SPAN 588

Spring 2020 All Classes

All Classes

Sem Second Lang Learn

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Credit: 4 hours.

Treats specific topics in second language learning that are of current research and/or theoretical interest. Topics vary from term to term.

Same as EALC 588, FR 588, GER 588, ITAL 588, LING 588, and PORT 588. May be repeated to a maximum of 16 hours if topics vary. Prerequisite: SPAN 580 or equivalent or consent of instructor.

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SPAN 588 class schedule data for spring 2020
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
60354	Lecture-Discussion	AM1	3:00PM -4:50PM	T	Foreign Languages Building	Mroz, A	Part of Term: 1 Date Range: 01/21/20-05/06/20 Section Title: Mix Methods research in SLATE Section Info: Topic Title: Mixed Methods for research in SLATE Description: Philosophy, conceptualization, protocols to conduct mixed methods study in SLATE. Assessment of the strengths and weaknesses of published mixed methods studies. Hands-on application of mixed methods designs for a research project. Dissemination and publication of mixed methods studies. Restriction(s): Restricted to Graduate - Urbana-Champaign.
57103	Lecture-Discussion	MB	3:00PM -5:50PM	M	Davenport Hall	Bowles, M	Part of Term: 1 Date Range: 01/21/20-05/06/20 Section Title: Inst Heritage Lang Acquisition Section Info: TOPIC TITLE: "Instructed Heritage Language Acquisition" Restriction(s): Restricted to Graduate - Urbana-Champaign.
53516	Lecture-Discussion	MSB	2:00PM -3:20PM	MW	Foreign Languages Building	Barlaz, M	Part of Term: 1 Date Range: 01/21/20-05/06/20 Section Title: Adv Analytical Methods Section Info: Topic Title: Advanced Analytical Methods for Linguistic Research Description: This course is an overview of advanced analytical methods for linguistic research. Focus will be placed on a critical analysis of current methods, as well as on scientific reproducibility and transparency. Students are expected to be familiar with statistical terms and basic inferential statistics. The course will be taught using the R software environment, and will cover topics including principal components analysis, linear discriminant analysis, generalized additive models, and an introduction to Bayesian analysis. Restriction(s): Restricted to Graduate - Urbana-Champaign.