Software engineering intelligent education platform based on LSTM training model

Fang Qin; Lin Li; Weijia Zeng; Tao Wang; Lijuan Wang

doi:10.1117/12.2653260

20 October 2022 Software engineering intelligent education platform based on LSTM training model

Fang Qin, Lin Li, Weijia Zeng, Tao Wang, Lijuan Wang

Proceedings Volume 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022); 123501R (2022) https://doi.org/10.1117/12.2653260
Event: 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 2022, Qingdao, China

Abstract

With the rapid development of the Internet, the way of education is gradually tending to the network platform, so the intelligent education platform plays an extremely important role in the diversified way of education. It has always been an important issue in software engineering teaching to provide learners with reading materials of appropriate complexity. At present, the automatic classification of text complexity is still mainly based on the construction of linear model formulas. But due to the limited number of features eventually entering the model, the accuracy is generally not high, and it is difficult to extend to other data sets. This paper aims to explore the performance of neural network technology in the text complexity classification models with the help of multi-dimensional features and feature optimization. After comparative experiments, the text complexity classification model based on the neural network has the best performance. Its accuracy, recall, and F1 comprehensive evaluation indicators in cross-validation are better than other methods, which not only have higher prediction accuracy, but also have more stable performance. The model established from that has a strong generalization ability for new data, with obvious advantages.

Citation Download Citation

Fang Qin, Lin Li, Weijia Zeng, Tao Wang, and Lijuan Wang "Software engineering intelligent education platform based on LSTM training model", Proc. SPIE 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 123501R (20 October 2022); https://doi.org/10.1117/12.2653260

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KEYWORDS

Performance modeling

Neural networks

Data modeling

Software engineering

Neurons

Software development

Logic

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