Bor Gregorcic

760 total citations · 1 hit paper
36 papers, 477 citations indexed

About

Bor Gregorcic is a scholar working on Education, Developmental and Educational Psychology and Artificial Intelligence. According to data from OpenAlex, Bor Gregorcic has authored 36 papers receiving a total of 477 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Education, 15 papers in Developmental and Educational Psychology and 9 papers in Artificial Intelligence. Recurrent topics in Bor Gregorcic's work include Innovative Teaching and Learning Methods (9 papers), Science Education and Pedagogy (8 papers) and Education and Technology Integration (7 papers). Bor Gregorcic is often cited by papers focused on Innovative Teaching and Learning Methods (9 papers), Science Education and Pedagogy (8 papers) and Education and Technology Integration (7 papers). Bor Gregorcic collaborates with scholars based in Sweden, Slovenia and United States. Bor Gregorcic's co-authors include Ann-Marie Pendrill, Eugenia Etkina, Gorazd Planinšič, John Airey, Cedric Linder, Stamatis Vokos, Filip Heijkenskjöld, Jesper Haglund, Raimund Girwidz and Andréas Müller and has published in prestigious journals such as SHILAP Revista de lepidopterología, International Journal of Science Education and Research in Science Education.

In The Last Decade

Bor Gregorcic

31 papers receiving 458 citations

Hit Papers

ChatGPT and the frustrated Socrates 2023 2026 2024 2025 2023 20 40 60

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bor Gregorcic Sweden 14 224 142 112 64 64 36 477
Konstantinos Τ. Kotsis Greece 12 291 1.3× 165 1.2× 76 0.7× 77 1.2× 117 1.8× 153 593
Benjamin D. Nye United States 10 70 0.3× 159 1.1× 264 2.4× 60 0.9× 183 2.9× 34 505
Mustafa Fidan Türkiye 11 329 1.5× 107 0.8× 80 0.7× 211 3.3× 101 1.6× 34 674
Shelley Yeo Australia 11 362 1.6× 137 1.0× 16 0.1× 33 0.5× 22 0.3× 18 590
Irene‐Angelica Chounta Germany 10 128 0.6× 89 0.6× 100 0.9× 81 1.3× 233 3.6× 42 431
Xianmin Yang China 14 259 1.2× 158 1.1× 51 0.5× 199 3.1× 117 1.8× 28 579
Jun Oshima Japan 11 233 1.0× 305 2.1× 40 0.4× 60 0.9× 158 2.5× 49 477
Farshid Marbouti United States 10 277 1.2× 152 1.1× 138 1.2× 60 0.9× 347 5.4× 37 584
Rianne Conijn Netherlands 11 351 1.6× 188 1.3× 171 1.5× 135 2.1× 417 6.5× 29 784
Lisa-Angelique Lim Australia 12 251 1.1× 172 1.2× 76 0.7× 49 0.8× 310 4.8× 29 502

Countries citing papers authored by Bor Gregorcic

Since Specialization
Citations

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

Fields of papers citing papers by Bor Gregorcic

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bor Gregorcic

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

All Works

20 of 20 papers shown
1.
Gregorcic, Bor. (2025). Do AI-generated videos obey physics laws?. Physics Education. 60(6). 65001–65001.
2.
Gregorcic, Bor, et al.. (2025). Creating a customisable Socratic AI physics tutor. Physics Education. 60(6). 65037–65037.
3.
Widenhorn, Ralf, et al.. (2025). Multilingual performance of a multimodal artificial intelligence system on multisubject physics concept inventories. Physical Review Physics Education Research. 21(2). 7 indexed citations
4.
Gregorcic, Bor, et al.. (2025). Multimodal large language models and physics visual tasks: comparative analysis of performance and costs. European Journal of Physics. 46(5). 55708–55708. 1 indexed citations
5.
Gregorcic, Bor, et al.. (2024). Performance of ChatGPT on the test of understanding graphs in kinematics. Physical Review Physics Education Research. 20(1). 34 indexed citations
6.
Gregorcic, Bor, et al.. (2024). Performance of freely available vision-capable chatbots on the test for understanding graphs in kinematics. KTH Publication Database DiVA (KTH Royal Institute of Technology). 336–341. 1 indexed citations
7.
Gregorcic, Bor, et al.. (2024). Exploring student reasoning in statistical mechanics: Identifying challenges in problem-solving groups. Physical Review Physics Education Research. 20(1).
8.
Gregorcic, Bor, et al.. (2024). ChatGPT as a tool for honing teachers’ Socratic dialogue skills. Physics Education. 59(4). 45005–45005. 15 indexed citations
9.
Gregorcic, Bor & Ann-Marie Pendrill. (2023). ChatGPT and the frustrated Socrates. Physics Education. 58(3). 35021–35021. 69 indexed citations breakdown →
10.
Kersting, Magdalena, et al.. (2023). What Is the Role of the Body in Science Education? A Conversation Between Traditions. Science & Education. 33(5). 1171–1210. 9 indexed citations
11.
Gregorcic, Bor, et al.. (2023). How understanding large language models can inform the use of ChatGPT in physics education. European Journal of Physics. 45(2). 25701–25701. 63 indexed citations
12.
Gregorcic, Bor, et al.. (2020). Learning to use Cartesian coordinate systems to solve physics problems: the case of ‘movability’. European Journal of Physics. 41(4). 45701–45701. 10 indexed citations
13.
Airey, John, et al.. (2020). Developing representational competence: linking real-world motion to physics concepts through graphs. Learning Research and Practice. 6(1). 88–107. 21 indexed citations
14.
Airey, John, et al.. (2019). Transduction and Science Learning: Multimodality in the Physics Laboratory. SHILAP Revista de lepidopterología. 11(1). 16–29. 28 indexed citations
15.
Girwidz, Raimund, Hendrik Jan Pol, Marisa Michelini, et al.. (2019). Physics teaching and learning with multimedia applications: a review of teacher-oriented literature in 34 local language journals from 2006 to 2015. International Journal of Science Education. 41(9). 1181–1206. 15 indexed citations
16.
Gregorcic, Bor, et al.. (2018). Exploring how physics students use a sandbox software to move between the physical and the formal. KTH Publication Database DiVA (KTH Royal Institute of Technology). 128–131. 3 indexed citations
17.
Airey, John, et al.. (2018). Physics students learning about abstract mathematical tools when engaging with �invisible� phenomena. KTH Publication Database DiVA (KTH Royal Institute of Technology). 408–411. 5 indexed citations
18.
Gregorcic, Bor & Jesper Haglund. (2018). Conceptual Blending as an Interpretive Lens for Student Engagement with Technology: Exploring Celestial Motion on an Interactive Whiteboard. Research in Science Education. 51(2). 235–275. 13 indexed citations
19.
Gregorcic, Bor, Eugenia Etkina, & Gorazd Planinšič. (2017). A New Way of Using the Interactive Whiteboard in a High School Physics Classroom: A Case Study. Research in Science Education. 48(2). 465–489. 30 indexed citations
20.
Gregorcic, Bor, Eugenia Etkina, & Gorazd Planinšič. (2015). Designing and Investigating New Ways of Interactive Whiteboard Use in Physics Instruction. The Physics Video Demonstration Database (Cornell University). 107–110. 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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