Tanya Nazaretsky

906 total citations · 2 hit papers
12 papers, 389 citations indexed

About

Tanya Nazaretsky is a scholar working on Artificial Intelligence, Education and Computer Science Applications. According to data from OpenAlex, Tanya Nazaretsky has authored 12 papers receiving a total of 389 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 4 papers in Education and 3 papers in Computer Science Applications. Recurrent topics in Tanya Nazaretsky's work include Explainable Artificial Intelligence (XAI) (4 papers), Innovative Teaching and Learning Methods (3 papers) and Online Learning and Analytics (3 papers). Tanya Nazaretsky is often cited by papers focused on Explainable Artificial Intelligence (XAI) (4 papers), Innovative Teaching and Learning Methods (3 papers) and Online Learning and Analytics (3 papers). Tanya Nazaretsky collaborates with scholars based in Israel, Switzerland and United Kingdom. Tanya Nazaretsky's co-authors include Giora Alexandron, Mutlu Cukurova, Moriah Ariely, Tanja Käser, Jamie N. Mikeska, Beata Beigman Klebanov, Thiemo Wambsganß and Antoine Bosselut and has published in prestigious journals such as Journal of Research in Science Teaching, British Journal of Educational Technology and Journal of Computer Assisted Learning.

In The Last Decade

Tanya Nazaretsky

11 papers receiving 373 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Teachers' trust in AI ‐powered educational technology and a professional development program to improve it

2022 216 citations Tanya Nazaretsky, Moriah Ariely et al. British Journal of Educational Technology profile →
The critical role of trust in adopting AI-powered educational technology for learning: An instrument for measuring student perceptions

2025 17 citations Tanya Nazaretsky, Tanja Käser et al. Computers and Education Artificial Intelligence profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Tanya Nazaretsky Israel	7	189	139	92	74	60	12	389
Ha Ngan Ngo New Zealand	3	178 0.9×	138 1.0×	66 0.7×	93 1.3×	99 1.6×	4	418
William Man-Yin Cheung Hong Kong	6	225 1.2×	107 0.8×	55 0.6×	81 1.1×	76 1.3×	6	395
Moriah Ariely Israel	5	117 0.6×	88 0.6×	70 0.8×	50 0.7×	38 0.6×	8	269
Irene‐Angelica Chounta Germany	10	233 1.2×	100 0.7×	128 1.4×	81 1.1×	42 0.7×	42	431
Mehmet Haldun Kaya Türkiye	4	181 1.0×	198 1.4×	51 0.6×	63 0.9×	193 3.2×	9	471
Owolabi Paul Adelana Nigeria	6	173 0.9×	84 0.6×	111 1.2×	120 1.6×	27 0.5×	18	371
Maya Bialik	2	236 1.2×	156 1.1×	105 1.1×	104 1.4×	74 1.2×	3	474
Clare Baek United States	10	178 0.9×	69 0.5×	81 0.9×	47 0.6×	30 0.5×	16	338
Olga Mariño Colombia	8	156 0.8×	113 0.8×	70 0.8×	103 1.4×	41 0.7×	22	331
Arne Bewersdorff Germany	7	127 0.7×	92 0.7×	51 0.6×	55 0.7×	57 0.9×	18	286

Countries citing papers authored by Tanya Nazaretsky

Since Specialization

Citations

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

Fields of papers citing papers by Tanya Nazaretsky

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tanya Nazaretsky

This figure shows the co-authorship network connecting the top 25 collaborators of Tanya Nazaretsky. A scholar is included among the top collaborators of Tanya Nazaretsky based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tanya Nazaretsky. Tanya Nazaretsky is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

Nazaretsky, Tanya, et al.. (2025). The critical role of trust in adopting AI-powered educational technology for learning: An instrument for measuring student perceptions. Computers and Education Artificial Intelligence. 8. 100368–100368. 17 indexed citations breakdown →

Nazaretsky, Tanya, et al.. (2025). Who Gives Feedback Matters: Student Biases Towards Human and AI ‐Generated Formative Feedback. Journal of Computer Assisted Learning. 42(1).

Nazaretsky, Tanya, et al.. (2024). Enhancing Procedural Writing Through Personalized Example Retrieval: A Case Study on Cooking Recipes. International Journal of Artificial Intelligence in Education. 35(1). 330–366. 4 indexed citations

Ariely, Moriah, Tanya Nazaretsky, & Giora Alexandron. (2024). Causal‐mechanical explanations in biology: Applying automated assessment for personalized learning in the science classroom. Journal of Research in Science Teaching. 61(8). 1858–1889. 10 indexed citations

Nazaretsky, Tanya, et al.. (2024). Explainable AI for Unsupervised Machine Learning: A Proposed Scheme Applied to a Case Study with Science Teachers. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 436–444. 3 indexed citations

Nazaretsky, Tanya, Jamie N. Mikeska, & Beata Beigman Klebanov. (2023). Empowering Teacher Learning with AI: Automated Evaluation of Teacher Attention to Student Ideas during Argumentation-focused Discussion. 122–132. 9 indexed citations

Ariely, Moriah, Tanya Nazaretsky, & Giora Alexandron. (2022). Machine Learning and Hebrew NLP for Automated Assessment of Open-Ended Questions in Biology. International Journal of Artificial Intelligence in Education. 33(1). 1–34. 26 indexed citations

Nazaretsky, Tanya, Moriah Ariely, Mutlu Cukurova, & Giora Alexandron. (2022). Teachers' trust in AI ‐powered educational technology and a professional development program to improve it. British Journal of Educational Technology. 53(4). 914–931. 216 indexed citations breakdown →

Nazaretsky, Tanya, et al.. (2022). Empowering Teachers with AI: Co-Designing a Learning Analytics Tool for Personalized Instruction in the Science Classroom. 1–12. 27 indexed citations

10.

Nazaretsky, Tanya, Mutlu Cukurova, & Giora Alexandron. (2022). An Instrument for Measuring Teachers’ Trust in AI-Based Educational Technology. 56–66. 70 indexed citations

11.

Ariely, Moriah, Tanya Nazaretsky, & Giora Alexandron. (2020). First Steps Towards NLP-based Formative Feedback to Improve Scientific Writing in Hebrew. 1 indexed citations

12.

Nazaretsky, Tanya, et al.. (2019). Kappa Learning: A New Item-Similarity Method for Clustering Educational Items from Response Data.. Educational Data Mining. 6 indexed citations

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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