Pre-conference Workshop

Two pre-conference workshops will take place on Friday, November 6, 2026.
Venue: Event Center, 26th Floor, 25 Park Place 

Ungrading: Principles, practices, and prospects for language teaching and assessment
(9:00 a.m. - 12:00 p.m.) 

Ungrading is an assessment philosophy (Cushing, 2024) comprising a family of approaches including specifications grading, labor-based grading, contract grading, and minimal grading, among others. While some of these approaches originated in composition and writing studies, they have been taken up in teaching a variety of subject areas. In language teaching, ungrading has attracted attention especially in second language writing (Crusan, 2024). This workshop introduces ungrading in language teaching more generally and considers its potential applications across different language skills and purposes. 

We’ll begin with a brief historical overview and typology of ungrading and then position it in relation to the classical alternative approaches to assessment in language teaching (Brown & Hudson, 1998) like projects, portfolios, and performance assessment. We’ll review the benefits ungrading offers to different assessment stakeholders and address some common criticisms. Then, focusing on specifications grading and labor-based grading, we will look at issues of reliability, validity, and practicality specifically for language teaching. 

In the hands-on segment of the workshop, each participant will have the opportunity to apply a selected ungrading approach to a sample language course syllabus. 

Toward the end of the session we’ll consider the compatibility of ungrading approaches with the critical language testing perspective (Shohamy, 2017) and their potential for language test activism (Carlsen & Rocca, 2022) for those so inclined. Finally, we’ll reflect on ungrading’s prospects as an assessment practice in the era of generative AI. 

This workshop is intended to create a space for playful implementation and cooperative learning by anyone interested in teaching and assessing language. No prior knowledge of ungrading or expertise in assessment is required, only some experience of language teaching. Participants are encouraged to bring a language-course syllabus of their own to explore how a selected ungrading approach might fit their unique context in keeping with the conference theme of localization. 

References 

• Brown, J. D., & Hudson, T. (1998). The Alternatives in Language Assessment. TESOL Quarterly, 32(4), 653–675. https://doi.org/10.2307/3587999  

• Carlsen, C. H., & Rocca, L. (2024). Language test activism. Language Policy, 21, 597-616.  https://doi.org/10.1007/s10993-022-09614-7 

• Crusan, D. (2024). Ungrading: Revolution or evolution. Journal of Second Language Writing, 66, 101149. https://doi.org/10.1016/j.jslw.2024.101149  

• Cushing, S. T. (2024). Ungrading as an assessment philosophy: Reliability, validity, and practicality. Journal of Second Language Writing, 66, 101152. https://doi.org/10.1016/j.jslw.2024.101152  

• Shohamy, E. (2017). Critical language testing. In E. Shohamy, I. Or, & S. May (Eds.), Language Testing and Assessment (3rd ed.). Encyclopedia of Language and Education. Springer. https://doi.org/10.1007/978-3-319-02261-1_26  

The Tidyverse Workflow for Descriptive Statistics and Data Visualization in R
(1:00 p.m. - 5:00 p.m.) 

Although SPSS is still the most widely used statistical analysis tool, R has seen wide adoption, especially in academia, and may soon be the most used statistical programming language (Muenchen, 2023). This popularity is motivated by several factors, including its open-source nature, support for reproducible reports, and exceptional flexibility for data analysis and visualization. Despite these strengths and growing popularity, R has a steep learning curve. Yet, proficiency in R is becoming an increasingly valuable skill, as quantitative methods continue to play a central role in language assessment research. 

To provide a systematic introduction to R, this workshop will focus on descriptive statistics and data visualizations using the `tidyverse` package, which is the primary package used by leading data scientists. Relying on the `tidyverse` package, this workshop will first provide a hands-on introduction to calculating descriptive statistics and then visualizing those statistics in R in an aesthetically pleasing manner. The descriptive statistics will include frequencies for categorical variables and mean, standard deviation, and five-number summary for numerical variables. The data visualizations will cover bar plots, box plots, histograms, and scatter plots. Along the way, participants will learn to wrangle data by grouping data based on given variables, dropping NA observations, creating new variables based on existing variables, and filtering data based on desired parameters, among others. The workshop will also provide attendees with a list of resources should they continue their learning journey in R.  

This workshop is for you if you want an accessible and systematic introduction to R while also learning how to produce descriptive statistics and data visualizations. We also welcome those who are comfortable using base R but have yet to learn the functions that come with the `tidyverse` package. 

References 

• Muenchen, B. (2023). Update to data science software popularity. R-bloggers. https://www.r-bloggers.com/2023/06/update-to-data-science-software-popularity/