Jon Good

1.6k citations
18 papers · 733 · 1 hit paper · h-index 8

Impact in

Papers in

Jon Good

18 papers receiving 700 citations

Jon Good's Hit Papers

Computational thinking in compulsory education: Towards an agenda for research and practice 2015 · 367 citations
3670+3+7Years since publication100200300

Peers

Jon Good
Comparison fields: 5 of 65
  • Computer Science Applications 585
  • Developmental and Educational Psychology 298
  • Software 36
  • Gender Studies 76
  • Media Technology 50
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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 24 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

18 of 18 papers shown
#Work
1
Computational thinking in compulsory education: Towards an agenda for research and practice
Hit paper breakdown →
2015367
2 2016138
3 201871
4 201629
5 201629
6 201625
7 200820
8 200216
9 20147
10 20156
11 20164
12 20084
13 20074
14
Computational Thinking in Computer Science Classrooms: Viewpoints from CS Educators
20173
15
Learning and Teaching Computational Thinking – Challenges for Teacher Education
20183
16 20033
17 20033
18 20161

About Jon Good

Jon Good is a scholar working on Computer Science Applications, Ecology, Developmental and Educational Psychology, Nature and Landscape Conservation and Artificial Intelligence, having authored 18 papers that have together received 733 indexed citations. Recurring topics across this work include Teaching and Learning Programming (9 papers), Physiological and biochemical adaptations (6 papers), Online Learning and Analytics (4 papers), Evolutionary Algorithms and Applications (4 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 (2 papers). The work is most often cited by research in Computer Science Applications (585 citations), Developmental and Educational Psychology (298 citations), Software (36 citations), Gender Studies (76 citations) and Media Technology (50 citations). Jon Good has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Aman Yadav, Punya Mishra, Joke Voogt, Petra Fisser, Alex Lishinski, Richard Enbody, Christina Krist, Phil Sands, Neil Hazon and W. Gary Anderson. Their work appears in journals such as Journal of Fish Biology, TechTrends, Comparative Biochemistry and Physiology Part A Molecular & Integrative Physiology, Education and Information Technologies 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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