Jon Good

1.6k total citations · 1 hit paper
18 papers, 733 citations indexed

About

Jon Good is a scholar working on Computer Science Applications, Ecology and Developmental and Educational Psychology. According to data from OpenAlex, Jon Good has authored 18 papers receiving a total of 733 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Science Applications, 6 papers in Ecology and 5 papers in Developmental and Educational Psychology. Recurrent topics in Jon Good's work include Teaching and Learning Programming (9 papers), Physiological and biochemical adaptations (6 papers) and Fish Ecology and Management Studies (4 papers). Jon Good is often cited by papers focused on Teaching and Learning Programming (9 papers), Physiological and biochemical adaptations (6 papers) and Fish Ecology and Management Studies (4 papers). Jon Good collaborates with scholars based in United States, United Kingdom and Australia. Jon Good's 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 and has published in prestigious journals such as Journal of Fish Biology, Comparative Biochemistry and Physiology Part A Molecular & Integrative Physiology and Education and Information Technologies.

In The Last Decade

Jon Good

18 papers receiving 700 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Computational thinking in compulsory education: Towards an agenda for research and practice

2015 367 citations Joke Voogt, Petra Fisser et al. Education and Information Technologies profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jon Good United States	8	585	298	122	105	95	18	733
Ian Sanders South Africa	13	311 0.5×	165 0.6×	106 0.9×	129 1.2×	14 0.1×	63	586
Lihui Sun China	13	442 0.8×	256 0.9×	107 0.9×	82 0.8×	41 0.4×	28	555
Patricia Haden New Zealand	15	509 0.9×	281 0.9×	109 0.9×	137 1.3×	35 0.4×	24	645
Danhua Zhou China	10	317 0.5×	179 0.6×	77 0.6×	57 0.5×	33 0.3×	19	408
David L. Barr United Kingdom	9	282 0.5×	156 0.5×	102 0.8×	70 0.7×	46 0.5×	26	510
Lijun Ni United States	14	426 0.7×	205 0.7×	205 1.7×	111 1.1×	20 0.2×	34	595
Kelly Mills United States	11	158 0.3×	102 0.3×	99 0.8×	45 0.4×	42 0.4×	25	330
Jeongmin Lee South Korea	8	346 0.6×	149 0.5×	273 2.2×	105 1.0×	17 0.2×	20	704
Nathan Holbert United States	11	251 0.4×	178 0.6×	106 0.9×	66 0.6×	19 0.2×	33	446
Amanda Peel United States	12	186 0.3×	159 0.5×	187 1.5×	18 0.2×	79 0.8×	25	438

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-authorship network of co-authors of Jon Good

This figure shows the co-authorship network connecting the top 25 collaborators of Jon Good. A scholar is included among the top collaborators of Jon Good based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jon Good. Jon Good is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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18 of 18 papers shown

Voogt, Joke, Birgit Eickelmann, Aman Yadav, et al.. (2018). Learning and Teaching Computational Thinking – Challenges for Teacher Education. PUB – Publications at Bielefeld University (Bielefeld University). 57–60. 3 indexed citations

Yadav, Aman, et al.. (2018). Computational thinking in elementary classrooms: measuring teacher understanding of computational ideas for teaching science. Computer Science Education. 28(4). 371–400. 71 indexed citations

Good, Jon, Aman Yadav, & Punya Mishra. (2017). Computational Thinking in Computer Science Classrooms: Viewpoints from CS Educators. Society for Information Technology & Teacher Education International Conference. 51–59. 3 indexed citations

Good, Jon & Punya Mishra. (2016). Creativity as Resistance. TechTrends. 60(4). 309–312. 4 indexed citations

Lishinski, Alex, Aman Yadav, Richard Enbody, & Jon Good. (2016). The Influence of Problem Solving Abilities on Students' Performance on Different Assessment Tasks in CS1. 329–334. 29 indexed citations

Yadav, Aman, Marc Berges, Phil Sands, & Jon Good. (2016). Measuring computer science pedagogical content knowledge. 92–95. 25 indexed citations

Lishinski, Alex, Jon Good, Phil Sands, & Aman Yadav. (2016). Methodological Rigor and Theoretical Foundations of CS Education Research. 161–169. 29 indexed citations

Good, Jon. (2016). Computational Thinking as a Computer Science Education Framework and the Related Effects on Gender Equity. 277–278. 1 indexed citations

Lishinski, Alex, Aman Yadav, Jon Good, & Richard Enbody. (2016). Learning to Program. 211–220. 138 indexed citations

10.

Lee, John, David Hicks, Danah Henriksen, et al.. (2015). Historical Soundscapes for Creative Synthesis. TechTrends. 59(5). 4–8. 6 indexed citations

11.

Voogt, Joke, Petra Fisser, Jon Good, Punya Mishra, & Aman Yadav. (2015). Computational thinking in compulsory education: Towards an agenda for research and practice. Education and Information Technologies. 20(4). 715–728. 367 indexed citations breakdown →

12.

Henriksen, Danah, Jon Good, & Punya Mishra. (2014). Embodied Thinking as a Trans-disciplinary Habit of Mind. TechTrends. 59(1). 6–11. 7 indexed citations

13.

Good, Jon, Alan W. Wells, & Neil Hazon. (2008). Measurement of blood volume in the elasmobranch fish Scyliorhinus canicula following acute and long‐term salinity transfers. Journal of Fish Biology. 73(6). 1301–1313. 4 indexed citations

14.

Pillans, Richard D., Jon Good, W. Gary Anderson, Neil Hazon, & Craig E. Franklin. (2008). Rectal gland morphology of freshwater and seawater acclimated bull sharks Carcharhinus leucas. Journal of Fish Biology. 72(7). 1559–1571. 20 indexed citations

15.

Hazon, Neil, et al.. (2007). Osmoregulation in elasmobranch fish — A review. Comparative Biochemistry and Physiology Part A Molecular & Integrative Physiology. 146(4). S87–S87. 4 indexed citations

16.

Anderson, W. Gary, Jon Good, Craig E. Franklin, & Neil Hazon. (2003). Scaling of rectal gland mass in the European lesser-spotted dogfish. Journal of Fish Biology. 62(3). 749–751. 3 indexed citations

17.

Anderson, W. Gary, Jon Good, Craig E. Franklin, & Neil Hazon. (2003). Scaling of rectal gland mass in the European lesser‐spotted dogfish. Journal of Fish Biology. 62(3). 749–752. 3 indexed citations

18.

Anderson, W. Gary, Jon Good, & Neil Hazon. (2002). Changes in chloride secretion rate and vascular perfusion in the rectal gland of the European lesser‐spotted dogfish in response to environmental and hormonal stimuli. Journal of Fish Biology. 60(6). 1580–1590. 16 indexed citations

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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