Add to ORKGWe use clustering, an analysis method not presently common to the physics education research community, to group and characterize student responses to written questions about two-dimensional kinematics. Previously, clustering has been used to analyze multiple-choice data; we analyze free-response data that includes both sketches of vectors and written elements. The primary goal of this paper is to describe the methodology itself; we include a brief overview of relevant results
Several researches in STEM education research highlight the advantages of an inte- grated approach t...
We suggest one redefinition of common clusters of questions used to analyze student responses on the...
Data analysis plays an indispensable role for understanding various phenomena. Cluster analysis, pri...
We use clustering, an analysis method not presently common to the physics education research communi...
Questionnaires are perhaps the most widely used instruments to assess conceptual learning in physics...
This study examined the evolution of student responses to seven contextually different versions of t...
The problem of taking a set of data and separating it into subgroups where the elements of each subg...
Many research papers have studied the problem of taking a set of data and separating it into subgrou...
In this paper, we applied a number of clustering algorithms on pretest data collected from 264 high-...
Cluster analysis can not only cluster observations/cases into several groups but also cluster variab...
Analyzing large trajectory sets enables deeper insights into multiple real-world problems. For exam...
This paper is part of the Focused Collection on Quantitative Methods in PER: A Critical Examination....
In this contribution we discuss the application of a quantitative, non-hierarchical clustering metho...
In the last years, research has paid strong attention to pre-service primary teachers’ views of math...
It is well--known that the provision of personalized instruction can enhance student learning. AI--b...
Several researches in STEM education research highlight the advantages of an inte- grated approach t...
We suggest one redefinition of common clusters of questions used to analyze student responses on the...
Data analysis plays an indispensable role for understanding various phenomena. Cluster analysis, pri...
We use clustering, an analysis method not presently common to the physics education research communi...
Questionnaires are perhaps the most widely used instruments to assess conceptual learning in physics...
This study examined the evolution of student responses to seven contextually different versions of t...
The problem of taking a set of data and separating it into subgroups where the elements of each subg...
Many research papers have studied the problem of taking a set of data and separating it into subgrou...
In this paper, we applied a number of clustering algorithms on pretest data collected from 264 high-...
Cluster analysis can not only cluster observations/cases into several groups but also cluster variab...
Analyzing large trajectory sets enables deeper insights into multiple real-world problems. For exam...
This paper is part of the Focused Collection on Quantitative Methods in PER: A Critical Examination....
In this contribution we discuss the application of a quantitative, non-hierarchical clustering metho...
In the last years, research has paid strong attention to pre-service primary teachers’ views of math...
It is well--known that the provision of personalized instruction can enhance student learning. AI--b...
Several researches in STEM education research highlight the advantages of an inte- grated approach t...
We suggest one redefinition of common clusters of questions used to analyze student responses on the...
Data analysis plays an indispensable role for understanding various phenomena. Cluster analysis, pri...