Jon Good

1.7k citations
25 papers · 1.3k · 1 hit paper · h-index 13

Impact in

Papers in

Jon Good

25 papers receiving 1.2k citations

Jon Good's Hit Papers

Computational thinking in compulsory education: Towards an agenda for research and practice 2015 · 488 citations
4880+3+7Years since publication100200300400

Peers

Jon Good
Comparison fields: 5 of 77
  • Computer Science Applications 1.0k
  • Developmental and Educational Psychology 501
  • Gender Studies 113
  • Software 50
  • Media Technology 99
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Citations per field
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Citations per year

Countries citing papers authored by Jon Good

Since Specialization
Citations

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

Fields of papers citing papers by Jon Good

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Computational thinking in compulsory education: Towards an agenda for research and practice
Hit paper breakdown →
2015488
2 2016152
3 2017144
4 201883
5 201682
6 201877
7 201668
8 201637
9 200933
10 201628
11 200824
12 200222
13 201817
14 20149
15 20155
16
Computational Thinking in Computer Science Classrooms: Viewpoints from CS Educators
20174
17 20164
18 20084
19 20074
20 20073

About Jon Good

Jon Good is a scholar working on Computer Science Applications, Developmental and Educational Psychology, Nature and Landscape Conservation, Ecology and Aquatic Science, having authored 25 papers that have together received 1.3k indexed citations. Recurring topics across this work include Teaching and Learning Programming (14 papers), Evolutionary Algorithms and Applications (6 papers), Physiological and biochemical adaptations (6 papers), Online Learning and Analytics (6 papers), Fish Ecology and Management Studies (4 papers), Innovative Teaching and Learning Methods (3 papers), Aquaculture Nutrition and Growth (3 papers) and Educational Games and Gamification (3 papers). The work is most often cited by research in Computer Science Applications (1.0k citations), Developmental and Educational Psychology (501 citations), Gender Studies (113 citations), Software (50 citations) and Media Technology (99 citations). Jon Good has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Aman Kumar Yadav, Petra Fisser, Joke M. Voogt, Punya Mishra, Alex Lishinski, Phil Sands, Richard J. Enbody, Sarah Gretter, Christina Krist and Neil Hazon. Their work appears in journals such as Journal of Fish Biology, TechTrends, The Journal of Strength and Conditioning Research, Computer Science Education and Medicine & Science in Sports & Exercise.

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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