Update README.html

README.html

@@ -174,7 +174,8 @@ <h2>A LASER Focus on Understanding and Improving STEM Education</h2>
 <div id="overview" class="section level3">
 <h3>Overview</h3>
 <p>This workshop will introduce participants to the Learning Analytics (LA), an emerging research and teaching field sitting at the intersection of Learning (e.g. educational technology, learning and assessment sciences), Analytics (e.g. visualization, computer/data sciences), and Human-Centered Design (e.g. usability, participatory design). LA is proving to be a powerful approach for understanding and improving the digital learning contexts highlighted in the national STEM education plan, while also examining persistent problems in STEM education from new angles.</p>
-<p>The instructors will provide a brief overview of LA methodologies, literature, applications, and ethical issues as they relate to STEM education, with an emphasis on digital learning environments and broadening participation in STEM programs. Participants will be introduced to open-access curriculum materials developed as part of the <a href="https://www.fi.ncsu.edu/projects/laser-institute/">Learning Analytics in STEM Education Research (LASER) Institute</a> to gain hands-on experience with computational analysis techniques (e.g. network analysis, text mining, machine learning) using R and RStudio.</p>
+<p>The instructors will provide a brief overview of LA methodologies, literature, applications, and ethical issues as they relate to STEM education, with an emphasis on digital learning environments and broadening participation in STEM programs. Participants will be introduced to open-access curriculum materials developed as part of the <a href="https://www.fi.ncsu.edu/projects/laser-institute/">Learning Analytics in STEM Education Research (LASER) Institute</a> to gain hands-on experience with computational analysis techniques (e.g. network analysis, text mining, 
+       ) using R and RStudio.</p>
 </div>
 <div id="presenters" class="section level3">
 <h3>Presenters</h3>
@@ -199,7 +200,7 @@ <h3>Schedule</h3>
 <p><strong>2:20-2:30.</strong> Q&amp;A/Break</p>
 <p><strong>2:30-3:10.</strong> Intro to Machine Learning (ML) in STEM</p>
 <ul>
-<li><strong>Introduction to Machine Learning</strong> includes a short <a href="https://laser-institute.github.io/aera-workshop/slides/machine-learning-intro.html">presentation</a> and <a href="https://laser-institute.github.io/aera-workshop/pages/machine-learning-demo.html">demonstration</a> designed to illustrate how machine learning can be applied in STEM education research and to provide workshop participants hands-on experience with the process of building a machine learning model. Content for this workshop is drawn from from <a href="https://github.com/laser-institute/machine-learning">ML Module</a>XXX taught at the LASER Institute Summer Workshop.</li>
+<li><strong>Introduction to Machine Learning</strong> includes a short <a href="https://laser-institute.github.io/aera-workshop/slides/machine-learning-intro.html">presentation</a> and <a href="https://laser-institute.github.io/aera-workshop/pages/machine-learning-demo.html">demonstration</a> designed to illustrate how machine learning can be applied in STEM education research and to provide workshop participants hands-on experience with the process of building a machine learning model. Content for this workshop is drawn from from <a href="https://github.com/laser-institute/machine-learning/tree/main/ML%20lab%201%20and%202">ML Module 1</a> taught at the LASER Institute Summer Workshop.</li>
 </ul>
 <p><strong>3:10-3:20.</strong> Q&amp;A/Break</p>
 <p><strong>3:20-4:00.</strong> Intro to Social Network Analysis (SNA) in STEM</p>