Measuring Young Learners’ Open-ended Agent-based Programming Practices with Learning Analytics
Date:
This study introduces a method to measure young learners’ agent-based programming practices using a 4-stage model, analyzing 2,300 projects from the Turtle Universe online community to highlight differences in ABP practices across various stages and modalities, and discussing implications for block-based ABP environments.
Chen, J., & Wilensky, U. J. (2023b). Measuring Young Learners’ Open-ended Agent-based Programming Practices with Learning Analytics. Presented at AERA Annual Meeting 2023.
Summary
Agent-based modeling (ABM) has been recognized as an important component of computational thinking and literacy. Agent-based programming (ABP) is the computational foundation of ABM. In this study, we propose a novel method to programmatically measure young learners’ ABP practices in open-ended programming contexts with a 4-stage model. We present results from the online community of Turtle Universe, a new version of NetLogo designed for mobile platforms and younger learners in informal contexts. We draw on a dataset of 2,300 block-based and text-based projects shared by out-of-school, unsupervised learners. Our approach generally succeeded in measuring learners’ open-ended ABP practices. Differences were found among projects of different stages and modalities. We discuss the implications of our approach and design of block-based ABP environments.