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Vocabulary recommendation approach for forced migrants using informal language learning tools

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Abstract

Learning a new language is a major challenge faced by many forced migrants. Current vocabulary learning curricula are not adapted to the migrants’ needs, which makes the learning process even more challenging. Today, the widespread use of smartphones among forced migrants provides us with new opportunities to collect and recommend the vocabulary they need. In this work, we propose a demographic- and content-based vocabulary recommendation approach that considers the migrant’s status, migration stage, and vocabulary themes. Based on our approach, the vocabulary recommended to a forced migrant belongs to the same theme as the vocabulary that other forced migrants in the same migration stage chose to learn. The approach was evaluated with 37 Syrian refugees in Lebanon and Germany that used SCROLL, an informal language learning tool, to learn their target language. We compared the learning achievement and motivation of the participants when they learned the recommended vocabulary and the standard textbook vocabulary. Our results showed that the proposed vocabulary recommendation approach resulted in higher learning achievement for refugees in Germany and higher motivation levels for refugees in Germany and Lebanon. Tailored vocabulary recommendation approaches showed potential to improve the language learning experience of forced migrants and warrant further study.

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The data used in this paper are available here: https://drive.google.com/file/d/1_SmUe1O59Mkm7Xi_0_LDoXEQfZqIAKwu/view?usp=sharing.

References

  1. Brooker, A., Lawrence, J., Dodds, A.: Using digital concept maps to distinguish between young Refugees’ challenges. J. Interact. Media Educ. (2017). https://doi.org/10.5334/jime.433

    Article  Google Scholar 

  2. Bach, R.L., Carroll-Seguin, R.: Labor force participation, household composition and sponsorship among Southeast Asian refugees. Int. Migrat. Rev. 20, 381–404 (1986). https://doi.org/10.1177/019791838602000214

    Article  Google Scholar 

  3. Morrice, L., Tip, L.K., Collyer, M., Brown, R.: ‘You can’t have a good integration when you don’t have a good communication’: English-language learning among resettled refugees in England. J. Refug. Stud. (2019). https://doi.org/10.1093/jrs/fez023

    Article  Google Scholar 

  4. Alqahtani, M.: The importance of vocabulary in language learning and how to be taught. Int. J. Teach. Educ. 3, 21–34 (2015). https://doi.org/10.20472/TE.2015.3.3.002

    Article  Google Scholar 

  5. Nation, P.: New Ways in Teaching Vocabulary. New Ways in TESOL Series: Innovative Classroom Techniques. TESOL (1994)

  6. Nation, P.: Vocabulary size, growth, and use. Biling. Lexicon (1993). https://doi.org/10.1075/sibil.6.07nat

    Article  Google Scholar 

  7. He, X., Godfroid, A.: Choosing words to teach: a novel method for vocabulary selection and its practical application. TESOL Q. 53, 348–371 (2019). https://doi.org/10.1002/tesq.483

    Article  Google Scholar 

  8. Adolphs, S., Schmitt, N.: Lexical coverage of spoken discourse. Appl. Linguist. 24, 425–438 (2003). https://doi.org/10.1093/applin/24.4.425

    Article  Google Scholar 

  9. Brezina, V., Gablasova, D.: Is there a core general vocabulary? Introducing the new general service list. Appl. Linguist. 36, 1–22 (2015). https://doi.org/10.1093/applin/amt018

    Article  Google Scholar 

  10. Tollefson, J.W.: Functional competencies in the US refugee program: theoretical and practical problems. TESOL Q. 20, 649–664 (1986). https://doi.org/10.2307/3586516

    Article  Google Scholar 

  11. AbuJarour, S., Krasnova, H.: Understanding the role of ICTS in promoting social inclusion: the case of Syrian refugees in Germany. In Proceedings of the 25th European Conference on Information Systems (ECIS), Guimarães, Portugal, June 5–10, 2017 (pp. 1792–1806) (2017).

