Lawrence J. Najjar

14 papers receiving 401 citations

Peers

Lawrence J. Najjar
Comparison fields: 5 of 85
  • Education 178
  • Developmental and Educational Psychology 133
  • Experimental and Cognitive Psychology 103
  • Computer Vision and Pattern Recognition 67
  • Human-Computer Interaction 66
Replace Eric A. Domeshek with:
Eric A. Domeshek United States
Patricia Baggett United States
Yu‐Hung Chien Taiwan
Niall Seery Ireland
John Bell United States
Lynna J. Ausburn United States
Dirk Börner Netherlands
Eleni Berki Finland
Elisabeth Etopio United States
Mike Wald United Kingdom
Lawrence J. Najjar relative to Eric A. Domeshek United States Eric A. Domeshek's profile →
Citations per field
00.5×2.6×
Eric A. Domeshek · 1×
Citations per year

Countries citing papers authored by Lawrence J. Najjar

Since Specialization
Citations

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

Fields of papers citing papers by Lawrence J. Najjar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lawrence J. Najjar

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

All Works

14 of 14 papers shown
#WorkIndexed citations
1 12
2 7
3 22
4 57
5 7
6 130
7 10
8 202
9
Factory automation support technology (FAST)
3
10
The Effects of Multimedia and Elaborative Encoding on Learning
17
11
Does Multimedia Information Help People Learn
4
12
Dual Coding as a Possible Explanation for the Effects of Multimedia on Learning
13
13
A Review of the Fundamental Effects of Multimedia Information Presentation on Learning
9
14 2

About Lawrence J. Najjar

Lawrence J. Najjar is a scholar working on Experimental and Cognitive Psychology, Human-Computer Interaction and Developmental and Educational Psychology, having authored 14 papers that have together received 495 indexed citations. Recurring topics across this work include Visual and Cognitive Learning Processes (6 papers), Intelligent Tutoring Systems and Adaptive Learning (4 papers) and Online and Blended Learning (2 papers). The work is most often cited by research in Human-Computer Interaction (66 citations), Computer Science Applications (58 citations) and Developmental and Educational Psychology (133 citations). Lawrence J. Najjar has collaborated with scholars based in United States and China. Frequent co-authors include Christopher D. Thompson, Robert W. Proctor, Misha W. Vaughan, Eric Rogers, Gavriel Salvendy, Kim‐Phuong L. Vu, Gregory M. Corso and Michael J. Patterson. Their work appears in journals such as Communications of the ACM, Human Factors The Journal of the Human Factors and Ergonomics Society and Computers in Industry.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026