This dataverse contains the written French and English productions generated by students from an advanced French course at a large public university, as well as the prompts for each task. The course focused on the development of students' L2 identities in French through self-inspired characters. For each 16 students, the dataverse contains three French productions written from the perspective of students' self-inspired characters, covering the genres of the personal narrative, personal letter, and portrait, and two meta-reflections in English in which students reflect on the development of their L2 identities through the writing process. (Names are pseudonyms.)
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61 to 70 of 170 Results
Aug 17, 2021 - Jacob Dataset
MS Word - 17.5 KB - MD5: 81601ecfc9f15ef041fd49808df36555
Personal letter written by Jacob from the perspective of his self-inspired character. Language: French
Aug 17, 2021 - Jacob Dataset
Adobe PDF - 45.5 KB - MD5: 9884e14e2b9b8513c3248ed1dc353f80
Aug 17, 2021 - Jacob Dataset
MS Word - 18.0 KB - MD5: 2a5e231d0e5dc47c5ca4e314059148db
Personal narrative written by Jacob from the perspective of his self-inspired character. Language: French
Aug 17, 2021 - Jacob Dataset
Adobe PDF - 102.1 KB - MD5: 220dddae4a2603c531dbbf26ee7315df
Aug 17, 2021 - Jacob Dataset
MS Word - 14.4 KB - MD5: 129366f2b88b748751c54ddf425a8035
Portrait written by Jacob from the perspective of his self-inspired character. Language: French
Aug 17, 2021 - Jacob Dataset
Adobe PDF - 66.2 KB - MD5: 557ba1663e530d7f93b6b2b2405db7ca
Aug 17, 2021 - Jacob Dataset
MS Word - 16.9 KB - MD5: 594cd3691e010280ef013eef73b0e7a1
Meta-linguistic reflection #1 written by Jacob about developing his L2 identities in French. Language: English
Aug 17, 2021 - Jacob Dataset
Adobe PDF - 43.7 KB - MD5: b89371df29c1da008b8139e55efc5484
Aug 17, 2021 - Jacob Dataset
MS Word - 17.1 KB - MD5: aca8ddf5d913c15aaaa0785defb60ed2
Meta-linguistic reflection #2 written by Jacob about developing his L2 identities in French. Language: English
Aug 17, 2021 - Jacob Dataset
Adobe PDF - 58.3 KB - MD5: 522af754118391c79b234fabd8d5a25c
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