Andrew Lan

63 papers receiving 847 citations

Hit Papers

Context-Aware Attentive Knowledge Tracing 2020 · 219 citations
219202020262022202450100150200

Peers

Andrew Lan
Comparison fields: 5 of 75
  • Computer Science Applications 419
  • Computational Mathematics 13
  • Artificial Intelligence 664
  • Information Systems 178
  • Developmental and Educational Psychology 99
Replace Xiangyu Song with:
Xiangyu Song China
Jianwen Sun China
Radek Pelánek Czechia
Ghadah Aldabbagh Saudi Arabia
Da Cao China
Patrik Floréen Finland
Fabiano Cutigi Ferrari Brazil
Abhimanu Kumar United States
Tiantian Wang China
Andrea Mocci Switzerland
Andrew Lan relative to Xiangyu Song China Xiangyu Song's profile →
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Citations per year

Countries citing papers authored by Andrew Lan

Since Specialization
Citations

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

Fields of papers citing papers by Andrew Lan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 68 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Context-Aware Attentive Knowledge Tracing
Hit paper breakdown →
2020219
2 201487
3 201442
4 201541
5
A Contextual Bandits Framework for Personalized Learning Action Selection.
201639
6 201839
7 202132
8 202027
9 201824
10 201421
11
Behavior-based latent variable model for learner engagement
201720
12 202119
13 202117
14 201815
15 202214
16
Grade Prediction Based on Cumulative Knowledge and Co-taken Courses.
201913
17 201913
18 202212
19 201712
20 202311

About Andrew Lan

Andrew Lan is a scholar working on Computer Science Applications, Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition and Developmental and Educational Psychology, having authored 68 papers that have together received 882 indexed citations. Recurring topics across this work include Intelligent Tutoring Systems and Adaptive Learning (25 papers), Online Learning and Analytics (24 papers), Topic Modeling (16 papers), Natural Language Processing Techniques (8 papers), Educational Technology and Assessment (7 papers), Machine Learning and Data Classification (7 papers), Machine Learning and Algorithms (7 papers) and Recommender Systems and Techniques (5 papers). The work is most often cited by research in Computer Science Applications (419 citations), Computational Mathematics (13 citations), Artificial Intelligence (664 citations), Information Systems (178 citations) and Developmental and Educational Psychology (99 citations). Andrew Lan has collaborated with scholars based in United States, United Kingdom and Taiwan. Frequent co-authors include Richard G. Baraniuk, Aritra Ghosh, Neil T. Heffernan, Christoph Studer, Andrew E. Waters, Mung Chiang, Christopher G. Brinton, Zichao Wang, Phillip J. Grimaldi and Xia Ning. Their work appears in journals such as International Journal of Artificial Intelligence in Education, IEEE Journal of Selected Topics in Signal Processing, Knowledge-Based Systems, IEEE Internet of Things Journal and Signal Processing.

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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