Maya Usher

529 total citations · 1 hit paper
19 papers, 309 citations indexed

About

Maya Usher is a scholar working on Computer Science Applications, Education and Artificial Intelligence. According to data from OpenAlex, Maya Usher has authored 19 papers receiving a total of 309 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Science Applications, 5 papers in Education and 4 papers in Artificial Intelligence. Recurrent topics in Maya Usher's work include Online Learning and Analytics (5 papers), Ethics and Social Impacts of AI (3 papers) and Artificial Intelligence in Healthcare and Education (3 papers). Maya Usher is often cited by papers focused on Online Learning and Analytics (5 papers), Ethics and Social Impacts of AI (3 papers) and Artificial Intelligence in Healthcare and Education (3 papers). Maya Usher collaborates with scholars based in Israel, Sweden and Germany. Maya Usher's co-authors include Miri Barak, Arnon Hershkovitz, Alona Forkosh‐Baruch, Hossam Haick, Orly Fuhrman, Marc Jansen, Sibel Erduran, Ofra Amir, Ido Roll and Eytan Ruppin and has published in prestigious journals such as Computers & Education, British Journal of Educational Technology and Assessment & Evaluation in Higher Education.

In The Last Decade

Maya Usher

18 papers receiving 293 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.

Generative AI vs. instructor vs. peer assessments: a comparison of grading and feedback in higher education

2025 10 citations Maya Usher Assessment & Evaluation in Higher Education profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Maya Usher Israel	10	152	93	68	56	27	19	309
Yunjeong Chang United States	9	220 1.4×	117 1.3×	50 0.7×	80 1.4×	17 0.6×	21	356
Chrissi Nerantzi United Kingdom	9	239 1.6×	106 1.1×	59 0.9×	56 1.0×	13 0.5×	43	380
Stephanie Moore United States	9	154 1.0×	35 0.4×	57 0.8×	29 0.5×	21 0.8×	40	298
Jane S. Vogler United States	8	206 1.4×	47 0.5×	43 0.6×	75 1.3×	12 0.4×	13	292
Mustafa Çevik Türkiye	11	264 1.7×	40 0.4×	56 0.8×	55 1.0×	18 0.7×	45	379
Susie Gronseth United States	7	212 1.4×	59 0.6×	83 1.2×	41 0.7×	13 0.5×	22	321
Brett Bligh United Kingdom	11	270 1.8×	79 0.8×	105 1.5×	70 1.3×	22 0.8×	37	447
Jimmy Frèrejean Netherlands	8	221 1.5×	42 0.5×	49 0.7×	116 2.1×	17 0.6×	15	344
H Boulton United Kingdom	12	221 1.5×	61 0.7×	63 0.9×	92 1.6×	18 0.7×	27	341

Countries citing papers authored by Maya Usher

Since Specialization

Citations

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

Fields of papers citing papers by Maya Usher

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maya Usher

This figure shows the co-authorship network connecting the top 25 collaborators of Maya Usher. A scholar is included among the top collaborators of Maya Usher 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 Maya Usher. Maya Usher is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

19 of 19 papers shown

Usher, Maya, et al.. (2025). Who grades best? Comparing ChatGPT, peer, and instructor evaluations across varying levels of student project quality. Assessment & Evaluation in Higher Education. 1–20.

Usher, Maya, et al.. (2025). Integrating Generative AI into Programming Education: Student Perceptions and the Challenge of Correcting AI Errors. International Journal of Artificial Intelligence in Education. 35(5). 3166–3184. 3 indexed citations

Usher, Maya, et al.. (2025). From Prompt to Polished: Exploring Student–Chatbot Interactions for Academic Writing Assistance. Education Sciences. 15(3). 329–329. 7 indexed citations

Usher, Maya, Miri Barak, & Sibel Erduran. (2025). What role should higher education institutions play in fostering AI ethics? Insights from science and engineering graduate students. International Journal of STEM Education. 12(1). 3 indexed citations

Usher, Maya, et al.. (2025). Bridging Virtual and Physical. Journal of Learning Analytics. 12(2). 35–49. 1 indexed citations

Usher, Maya. (2025). Generative AI vs. instructor vs. peer assessments: a comparison of grading and feedback in higher education. Assessment & Evaluation in Higher Education. 50(6). 912–927. 10 indexed citations breakdown →

Usher, Maya, Ido Roll, Orly Fuhrman, & Ofra Amir. (2024). Supporting Coordination and Peer Editing in Students’ Online Collaborative Writing Processes. International Journal of Artificial Intelligence in Education. 35(3). 1504–1527. 2 indexed citations

Usher, Maya, et al.. (2024). Towards a call for transformative practices in academia enhanced by generative AI. European Journal of Open Distance and E-Learning. 26(S1). 20–34. 1 indexed citations

Usher, Maya & Miri Barak. (2024). Unpacking the role of AI ethics online education for science and engineering students. International Journal of STEM Education. 11(1). 31 indexed citations

10.

Usher, Maya & Arnon Hershkovitz. (2023). Data-driven Decisions of Higher Education Instructors in an Era of a Global Pandemic. Online Learning. 27(2). 3 indexed citations

11.

Usher, Maya & Arnon Hershkovitz. (2023). From guides to jugglers, from audience to outsiders: a metaphor analysis of synchronous hybrid learning. Learning Environments Research. 27(1). 1–16. 9 indexed citations

12.

Usher, Maya & Arnon Hershkovitz. (2022). Interest in Educational Data and Barriers to Data Use Among Massive Open Online Course Instructors. Journal of Science Education and Technology. 31(5). 649–659. 11 indexed citations

13.

Usher, Maya, Miri Barak, & Hossam Haick. (2021). Online vs. on-campus higher education: Exploring innovation in students' self-reports and students' learning products. Thinking Skills and Creativity. 42. 100965–100965. 16 indexed citations

14.

Barak, Miri & Maya Usher. (2021). The innovation level of engineering students’ team projects in hybrid and MOOC environments. European Journal of Engineering Education. 47(2). 299–313. 11 indexed citations

15.

Usher, Maya, Arnon Hershkovitz, & Alona Forkosh‐Baruch. (2021). From data to actions: Instructors' decision making based on learners' data in online emergency remote teaching. British Journal of Educational Technology. 52(4). 1338–1356. 37 indexed citations

16.

Usher, Maya & Miri Barak. (2019). Team diversity as a predictor of innovation in team projects of face-to-face and online learners. Computers & Education. 144. 103702–103702. 55 indexed citations

17.

Barak, Miri & Maya Usher. (2019). The innovation profile of nanotechnology team projects of face-to-face and online learners. Computers & Education. 137. 1–11. 26 indexed citations

18.

Usher, Maya & Miri Barak. (2017). Peer assessment in a project-based engineering course: comparing between on-campus and online learning environments. Assessment & Evaluation in Higher Education. 43(5). 745–759. 81 indexed citations

19.

Ruppin, Eytan & Maya Usher. (1990). An attractor neural network model of semantic fact retrieval. Network Computation in Neural Systems. 1(3). 325–344. 2 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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