Towards an Adaptive Language MOOC: Examining Differences of Language Error Patterns across Cultural Domains
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| Publicado en: | Turkish Online Journal of Distance Education vol. 26, no. 2 (2025), p. 16 |
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| Otros Autores: | , |
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Anadolu University
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| Acceso en línea: | Citation/Abstract Full text outside of ProQuest |
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| 001 | 3206891650 | ||
| 003 | UK-CbPIL | ||
| 035 | |a 3206891650 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a EJ1466291 | ||
| 100 | 1 | |a Ozlem Ozan | |
| 245 | 1 | |a Towards an Adaptive Language MOOC: Examining Differences of Language Error Patterns across Cultural Domains | |
| 260 | |b Anadolu University |c 2025 | ||
| 513 | |a Report Article | ||
| 520 | 3 | |a This study analyzed linguistic errors as part of the Differentiated Distance Education of Turkish as a Foreign Language Project, which pursues the development of an adaptive MOOC for Turkish as a second language. Therefore, the Turkish CEFR (Common European Framework of Reference for Languages) A1-level writing exam papers of 177 learners were analyzed. Linguistic error analysis techniques were used. A Chi-square test of independence, a Kruskal-Wallis H test, and a Mann-Whitney U test were conducted to examine the data. The results show a relationship between error frequency and learner group (Arabic--Farsi, Turkic, Balkan, and Other). Similarly, the error density varied as a function of the learner group. There is also a relationship between error frequency and the language family of the learner's mother language. On the other hand, there is no significant difference in error density by language family. The number of languages the learner knows, has no significant effect on error frequency and density. The findings suggest that there are gender-based differences in error density among learners, but that these differences are not reflected in the frequency of errors. The topics for differentiation were identified based on the error distribution of learner groups. The topic that requires the most differentiation is noun phrases. The learner groups that need the most differentiation are the Arabic and Farsi Nations, while the Turkic Nations require the least differentiation. | |
| 651 | 4 | |a Turkey | |
| 653 | |a MOOCs | ||
| 653 | |a Language Patterns | ||
| 653 | |a Language Usage | ||
| 653 | |a Error Patterns | ||
| 653 | |a Second Language Learning | ||
| 653 | |a Turkish | ||
| 653 | |a Error Analysis (Language) | ||
| 653 | |a Language Acquisition | ||
| 653 | |a Gender Differences | ||
| 653 | |a Foreign Countries | ||
| 653 | |a Arabic | ||
| 653 | |a Indo European Languages | ||
| 700 | 1 | |a Ozarslan, Yasin | |
| 700 | 1 | |a Zenci, Sevgi Calisir | |
| 773 | 0 | |t Turkish Online Journal of Distance Education |g vol. 26, no. 2 (2025), p. 16 | |
| 786 | 0 | |d ProQuest |t ERIC | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3206891650/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full text outside of ProQuest |u http://eric.ed.gov/?id=EJ1466291 |