BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Date iCal//NONSGML kigkonsult.se iCalcreator 2.20.2// METHOD:PUBLISH BEGIN:VTIMEZONE TZID:America/Toronto BEGIN:STANDARD DTSTART:20251102T020000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST END:STANDARD BEGIN:DAYLIGHT DTSTART:20260308T020000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:calendar.2803.events_uoft_date.0@www.nmc.utoronto.ca CREATED:20260122T211820Z DESCRIPTION:\nWhen and Where: \nSaturday, February 07, 2026 1:00 pm to 2: 30 pm \n Online \n\nSpeakers \nMina Golestani, Georg-August-Universität G öttingen \n\nDescription: \nDeveloping a Persian Collocation Resource Usin g AI and Computational Methods for Language PedagogyThe Elahé Omidyar Mir- Djalali Institute of Iranian Studies in collaboration with the Department of Middle Eastern Studies and the Center for Middle Eastern Studies, Univ ersity of Chicago  jointly present 'Developing a Persian Collocation Resou rce Using AI and Computational Methods for Language Pedagogy' on Saturday\ , February 7, 2026, 1 p.m. (Eastern Time: Canada and US).Abstract This s tudy addresses a significant gap in Persian language pedagogy by leveragin g artificial intelligence (Al) and computational tools to create a structu red, up-to-date, and publicly accessible resource of Persian collocation s. Collocation words are essential for fluency and naturalsounding languag e use. Through a survey among both Persian learners and experienced Persia n language teachers, the strong need for such an important resource was i dentified. Therefore, this project aims to extract Persian collocations f rom two selected corpora using complementary techniques. To build this res ource, two corpora were selected for analysis: Persian Twitter NER (ParsT wiNER), which represents informal and social media language, and Persica , a corpus of formal Persian texts suitable for Multipurpose Text Mining and natural language processing. These corpora were chosen based on their availability, licensing, and suitability for text mining for the goal of this project.After evaluating the advantages and limitations of various c ollocation extraction techniques, including statistical measures (like PM I and t-score) and embedding-based methods (such as Word2Vec), the projec t ultimately adopts a hybrid approach, combining the most effective compu tational and Al-driven methods to extract collocations that are both frequ ent and semantically meaningful.The final product is intended to support b oth classroom instruction and selfstudy, while also serving as a foundati on for further research in Persian linguistics. The paper discusses the cu rrent state of Persian collocation resources, compares alternative extrac tion methods, presents the methodology used, and evaluates the output. B y integrating Al-driven methods into language pedagogy, this study contri butes to the growing field of technology-enhanced learning for less-resour ced and less commonly taught languages such as Persian.Bio: Mina Golestani is a student research assistant and a Master's student in Iranian studies and Digital Humanities at the University of Gottingen. She holds a Bachel or's degree in Persian Language and Literature, which laid the foundation for her continued interest in Persian pedagogy. With four years of experi ence collaborating with the education sector of the Academy of Persian Lan guage and Literature on three different projects, she has developed a gro wing interest in Language Pedagogy and digital methodologies. Currently, she is working on two projects aimed at developing digital tools that supp ort Persian pedagogy using Al and computational approachesZoom Meeting Reg istration: https://utoronto.zoom.us/meeting/register/i5HR3liYShGHU9rXmcg6c w After registering, you will receive a confirmation email containing inf ormation about joining the meeting. \n\nCategories \n SeminarsThe Elahé Om idyar Mir-Djalali Institute of Iranian Studies \n\nAudiences \n Alumni and FriendsCommunityFacultyGraduate StudentsProspective StudentsStaffUndergra duate StudentsGeneral Public DTSTART;TZID=America/Toronto:20260207T130000 DTEND;TZID=America/Toronto:20260207T143000 LAST-MODIFIED:20260122T212001Z SUMMARY:AI-Driven Language Pedagogy for Less Commonly Taught Languages: Min a Golestani URL;TYPE=URI:https://www.nmc.utoronto.ca/events/ai-driven-language-pedagogy -less-commonly-taught-languages-mina-golestani END:VEVENT END:VCALENDAR