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.
Toward the development of an elementary teacher's science teaching efficacy belief instrument
1990706 citationsIris M. Riggs, Larry G. EnochsScience Educationprofile →
Further Development of an Elementary Science Teaching Efficacy Belief Instrument: A Preservice Elementary Scale
1990536 citationsLarry G. Enochs, Iris M. RiggsSchool Science and Mathematicsprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Iris M. Riggs'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 Iris M. Riggs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Iris M. Riggs more than expected).
This network shows the impact of papers produced by Iris M. Riggs. 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 Iris M. Riggs. The network helps show where Iris M. Riggs may publish in the future.
Co-authorship network of co-authors of Iris M. Riggs
This figure shows the co-authorship network connecting the top 25 collaborators of Iris M. Riggs.
A scholar is included among the top collaborators of Iris M. Riggs 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 Iris M. Riggs. Iris M. Riggs is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Lewis, Jennifer M., et al.. (2013). Teacher Learning in Lesson Study. The Mathematics Enthusiast. 10(3). 583–620.19 indexed citations
4.
Verdi, Michael P., Matt L. Riggs, & Iris M. Riggs. (2012). The California Teaching Performance Assessment Task for Assessing Student Learning: What Do Teacher Education Candidates Really Learn?.. Teacher education & practice. 25(3). 336–349.1 indexed citations
5.
Robertson, Mark P., Martin H. Villet, Dean H.K. Fairbanks, et al.. (2003). A proposed prioritization system for the management of invasive alien plants in South Africa. South African Journal of Science. 99. 37–43.51 indexed citations
6.
Riggs, Iris M., et al.. (2002). Professional Development of Mentors within a Beginning Teacher Induction Program: How Does the Garden (Mentors) Grow?..18 indexed citations
7.
Finson, Kevin D., et al.. (2000). The Relationship of Science Teaching Self Efficacy and Outcome Expectancy to the Draw-a-Science-Teacher-Teaching Checklist..18 indexed citations
Riggs, Iris M.. (1991). Gender Differences in Elementary Science Teacher Self-Efficacy..42 indexed citations
17.
Riggs, Iris M. & Larry G. Enochs. (1990). Toward the development of an efficacy belief instrument for elementary teachers. Science Education. 74(6).14 indexed citations
18.
Enochs, Larry G. & Iris M. Riggs. (1990). Further Development of an Elementary Science Teaching Efficacy Belief Instrument: A Preservice Elementary Scale. School Science and Mathematics. 90(8). 694–706.536 indexed citations breakdown →
19.
Riggs, Iris M. & Matt L. Riggs. (1990). A Test of the Validity of Selected Predictors of Student Success in a Teacher Education Program..8 indexed citations
20.
Riggs, Iris M. & Larry G. Enochs. (1990). Toward the development of an elementary teacher's science teaching efficacy belief instrument. Science Education. 74(6). 625–637.706 indexed citations breakdown →
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.