From Traditional Linguistics to Computational Linguistics. The Relevance of Digital Corpuses in Education
Marius OPINCARIU
Descriere autor:
Universitatea „Lucian Blaga” din Sibiu, Facultatea de Litere și Arte; Lucian Blaga University of Sibiu, Faculty of Letters and Arts
E-mail:
E-mail personal autor:
opincariugroup@gmail.com
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Rubrica:
Științele limbii
From Traditional Linguistics to Computational Linguistics.
The Relevance of Digital Corpuses in Education
Recent advances in natural language processing architectures open new opportunities for enhanced educational designs. From proto-linguistics to natural language processing, the new era of internet-linguistics facilitates significant progress in the fields of computational linguistics and annotated digital corpora. With the help of quantitative linguistics, digital text compositions gain increased relevance in contemporary educational discourse
analysis via computational semantics and word sense disambiguation. Digital linguistics may provide key performance indicators to fields such as higher education where written contributions are of critical importance.
Keywords: responsive e-learning, educational data mining, syntactic maps, cognitive curriculum calibration, affective curriculum calibration.
Abbasi Manshad Mohsin, and Anatoly Beltiukov. “Summarizing Emotions from Text Using Plutchik’s Wheel of Emotions.” Advances in Intelligent Systems Research, Vol. 166, 7th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS), 291 – 294. Paris: Atlantis Press, 2019.
Ademi, Neslihan, Suzana Loshkovska, and Slobodan Kalajdziski. “Prediction of Student Success Through Analysis of Moodle Logs: Case Study.” In Communications in Computer and Information Science 1110, Big Data Processing and Mining, 11th International Conference, Ohrid, North Macedonia, October 17–19, edited by S. Gievska and G. Madjarov, 27-40. Berlin: Springer, 2019.
Crosthwaite, Peter. Data-driven learning and younger learners: Introduction to the volume. In Crosthwaite (Ed.) Data-Driven Learning for the Next Generation: Corpora and DDL for pre-tertiary Learners. London: Routledge, 2019.
Despotovski, Filip, and Sonja Gievska. “An In-Depth Analysis of Personality Prediction.” Communications in Computer and Information Science 1110, Big Data Processing and Mining, 11th International Conference, Ohrid, North Macedonia, October 17–19, edited by S. Gievska and G. Madjarov, 134-147. Berlin: Springer 2019.
Balahur, Alexandra, Rada Mihalcea, and Andrés Montoyo. “Computational approaches to subjectivity and sentiment analysis: Present and envisaged methods and applications.” Computer Speech and Language 28 (2014): 1-6.
Banea, Carmen, Rada Mihalcea, Janyce Wiebe, and Samer Hassan. “Multilingual Subjectivity Analysis Using Machine Translation.” Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, 127-135. Honolulu: Association For Computational Linguistics, October 2008.
Cukurova, Mutlu, Rosemary Luckin, and Carmel Kent. “Impact of an Artificial Intelligence Research Frame on the Perceived Credibility of Educational Research Evidence.” International Journal of Artificial Intelligence in Education no. 30 (December 2019): 205-235.
Drăgulescu, Radu. “Online Media and New Technologies in Teaching Linguistic Disciplines.” Proceedings of the International Conference Globalization, Intercultural Dialogue and National Identity. Târgu-Mureș: Arhipelag XXI Press, 2014.
Drăgulescu, Radu. “Psycholinguistic and Neurolinguistic Approaches on Communicational Distorsions.” Proceedings of the International Conference Globalization, Intercultural Dialogue and National Identity. Târgu-Mureș: Arhipelag XXI Press, 2014.
Drăgulescu, Radu. “Qualitative Research on Learning Romanian as a Foreign Language in Endo-Linguistic Context.” Revista Transilvania no. 1 (2019): 73-81.
