Gökhan Akçapınar

869 total citations
56 papers, 536 citations indexed

About

Gökhan Akçapınar is a scholar working on Computer Science Applications, Information Systems and Artificial Intelligence. According to data from OpenAlex, Gökhan Akçapınar has authored 56 papers receiving a total of 536 indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Computer Science Applications, 17 papers in Information Systems and 14 papers in Artificial Intelligence. Recurrent topics in Gökhan Akçapınar's work include Online Learning and Analytics (41 papers), Online and Blended Learning (10 papers) and Innovative Teaching and Learning Methods (10 papers). Gökhan Akçapınar is often cited by papers focused on Online Learning and Analytics (41 papers), Online and Blended Learning (10 papers) and Innovative Teaching and Learning Methods (10 papers). Gökhan Akçapınar collaborates with scholars based in Türkiye, Japan and Norway. Gökhan Akçapınar's co-authors include Hiroaki Ogata, Arif Altun, Petek Aşkar, Brendan Flanagan, Rwitajit Majumdar, Mehmet Kokoç, Hiroshi Ueda, Ivica Botički, Erkan Er and Kousuke Mouri and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computers & Education and Sensors.

In The Last Decade

Gökhan Akçapınar

52 papers receiving 505 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gökhan Akçapınar Türkiye 11 354 166 134 109 109 56 536
María Puerto Paule Ruiz Spain 12 369 1.0× 223 1.3× 168 1.3× 178 1.6× 129 1.2× 28 630
Pedro Manuel Moreno-Marcos Spain 13 582 1.6× 194 1.2× 188 1.4× 135 1.2× 76 0.7× 32 727
Rwitajit Majumdar Japan 13 394 1.1× 356 2.1× 125 0.9× 153 1.4× 214 2.0× 85 793
Katerina Mangaroska Norway 13 396 1.1× 207 1.2× 152 1.1× 128 1.2× 169 1.6× 26 615
Timo Hynninen Finland 9 285 0.8× 74 0.4× 113 0.8× 114 1.0× 92 0.8× 25 466
Sherif Halawa United States 9 394 1.1× 214 1.3× 105 0.8× 63 0.6× 82 0.8× 16 564
Si Na Kew Malaysia 16 234 0.7× 368 2.2× 93 0.7× 201 1.8× 127 1.2× 53 699
Ruth Cobos Spain 14 330 0.9× 197 1.2× 120 0.9× 176 1.6× 207 1.9× 70 635
Yeongwook Yang South Korea 13 263 0.7× 60 0.4× 186 1.4× 119 1.1× 172 1.6× 35 544
I‐Han Hsiao United States 14 438 1.2× 110 0.7× 227 1.7× 182 1.7× 232 2.1× 65 679

Countries citing papers authored by Gökhan Akçapınar

Since Specialization
Citations

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

Fields of papers citing papers by Gökhan Akçapınar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gökhan Akçapınar

This figure shows the co-authorship network connecting the top 25 collaborators of Gökhan Akçapınar. A scholar is included among the top collaborators of Gökhan Akçapınar 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 Gökhan Akçapınar. Gökhan Akçapınar 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.
Er, Erkan, et al.. (2024). Assessing student perceptions and use of instructor versus AI ‐generated feedback. British Journal of Educational Technology. 56(3). 1074–1091. 18 indexed citations
2.
Akçapınar, Gökhan, et al.. (2024). Investigating features that play a role in predicting gifted student engagement using machine learning: Video log and self-report data. Education and Information Technologies. 29(13). 16317–16343. 1 indexed citations
3.
Akçapınar, Gökhan, et al.. (2024). Decoding Video Logs: Unveiling Student Engagement Patterns in Lecture Capture Videos. The International Review of Research in Open and Distributed Learning. 25(2). 94–113.
4.
Akçapınar, Gökhan, et al.. (2024). AI chatbots in programming education: guiding success or encouraging plagiarism. SHILAP Revista de lepidopterología. 4(1). 7 indexed citations
5.
Khalil, Mohammad, et al.. (2023). Video Analytics in Digital Learning Environments: Exploring Student Behaviour Across Different Learning Contexts. Technology Knowledge and Learning. 29(4). 1877–1905. 6 indexed citations
6.
Akçapınar, Gökhan, et al.. (2023). Design and Development of an Interactive Video Player for Supporting Formative Assessment in Online Learning. Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi. 14(Özel Sayı). 320–331. 1 indexed citations
7.
Ilgaz, Hale, et al.. (2023). The Effects of Exam Setting on Students’ Test-Taking Behaviors and Performances: Proctored Versus Unproctored. The International Review of Research in Open and Distributed Learning. 24(4). 174–193.
8.
Akçapınar, Gökhan, et al.. (2023). Öğrenme analitiği sürecine yönelik modellere genel bir bakış: Kavramsal bir çerçeve önerisi. DergiPark (Istanbul University). 9(1). 92–117. 2 indexed citations
9.
Kokoç, Mehmet, et al.. (2021). Unfolding Students’ Online Assignment Submission Behavioral Patterns using Temporal Learning Analytics. SHILAP Revista de lepidopterología. 25 indexed citations
10.
Chen, Irene Y.L., et al.. (2021). Using a Summarized Lecture Material Recommendation System to Enhance Students' Preclass Preparation in a Flipped Classroom. Educational Technology & Society. 24(2). 1–13. 8 indexed citations
11.
12.
Flanagan, Brendan, et al.. (2019). Investigating Subpopulation of Students in Digital Textbook Reading Logs by Clustering. Kyoto University Research Information Repository (Kyoto University). 465–470. 3 indexed citations
13.
Akçapınar, Gökhan, et al.. (2019). Using Learning Analytics to Detect Off-Task Reading Behaviors in Class. Kyoto University Research Information Repository (Kyoto University). 471–476. 4 indexed citations
14.
Majumdar, Rwitajit, et al.. (2019). Learning Analytics Dashboard Widgets to Author Teaching-Learning Cases for Evidence-based Education. Kyoto University Research Information Repository (Kyoto University). 7 indexed citations
15.
Majumdar, Rwitajit, et al.. (2019). LAView: Learning Analytics Dashboard Towards Evidence-based Education. Kyoto University Research Information Repository (Kyoto University). 16 indexed citations
16.
Akçapınar, Gökhan, et al.. (2019). ÖĞRENCİLERİN STEM EĞİTİMİ TERCİHLERİNİN VERİ MADENCİLİĞİ YAKLAŞIMI ile TAHMİN EDİLMESİ. Eğitim Teknolojisi Kuram ve Uygulama. 9(1). 73–88. 4 indexed citations
17.
Flanagan, Brendan, et al.. (2018). Maintaining reading experience continuity across e-book revisions. Research and Practice in Technology Enhanced Learning. 13(1). 24–24. 2 indexed citations
18.
Ogata, Hiroaki, et al.. (2018). Beyond Learning Analytics: Framework for Technology-Enhanced Evidence-Based Education and Learning. Kyoto University Research Information Repository (Kyoto University). 493–496. 20 indexed citations
19.
Akçapınar, Gökhan. (2016). PREDICTING STUDENTS' APPROACHES TO LEARNING BASED ON MOODLE LOGS. EDULEARN proceedings. 1. 2347–2352. 6 indexed citations
20.
Akçapınar, Gökhan, Erdal Coşgun, & Arif Altun. (2011). Prediction of Perceived Disorientation in Online Learning Environment with Random Forest Regression.. Educational Data Mining. 259–264. 7 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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