Joan Moss

1.5k citations
22 papers · 882 · h-index 10

Impact in

Papers in

    • Mathematics Education and Teaching Techniques 12
    • Education and Technology Integration 2
    • Cognitive and developmental aspects of mathematical skills 9
    • Statistics Education and Methodologies 2

Joan Moss

19 papers receiving 792 citations

Peers

Joan Moss
Comparison fields: 5 of 63
  • Statistics and Probability 483
  • Developmental and Educational Psychology 299
  • Automotive Engineering 268
  • Education 560
  • Geography, Planning and Development 71
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Citations per field
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Citations per year

Countries citing papers authored by Joan Moss

Since Specialization
Citations

This map shows the geographic impact of Joan Moss'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 Joan Moss with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joan Moss more than expected).

Fields of papers citing papers by Joan Moss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joan Moss. 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 Joan Moss. The network helps show where Joan Moss may publish in the future.

Co-authors

The 17 scholars most cited alongside Joan Moss, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Joan Moss Line = papers co-authored together Joan Moss links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999254
2 2017123
3 2015119
4 201977
5 200658
6
Psychological models for the development of mathematical understanding: rational numbers and functions
200155
7 201550
8 201642
9 201240
10 201022
11 20199
12 20178
13 19906
14 20155
15 20155
16 20043
17 20122
18
Introducing Percents in Linear Measurement to Foster an Understanding of Rational-Number Operations
20031
19 20201
20 20031

About Joan Moss

Joan Moss is a scholar working on Education, Statistics and Probability, Developmental and Educational Psychology, Automotive Engineering and Geography, Planning and Development, having authored 22 papers that have together received 882 indexed citations. Recurring topics across this work include Mathematics Education and Teaching Techniques (12 papers), Cognitive and developmental aspects of mathematical skills (9 papers), Spatial Cognition and Navigation (5 papers), Innovative Teaching and Learning Methods (4 papers), Geography Education and Pedagogy (3 papers), Education and Technology Integration (2 papers), Cognitive Science and Mapping (2 papers) and Statistics Education and Methodologies (2 papers). The work is most often cited by research in Statistics and Probability (483 citations), Developmental and Educational Psychology (299 citations), Automotive Engineering (268 citations), Education (560 citations) and Geography, Planning and Development (71 citations). Joan Moss has collaborated with scholars based in Canada, United States and Australia. Frequent co-authors include Robbie Case, Zachary Hawes, Beverly Caswell, Ruth Beatty, Nathalie Sinclair, Daniel Ansari, Walter Whiteley, Joanne Mulligan, Yuko Okamoto and Geoff Woolcott. Their work appears in journals such as Mind Brain and Education, Cognitive Psychology, Academic Medicine, International Journal of Educational Research and International Journal of Computer-Supported Collaborative Learning.

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.

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