Related Experiment Videos
Intelligent automated essay scoring under uncertainty using type 2 neutrosophic ontologies
Saad M Darwish1, Noha A Bagi2, Noha A El-Shoafy3
1Department of Information Technology, Institute of Graduate Studies and Research, Alexandria University, 163 Horreya Avenue, El-Shatby, Alexandria, 21526, Egypt. saad.darwish@alexu.edu.eg.
Scientific Reports
|June 3, 2026
Summary
This study introduces Type-2 Neutrosophic Sets (T2NS) to enhance automated essay scoring (AES) systems. The novel approach improves scoring reliability by effectively handling uncertainty in educational assessments.
Area of Science:
- Artificial Intelligence
- Educational Technology
- Fuzzy Logic
Background:
- Computing with uncertainty is crucial in domains like decision support and intelligent assessment.
- Automated Essay Scoring (AES) faces challenges due to linguistic ambiguity and subjective interpretation.
- Traditional ontology-based AES systems struggle with uncertainty, impacting scoring reliability.
Purpose of the Study:
- To propose a novel approach integrating Type-2 Neutrosophic Sets (T2NS) into ontology-driven AES frameworks.
- To address the limitations of traditional AES in handling uncertain, indeterminate, and inconsistent information.
- To enhance the robustness and interpretability of scoring decisions in automated essay evaluation.
Main Methods:
- Concept extraction and rule-based scoring using ontologies.
- Extension of ontology with Type-2 Neutrosophic Sets (T2NS) for uncertainty representation.
- Application of membership functions to quantify uncertainty levels in essay evaluation.
Main Results:
- The T2NS-enhanced framework significantly outperforms conventional AES methods.
- Improved handling of uncertain, indeterminate, and inconsistent information in essay scoring.
- More robust and interpretable scoring decisions achieved.
Conclusions:
- Integrating T2NS into ontology-driven AES offers a superior method for managing uncertainty.
- The proposed framework enhances the reliability and accuracy of automated essay scoring.
- This approach provides a more sophisticated solution for educational assessment under uncertainty.
Related Concept Videos
01:26Classification of Systems-I
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
01:24Natural and Artificial Concepts
In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint Vincent in...
01:31Classification of Systems-II
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
00:59Uncertainty: Overview
In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
01:21Heuristics
Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
01:28Automatic Processing and Automatic Social Behavior
Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...