优化集体深度学习,用于对学生成绩的预测分析
Kaitong Wang1,2
1Student Affairs Department, Institute of Science and Technology, Luoyang, Henan Province, China.
PloS one
|August 26, 2024
概括
这项研究引入了一种新的混合方法 (DistilBERT与LSTM和斑点虫优化器) 来预测学生的表现. 该方法显著提高了准确性,并减少了教育数据挖掘中的处理时间.
科学领域:
- 教育技术的教育技术
- 教育中的人工智能
- 数据挖掘 数据挖掘
背景情况:
- 教育对于个人和社会进步至关重要.
- 技术进步,特别是人工智能,正在改变学习的可访问性和方法.
- 高等教育整合了技术,以改善传统的教学.
研究的目的:
- 提出一种创新的混合方法,用于预测学生在教育环境中的表现.
- 为了应对在研究生和研究生课程中数据量增加的挑战.
- 提高教育数据挖掘的效率和准确性.
主要方法:
- 开发了一种混合模型,将DistilBERT与长短期存储器 (DBTM) 结合起来.
- 使用SHO (斑点的海优化器) 来优化DBTM模型的参数.
- 拟议的DBTM-SHO方法在广泛的数据集上进行了评估.
主要成果:
- 与以前的模型相比,DBTM-SHO模型在准确性,日志损失和执行时间方面取得了显著的改进.
- 实现了98.7%的准确性和0.03%的日志损失.
- 通过优化减少15-25%的处理时间,有效处理大型数据集.
结论:
- 在大数据时代,DBTM-SHO方法为学生绩效预测提供了强大的解决方案.
- 这种方法代表了教育数据挖掘的重大进步.
- 提供了一个坚实的基础,为机构评估学生的成绩大数据集.
更多相关视频
06:37Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
Published on: December 15, 2023
2.7K
09:34A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
Published on: September 25, 2021
3.9K
相关概念视频
Prediction Intervals
2.2K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
2.2K
Associative Learning
318
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
Classical conditioning, also known...
318
Regression Toward the Mean
6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K
Regression Analysis
5.7K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
5.7K
Multiple Regression
3.0K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.0K
End Point Prediction: Gran Plot
300
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
For potentiometric titration, the Gran plot is created by plotting...
300
