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.
The mathematics teacher’s specialised knowledge (MTSK) model*
2018220 citationsJosé Carrillo, Nuria Climent et al.Research in Mathematics Educationprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Miguel Montes'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 Miguel Montes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miguel Montes more than expected).
This network shows the impact of papers produced by Miguel Montes. 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 Miguel Montes. The network helps show where Miguel Montes may publish in the future.
Co-authorship network of co-authors of Miguel Montes
This figure shows the co-authorship network connecting the top 25 collaborators of Miguel Montes.
A scholar is included among the top collaborators of Miguel Montes 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 Miguel Montes. Miguel Montes is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Montes, Miguel, et al.. (2020). Análisis de los problemas matemáticos planteados por los libros de texto de la editorial Edebé en Educación Primaria. 59–79.
9.
Montes, Miguel, et al.. (2019). Un acercamiento al conocimiento del formador de profesores de matematicas. The International Islamic University Malaysia Repository (The International Islamic University Malaysia). 473–482.4 indexed citations
10.
Carrillo, José, Nuria Climent, Miguel Montes, et al.. (2018). The mathematics teacher’s specialised knowledge (MTSK) model*. Research in Mathematics Education. 20(3). 236–253.220 indexed citations breakdown →
Montes, Miguel, et al.. (2015). Arithmetic Knowledge of prospective teachers. Strengths and Weaknesses. Revista de educación.1 indexed citations
15.
Montes, Miguel, et al.. (2015). Conocimiento de aritmética de futuros maestros. Debilidades y fortalezas = Arithmetic Knowledge of prospective teachers. Strengthsand Weaknesses. Revista de educación. 36–62.1 indexed citations
16.
Montes, Miguel, et al.. (2015). Conocimiento de aritmética de futuros maestros : debilidades y fortalezas. Revista de educación. 36–62.3 indexed citations
17.
Ribeiro, Carlos Miguel, Ceneıda Fernández, Miguel Montes, et al.. (2014). Mejorar nuestro propio conocimiento mediante el análisis de un episodio de la práctica, distintos focos de análisis. idUS (Universidad de Sevilla).
18.
Montes, Miguel, et al.. (2013). La clasificación de las figuras planas en Primaria: una visión de progresión entre etapas y ciclos. Dialnet (Universidad de la Rioja).
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.