Sam Cunningham

27 papers receiving 265 citations

Peers

Sam Cunningham
Comparison fields: 5 of 73
  • Health Informatics 21
  • Computer Science Applications 81
  • Artificial Intelligence 89
  • Education 74
  • Soil Science 22
Replace Katharine Welsh with:
Katharine Welsh United Kingdom
Terence Day Canada
Yanping Song China
Sithara H. P. W. Gamage Australia
Karsten Maurer United States
Judy Lambert United States
Alex Gekker Netherlands
Jennifer L. Snyder United States
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Citations per field
00.5×3.9×
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Citations per year

Countries citing papers authored by Sam Cunningham

Since Specialization
Citations

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

Fields of papers citing papers by Sam Cunningham

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A review of chatbots in education: Practical steps forward
201950
2 201949
3 201645
4 201625
5 202022
6 202122
7 202013
8 202213
9 19589
10 20235
11 20235
12 20234
13
Visually exploring sentiment and keywords for analysing student satisfaction data
20184
14 20183
15
Linking numerical scores with sentiment analysis of students' teaching and subject evaluation surveys: Pointers to teaching enhancements
20163
16 19973
17
Coverage-based next best view selection
20152
18
Visualising student satisfaction
20172
19
Pointers to Conceptual Understanding
20172
20 20241

About Sam Cunningham

Sam Cunningham is a scholar working on Education, Information Systems, Artificial Intelligence, Media Technology and Computer Science Applications, having authored 32 papers that have together received 290 indexed citations. Recurring topics across this work include Evaluation of Teaching Practices (5 papers), Engineering Education and Curriculum Development (4 papers), Advanced Text Analysis Techniques (4 papers), Educational Assessment and Pedagogy (3 papers), Student Assessment and Feedback (3 papers), Sentiment Analysis and Opinion Mining (3 papers), Biomedical and Engineering Education (3 papers) and Online Learning and Analytics (3 papers). The work is most often cited by research in Health Informatics (21 citations), Computer Science Applications (81 citations), Artificial Intelligence (89 citations), Education (74 citations) and Soil Science (22 citations). Sam Cunningham has collaborated with scholars based in Australia, United States and Tanzania. Frequent co-authors include Wageeh Boles, Mahsa Baktashmotlagh, Lori S. Bennear, Martin D. Smith, Abby Cathcart, Les Dawes, Howard Stein, Kelly Askew, Faustin Maganga and Rie Odgaard. Their work appears in journals such as Student Success, Assessment & Evaluation in Higher Education, The Journal of Development Studies, Australasian Journal of Educational Technology and IEEE Transactions on Learning Technologies.

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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