diff --git a/data/xml/2024.teachingnlp.xml b/data/xml/2024.teachingnlp.xml
index 5064ea76c2..0b9c2ee8d9 100644
--- a/data/xml/2024.teachingnlp.xml
+++ b/data/xml/2024.teachingnlp.xml
@@ -151,7 +151,7 @@
     </paper>
     <paper id="12">
       <title>A Prompting Assignment for Exploring Pretrained <fixed-case>LLM</fixed-case>s</title>
-      <author><first>Carolyn</first><last>Anderson</last><affiliation>Wellesley College</affiliation></author>
+      <author><first>Carolyn Jane</first><last>Anderson</last><affiliation>Wellesley College</affiliation></author>
       <pages>81-84</pages>
       <abstract>As the scale of publicly-available large language models (LLMs) has increased, so has interest in few-shot prompting methods. This paper presents an assignment that asks students to explore three aspects of large language model capabilities (commonsense reasoning, factuality, and wordplay) with a prompt engineering focus. The assignment consists of three tasks designed to share a common programming framework, so that students can reuse and adapt code from earlier tasks. Two of the tasks also involve dataset construction: students are asked to construct a simple dataset for the wordplay task, and a more challenging dataset for the factuality task. In addition, the assignment includes reflection questions that ask students to think critically about what they observe.</abstract>
       <url hash="6d45548e">2024.teachingnlp-1.12</url>