CLSA model structure The MOOC dropout Process overview This study proposes a CLSA-based MOOC dropout prediction model. The prediction process based on this model is shown in Fig. 4 and has three parts: Dataset preprocessing, model prediction, and model evaluation. First, we processed the clickstre...
Dropout predictionFeature extractionMassive Open Online Courses (MOOCs)Predicting students' performance is critical in Massive Open Online Courses (MOOCs) in order to benefit from many aspects such as students' retention and make timely interventions. In this paper, we propose a hyper-model of ...
The current work explores, for the first time, the predictive power that can be drawn from the analysis of the LMS-based QoI using Deep Learning. The proposed enhancement of LMS, namely DeepLMS, fills the gap in predictive use of LMS-based QoI to early inform effective feedback providers, ...
Deep Interest Network for Click-Through Rate Prediction [arXiv] Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study [arXiv] [article] Structure Learning in Motor Control: A Deep Reinforcement Learning Model [arXiv] Programmable Agents [arXiv] Grounded Language Learning in a Sim...
The main contribution of this research is to introduce an ML/DL-based framework for short-term SA and long-term CA prediction. This objective has been set by the authors to address the following gaps in the literature: 1. Provide accurate predictions of SA and CA behavior using DL, ML, ...
Software vulnerabilities pose a significant threat to system security, necessitating effective automatic detection methods. Current techniques face challenges such as dependency issues, language bias, and coarse detection granularity. This study presents
A Brief Survey of Deep Learning Approaches for Learning Analytics on MOOCs Chapter© 2021 Algorithms for the Development of Deep Learning Models for Classification and Prediction of Learner Behaviour in MOOCs Chapter© 2022 Predictive learning analytics using deep learning model in MOOCs’ courses vid...
3.4.3. Other prediction Emotion analysis can also be used to predict public opinion regarding various policy events (such as personal income tax adjustment, medical insurance reform, and retirement delays) as well as provide support for national policy formulation. In addition, emotion analysis can ...
A system and method for using a deep learning model to learn program semantics is disclosed. The method includes receiving a plurality of execution traces of a program, each executi
Although MOOCs are popular among people, it faces a great challenge鈥攖he high dropout rate, which affects its development. Predicting the dropout rate in advance can take relevant measures to avoid as many dropouts as possible. Traditional machine learning classification prediction and single sequence...