This map shows the geographic impact of Susan Ramlo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Susan Ramlo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Susan Ramlo more than expected).
This network shows the impact of papers produced by Susan Ramlo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Susan Ramlo. The network helps show where Susan Ramlo may publish in the future.
Co-authorship network of co-authors of Susan Ramlo
This figure shows the co-authorship network connecting the top 25 collaborators of Susan Ramlo.
A scholar is included among the top collaborators of Susan Ramlo based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Susan Ramlo. Susan Ramlo is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Ramlo, Susan, et al.. (2020). Divergent student views of cybersecurity. DigitalCommons - Kennesaw State University (Kennesaw State University). 2019(2).4 indexed citations
6.
Ramlo, Susan. (2017). Improving Student Evaluation of Teaching: Determining Multiple Perspectives within a Course for Future Math Educators.. 27(1). 49–78.12 indexed citations
7.
Ramlo, Susan. (2017). The Preferences of Q Methodologists at the Factor-Analytic Stage: An Examination of Practice.. Research in the schools. 24(2). 41–56.7 indexed citations
8.
Ramlo, Susan. (2016). Centroid and Theoretical Rotation: Justification for Their Use in Q Methodology Research.. ScholarWorks@BGSU (Bowling Green State University). 28(1). 73–92.29 indexed citations
9.
Ramlo, Susan. (2015). Q Methodology as a Tool for Program Assessment.. ScholarWorks@BGSU (Bowling Green State University). 27(3). 207–223.10 indexed citations
10.
Ramlo, Susan. (2015). Theoretical Significance in Q Methodology: A Qualitative Approach to a Mixed Method.. Research in the schools. 22(1). 73–87.29 indexed citations
11.
Ramlo, Susan. (2015). Student Views about a Flipped Physics Course: A Tool for Program Evaluation and Improvement. Research in the schools. 22(1). 44–59.13 indexed citations
12.
Ramlo, Susan, et al.. (2013). Using Q Methodology to Study Wellbeing Associated with Informal Caregiving. 11(1). 157–174.3 indexed citations
13.
Ramlo, Susan. (2012). Determining Faculty and Student Views: Applications of Q Methodology in Higher Education.. 22(1). 86–107.13 indexed citations
14.
Ramlo, Susan & Isadore Newman. (2011). Reply to Gourlay. Operant Subjectivity. 34(3). 213–214.1 indexed citations
15.
Ramlo, Susan. (2011). Using Word Clouds to Visually Present Q Methodology Data and Findings. 9(2). 95–108.7 indexed citations
16.
Ramlo, Susan. (2011). Facilitating a Faculty Learning Community: Determining Consensus Using Q Methodology.. ScholarWorks@BGSU (Bowling Green State University). 24(1). 30–38.7 indexed citations
17.
Ramlo, Susan, et al.. (2009). In-service science teachers' views about learning physics after a one-week workshop. 7(2). 89–101.1 indexed citations
18.
Ramlo, Susan. (2008). Student perspectives on learning physics and their relationship with learning force and motion concepts. 6(2). 77–95.5 indexed citations
19.
Ramlo, Susan. (2005). A Physicist's Reflection on Q Methodology, Quantum Mechanics & Stephenson. Operant Subjectivity. 29. 81–86.4 indexed citations
20.
Ramlo, Susan. (2003). A multivariate assessment of the effect of the laboratory homework component of a microcomputer-based laboratory for a college freshman physics course. PhDT. 1–239.3 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.