Monitoring Second Language Learning with PageRank-Based Student Performance Analysis

The use of technology has permeated all aspects of modern society, including education. Within pedagogy, computer- assisted language learning (CALL) has gained popularity as a result of technological advancements. The potential for combining this sub-field of L2 learning and algorithm-driven approaches to monitor in-class performance has remained unexplored. This study draws on PageRank (PR) and social network analysis (SNA) to monitor student interactions in an SLA environ- ment. This study compares the effectiveness of PageRank and eigenvector centrality in reflecting student in-class performance using data from an L2 Spanish lecture. The results suggest that PageRank outperforms other metrics at abstracting in-class performance, showing 91% of score uniqueness against the 33% obtained by eigenvector centrality.