Daniel Zingaro

2.7k citations
70 papers · 1.7k indexed · h-index 25

Daniel Zingaro

69 papers receiving 1.6k citations

Peers

Daniel Zingaro
Comparison fields: 5 of 67
  • Computer Science Applications 1.2k
  • Media Technology 412
  • Developmental and Educational Psychology 557
  • Software 94
  • Education 714
Replace Leo Porter with:
Leo Porter United States
Geoffrey Herman United States
Anna Eckerdal Sweden
Yifat Ben‐David Kolikant Israel
Michelle Craig Canada
Quintin Cutts United Kingdom
Briana B. Morrison United States
Colleen M. Lewis United States
Miriam Ferzli United States
Charles Riedesel United States
Daniel Zingaro relative to Leo Porter United States Leo Porter's profile →
Citations per field
00.5×1.5×
Leo Porter · 1×
Citations per year

Countries citing papers authored by Daniel Zingaro

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Zingaro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20260
2 202510
3 20252
4 202410
5 202432
6 20243
7 202013
8 20207
9 201967
10 201950
11 20198
12 201814
13 201615
14 20164
15 201444
16
Peer instruction in CS: research and experience
20131
17 201387
18
Student Moderators in Asynchronous Online Discussion: A Question of Questions
201211
19
Peer instruction in the CS classroom: a hands-on introduction: conference tutorial
20111
20
Experience Report: Peer Instruction in Remedial Computer Science
201023

About Daniel Zingaro

Daniel Zingaro is a scholar working on Computer Science Applications, Media Technology and Developmental and Educational Psychology, having authored 70 papers that have together received 1.7k indexed citations. Recurring topics across this work include Teaching and Learning Programming (45 papers), Innovative Teaching Methods (31 papers), Experimental Learning in Engineering (22 papers), Online Learning and Analytics (20 papers), Innovative Teaching and Learning Methods (17 papers), Online and Blended Learning (8 papers), Educational Games and Gamification (5 papers) and Evolutionary Algorithms and Applications (4 papers). The work is most often cited by research in Computer Science Applications (1.2k citations), Media Technology (412 citations) and Developmental and Educational Psychology (557 citations). Daniel Zingaro has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Leo Porter, Andrew Petersen, Murat Öztok, Beth Simon, Michelle Craig, Cynthia Bailey Lee, Clare Brett, Jim Hewitt, Soohyun Nam Liao and Cynthia Taylor. Their work appears in journals such as ACM Transactions on Computing Education, British Journal of Educational Technology, Computers & Education, Online Learning and The Internet and Higher 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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