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.
State of the art – teacher effectiveness and professional learning
2014319 citationsLeōnidas Kyriakidēs, Bert Creemers et al.School Effectiveness and School Improvementprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Leōnidas Kyriakidēs
Since
Specialization
Citations
This map shows the geographic impact of Leōnidas Kyriakidēs'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 Leōnidas Kyriakidēs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leōnidas Kyriakidēs more than expected).
Fields of papers citing papers by Leōnidas Kyriakidēs
This network shows the impact of papers produced by Leōnidas Kyriakidēs. 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 Leōnidas Kyriakidēs. The network helps show where Leōnidas Kyriakidēs may publish in the future.
Co-authorship network of co-authors of Leōnidas Kyriakidēs
This figure shows the co-authorship network connecting the top 25 collaborators of Leōnidas Kyriakidēs.
A scholar is included among the top collaborators of Leōnidas Kyriakidēs 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 Leōnidas Kyriakidēs. Leōnidas Kyriakidēs is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Creemers, Bert & Leōnidas Kyriakidēs. (2013). Using the dynamic model to identify stages of effective teaching: An introduction to the special issue. The Journal of classroom interaction. 48(2). 4–9.2 indexed citations
11.
Kyriakidēs, Leōnidas & Bert Creemers. (2013). Using the dynamic model of educational effectiveness to identity stages of effective teaching: An introduction to the special issue. The Journal of classroom interaction. 48(2). 4–10.1 indexed citations
12.
Kyriakidēs, Leōnidas, Isabelle Archambault, & Michel Janosz. (2013). Searching for stages of effective teaching: A study testing the validity of the dynamic model in Canada. The Journal of classroom interaction. 48(2). 11–24.14 indexed citations
Kyriakidēs, Leōnidas. (2006). International studies on educational effectiveness. The Library of Electronic Cyprus Thematic Organized Collections (LYKYTHOS) (University of Cyprus).1 indexed citations
18.
Kyriakidēs, Leōnidas. (2005). Drawing from Teacher Effectiveness Research and Research into Teacher Interpersonal Behaviour to Establish a Teacher Evaluation System: A Study on the Use of Student Ratings to Evaluate Teacher Behaviour.. The Journal of classroom interaction. 40(2). 44–66.53 indexed citations
19.
Charalambous, Charalambos Y., et al.. (2003). Testing a Comprehensive Model for Measuring Problem Solving and Problem Posing Skills of Primary Pupils.. Proceedings of the ... PME Conference. 2. 205–212.5 indexed citations
20.
Kyriakidēs, Leōnidas. (1994). Primary teachers' perceptions of policy for curriculum reform in Cyprus : with special reference to mathematics. Warwick Research Archive Portal (University of Warwick). 1(2). 77–93.7 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.