Redirigiendo al acceso original de articulo en 24 segundos...
ARTÍCULO
TITULO

Clustering Algorithm to Measure Student Assessment Accuracy: A Double Study

Sónia Rolland Sobral and Catarina Félix de Oliveira    

Resumen

Self-assessment is one of the strategies used in active teaching to engage students in the entire learning process, in the form of self-regulated academic learning. This study aims to assess the possibility of including self-evaluation in the student?s final grade, not just as a self-assessment that allows students to predict the grade obtained but also as something to weigh on the final grade. Two different curricular units are used, both from the first year of graduation, one from the international relations course (N = 29) and the other from the computer science and computer engineering courses (N = 50). Students were asked to self-assess at each of the two evaluation moments of each unit, after submitting their work/test and after knowing the correct answers. This study uses statistical analysis as well as a clustering algorithm (K-means) on the data to try to gain deeper knowledge and visual insights into the data and the patterns among them. It was verified that there are no differences between the obtained grade and the thought grade by gender and age variables, but a direct correlation was found between the thought grade averages and the grade level. The difference is less accentuated at the second moment of evaluation?which suggests that an improvement in the self-assessment skill occurs from the first to the second evaluation moment.

 Artículos similares

       
 
Yuting Bai, Yijie Niu, Zhiyao Zhao, Xuebo Jin and Xiaoyi Wang    
The phenomenon of algal bloom seriously affects the function of the aquatic ecosystems, damages the landscape of urban river and lakes, and threatens the safety of water use. The introduction of a multi-attribute decision-making method avoids the shortco... ver más
Revista: Water

 
Gary Reyes, Roberto Tolozano-Benites, Laura Lanzarini, César Estrebou, Aurelio F. Bariviera and Julio Barzola-Monteses    
Persistently, urban regions grapple with the ongoing challenge of vehicular traffic, a predicament fueled by the incessant expansion of the population and the rise in the number of vehicles on the roads. The recurring challenge of vehicular congestion ca... ver más

 
Xiaokai Sun, Baoyun Guo, Cailin Li, Na Sun, Yue Wang and Yukai Yao    
In urban point cloud scenarios, due to the diversity of different feature types, it becomes a primary challenge to effectively obtain point clouds of building categories from urban point clouds. Therefore, this paper proposes the Enhanced Local Feature A... ver más

 
Xiaolong Li, Yun Zhang, Longgang Xiang and Tao Wu    
Lane-level road information is especially crucial now that high-precision navigation maps are in more demand. Road information may be obtained rapidly and affordably by mining floating vehicle data (FCD). A method is proposed to extract the number of lan... ver más

 
Song Chen, Fuhao Zhang, Zhiran Zhang, Siyi Yu, Agen Qiu, Shangqin Liu and Xizhi Zhao    
Spatial clustering is dependent on spatial scales. With the widespread use of web maps, a fast clustering method for multi-scale spatial elements has become a new requirement. Therefore, to cluster and display elements rapidly at different spatial scales... ver más