David Lang

407 citations
20 papers · 205 · h-index 9

Impact in

Papers in

David Lang

20 papers receiving 201 citations

Peers

David Lang
Comparison fields: 5 of 59
  • Computer Science Applications 67
  • Developmental and Educational Psychology 47
  • Education 73
  • Artificial Intelligence 67
  • Modeling and Simulation 8
Replace Kimberly F. Colvin with:
Kimberly F. Colvin United States
Osama Swidan Israel
Elham Hussein United Arab Emirates
Lucrezia Crescenzi Lanna Spain
Hanxiang Du United States
Aida Suraya Md. Yunus Malaysia
Sumaya Daoud United Arab Emirates
Alan Bailin United States
Jesper Bruun Denmark
Brendan Eagan United States
David Lang relative to Kimberly F. Colvin United States Kimberly F. Colvin's profile →
Citations per field
00.5×1.5×
Kimberly F. Colvin · 1×
Citations per year

Countries citing papers authored by David Lang

Since Specialization
Citations

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

Fields of papers citing papers by David Lang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 202031
2 201931
3 202131
4 202222
5 202215
6 202113
7 202313
8
Predictors of student satisfaction: a large-scale study of human-human online tutorial dialogues
20199
9 20229
10 20237
11 20236
12 20226
13 20173
14
Changing Patterns of Growth in Oral Reading Fluency during the COVID-19 Pandemic. Working Paper.
20212
15 20212
16 20211
17
Making the Grade: How Learner Engagement Changes after Passing a Course.
20171
18 20201
19 20181
20 20201

About David Lang

David Lang is a scholar working on Artificial Intelligence, Computer Science Applications, Education, Developmental and Educational Psychology and Management Science and Operations Research, having authored 20 papers that have together received 205 indexed citations. Recurring topics across this work include Online Learning and Analytics (9 papers), Intelligent Tutoring Systems and Adaptive Learning (6 papers), Topic Modeling (6 papers), Foreign Language Teaching Methods (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Psychometric Methodologies and Testing (2 papers), Behavioral and Psychological Studies (1 paper) and Software Reliability and Analysis Research (1 paper). The work is most often cited by research in Computer Science Applications (67 citations), Developmental and Educational Psychology (47 citations), Education (73 citations), Artificial Intelligence (67 citations) and Modeling and Simulation (8 citations). David Lang has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Benjamin W. Domingue, Jason D. Yeatman, Andreas Paepcke, Guanling Chen, Heather J. Hough, Dragan Gašević, Guanliang Chen, Jionghao Lin, Robb Willer and Heather Hough. Their work appears in journals such as AERA Open, Journal of Experimental Political Science, Future Generation Computer Systems, IEEE Transactions on Learning Technologies and Science.

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