Use data analysis to identify the success rate of a given question
Analyzing data to identify the success rate of a given question involves examining the performance or outcomes associated with that specific question within a dataset. By systematically analyzing the data related to a specific question, it is possible to valuable insights into its success rate and contribute to informed decision-making in educational or evaluative contexts. There are many pattern recognition and statistical techniques that can be used for this purpose, such as percentage, average, mode, and median evaluation, as well as the machine learning techniques used for pattern recognition, such as random forest, support vector machine, and d among many others [1].
Example:
The study proposed in [2] refers to a comprehensive investigation of the patterns that may exist within the set of questions available on the MathE platform. Then, it investigates how to evaluate the students' opinions about the questions’ difficulty levels based on the variables extracted from student answers collected through pattern recognition techniques. Moreover, a comparative study between variables is performed using correlation and hypothesis tests. Based on the results of the data analysis, it was possible to define the most appropriate number of answers that should be considered to categorize the question's difficulty level.
Reference:
[1] Bishop, C. Pattern Recognition and Machine Learning. (Springer,2006 )
[2] Azevedo, B., Souza, R., Pacheco, M., Fernandes, F. \& Pereira, A. Application of Pattern Recognition Techniques for MathE Questions Difficulty Level Definition. Communications in Computer and Information Science. In: Pereira A.I. et al. (eds ) Optimization, Learning Algorithms and Applications. OL2A 2023 (In Press ).
[2] Azevedo, B., Souza, R., Pacheco, M., Fernandes, F. \& Pereira, A. Application of Pattern Recognition Techniques for MathE Questions Difficulty Level Definition. Communications in Computer and Information Science. In: Pereira A.I. et al. (eds ) Optimization, Learning Algorithms and Applications. OL2A 2023 (In Press ).
Author of the tip:
Florbela P. Fernandes
Instituto Politécnico de Bragança