| Asia Pacific Journal of Corpus Research Vol. 5, No. 1, pp. 23-36 |
| Abbreviation: APJCR |
| e-ISSN: 2733-8096 |
| Publication date: 31 August 2024 |
| Received: 22 April 2024 / Received in Revised Form: 7 August 2024 / Accepted: 13 August 2024 |
| DOI: https://doi.org/10.22925/apjcr.2024.5.1.23
|
Corpus of eye movements in L3 Spanish reading: A prediction model
|
| Hui-Chuan Lu (National Cheng Kung University), TAIWAN; Li-Chi Kao (National Cheng Kung University), TAIWAN; Zong-Han Li (National Cheng Kung University), TAIWAN; Wen-Hsiang Lu (National Cheng Kung University), TAIWAN; An-Chung Cheng (University of Toledo), USA |
| Copyright 2024 APJCR
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted, distribution, and reproduction in any medium, provided the original work is properly cited. |
Abstract |
| This research centers on the Taiwan Eye-Movement Corpus of Spanish (TECS), a specially created corpus comprising eye-tracking data from Chinese-speaking learners of Spanish as a third language in Taiwan. Its primary purpose is to explore the broad utility of TECS in understanding language learning processes, particularly the initial stages of language learning. Constructing this corpus involves gathering data on eye-tracking, reading comprehension, and language proficiency to develop a machine-learning model that predicts learner behaviors, and subsequently undergoes a predictability test for validation. The focus is on examining attention in input processing and their relationship to language learning outcomes. The TECS eye-tracking data consists of indicators derived from eye movement recordings while reading Spanish sentences with temporal references. These indicators are obtained from eye movement experiments focusing on tense verbal inflections and temporal adverbs. Chinese expresses tense using aspect markers, lexical references, and contextual cues, differing significantly from inflectional languages like Spanish. Chinese-speaking learners of Spanish face particular challenges in learning verbal morphology and tenses. The data from eye movement experiments were structured into feature vectors, with learner behaviors serving as class labels. After categorizing the collected data, we used two types of machine learning methods for classification and regression: Random Forests and the k-nearest neighbors algorithm (KNN). By leveraging these algorithms, we predicted learner behaviors and conducted performance evaluations to enhance our understanding of the nexus between learner behaviors and language learning process. Future research may further enrich TECS by gathering data from subsequent eye-movement experiments, specifically targeting various Spanish tenses and temporal lexical references during text reading. These endeavors promise to broaden and refine the corpus, advancing our understanding of language processing. |
Keywords |
| Corpus Development, Machine Learning, Input Processing, Second Language Acquisition, Eye-Tracking |
References |
| Barral, O., Lallé, S., Iranpour, A., & Conati, C. (2021). Effect of adaptive guidance and visualization literacy on gaze attentive behaviors and sequential patterns on magazine-style narrative visualizations. ACM Transactions on Interactive Intelligent Systems (TiiS), 11(3-4), 1-46.
