uts statistika kelompok 3

Nelineárne špecifikácie

Data sources such as digital learning environments and administrative data systems, as well as data produced by social media websites and the mass digitization of academic and practitioner publications, hold enormous potential to address a range of pressing problems in education, but collecting and analyzing text-based data also presents unique challenges. This week, our case study is guided by Josh Rosenberg's study, Advancing new methods for understanding public sentiment about educational reforms: The case of Twitter and the Next Generation Science Standards. We will focus on conducting a very simplistic "replication study" by comparing the sentiment of tweets about the Next Generation Science Standards (NGSS) and Common Core State Standards (CCSS) in order to better understand public reaction to these two curriculum reform efforts. Specifically, our Unit 3 case study will cover the following topics

week5 scenairo 1

In Unit 2, we learn about five basic steps in a supervised machine learning process in addition to some other components of a learning analytics workflow. For example, to help prepare for analysis, we'll first take a step back and think about how we want to use machine learning, and predicting is a key word. Many scholars have focused on predicting students who are at-risk: of dropping a course or not succeeding in it. In this introductory machine learning case study, we will cover the following workflow processes from @krumm2018 as we attempt to develop our own model for predicting student drop-out