Drăgulescu, Radu. “Trends and new technologies in teaching and learning General Linguistics. Edmodo.” Intercultural Exchanges in the age of globalization, 568-575. Saarbrücken: LAP Lambert Academic Publishing, 2015.
Drăgulescu, Radu. “Observații Privind Anxietatea Învățării Limbii Române ca Limbă Străină și Comunicarea Interculturală.” Revista Transilvania no. 2 (2019): 84-90.
Drăgulescu Radu. “Considerații privind Statutul Limbii Române ca Limbă Maternă, Limbă Secundară și Limbă Străină.” Revista Transilvania, no. 11-12 (2017): 83-89.
Graham, Steve. “Writers in Community Model: 15 Recommendations for Future Research in Using Writing to Promote Science Learning.” In Theorizing the Future of Science Education Research, edited by V. Prain, and B. Hand. Switzerland: Springer Nature AG, 2019.
Ilkka, Tuomi. The Impact of Artificial Intelligence on Learning, Teaching, and Education. JRC Science for Policy Report. Edited by Marcelino Cabrera, Riina Vuorikari, and Yves Punie, 1-42. Luxembourg: Publications Office of the European Union, JRC Science for Policy Report, 2018.
Joel, Martin, Rada Mihalcea, and Ted Pedersen. “Word Alignment for Languages with Scarce Resources.” Proceedings of the ACL Workshop on Building and Using Parallel Texts. Ann Arbor, MI, Association for Computational Linguistics (June 2005): 65–74.
Ponti, Edoardo Maria et al. “Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing”. Computational Linguistics 45 (6) (2019): 1-43.
Salajan, Florin D., and Jules D. Tavis. Introduction: The Educational Intelligent Economy. In Educational Intelligence and Big Data in The Educational Intelligent Economy: Big Data, Artificial Intelligence, Machine Learning and the Internet of Things in Education, edited by Florin D. Salajan, and Jules D. Tavis. Bingley: Emerald Publishing Limited, 2020.
Schulz, Eric, Maarten Speekenbrink, and Andreas Krause. “A tutorial on Gaussian Process Regression: Modelling, Exploring, and Exploiting Functions.” Journal of Mathematical Psychology, no. 85 (2018): 1-16.
Strapparava, Carlo, and Rada Mihalcea. “SemEval-2007 Task 14: Affective Text.” Proceedings of the 4th International Workshop on Semantic Evaluations. Prague: Association for Computational Linguistics, 2007.
Szmrecsanyi, Benedikt, and Laura Rosseel. English Corpus Linguistics: The Current State-of-the-Art, and a Critical Appraisal. Leuven: Katholieke Universiteit Leuven, 2019.
Tang Kok-Sing. “Scientific Practices as an Actor-Network of Literacy Events: Forging a convergence Between Disciplinary Literacy and Scientific Practices.” In Theorizing the Future of Science Education Research, Contemporary Trends and Issues in
Science Education Vol. 49, edited by V. Prain, and B. Hand 83-98. Switzerland: Springer Nature, 2019.
Toshevska, Martina and Slobodan Kalajdziski. Exploring the Attention Mechanism in Deep Models: A Case Study on Sentiment Analysis. In Communications in Computer and Information Science 1110, Big Data Processing and Mining, 11th International
Conference, Ohrid, North Macedonia, October 17–19, edited by S. Gievska and G. Madjarov. Berlin: Springer 2019.
Webb, Paul, and Bill J. W. Whitlow. “Merging Cognitive and Sociocultural Approaches: Toward Better Understandings of the Processes of Developing Thinking and Reasoning.” In Theorizing the Future of Science Education Research, Contemporary Trends and Issues in Science Education, edited by V. Prain, and B. Hand. Switzerland: Springer Nature, 2019.
Wilson, Steven R., and Rada Mihalcea. “Predicting Human Activities from User-Generated Content.” arXiv:1907.08540v1 [cs.CL] (19 Jul 2019): 1-11.