Cheng, A. C., & Lu, H. C. (2022). A corpus analysis of temporal references and verb tenses cooccurrence in Spanish, English, and Chinese. Asia Pacific Journal of Corpus Research, 3(2), 1-16. da Silva Soares Jr, R., Oku, A. Y. A., Barreto, C. D. S. F., & Sato, J. R. (2023). Exploring the potential of eye tracking on personalized learning and real-time feedback in modern education. Progress in Brain Research, 282, 49-70. Dussias, P. E. (2010). Uses of eye-tracking data in second language sentence processing research. Annual Review of Applied Linguistics, 30, 149-166. Ellis, N. C., Hafeez, K., Martin, K. I., Chen, L., Boland, J., & Sagarra, N. (2014). An eye-tracking study of learned attention in Second Language Acquisition. Applied Psycholinguistics, 35(3), 547-579. Fix, E., & Hodges, J. L. (1951). Discriminatory Analysis, Nonparametric Discrimination: Consistency Properties. Texas: USAF School of Aviation Medicine. Gass, S. M., & Mackey, A. (2007). Input, interaction, and output in second language acquisition. In B. Vanpatten, & J. Williams (Eds.), Theories in Second Language Acquisition (pp. 175-200). London: Routledge. Guan, Y. H. (2020). Exploring the effects of phonological processing on foreign-language reading: An eye-tracking study for Chinese learners of Japanese-as-a-foreign language. Bulletin of Educational Psychology, 51(3), 483-504. Ho, T. K. (1998). The random subspace method for constructing decision forests. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(8), 832-844. Liu, T. S. W., Liu, Y. T., & Chen, C. Y. D. (2019). Meaningfulness is in the eye of the reader: Eye-tracking insights of L2 learners reading e-books and their pedagogical implications. Interactive Learning Environments, 27(2), 181-199. Parikh, S. S., & Kalva, H. (2020). Feature weighted linguistics classifier for predicting learning difficulty using eye tracking. ACM Transactions on Applied Perception, 17(2), 1-25. Rayner, K. (1998). Eye movements in reading and information processing: 20 years of research. Psychological Bulletin, 124(3), 372-422. Sagarra, N., & Ellis, N. C. (2013). From seeing adverbs to seeing verbal morphology: Language experience and adult acquisition of L2 tense. Studies in Second Language Acquisition, 35(2), 261-290. Sáiz-Manzanares, M. C., Pérez, I. R., Rodríguez, A. A., Arribas, S. R., Almeida, L., & Martin, C. F. (2021). Analysis of the learning process through eye-tracking technology and feature selection techniques. Applied Sciences, 11(13), 6157. Sweller, J. (1988). Cognitive load during problem-solving: Effects on learning. Cognitive Science, 12(2), 257-285. VanPatten, B. (1996). Input Processing and Grammar Instruction in Second Language Acquisition. New York: Ablex. VanPatten, B. (2002). Processing instruction: An update. Language Learning, 52, 755-804. VanPatten, B. (2007). Input Processing in Adult Second Language Acquisition. In B. VanPatten & J. Williams (Eds.), Theories in Second Language Acquisition: An Introduction (pp.115–135.) Mahwah: Lawrence Erlbaum Associates Publishers. Vasseur, A., Passalacqua, M., Senecal, S., & Leger, P. (2023). The use of eye-tracking in information systems research: A literature review of the last decade. AIS Transactions on Human-Computer Interaction, 15(3), 292-321. Zhan, Z., Zhang, L., Mei, H., & Fong, P. S. (2016). Online learners’ reading ability detection based on eye-tracking sensors. Sensors, 16(9), 1457. |
The Authors |
| Dr. Hui-Chuan Lu currently serves as a tenured professor within the Department of Foreign Languages and Literature at National Cheng Kung University in Taiwan, specializing in the fields of Spanish Linguistics, corpus linguistics, and syntax studies.
Li-Chi Kao is a part-time researcher at National Cheng Kung University. She will earn her master’s degree in computer science and information engineering in 2024. Zong-Han Li is a part-time researcher at National Cheng Kung University. He will earn his master’s degree in computer science and information engineering in 2025. Dr. Wen-Hsiang Lu is a tenured Professor at National Cheng Kung University. He earned his PhD in information engineering in 2003 at Chiao Tung University, Taiwan. His principal research lies in the field of natual language processing. Dr. An Chung Cheng is the Chair and professor of the Department of World Languages and Cultures and Director of the Asian Studies Insitute at the University of Toledo in the United States. |
The Authors’ Addresses |
| First and Corresponding Author Hui-Chuan Lu Professor National Cheng Kung University 1 University Road, Tainan, TAIWAN E-mail: hclu@mail.ncku.edu.twCo-authors Li-Chi Kao MA student National Cheng Kung University 1 University Road, Tainan, TAIWAN E-mail: joycem45@gmail.com Zong-Han Li Wen-Hsiang Lu An-Chung Cheng
|
