Doing Experiments for Linguistics.

Instructors: Brian Dillon (University of Massachusetts Amherst), Rodica Ivan (University of Massachusetts Amherst)

Room: Imperial C

Date: Thursday, January 4

Time: 10:00 AM - 3:00 PM, with a one-hour break for lunch

Researchers are increasingly turning to web-based methods for collecting experimental data, such as acceptability judgment questionnaires. Performing experiments over the Internet has many advantages: rapid data collection and access to populations other than the typical undergraduate population sampled by in-lab experiments, including access to participants from other countries, to name a few. However, this approach comes with its own challenges as well. The goal of this mini-course is to give participants an orientation to doing web-based experimentation, with a focus on acceptability judgment experiments and experimental syntax. The first part of the course with consist of a hands-on introduction to running questionnaire-based experiments using the experimental platform Ibexfarm. We will explore how to implement various experimental paradigms in Ibexfarm, how to customize or extend Ibexfarm, and how to export the data collected by Ibexfarm for analysis in Excel or R. Although the focus of this discussion is largely practical and hands-on in nature, we will also discuss the different methods of collecting acceptability judgment data that Ibex makes available. The second part of this course will cover several different methods for recruiting participants over the web using Ibexfarm, including the use of various crowd-sourcing platforms such as Amazon’s Mechanical Turk, as well as running experiments on a language not spoken in the researcher's current location. As part of this discussion, we will explore possible solutions to challenges posed by Internet data collection, such as how to detect non-compliant participants and the problem of participant non-naiveté, and the conditions under which web-based data may differ from data collected in the lab.


Innovative Pedagogy in the Linguistics Classroom

Sponsor: LSA Committee on Linguistics In Higher Education (LiHEC)

Room: Imperial D

Date: Thursday, January 4

Time:  9:00 AM - 2:15 PM

Pedagogy-specific training for those preparing to teach in higher education is often erratic, with much of the training acquired by serving as teaching assistants. Often the pedagogical training that does occur is focused on teaching subjects adjacent to linguistics, such as composition or second language courses. This instruction often focuses on course-related requirements and assessment details rather than providing new instructors with the pedagogical tools that will help them engage students in learning.

Due to internal and external pressures, many colleges and universities have renewed their interests in teaching and its assessment in recent years (McKinney, 2013). This has led to increased investment in innovative and engaging pedagogies and assessments at both the institutional and individual levels. The use of evidence-based instructional practices (EBIPs) has proliferated throughout academia, but especially in STEM-related fields.

In this 4-hour mini-course, participants (ABD to professor) will learn about incorporating innovative practices into their teaching. The course will focus on using EBIPs in the linguistics classroom, whether the classroom is at the university, online, or in the community. We will provide participants with the grounding of EBIPs and tools to take into their classrooms.


Professional Paths for Linguists: Preparing for What's Next

Organizer: Anastasia Nylund, Georgetown University

Room: Savoy

Date: Thursday, January 4

Time:  9:00 AM - 3:30 PM with a one-hour break for lunch

This full-day minicourse is for anyone interested in exploring career paths for linguists. We will approach the job search as a research process, starting with the task of identifying skills, abilities, and professional goals, followed by practice in telling effective stories about ourselves as professionals and as linguists. Participants will: 1) identify their own professional skills, interests, and values, 2) hear the stories of linguists who have found professional expression of their academic skills and training, and 3) learn to craft professional stories that resonate, and develop key job search texts including resumes, cover letters, LinkedIn presence, interviews, etc.Linguists at all levels of training (from undergraduates to PhDs and beyond) are welcome. Organized by the LSA "Linguistics Beyond Academia" Special Interest Group.

Bring along a 'career text' - your resume, a cover letter, a copy of your LinkedIn bio, or something similar. We will workshop these texts to help you better tell your story!



QGIS for Linguistic Research

Instructors: Jennifer Cramer, University of Kentucky and Ben Jones, University of Washington

Download course materials here.

Room: Envoy

Date :Thursday, January 4

Time: 10: 00 AM - 3:00 PM with a one-hour break at noon for lunch

Description: Geographic Information System (GIS) technologies are tools that allow users to “visualize, question, analyze, interpret, and understand data to reveal relationships, patterns, and trends” (ESRI 2017) with a geographic scope. Linguistic data is well-suited to exploration with GIS tools, and in this four-hour minicourse, we will provide in-depth instruction on the use of a specific GIS tool, the free, open-source product QGIS (, for various linguistics research applications. The main portion of the workshop will be devoted to the description of several available functions within QGIS, with a specific focus on the tools that will be most beneficial in linguistic research. Participants will be provided with a “quick glance” guide with reference to the tools discussed. The course requires that participants come prepared with a laptop, on which QGIS has already been installed ( Further details on QGIS installation and data sets for the hands-on portion will be provided in advance. If time allows, participants will be able to attempt some preliminary analyses of a data set of their choosing. No previous knowledge of GIS technologies is required, but having command of basic desktop computer skills and an openness to acquire new skills for research in a computational environment will be beneficial.