Using Students’ Digital Written Text in Moroccan Dialect For The Detection of Student Personality Factors

Nisserine El Bahri; Zakaria Itahriouan; Anouar Abtoy; Samir Brahim Belhaouari

doi:10.23947/2334-8496-2023-11-3-389-400

Authors

Nisserine El Bahri Abdelmalek Essadi University, Tetouan, Morocco https://orcid.org/0000-0001-6204-8630
Zakaria Itahriouan Moulay Ismail University, Meknes, Morroco; Private University of Fez, Morroco https://orcid.org/0000-0001-6573-090X
Anouar Abtoy Abdelmalek Essadi University, Tetouan, Morocco https://orcid.org/0000-0002-7955-6719
Samir Brahim Belhaouari Hamad Bin Khalifa University, Doha, Qatar https://orcid.org/0000-0003-2336-0490

DOI:

https://doi.org/10.23947/2334-8496-2023-11-3-389-400

Keywords:

FFM personalities, social media learning environment, Moroccan dialect text

Abstract

In the contemporary digital era, social media platforms have a big influence on students’ lives. They use these platforms for self-expression, opinion sharing, and experience reporting (writing or sharing videos or photos about personal experiences) in addition to social interaction. Education professionals and academics may get valuable insights into students’ thoughts, sentiments, interests, academic success, and even personalities by studying their writing on social media. We can improve our teaching, enhance students’ social and emotional development, and create a more engaging learning environment if we have a better knowledge of the student. The purpose of this study is to ascertain whether or not students interact with classmates and other participants in learning platforms in a way that accurately represents their personalities. Data from a sample of students at Abdelmalek Essaadi University of Tetouan were collected from various social media learning environments for the experimental investigation presented in this work, and Symanto AI-based personality tool was used to assess the data. The Big Five Questionnaire was then utilized to assess the personalities of the same students, and the findings were compared to the personality traits discovered by the AI-based approach. The study has shown that the AI based tool has correctly predicted the personality traits of 7 students out of 10 with a correlation of about 0,9 which means that social media-based learning environments can be used by institutions to understand the personality of the student. This paper also gives recommendations about data for obtaining good quality in personality prediction.

Downloads

Download data is not yet available.

References

Barrot, J. S. (2022). Social media as a language learning environment: a systematic review of the literature (2008-2019). Computer assisted language learning, 35(9), 2534-2562. https://doi.org/10.1080/09588221.2021.188673 DOI: https://doi.org/10.1080/09588221.2021.1883673

Bronfenbrenner, U., (1951). Toward an integrated theory of personality, in: Perception: An Approach to Personality. Ronald Press Company, New York, NY, US, pp. 206–257. https://doi.org/10.1037/11505-008 DOI: https://doi.org/10.1037/11505-008

Caprara, G. V., Barbaranelli, C., Borgogni, L., & Perugini, M. (1993). The “Big Five Questionnaire”: A new questionnaire to assess the five factor model. Personality and individual Differences, 15(3), 281-288. https://doi.org/10.1016/0191-8869(93)90218-R DOI: https://doi.org/10.1016/0191-8869(93)90218-R

Christian, H., Suhartono, D., Chowanda, A., Zamli, K.Z. (2021). Text based personality prediction from multiple social media data sources using pre-trained language model and model averaging. Journal of Big Data 8, 68. https://doi.org/10.1186/s40537-021-00459-1

Christine Greenhow, Sarah M. Galvin, K. Bret Staudt Willet, (2019). What Should Be the Role of Social Media in Education? [WWW Document]. Retrieved from https://journals.sagepub.com/doi/abs/10.1177/2372732219865290 (accessed 9.5.2023).

Digman, J. M. (1990). Personality structure: Emergence of the five-factor model. Annual review of psychology, 41(1), 417-440. https://doi.org/10.1146/annurev.ps.41.020190.002221 DOI: https://doi.org/10.1146/annurev.ps.41.020190.002221

Hans, C., Suhartono, D., Andry, C., & Zamli, K. Z. (2021). Text based personality prediction from multiple social media data sources using pre-trained language model and model averaging. Journal of Big Data, 8(68). https://doi.org/10.1186/s40537-021-00459-1 DOI: https://doi.org/10.1186/s40537-021-00459-1

Eysenck, H. J. (1981). General features of the model. In A model for personality (pp. 1-37). Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-67783-0 DOI: https://doi.org/10.1007/978-3-642-67783-0_1

Eysenck, H. J. (1991). Dimensions of personality: The biosocial approach to personality. In Explorations in temperament: International perspectives on theory and measurement (pp. 87-103). Boston, MA: Springer US. https://doi.org/10.1007/978-1-4899-0643-4_7 DOI: https://doi.org/10.1007/978-1-4899-0643-4_7

Eysenck, H. J. (1994). The “Big Five” or “Giant 3”? Criteria for a paradigm. The developing structure of temperament and personality from infancy to adulthood. Hillsdale, NJ: Erlbaum.

