Yoav Bergner

1.2k citations
48 papers · 734 · h-index 13

Impact in

Papers in

Yoav Bergner

45 papers receiving 669 citations

Peers

Yoav Bergner
Comparison fields: 5 of 82
  • Computer Science Applications 501
  • Developmental and Educational Psychology 160
  • Education 227
  • Artificial Intelligence 225
  • Human-Computer Interaction 36
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David Joyner United States
Piotr Mitros United States
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Citations per field
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Citations per year

Countries citing papers authored by Yoav Bergner

Since Specialization
Citations

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

Fields of papers citing papers by Yoav Bergner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014173
2
Model-Based Collaborative Filtering Analysis of Student Response Data: Machine-Learning Item Response Theory
201266
3
Adapting Bayesian Knowledge Tracing to a Massive Open Online Course in edX
201351
4 201847
5
MOOC learner behaviors by country and culture; An exploratory analysis
201636
6
Language to Completion: Success in an Educational Data Mining Massive Open Online Class
201529
7 201627
8 202126
9
Methodological Challenges in the Analysis of MOOC Data for Exploring the Relationship between Discussion Forum Views and Learning Outcomes.
201524
10
Visualization and Confirmatory Clustering of Sequence Data from a Simulation-Based Assessment Task
201420
11 202216
12 202315
13 201414
14 202212
15
Communities of performance & communities of preference
201512
16 201912
17 201512
18 200411
19 201611
20 201910

About Yoav Bergner

Yoav Bergner is a scholar working on Computer Science Applications, Artificial Intelligence, Developmental and Educational Psychology, Education and Social Psychology, having authored 48 papers that have together received 734 indexed citations. Recurring topics across this work include Online Learning and Analytics (20 papers), Innovative Teaching and Learning Methods (9 papers), Teaching and Learning Programming (9 papers), Intelligent Tutoring Systems and Adaptive Learning (6 papers), Online and Blended Learning (6 papers), Innovative Human-Technology Interaction (4 papers), Team Dynamics and Performance (3 papers) and Psychometric Methodologies and Testing (3 papers). The work is most often cited by research in Computer Science Applications (501 citations), Developmental and Educational Psychology (160 citations), Education (227 citations), Artificial Intelligence (225 citations) and Human-Computer Interaction (36 citations). Yoav Bergner has collaborated with scholars based in United States, Ireland and Australia. Frequent co-authors include David E. Pritchard, Daniel Seaton, Isaac L. Chuang, Piotr Mitros, Alina A. von Davier, Ryan S. Baker, Gerd Kortemeyer, Luís M. A. Bettencourt, Saif Rayyan and Zachary A. Pardos. Their work appears in journals such as Journal of Learning Analytics, Educational Technology Research and Development, Psychometrika, Communications of the ACM and Statistics Education Research Journal.

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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