Lele Sha

966 citations
15 papers · 452 · 1 hit paper · h-index 8

Impact in

Papers in

Lele Sha

13 papers receiving 433 citations

Lele Sha's Hit Papers

Practical and ethical challenges of large language models in education: A systematic scoping review 2023 · 288 citations
2880+1+2Years since publication50100150200250

Peers

Lele Sha
Comparison fields: 5 of 67
  • Health Informatics 127
  • Computer Science Applications 159
  • Artificial Intelligence 246
  • Safety Research 60
  • Developmental and Educational Psychology 50
Replace Yueqiao Jin with:
Yueqiao Jin Australia
Linxuan Zhao Australia
Mehmet Haldun Kaya Türkiye
Ricardo Thierry-Aguilera Mexico
Xinyu Li Australia
William Man-Yin Cheung Hong Kong
Sambhav Gupta India
Arne Bewersdorff Germany
Maya Bialik
Duane Searsmith United States
Lele Sha relative to Yueqiao Jin Australia Yueqiao Jin's profile →
Citations per field
00.5×3.7×
Yueqiao Jin · 1×
Citations per year

Countries citing papers authored by Lele Sha

Since Specialization
Citations

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

Fields of papers citing papers by Lele Sha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1
Practical and ethical challenges of large language models in education: A systematic scoping review
Hit paper breakdown →
2023288
2 202353
3 202236
4 202316
5 202113
6 20229
7 20239
8 20248
9 20247
10
Which Hammer should I Use? A Systematic Evaluation of Approaches for Classifying Educational Forum Posts
20217
11 20243
12 20222
13 20251
14 20260
15 20250

About Lele Sha

Lele Sha is a scholar working on Artificial Intelligence, Computer Science Applications, Developmental and Educational Psychology, Health Informatics and Safety Research, having authored 15 papers that have together received 452 indexed citations. Recurring topics across this work include Online Learning and Analytics (7 papers), Topic Modeling (5 papers), Innovative Teaching and Learning Methods (3 papers), Artificial Intelligence in Healthcare and Education (2 papers), Imbalanced Data Classification Techniques (2 papers), Machine Learning and Data Classification (2 papers), Text Readability and Simplification (2 papers) and Business Process Modeling and Analysis (1 paper). The work is most often cited by research in Health Informatics (127 citations), Computer Science Applications (159 citations), Artificial Intelligence (246 citations), Safety Research (60 citations) and Developmental and Educational Psychology (50 citations). Lele Sha has collaborated with scholars based in Australia, Saudi Arabia and United Kingdom. Frequent co-authors include Dragan Gašević, Guanliang Chen, Yuheng Li, Lixiang Yan, Linxuan Zhao, Xinyu Li, Roberto Martínez‐Maldonado, Yueqiao Jin, Mladen Raković and Jionghao Lin. Their work appears in journals such as IEEE Transactions on Learning Technologies, British Journal of Educational Technology, Behaviour and Information Technology, Computers and Education Artificial Intelligence and Expert Systems with Applications.

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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