---
title: "LAK (A): papers and universities"
description: "LAK (International Conference on Learning Analytics and Knowledge) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 302 of its papers from 2024–2026 (95 in 2024, 101 in 2025, 106 in 2026). By the countries of the authors' institutions, the most papers come from the United States (144), Australia (62) and Germany (27)."
url: https://scholar4ai.com/proceedings/lak
markdown_url: https://scholar4ai.com/proceedings/lak.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "LAK (International Conference on Learning Analytics and Knowledge) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 302 of its papers from 2024–2026 (95 in 2024, 101 in 2025, 106 in 2026). (as of 2026-11-02)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-02T12:20:52+09:00
window: 2026-10-04 to 2026-11-02
source: OpenAlex (CC0)
---

# LAK: International Conference on Learning Analytics and Knowledge — papers and institutions, 2024–2026

Papers of LAK, International Conference on Learning Analytics and Knowledge (CORE rank A; field: Human-centred computing, Applied computing), 2024–2026: per year, the institutions, countries and topics, and the most-cited papers. Ranks are those of the CORE Conference Rankings, edition ICORE2026 (portal.core.edu.au), applied to every year shown. Papers are the works OpenAlex lists for the conference's proceedings, or for the issues of a conference-linked journal that publishes its papers (such as PACMPL, PVLDB or ACM TOG), by publication year; workshops, companion volumes, posters and Findings are left out. A paper counts once for each institution and country among its authors' affiliations as OpenAlex assigns them; papers without affiliations in OpenAlex count for none. For conferences published in book series that OpenAlex files as one source (LNCS, LIPIcs, SIAM and IOS Press proceedings), the papers are found by DOI: those of the volumes with the conference's title in Crossref, or LIPIcs DOIs, which name the conference. Conferences without DOIs (PMLR, USENIX, OpenReview) are listed without counts. A dash (–) for a year means OpenAlex has no papers of the conference for it yet: the proceedings are not published or indexed yet, or the conference did not meet that year (some meet every other year). 2026 counts what OpenAlex had indexed by 2026-11-02.

All conferences: https://scholar4ai.com/proceedings.md

## Key findings

- LAK (International Conference on Learning Analytics and Knowledge) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 302 of its papers from 2024–2026 (95 in 2024, 101 in 2025, 106 in 2026).
- By the countries of the authors' institutions, the most papers come from the United States (144), Australia (62) and Germany (27).
- The institutions with the most papers are Monash University (40), Carnegie Mellon University (34) and University of Pennsylvania (22).
- Its most-cited paper of these years is “Generative Artificial Intelligence in Learning Analytics: Contextualising Opportunities and Challenges through the Learning Analytics Cycle” (2024), with 113 citations.

## Papers per year

*LAK papers per publication year in OpenAlex (–: not in OpenAlex yet)*

| Year | Papers | With affiliations |
|---|---:|---:|
| 2024 | 95 | 94 |
| 2025 | 101 | 101 |
| 2026 | 106 | 104 |

## Sources

*Where OpenAlex lists the papers*

| OpenAlex source | Which papers |
|---|---|
| [S7407086742](https://openalex.org/S7407086742) | The conference's proceedings |

## Who publishes there

*Institutions with the most LAK papers, 2024–2026*

| # | Institution | Papers |
|---:|---|---:|
| 1 | [Monash University](https://scholar4ai.com/institutions/monash-university.md) | 40 |
| 2 | Carnegie Mellon University | 34 |
| 3 | University of Pennsylvania | 22 |
| 4 | University of Florida | 16 |
| 5 | [Peking University](https://scholar4ai.com/institutions/peking-university.md) | 14 |
| 6 | [University of Hong Kong](https://scholar4ai.com/institutions/university-of-hong-kong.md) | 11 |
| 7 | University of California, Irvine | 10 |
| 8 | [Stanford University](https://scholar4ai.com/institutions/stanford-university.md) | 10 |
| 9 | University of Bergen | 9 |
| 10 | University of Minnesota | 8 |

*Countries with the most LAK papers, 2024–2026*

| # | Country | Papers |
|---:|---|---:|
| 1 | United States | 144 |
| 2 | Australia | 62 |
| 3 | Germany | 27 |
| 4 | China | 24 |
| 5 | United Kingdom | 20 |
| 6 | Netherlands | 20 |
| 7 | Hong Kong | 17 |
| 8 | Canada | 11 |
| 9 | Norway | 11 |
| 10 | Japan | 10 |

