2015/12/30 by Onofrio Rosario Battaglia, Battaglia, Onofrio Rosario, Benedetto Di Paola +3
Agricultural and Biological Sciences · Computer Science · Decision Sciences · Mathematics · Physics and Astronomy · #Advanced Text Analysis Techniques #FOS: Physical sciences #Multi-Criteria Decision Making #Physics Education (physics.ed-ph) #Sensory Analysis and Statistical Methods #Statistical Methods and Applications #physics.ed-ph
paper · pdf · doi:10.48550/arxiv.1512.08998
30 pages
openalex publication_date 2015/12/30 · arxiv created 2017/08/16 · arxiv updated 2017/08/17 · openalex created_date 2022/09/14 · openalex updated_date 2026/07/28
In the last years many studies examined the consistency of students' answers in a variety of contexts. Some of these papers tried to develop more detailed models of the consistency of students' reasoning, or to subdivide a sample of students into intellectually similar subgroups. The problem of taking a set of data and separating it into subgroups where the elements of each subgroup are more similar to each other than they are to elements not in the subgroup has been extensively studied through the methods of Cluster Analysis. This method can separate students into groups that can be recognized and characterized by common traits in their answers, without any prior knowledge of what form those groups would take (unbiased classification). In this paper we start from a detailed analysis of the data coding needed in Cluster Analysis, in order to discuss the meaning and the limits of the interpretation of quantitative results. Then two methods commonly used in Cluster Analysis are described and the variables and parameters involved are outlined and criticized. Section III deals with the application of these methods to the analysis of data from an open-ended questionnaire administered to a sample of university students, and the quantitative results are discussed. Finally, the quantitative results are related to student answers and compared with previous results reported in the literature, by pointing out the new insights resulting from the application of such new methods.