In this paper, we propose a novel Test-aware Attention-based Convolutional. Neural Network (TACNN) framework to automatically solve this Question Difficulty ...
Abstract. Standard tests aim to evaluate the performance of examinees using different tests with consistent difficulties. Thus, a critical demand is to predict ...
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Feb 12, 2017 · In this paper, we propose a novel Test-aware Attention-based Convolutional Neural Network (TACNN) framework to automatically solve this Question ...
Standard tests aim to evaluate the performance of examinees using different tests with consistent difficulties. Thus, a critical demand is to predict the ...
➢ Goal: Automatically predict question difficulty in newly-conduct tests ... ➢ Collected from real-world standard tests for READING problems in Chinese.
A novel Test-aware Attention-based Convolutional Neural Network (TACNN) framework to automatically solve this Question Difficulty Prediction (QDP) task for ...
The main objective of the project is to predict the difficulty of each given question based on its context materials which include several components (such like ...
Sep 8, 2023 · In this paper, we provide a comprehensive and systematic review of methods for the priori prediction of question difficulty.
We explore automated approaches to rank MC questions by difficulty. However, there is limited data for explicit training of a system for difficulty scores.
We conclude that question difficulty order in tests has important policy implications for optimal test design and performance. It additionally may have ...