37.1266, Books: Natural Language Processing Applications in Teaching Persian as a Foreign Language: Karimipour (2026)

[The LINGUIST List]

LINGUIST List: Vol-37-1266. Mon Mar 30 2026. ISSN: 1069 - 4875.

Subject: 37.1266, Books: Natural Language Processing Applications in Teaching Persian as a Foreign Language: Karimipour (2026)

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Date: 25-Mar-2026
From: Ulrich Lueders [contact at lincom.eu]
Subject: Natural Language Processing Applications in Teaching Persian as a Foreign Language: Karimipour (2026)


Title: Natural Language Processing Applications in Teaching Persian as
a Foreign Language
Series Title: LINCOM Studies in Second Language Teaching 36
Publication Year: 2026

Publisher: Lincom GmbH
           https://lincom-shop.eu/
Book URL:
https://lincom-shop.eu/epages/57709feb-b889-4707-b2ce-c666fc88085d.sf/en_GB/?ViewObjectPath=%2FShops%2F57709feb-b889-4707-b2ce-c666fc88085d%2FProducts%2F%22ISBN%209783969392874%22

Author(s): Amir Karimipour, Ferdowsi University of Mashhad

17x24 cm. ISBN 9783969392874. LINCOM Studies in Second Language
Teaching 36. 120pp. 2026. EUR 68.80.

Abstract:

This book explores the application of Natural Language Processing
(NLP) technologies to teaching Persian as a foreign language, with
particular focus on Arabic-speaking learners. Drawing on empirical
data from the AZFA Persian Learner Corpus at Ilam University, it
demonstrates how computational methods can address longstanding
pedagogical challenges in Persian language instruction. The work
examines learner corpus development and annotation frameworks,
presenting systematic approaches to categorizing morphological,
syntactic, lexical, and orthographic errors specific to Persian
interlanguage. It investigates both rule-based and machine learning
approaches to automated error detection and correction, achieving F1
scores of approximately 0.82 with transformer-based models. The book
discusses intelligent tutoring systems and adaptive learning pathways
that personalize instruction based on individual learner profiles,
showing significant improvements in grammatical accuracy (23% vs. 15%
for traditional instruction) and learner satisfaction. It also
addresses automated assessment of writing and speaking, ethical
considerations including data privacy and algorithmic bias, and
practical integration strategies for Persian language classrooms.
Looking forward, the work examines emerging technologies such as
transformer architectures and large language models while providing
detailed recommendations for educators, researchers, and developers.
Throughout, it emphasizes that NLP tools should complement rather than
replace human instruction, supporting the development of comprehensive
communicative competence while respecting learner autonomy and
cultural diversity in Persian language education.

Linguistic Field(s): Language Acquisition

Subject Language(s): Persian (fas)

Written In: English (eng)



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