  12. Kaufmann, K.: Navigating a new life: Syrian refugees and their smartphones in Vienna. Inf. Commun. Soc. 21, 882–898 (2018). https://doi.org/10.1080/1369118X.2018.1437205

    Article  Google Scholar 

  13. Comas-Quinn, A., Mardomingo, R., Valentine, C.: Mobile blogs in language learning: making the most of informal and situated learning opportunities. ReCALL 21, 96–112 (2009). https://doi.org/10.1017/S0958344009000032

    Article  Google Scholar 

  14. Kukulska-Hulme, A., Gaved, M., Paletta, L., Scanlon, E., Jones, A., Brasher, A.: Mobile incidental learning to support the inclusion of recent immigrants. Ubiquit. Learn. Int. J. 7, 9–21 (2015). https://doi.org/10.18848/1835-9795/CGP/v07i02/58070

    Article  Google Scholar 

  15. Bustamante Duarte, A.M., Degbelo, A., Kray, C.: Exploring forced migrants (re) settlement and the role of digital services. In: Proceedings of 16th European Conference on Computer-Supported Cooperative Work-Exploratory Papers. European Society for Socially Embedded Technologies (EUSSET) (2018)

  16. Abou-Khalil, V., Helou, S., Flanagan, B., Pinkwart, N., Ogata, H.: Language learning tool for refugees: identifying the language learning needs of Syrian refugees through participatory design. Languages 4, 71 (2019). https://doi.org/10.3390/languages4030071

    Article  Google Scholar 

  17. Drachman, D.: A stage-of-migration framework for service to immigrant populations. Soc. Work 37, 68–72 (1992)

    Google Scholar 

  18. Ngan, H.Y., Lifanova, A., Jarke, J., Broer, J.: Refugees welcome: supporting informal language learning and integration with a gamified mobile application. In: European Conference on Technology Enhanced Learning. Springer, pp. 521–524 (2016)

  19. Jung, J., Graf, S.: An approach for personalized web-based vocabulary learning through word association games. In: 2008 International Symposium on Applications and the Internet. IEEE, pp. 325–328 (2008)

  20. Barker, D.: A personalized approach to analyzing ‘cost’ and ‘benefit’ in vocabulary selection. System 35, 523–533 (2007). https://doi.org/10.1016/j.system.2007.09.001

    Article  Google Scholar 

  21. Choi, M.L., Ma, Q.: Realising personalised vocabulary learning in the Hong Kong context via a personalised curriculum featuring ‘student-selected vocabulary.’ Lang. Educ. 29, 62–78 (2015). https://doi.org/10.1080/09500782.2014.942318

    Article  Google Scholar 

  22. Sun, F., Yu, M., Zhang, X., Chang, T.-W.: A vocabulary recommendation system based on knowledge graph for Chinese language learning. In: 2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT). IEEE, pp. 210–212 (2020)

  23. Ismail, H.M., Harous, S., Belkhouche, B.: Review of personalized language learning systems. In: 2016 12th International Conference on Innovations in Information Technology (IIT). IEEE, pp. 1–6 (2016)

  24. Nascimento, H., Marques, L.B., de Souza, D.G., Salgado, F.M., Bessa, R.Q.: A AIED Game to help children with learning disabilities in literacy in the Portuguese language. SBC-Proceedings of SBGames (2012)

  25. Chen, C.-M., Chung, C.-J.: Personalized mobile English vocabulary learning system based on item response theory and learning memory cycle. Comput. Educ. 51, 624–645 (2008)

    Article  Google Scholar 

  26. Chen, C.-P., Wang, C.-H.: The effects of learning style on mobile augmented-reality-facilitated English vocabulary learning. In: 2015 2nd International Conference on Information Science and Security (ICISS). IEEE, pp. 1–4 (2015)

  27. Zou, D., Wang, M., Xie, H., Cheng, G., Wang, F.L., Lee, L.-K.: A comparative study on linguistic theories for modeling EFL learners: facilitating personalized vocabulary learning via task recommendations. Interact. Learn. Environ. (2020). https://doi.org/10.1080/10494820.2020.1789178

    Article  Google Scholar 

  28. Zou, D., Xie, H.: Personalized word-learning based on technique feature analysis and learning analytics. J. Educ. Technol. Soc. 21, 233–244 (2018)

    Google Scholar 

  29. Chen, C.-M., Li, Y.-L.: Personalised context-aware ubiquitous learning system for supporting effective English vocabulary learning. Interact. Learn. Environ. 18, 341–364 (2010). https://doi.org/10.1080/10494820802602329

    Article  Google Scholar 

  30. Kukulska-Hulme, A.: Personalization of language learning through mobile technologies (2016)

  31. Ricci, F., Rokach, L., Shapira, B.: Introduction to recommender systems handbook. In: Recommender systems handbook. Springer, pp. 1–35 (2011)

  32. Wang, Y., Chan, S.C.-F., Ngai, G.: Applicability of demographic recommender system to tourist attractions: a case study on trip advisor. In: 2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology. IEEE, pp. 97–101 (2012)

  33. Ogata, H., Li, M., Hou, B., Uosaki, N., El-Bishouty, M.M., Yano, Y.: SCROLL: Supporting to share and reuse ubiquitous learning log in the context of language learning. Res. Pract. Technol. Enhanc. Learn. (2011)

