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This study examines the impact of academic supervision on teacher performance in educational research from 2014 to 2023 using bibliometric analysis. This study used the Scopus database and the PRISMA method to search for relevant literature on academic supervision and teacher performance. The analysis used includes WordCloud, word frequency, topic trends, and thematic evolution to analyze journals and conference proceedings. This study highlights the importance of academic supervision in improving teacher performance, with a focus on knowledge development and knowledge transfer. The application of technologies, such as computer vision and convolutional neural networks, can also improve teacher performance. Gender differences in the research approach indicate the need for more in-depth analysis. This research also explores the integration of technology and language analysis, with a focus on network architecture and machine learning. However, this study has limitations, including bibliometric data that does not cover all important aspects and linguistic bias. The results suggest that academic supervision has a significant role in improving teacher performance and modern technology can be an effective tool in this process. This research encourages further development in the use of technology to support academic supervision and teacher performance.


Academic Supervision Business Performance Bibliometric Analysis Education Research Technology Integration

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How to Cite
Warman, W., Sitorus, E. R. B., Handayani, N., Widiayati, W., & Utomo, A. P. (2024). Bibliometric Analysis of the Impact of Academic Supervision on Teacher Performance in Educational Research. Sang Pencerah: Jurnal Ilmiah Universitas Muhammadiyah Buton, 10(2), 452–467. Retrieved from