*Keywords with the most LAK papers, 2024–2026*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | learning analytics | 87 |
| 2 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 50 |
| 3 | student engagement | 26 |
| 4 | student self-regulation | 26 |
| 5 | cooperative learning | 17 |
| 6 | [generative AI](https://scholar4ai.com/keywords/generative-ai.md) | 16 |
| 7 | learning outcomes | 16 |
| 8 | multimodal learning analytics | 13 |
| 9 | automated feedback | 12 |
| 10 | collaborative problem solving | 12 |

## Most-cited papers

*Most-cited LAK papers of 2024–2026 (citations counted by OpenAlex)*

| # | Citations | Title | Published | Authors |
|---:|---:|---|---|---|
| 1 | 113 | [Generative Artificial Intelligence in Learning Analytics: Contextualising Opportunities and Challenges through the Learning Analytics Cycle](https://doi.org/10.1145/3636555.3636856) | 2024-03-05 | Lixiang Yan, Roberto Martínez‐Maldonado, Dragan Gašević |
| 2 | 100 | [Human-AI Collaborative Essay Scoring: A Dual-Process Framework with LLMs](https://doi.org/10.1145/3706468.3706507) | 2025-02-21 | Changrong Xiao, Wenxing Ma, Qingping Song et al. |
| 3 | 75 | [Have Learning Analytics Dashboards Lived Up to the Hype? A Systematic Review of Impact on Students' Achievement, Motivation, Participation and Attitude](https://doi.org/10.1145/3636555.3636884) | 2024-03-05 | Rogers Kaliisa, Kamila Misiejuk, Sonsoles López‐Pernas et al. |
| 4 | 73 | [Can AI grade your essays? A comparative analysis of large language models and teacher ratings in multidimensional essay scoring](https://doi.org/10.1145/3706468.3706527) | 2025-02-21 | Kathrin Seßler, Maurice Fürstenberg, Babette Bühler et al. |
| 5 | 64 | [Automating Human Tutor-Style Programming Feedback: Leveraging GPT-4 Tutor Model for Hint Generation and GPT-3.5 Student Model for Hint Validation](https://doi.org/10.1145/3636555.3636846) | 2024-03-05 | Tung Phung, Victor-Alexandru Pădurean, Anjali Singh et al. |
| 6 | 61 | [Improving Student Learning with Hybrid Human-AI Tutoring: A Three-Study Quasi-Experimental Investigation](https://doi.org/10.1145/3636555.3636896) | 2024-03-05 | Danielle R. Thomas, Jionghao Lin, Erin E. Gatz et al. |
| 7 | 54 | [Transition Network Analysis: A Novel Framework for Modeling, Visualizing, and Identifying the Temporal Patterns of Learners and Learning Processes](https://doi.org/10.1145/3706468.3706513) | 2025-02-21 | Mohammed Saqr, Sonsoles López‐Pernas, Tiina Törmänen et al. |
| 8 | 42 | [Kattis vs ChatGPT: Assessment and Evaluation of Programming Tasks in the Age of Artificial Intelligence](https://doi.org/10.1145/3636555.3636882) | 2024-03-05 | Nora Dunder, Saga Lundborg, Jacqueline Wong et al. |
| 9 | 41 | [Automatic Short Answer Grading in the LLM Era: Does GPT-4 with Prompt Engineering beat Traditional Models?](https://doi.org/10.1145/3706468.3706481) | 2025-02-21 | Rafael Ferreira Mello, Cleon Pereira Junior, Luiz Rodrigues et al. |
| 10 | 41 | [Scaling While Privacy Preserving: A Comprehensive Synthetic Tabular Data Generation and Evaluation in Learning Analytics](https://doi.org/10.1145/3636555.3636921) | 2024-03-05 | Qinyi Liu, Mohammad Khalil, Jelena Jovanović et al. |

## Cite this page

Scholar4AI. (2026). LAK: International Conference on Learning Analytics and Knowledge — papers and institutions, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/lak

```bibtex
@misc{scholar4ai-proceedings-lak,
  author = {{Scholar4AI}},
  title = {LAK: International Conference on Learning Analytics and Knowledge — papers and institutions, 2024–2026},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/proceedings/lak}},
  urldate = {2026-11-02},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).