  34. Cambridge English: https://www.cambridgeenglish.org/. Accessed 22 Apr 2020 (2020)

  35. Streitwieser, B., Brück, L.: Competing motivations in Germany’s higher education response to the “refugee crisis.” Refuge: Canada’s J. Refug. 34:38–51 (2018). https://doi.org/10.7202/1055575ar

  36. Abou-Khalil, V., Helou, S., Flanagan, B., Chen, M.-R.A., Ogata, H.: Learning isolated polysemous words: identifying the intended meaning of language learners in informal ubiquitous language learning environments. Smart Learn. Environ. 6, 13 (2019). https://doi.org/10.1186/s40561-019-0095-0

    Article  Google Scholar 

  37. Studer, T.: Internationale Zertifikate für Deutsch als Fremdsprache in der Schweiz. Bull Vals-asla 79, 69–97 (2004)

  38. Hwang, G.-J., Yang, L.-H., Wang, S.-Y.: A concept map-embedded educational computer game for improving students’ learning performance in natural science courses. Comput. Educ. 69, 121–130 (2013). https://doi.org/10.1016/j.compedu.2013.07.008

    Article  Google Scholar 

  39. Hwang, G.-J., Chang, H.-F.: A formative assessment-based mobile learning approach to improving the learning attitudes and achievements of students. Comput. Educ. 56, 1023–1031 (2011). https://doi.org/10.1016/j.compedu.2010.12.002

    Article  Google Scholar 

  40. UNHCR: Document—Vulnerability Assessment of Syrian Refugees in Lebanon—VASyR 2017. https://data2.unhcr.org/en/documents/details/61312. Accessed 26 Apr 2020 (2017)

  41. Howatt, A.P., Smith, R.: The history of teaching English as a foreign language, from a British and European perspective. Lang. Hist. 57, 75–95 (2014). https://doi.org/10.1179/1759753614Z.00000000028

    Article  Google Scholar 

  42. Richards, J.C., Rodgers, T.S.: Approaches and Methods in Language Teaching. Cambridge University Press, Cambridge (2014)

    Book  Google Scholar 

  43. Tamatea, L., Pramitasari, G.A.A.M.: Bourdieu and programming classes for the disadvantaged: a review of current practice as reported online—implications for non-formal coding classes in Bali. Res. Pract. Technol. Enhanc. Learn. 13, 1 (2018). https://doi.org/10.1186/s41039-018-0068-x

    Article  Google Scholar 

  44. Freedman, K., Liu, M.: The importance of computer experience, learning processes, and communication patterns in multicultural networking. ETR&D 44, 43–59 (1996). https://doi.org/10.1007/BF02300325

    Article  Google Scholar 

  45. Yamada, M., Kitamura, S., Matsukawa, H., Misono, T., Kitani, N., Yamauchi, Y.: Collaborative filtering for expansion of learner’s background knowledge in online language learning: does “top-down” processing improve vocabulary proficiency? Educ. Tech. Res. Dev. 62, 529–553 (2014). https://doi.org/10.1007/s11423-014-9344-7

    Article  Google Scholar 

  46. Ghauth, K.I., Abdullah, N.A.: Learning materials recommendation using good learners’ ratings and content-based filtering. Educ. Tech. Res. Dev. 58, 711–727 (2010). https://doi.org/10.1007/s11423-010-9155-4

    Article  Google Scholar 

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Funding

The research is funded by the Japan Society of Promotion of Science (JSPS) KANHEKI Grant No. 19J15167.

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Authors and Affiliations

  1. Academic Center for Computing and Media Studies, Kyoto University, Yoshida Nihonmatsu-cho, Sakyo-ku, Kyoto, 606-8501, Japan

    Victoria Abou-Khalil, Mei‐Rong Alice Chen, Brendan Flanagan, Louis Lecailliez & Hiroaki Ogata

  2. Global Center for Medical Engineering and Informatics, Osaka University, Osaka, 565-0871, Japan

    Samar Helou

  3. Inst. F. Informatik, Humboldt-Universität Zu Berlin, Rudower Chaussee 25, 12489, Berlin, Germany

    Niels Pinkwart

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  1. Victoria Abou-Khalil
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  2. Samar Helou
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Correspondence to Victoria Abou-Khalil.

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Abou-Khalil, V., Helou, S., Chen, M.A. et al. Vocabulary recommendation approach for forced migrants using informal language learning tools. Univ Access Inf Soc 21, 983–994 (2022). https://doi.org/10.1007/s10209-021-00813-3

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