Gjurković, M., Vukojević, I., & Šnajder, J. (2022). SIMPA: statement-to-item matching personality assessment from text. Future Generation Computer Systems, 130, 114-127. https://doi.org/10.1016/j.future.2021.12.014 DOI: https://doi.org/10.1016/j.future.2021.12.014

Greenhow, C., Galvin, S. M., & Staudt Willet, K. B. (2019). What should be the role of social media in education?. Policy Insights from the Behavioral and Brain Sciences, 6(2), 178-185. https://doi.org/10.1177/2372732219865290 DOI: https://doi.org/10.1177/2372732219865290

Josué, A., Bedoya-Flores, M. C., Mosquera-Quiñonez, E. F., Mesías-Simisterra, Á. E., & Bautista-Sánchez, J. V. (2023). Educational Platforms: Digital Tools for the teaching-learning process in Education. Ibero-American Journal of Education & Society Research, 3(1), 259-263. https://doi.org/10.56183/iberoeds.v3i1.626 DOI: https://doi.org/10.56183/iberoeds.v3i1.626

Namaziandost, E., & Nasri, M. (2019). The impact of social media on EFL learners’ speaking skill: a survey study involving EFL teachers and students. Journal of Applied Linguistics and Language Research, 6(3), 199-215. https://www.jallr.com/index.php/JALLR/article/view/1031

Pittenger, D. J. (1993). Measuring the MBTI… and coming up short. Journal of Career Planning and Employment, 54(1), 48-52. https://img3.reoveme.com/m/614576efb2b91676.pdf

Rahman, M. A., Al Faisal, A., Khanam, T., Amjad, M., & Siddik, M. S. (2019, May). Personality detection from text using convolutional neural network. In 2019 1st international conference on advances in science, engineering and robotics technology (ICASERT) (pp. 1-6). IEEE. https://doi.org/10.1109/ICASERT.2019.8934548 DOI: https://doi.org/10.1109/ICASERT.2019.8934548

See Yin Lim, J., Agostinho, S., Harper, B., & Chicharo, J. (2014). The engagement of social media technologies by undergraduate informatics students for academic purpose in Malaysia. Journal of Information, Communication and Ethics in Society, 12(3), 177-194. https://doi.org/10.1108/JICES-03-2014-0016 DOI: https://doi.org/10.1108/JICES-03-2014-0016

Sugerman, J. (2009). Using the DiSC® model to improve communication effectiveness. Industrial and Commercial Training, 41(3), 151-154. https://doi.org/10.1108/00197850910950952 DOI: https://doi.org/10.1108/00197850910950952

Swaminathan, T. N., Harish, A., & Cherian, B. (2013). Effect of social media outreach engagement in institutions of higher learning in India. Asia-Pacific Journal of Management Research and Innovation, 9(4), 349-357. https://doi.org/10.1177/2319510X14523101 DOI: https://doi.org/10.1177/2319510X14523101

Tlili, A., Essalmi, F., Jemni, M., & Chen, N. S. (2016). Role of personality in computer based learning. Computers in Human Behavior, 64, 805-813. https://doi.org/10.1016/j.chb.2016.07.043 DOI: https://doi.org/10.1016/j.chb.2016.07.043

Utami, E., Hartanto, A. D., Adi, S., Oyong, I., & Raharjo, S. (2022). Profiling analysis of DISC personality traits based on Twitter posts in Bahasa Indonesia. Journal of King Saud University-Computer and Information Sciences, 34(2), 264-269. https://doi.org/10.1016/j.jksuci.2019.10.008 DOI: https://doi.org/10.1016/j.jksuci.2019.10.008

Utami, N. A., Maharani, W., & Atastina, I. (2021). Personality classification of facebook users according to big five personality using SVM (support vector machine) method. Procedia Computer Science, 179, 177-184. https://doi.org/10.1016/j.procs.2020.12.023 DOI: https://doi.org/10.1016/j.procs.2020.12.023

Wickramanayake, L., & Muhammad Jika, S. (2018). Social media use by undergraduate students of education in Nigeria: A survey. The Electronic Library, 36(1), 21-37. https://doi.org/10.1108/EL-01-2017-0023 DOI: https://doi.org/10.1108/EL-01-2017-0023

Zhang, S. (2020, April). Psychoanalysis: The influence of Freud’s theory in personality psychology. In International Conference on Mental Health and Humanities Education (ICMHHE 2020) (pp. 229-232). Atlantis Press. https://doi.org/10.2991/assehr.k.200425.051 DOI: https://doi.org/10.2991/assehr.k.200425.051