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📃: Automated Essay Scoring System #66

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Avdhesh-Varshney opened this issue Jun 30, 2024 · 4 comments
Open

📃: Automated Essay Scoring System #66

Avdhesh-Varshney opened this issue Jun 30, 2024 · 4 comments
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@Avdhesh-Varshney
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🔴 Title : Automated Essay Scoring System
🔴 Aim : Create a system to automatically score essays using NLP techniques.
🔴 Brief Explanation :

  • Collect and preprocess a dataset of graded essays.
  • Train an NLP model to evaluate the quality of essays based on predefined criteria.
  • Develop an interface for users to submit essays and receive scores.
  • Ensure the UI is user-friendly and provides detailed feedback.

Screenshots 📷

N/A


To be Mentioned while taking the issue :

  • Full name :
  • What is your participant role? (Mention the Open Source Program name. Eg. GSSOC, SSOC, JWOC, etc.)

Happy Contributing 🚀

All the best. Enjoy your open source journey ahead. 😎

@Avdhesh-Varshney Avdhesh-Varshney added the Up-for-Grabs ✋ Issues are opened for the contributors label Jun 30, 2024
@fspzar123
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Full name : Filbert Shawn
What is your participant role? SSOC' 24
Data Collection: Automated Student Assessment Prize (ASAP)
Preprocessing: Text Cleaning, Tokenization, Words Removal, Lemmatization/Stemming
Feature Engineering:

  • Text Features: Take out attributes such as average word length, sentence count, and word count.
  • Lexical Richness: Determine the usage of uncommon terms, lexical diversity, etc.
  • Syntactic Features: Examine grammatical structures by parsing sentences.
  • Semantic Features: To capture semantic meaning, apply methods such as word embeddings (Word2Vec, GloVe) or contextual embeddings (BERT, GPT).
  • Calculate readability scores (Flesch-Kincaid, for example).

Machine Learning Model Selection & Training:

  • Traditional Machine Learning: Use algorithms like Linear Regression, Support Vector Machines (SVM), Random Forest, etc.
  • Deep Learning: Implement Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), or Transformers (BERT, GPT) for better performance on text data.

Evaluation & Refinement:
Assess the model's performance on a separate dataset. This helps identify areas for improvement.
Fine-tune the model by adjusting parameters or incorporating additional features until it achieves an acceptable level of accuracy and reliability compared to human scoring.

@Avdhesh-Varshney
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@fspzar123 go ahead.

@ChampGupta
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Please assign this work to me @Avdhesh-Varshney .

@Shalinis19137
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I really like your website and want to contribute can you assign me this issue under gssoc-ext2024

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