Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Educational Gaming for Pharmacy Students – Design and Evaluation of a Diabetes-themed Escape Room
2017224 citationsHeidi Eukel, Jeanne E. Frenzel et al.American Journal of Pharmaceutical Educationprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Dan Cernusca'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 Dan Cernusca with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Cernusca more than expected).
This network shows the impact of papers produced by Dan Cernusca. 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 Dan Cernusca. The network helps show where Dan Cernusca may publish in the future.
Co-authorship network of co-authors of Dan Cernusca
This figure shows the co-authorship network connecting the top 25 collaborators of Dan Cernusca.
A scholar is included among the top collaborators of Dan Cernusca 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 Dan Cernusca. Dan Cernusca is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Cernusca, Dan & Sanku Mallik. (2018). Making Failure Productive in an Active Learning Context: Improved Student Performance and Perceptions in a Pharmaceutics Chemistry Course.. The Quarterly Review of Distance Education. 19(2). 37–49.2 indexed citations
8.
Cernusca, Dan, et al.. (2017). Turning a Problem into a Solution: Instructional Benefits of Using ExamSoft to Map Multiple-Choice Responses. 17(7). 22–34.1 indexed citations
Eukel, Heidi, Jeanne E. Frenzel, & Dan Cernusca. (2017). Educational Gaming for Pharmacy Students – Design and Evaluation of a Diabetes-themed Escape Room. American Journal of Pharmaceutical Education. 81(7). 6265–6265.224 indexed citations breakdown →
Cernusca, Dan, et al.. (2012). Prior Knowledge Influence on Self-Explanation Effectiveness When Solving Problems: An Exploratory Study in Science Learning. International journal on teaching and learning in higher education. 24(3). 349–358.15 indexed citations
14.
Cernusca, Dan & Daniel Forciniti. (2011). AC 2011-575: INSTRUCTIONAL VIDEOS WITH PURPOSE: COMPEN- SATE, SUPPORT, AND CHALLENGE CHEMICAL ENGINEERING STU- DENTS IN AN INTRODUCTORY THERMODYNAMICS COURSE.1 indexed citations
15.
He, Wu, Dan Cernusca, & M’hammed Abdous. (2011). Exploring Cloud Computing for Distance Learning. Online journal of distance learning administration. 14(3).11 indexed citations
Forciniti, Daniel & Dan Cernusca. (2010). Teaching Thermodynamics: Designing a Course That Compensate, Support, and Challenge Students' Learning.
18.
Ströbel, Johannes, Dan Cernusca, & David H. Jonassen. (2004). Different Majors - Different Epistemological Beliefs?. Academic exchange quarterly. 8(1). 208–211.9 indexed citations
19.
He, Wu, et al.. (2003). Interface support for case retrieval in a Case-Based Reasoning knowledge repository-Knowledge Innovation for Technology in Education(KITE). Society for Information Technology & Teacher Education International Conference. 2003(1). 3598–3600.1 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.