grading?
Automated grading is generally accurate for objective questions but may face challenges with subjective responses. Its accuracy improves with better algorithms and diverse training data, but human involvement ensures fairness.
- What are the benefits of automated grading in education?
Automated grading increases efficiency, reduces grading time, and provides faster feedback to students.
