Scalable self-paced e-learning of statistical programming with fine-grained feedback and assessment

Date

August 8, 2024

Format

15min talk

Presenter

Cynthia A Huang

Venue

Contributed Paper Session, Joint Statistical Meetings 2024

Abstract

Assessing statistical programming skills consistently and at scale is challenging. Much like writing style is assessed in essay tasks, discriminating code quality and style from code function or output is becoming increasingly important as students adopt code-generating tools such as ChatGPT. In many cases checking code output alone is insufficient to assess students’ understanding and ability to write statistical code. Instead, instructors often need to check the code itself for evidence of computational thinking, such as the use of appropriate functions, data structures, and comments. Unfortunately, manual review of code is time-consuming and subjective, and the skills needed to automate this process are complex to learn and use. In this talk, we introduce a new approach to authoring self-paced interactive modules for learning statistics with R. It is built using Quarto and WebR, leveraging literate programming to quickly create exercises and automate assessments. We discuss how this format can be used to write assessments with automated checking of multi-choice quizzes, code input and outputs, and the advantages of in-browser execution via WebR compared to existing server based solutions.

 

Joint Statistical Meeting 2024, Portland, Oregon (USA)

Session Details

Go big or go home: Innovations in large scale assessment practice

Various data technologies and automated approaches can assist with assessment, but care is needed to develop tools and practices that value and support the human learning experience, at the same time as optimising for efficiency and accuracy. Tools are also needed that support teachers to make consistent and valid judgments across very large quantities of responses. This session will present talks related to research and practice within the emerging area of large scale automated-assisted assessment. Primarily using the teaching context of introductory statistics and data science courses, each speaker will discuss their development of different innovative assessment practices and the opportunities, challenges, and rewards of using automation with respect to teaching and research. The following four talks are proposed for this session.

Format: 15min talk

Slides