Timothy J. Hickey

1.5k citations
66 papers · 813 indexed · h-index 13
Topics
Teaching and Learning Programming (20 papers)Experimental Learning in Engineering (13 papers)Logic, programming, and type systems (11 papers)

In The Last Decade

Timothy J. Hickey

62 papers receiving 717 citations

Peers

Timothy J. Hickey
Comparison fields: 5 of 94
  • Artificial Intelligence 281
  • Computational Theory and Mathematics 222
  • Information Systems 130
  • Computer Science Applications 122
  • Software 112
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Countries citing papers authored by Timothy J. Hickey

Since Specialization
Citations

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

Fields of papers citing papers by Timothy J. Hickey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Timothy J. Hickey. 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 Timothy J. Hickey. The network helps show where Timothy J. Hickey may publish in the future.

Co-authorship network of co-authors of Timothy J. Hickey

This figure shows the co-authorship network connecting the top 25 collaborators of Timothy J. Hickey. A scholar is included among the top collaborators of Timothy J. Hickey 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 Timothy J. Hickey. Timothy J. Hickey is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 2
3
Early detection of at-risk students in CS1 using teachback/spinoza
13
4
Building Bridges between Science Courses Using Honors Organic Chemistry Projects.
2
5 6
6
The Spinoza code tutor: faculty poster abstract
2
7 6
8
Adaptive mediation in groupware
4
9 3
10
Enhancing CS programming lab courses using collaborative editors
12
11 0
12
Using Analytic CLP to Model and Analyze Hybrid Systems
4
13
Integrating tools and resources: a case study in building educational groupware for collaborative programming
11
14
Metalevel Interval Arithmetic and Verifiable Constraint Solving.
8
15
SILK - a playful blend of Scheme and Java
3
16 2
17
Functional Constraints in CLP Languages.
4
18 10
19
Partial evaluation of a CLP language
14
20 22

About Timothy J. Hickey

Timothy J. Hickey is a scholar working on Computer Science Applications, Software and Media Technology, having authored 66 papers that have together received 813 indexed citations. Recurring topics across this work include Teaching and Learning Programming (20 papers), Experimental Learning in Engineering (13 papers) and Logic, programming, and type systems (11 papers). The work is most often cited by research in Software (112 citations), Computer Science Applications (122 citations) and Computational Theory and Mathematics (222 citations). Timothy J. Hickey has collaborated with scholars based in United States, Saudi Arabia and Canada. Frequent co-authors include Jacques Cohen, M. H. van Emden, Astrid A. Prinz, Eve Marder, Adam L. Taylor, Donald A. Smith, Richard Alterman, Robert Sekuler, Barbara Shinn‐Cunningham and Mei‐Hua Hall. Their work appears in journals such as Journal of Neurophysiology, Communications of the ACM and Journal of the ACM.

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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