Susan Bergin

1.3k citations
34 papers · 793 · h-index 14

Impact in

Papers in

Susan Bergin

34 papers receiving 756 citations

Peers

Susan Bergin
Comparison fields: 5 of 61
  • Computer Science Applications 659
  • Developmental and Educational Psychology 288
  • Software 53
  • Gender Studies 109
  • Health Informatics 12
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Citations per field
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Citations per year

Countries citing papers authored by Susan Bergin

Since Specialization
Citations

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

Fields of papers citing papers by Susan Bergin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 19 scholars most cited alongside Susan Bergin, 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 Susan Bergin Line = papers co-authored together Susan Bergin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005161
2 2005150
3 200567
4 201956
5 200655
6 201845
7 201633
8 201728
9 202023
10
Using Machine Learning Techniques to Predict IntroductoryProgramming Performance
201518
11 201615
12 201815
13
Automated assessment in CS1
200614
14
PreSS#, A Web-Based Educational System to Predict ProgrammingPerformance
201514
15
Programming: Further Factors that Influence Success.
201612
16
An Overview of the Integration of Problem Based Learning into an existing Computer Science Programming Module
200411
17 201910
18 20038
19 20118
20
Facilitating student learning in Computer Science: large class sizes and interventions
20158

About Susan Bergin

Susan Bergin is a scholar working on Computer Science Applications, Education, Developmental and Educational Psychology, Gender Studies and Media Technology, having authored 34 papers that have together received 793 indexed citations. Recurring topics across this work include Teaching and Learning Programming (21 papers), Online Learning and Analytics (11 papers), Gender and Technology in Education (7 papers), Experimental Learning in Engineering (6 papers), Educational Games and Gamification (5 papers), Innovative Teaching and Learning Methods (3 papers), Innovative Teaching Methods (2 papers) and Open Education and E-Learning (2 papers). The work is most often cited by research in Computer Science Applications (659 citations), Developmental and Educational Psychology (288 citations), Software (53 citations), Gender Studies (109 citations) and Health Informatics (12 citations). Susan Bergin has collaborated with scholars based in Ireland and United Kingdom. Frequent co-authors include Richard B. Reilly, Keith Quille, Keith Nolan, Aidan Mooney, Carole Mockford, Brett A. Becker, J. Paul Gibson, John G. Keating, James F. Power and Thomas J. Whelan. Their work appears in journals such as Computer Science Education, Artificial Intelligence Review, British Journal of Community Nursing, Journal of Software Maintenance and Evolution Research and Practice and ARROW@Dublin Institute of Technology (Dublin Institute of Technology).

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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