Amber Settle

1.8k citations
84 papers · 1.4k · h-index 20

Impact in

Papers in

Amber Settle

79 papers receiving 1.3k citations

Peers

Amber Settle
Comparison fields: 5 of 70
  • Computer Science Applications 1.0k
  • Developmental and Educational Psychology 480
  • Software 111
  • Information Systems 312
  • Media Technology 117
Replace Joyce Malyn‐Smith with:
Joyce Malyn‐Smith United States
Jesús Moreno-León Spain
Brian Hanks United States
Eric Roberts United States
Barbara Ericson United States
Charles Riedesel United States
Colleen M. Lewis United States
Briana B. Morrison United States
Brian Dorn United States
Michael E. Caspersen Denmark
Amber Settle relative to Joyce Malyn‐Smith United States Joyce Malyn‐Smith's profile →
Citations per field
00.5×2.6×
Joyce Malyn‐Smith · 1×
Citations per year

Countries citing papers authored by Amber Settle

Since Specialization
Citations

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

Fields of papers citing papers by Amber Settle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Amber Settle, 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 Amber Settle Line = papers co-authored together Amber Settle links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 84 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014261
2 2012113
3 2010103
4 201668
5 201664
6 201548
7 200547
8 201746
9 200938
10 201231
11 201630
12 201129
13 201827
14 202127
15 200223
16 200923
17 200421
18 201521
19 201320
20 200819

About Amber Settle

Amber Settle is a scholar working on Computer Science Applications, Developmental and Educational Psychology, Information Systems, Education and Sociology and Political Science, having authored 84 papers that have together received 1.4k indexed citations. Recurring topics across this work include Teaching and Learning Programming (46 papers), Online Learning and Analytics (19 papers), Educational Games and Gamification (13 papers), Information Systems Education and Curriculum Development (13 papers), Innovative Teaching and Learning Methods (11 papers), Digital Games and Media (10 papers), Experimental Learning in Engineering (8 papers) and Online and Blended Learning (7 papers). The work is most often cited by research in Computer Science Applications (1.0k citations), Developmental and Educational Psychology (480 citations), Software (111 citations), Information Systems (312 citations) and Media Technology (117 citations). Amber Settle has collaborated with scholars based in United States, New Zealand and Finland. Frequent co-authors include Monica M. McGill, Claudio Mirolo, Linda Mannila, Ljubomir Perković, Nataša Grgurina, Barbara Demo, Adrienne Decker, Lennart Rolandsson, Valentina Dagienė and Will Marrero. Their work appears in journals such as ACM Transactions on Computing Education, Theoretical Computer Science, International journal of doctoral studies, International Journal of Educational Research and Computer Science Education.

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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