  1. Ansar, R. 2015. “Measuring the Performance of School Superintendent.” Journal of Education and Practice 6(2):103–8.
  2. Baas, Jeroen, Michiel Schotten, Andrew Plume, Grégoire Côté, and Reza Karimi. 2020. “Scopus as a Curated, High-Quality Bibliometric Data Source for Academic Research in Quantitative Science Studies.” Quantitative Science Studies 1(1):377–86. doi: 10.1162/qss_a_00019.
  3. Bastalich, Wendy. 2017. “Content and Context in Knowledge Production: A Critical Review of Doctoral Supervision Literature.” Studies in Higher Education 42(7):1145–57. doi: 10.1080/03075079.2015.1079702.
  4. Boehe, Dirk Michael. 2016. “Supervisory Styles: A Contingency Framework.” Studies in Higher Education 41(3):399–414. doi: 10.1080/03075079.2014.927853.
  5. Borders, L. Di Anne, and Lori L. Brown. 2022. The New Handbook of Counseling Supervision. Routledge.
  6. Derrington, Mary Lynne, and John W. Campbell. 2015. “Implementing New Teacher Evaluation Systems: Principals’ Concerns and Supervisor Support.” Journal of Educational Change 16(3):305–26. doi: 10.1007/s10833-015-9244-6.
  7. Fahd, Kiran, Sitalakshmi Venkatraman, Shah J. Miah, and Khandakar Ahmed. 2022. “Application of Machine Learning in Higher Education to Assess Student Academic Performance, at-Risk, and Attrition: A Meta-Analysis of Literature.” Education and Information Technologies 27(3):3743–75. doi: 10.1007/s10639-021-10741-7.
  8. Flores, Maria Assunção, and Mary Lynne Derrington. 2018. “Improving Teacher Evaluation: Key Issues for Appraisers in a Globalised Era.” Teachers and Teaching: Theory and Practice 24(3):203–8.
  9. Gacs, Adam, Senta Goertler, and Shannon Spasova. 2020. “Planned Online Language Education versus Crisis-Prompted Online Language Teaching: Lessons for the Future.” Foreign Language Annals 53(2):380–92. doi: 10.1111/flan.12460.
  10. Gibson, Carter, Jay H. Hardy, and M. Ronald Buckley. 2014. “Understanding the Role of Networking in Organizations.” Career Development International 19(2):146–61. doi: 10.1108/CDI-09-2013-0111.
  11. Grimmett, Peter P., and E. Patricia Crehan. 2014. “The Nature of Collegiality in Teacher Development: The Case of Clinical Supervision.” Pp. 56–85 in Teacher Development and Educational Change. Routledge.
  12. Guarino, Cassandra M., and Victor M. H. Borden. 2017. “Faculty Service Loads and Gender: Are Women Taking Care of the Academic Family?” Research in Higher Education 58(6):672–94. doi: 10.1007/s11162-017-9454-2.
  13. Jennings, Jennifer L., and Jonathan Marc Bearak. 2014. “‘Teaching to the Test’ in the NCLB Era: How Test Predictability Affects Our Understanding of Student Performance.” Educational Researcher 43(8):381–89. doi: 10.3102/0013189X14554449.
  14. Kahu, Ella R., and Karen Nelson. 2018. “Student Engagement in the Educational Interface: Understanding the Mechanisms of Student Success.” Higher Education Research and Development 37(1):58–71. doi: 10.1080/07294360.2017.1344197.
  15. Kemmis, Stephen, Hannu L. T. Heikkinen, Göran Fransson, Jessica Aspfors, and Christine Edwards-Groves. 2014. “Mentoring of New Teachers as a Contested Practice: Supervision, Support and Collaborative Self-Development.” Teaching and Teacher Education 43:154–64. doi: 10.1016/j.tate.2014.07.001.
  16. Khan, Anupam, and Soumya K. Ghosh. 2021. “Student Performance Analysis and Prediction in Classroom Learning: A Review of Educational Data Mining Studies.” Education and Information Technologies 26(1):205–40. doi: 10.1007/s10639-020-10230-3.
  17. Kraft, Matthew A., David Blazar, and Dylan Hogan. 2018. “The Effect of Teacher Coaching on Instruction and Achievement: A Meta-Analysis of the Causal Evidence.” Review of Educational Research 88(4):547–88. doi: 10.3102/0034654318759268.
  18. Kristiawan, Muhammad, Dewi Kartini, Happy Fitria, Sma Negeri, and Muara Sugihan. 2020. “The Influence of Principal’s Leadership, Academic Supervision, and Professional Competence toward Teachers’ Performance Mapping Managerial Competence of Primary School Principals in South Sumatera View Project The Influence of Principal’s Leadership, Academic Supervision, and Professional Competence toward Teachers’ Performance.” International Journal of Progressive Sciences and Technologies (IJPSAT) 20(1):156–64.
  19. Lam, Shui fong, Shane Jimerson, Hyeonsook Shin, Carmel Cefai, Feliciano H. Veiga, Chryse Hatzichristou, Fotini Polychroni, Eve Kikas, Bernard P. H. Wong, Elena Stanculescu, Julie Basnett, Robert Duck, Peter Farrell, Yi Liu, Valeria Negovan, Brett Nelson, Hongfei Yang, and Josef Zollneritsch. 2016. “Cultural Universality and Specificity of Student Engagement in School: The Results of an International Study from 12 Countries.” British Journal of Educational Psychology 86(1):137–53. doi: 10.1111/bjep.12079.
  20. Law, Kris M. Y., Shuang Geng, and Tongmao Li. 2019. “Student Enrollment, Motivation and Learning Performance in a Blended Learning Environment: The Mediating Effects of Social, Teaching, and Cognitive Presence.” Computers and Education 136:1–12. doi: 10.1016/j.compedu.2019.02.021.
  21. Lawelai, Herman, Iswanto Iswanto, and Nia Maharani Raharja. 2023. “Use of Artificial Intelligence in Public Services: A Bibliometric Analysis and Visualization.” TEM Journal 12(2):798–807. doi: 10.18421/TEM122-24.
  22. Li, Zhuang Shuang, and Felicity Hasson. 2020. “Resilience, Stress, and Psychological Well-Being in Nursing Students: A Systematic Review.” Nurse Education Today 90:104440. doi: 10.1016/j.nedt.2020.104440.
  23. Liebowitz, David D., and Lorna Porter. 2019. “The Effect of Principal Behaviors on Student, Teacher, and School Outcomes: A Systematic Review and Meta-Analysis of the Empirical Literature.” Review of Educational Research 89(5):785–827. doi: 10.3102/0034654319866133.
  24. Mashhadlou, Haleh, and Siros Izadpanah. 2021. “Assessing Iranian EFL Teachers’ Educational Performance Based on Gender and Years of Teaching Experience.” Language Testing in Asia 11(1):23. doi: 10.1186/s40468-021-00140-7.
  25. Mclean, Leigh, and Carol Mcdonald Connor. 2015. “Depressive Symptoms in Third-Grade Teachers: Relations to Classroom Quality and Student Achievement.” Child Development 86(3):945–54. doi: 10.1111/cdev.12344.
  26. Meurers, Detmar, and Markus Dickinson. 2017. “Evidence and Interpretation in Language Learning Research: Opportunities for Collaboration With Computational Linguistics.” Language Learning 67(S1):66–95. doi: 10.1111/lang.12233.
  27. Miranda-González, Andrea, Samin Aref, Tom Theile, and Emilio Zagheni. 2020. “Scholarly Migration within Mexico: Analyzing Internal Migration among Researchers Using Scopus Longitudinal Bibliometric Data.” EPJ Data Science 9(1):34. doi: 10.1140/epjds/s13688-020-00252-9.
  28. Moulding, Louise R., Penée W. Stewart, and Megan L. Dunmeyer. 2014. “Pre-Service Teachers’ Sense of Efficacy: Relationship to Academic Ability, Student Teaching Placement Characteristics, and Mentor Support.” Teaching and Teacher Education 41:60–66.
  29. Nkrumah, Maame Afua. 2018. “The Relevance of Teacher Factors in Understanding Tertiary Students’ Performances.” Quality Assurance in Education 26(4):476–88. doi: 10.1108/QAE-02-2018-0017.
  30. da Silva, Carlos Eduardo M. Viega., Rubens Nunes, and Elisabete Maria Macedo Viegas. 2018. “A Genealogy of the Brazilian Scientific Research on Freshwater Fish Farming by Means of the Academic Supervision Linkage.” Scientometrics 117(3):1535–53. doi: 10.1007/s11192-018-2940-2.
  31. Sunaryo, Yohanes. 2020. “Academic Supervision of School Principals and Teacher Performance: A Literature Review.” International Journal Pedagogy of Social Studies 5(2):17–34.
  32. Susanti, S., D. Wardiah, and B. Lian. 2020. “Effect of Academic Supervision of School Heads and School Culture on Quality Teaching Teachers.” International Journal of Progressive Sciences and Technologies 20(1):67–77.
  33. Tampubolon, Khairuddin, and Nunti Sibuea. 2023. “The Influence of Supervisory Work Motivation and Competence on the Performance of School Superintendents in Padangsidimpuan City Education Office.” International Journal of Educational Review 3(21):1–13.
  34. Yang, Xinyuan, Li Jen Kuo, Xuejun Ji, and Erin McTigue. 2018. “A Critical Examination of the Relationship among Research, Theory, and Practice: Technology and Reading Instruction.” Computers and Education 125:62–73. doi: 10.1016/j.compedu.2018.03.009.