Identifying Great Teachers Through Their Online Presence

  • Evanthia FaliagkaEmail author
  • Maria Rigou
  • Spiros Sirmakessis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9881)


Evaluating candidate teachers is a very tricky task, as there are a lot of criteria -objective and not- that are important for identifying a good teacher. The teacher’s efficiency depends on the academic qualifications and experience, on teacher’s personality, even the students of the class and how well teaching and learning dynamically ‘grows’. In this work we propose a novel approach for teacher online evaluation. We implemented a prototype system which extracts values for a set of objective criteria from the teachers’ LinkedIn profile, and infers personality characteristics using linguistic analysis on their Facebook and Twitter posts. Machine learning algorithms were used to solve the final ranking problem.


E-recruitment systems Personality mining Personality traits Social web mining Recommendation systems Teacher evaluation 


  1. 1.
    De Raad, B., Schouwenburg, H.: Personality in learning and education: a review. Eur. J. Pers. 10, 303–336 (1996)CrossRefGoogle Scholar
  2. 2.
    Entwistle, N., Entwistle, D.: The relationships between personality, study methods and academic performance. Br. J. Educ. Psychol. 40, 132–143 (1970)CrossRefzbMATHGoogle Scholar
  3. 3.
    Amon, S., Reichel, N.: Who is the ideal teacher? Am I? Similarity and difference in perception of students of education regarding the qualities of a good teacher and of their own qualities as teachers. Teach. Teach.: Theory Pract. 13(5), 441–464 (2007)CrossRefGoogle Scholar
  4. 4.
    Goldstein, G., Benassi, V.: Students’ and instructors beliefs about excellent lecturers and discussion leaders. Res. High. Educ. 47(6), 685–707 (2006)CrossRefGoogle Scholar
  5. 5.
    Grieve, A.M.: Exploring the characteristics of “teachers for excellence:” teachers’ own perceptions. Eur. J. Teach. Educ. 33(3), 265–277 (2010)CrossRefGoogle Scholar
  6. 6.
    Montalvo, G., Mansfield, E., Miller, R.: Liking or disliking the teacher: student motivation, engagement and achievement. Eval. Res. Educ. 20(3), 144–158 (2007)CrossRefGoogle Scholar
  7. 7.
    Polk, J.A.: Traits of effective teachers. Arts Educ. Policy Rev. 107(4), 23–29 (2006)CrossRefGoogle Scholar
  8. 8.
    Beishuizen, J.J., Hof, E., Putten, C.M., van Bouwmeester, S., Asscher, J.J.: Students’ and teachers’ cognitions about good thinking. Br. J. Educ. Psychol. 71, 185–201 (2001)CrossRefGoogle Scholar
  9. 9.
    Hill, J.S., Christian, T.Y.: College student perceptions and ideals of teaching: an exploratory pilot study. Coll. Stud. J. 46(3), 589–601 (2012)Google Scholar
  10. 10.
    Kyriacou, C., Stephens, P.: Student teachers’ concerns during teaching practice. Eval. Res. Educ. 13(1), 18–31 (1999)CrossRefGoogle Scholar
  11. 11.
    Thibodeau, G.P., Hillman, S.J.: In retrospect: teachers who made a difference from the perspective of pre-service and experienced teachers. Education 124(1), 168–181 (2003)Google Scholar
  12. 12.
    Bennett, S.K.: Student perceptions of and expectations for male and female instructors: evidence relating to the question of gender bias in teaching evaluation. J. Educ. Psychol. 74, 170–179 (1982)CrossRefGoogle Scholar
  13. 13.
    Larsgaard, J.O., Charles, E., Kelso, J.R., Thomas, W., Schumacher, M.S.: Personality characteristics of teachers serving in Washington State Correctional Institutions. J. Correctional Educ. 49(1), 20–38 (1998)Google Scholar
  14. 14.
    Eilam, B., Vidergor, H.E.: Gifted Israeli students’ perceptions of teachers’ desired characteristics: a case of cultural orientation. Roeper Rev. 33, 86–96 (2011)CrossRefGoogle Scholar
  15. 15.
    Erdle, S., Murray, H.G., Rushton, J.P.: Personality, classroom behavior, and student ratings of college teaching effectiveness: a path analysis. J. Educ. Psychol. 77, 394–407 (1985)CrossRefGoogle Scholar
  16. 16.
    McCrae, R.R., Costa, P.T.: Personality in Adulthood. The Guilford Press, New York (2003)CrossRefGoogle Scholar
  17. 17.
    Neuman, C.: Prospero: a tool for organizing internet resources. Internet Res. 20, 408–419 (2010)CrossRefGoogle Scholar
  18. 18.
    Ho, L., Kuo, T., Lin, B.: Influence of online learning skills in cyberspace. Internet Res. 20, 55–71 (2010)CrossRefGoogle Scholar
  19. 19.
    Jansen, B., Jansen, K., Spink, A.: Using the web to look for work: implications for online job seeking and recruiting. Internet Res. 15, 49–66 (2005)CrossRefGoogle Scholar
  20. 20.
    Bizer, R.H., Rainer, E.: Impact of Semantic web on the job recruitment Process, Wirtschaftsinformatik. Physica-Verlag HD (2005)Google Scholar
  21. 21.
    Pande, S.: E-recruitment creates order out of chaos at SAT telecom: system cuts costs and improves efficiency. Hum. Resour. Manag. Int. Dig. 19, 21–23 (2011)CrossRefGoogle Scholar
  22. 22.
    Faliagka, E., Tsakalidis, A., Tzimas, G.: An integrated e-recruitment system for automated personality mining and applicant ranking. Internet Res. 22(5), 551–568 (2012)CrossRefGoogle Scholar
  23. 23.
    Faliagka, E., Iliadis, L., Karydis, I., Rigou, M., Sioutas, S., Tsakalidis, A., Tzimas, G.: On-line consistent ranking on e-recruitment: seeking the truth behind a well-formed CV. Artif. Intell. Rev. 42, 515–528 (2014)CrossRefGoogle Scholar
  24. 24.
    Faliagka, E., Rigou, M., Sirmakessis, S.: An e-recruitment system exploiting candidates’ social presence. In: Daniel, F., Diaz, O. (eds.). LNCS, vol. 9396, pp. 153–162. Springer, Heidelberg (2015). doi: 10.1007/978-3-319-24800-4_13 CrossRefGoogle Scholar
  25. 25.
    Pennebaker, J.W., King, L.A.: Linguistic styles: language use as an individual difference. J. Pers. Soc. Psychol. 77(6), 1296–1312 (1999)CrossRefGoogle Scholar
  26. 26.
    Eryilmaz, A.: Perceived personality traits and types of teachers and their relationship to the subjective well-being and academic achievements of adolescents. Educ. Sci.: Theory Pract. 14(6), 2049–2062 (2014)Google Scholar
  27. 27.
    Mairesse, F., Walker, M., Mehl, M., Moore, R.: Using linguistic cues for the automatic recognition of personality in conversation and text. J. Artif. Intell. Res. 30, 457–500 (2007)zbMATHGoogle Scholar
  28. 28.
    Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software: an update. ACM SIGKDD Explor. Newslett. 11(1), 10–18 (2009)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Evanthia Faliagka
    • 1
    Email author
  • Maria Rigou
    • 2
    • 3
  • Spiros Sirmakessis
    • 1
    • 3
  1. 1.Department of Computer and Informatics EngineeringTechnological Institution of Western GreeceAntirrioGreece
  2. 2.Department of Computer Engineering and InformaticsUniversity of PatrasPatrasGreece
  3. 3.Hellenic Open UniversityPatrasGreece

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