Group items tagged

The Department of Education's (ED) Office of Educational Technology today released a draft issue brief - Enhancing Teaching and Learning Through Educational Data Mining and Learning Analytics - representing the results of a months-long discourse among 8 academic and 15 industrial data mining and learning analytics experts conducted by SRI International. The brief, inspired by ED's 2010 National Educational Technology Plan (NETP), articulates the challenges and opportunities of Big Data in improving student outcomes and overall productivity of K-2 education systems. It focuses on three key research areas - educational data mining, learning analytics, and visual data analytics - and offers a set of corresponding recommendations, categorized by various stakeholders. ED is now seeking public comment on the draft.

Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.

Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.

A report of some MOOC analysis of discussion forums. Sounds like the analysis is flawed from the report here.

"Brute computing force alone can't solve the world's problems. Data mining innovator Shyam Sankar explains why solving big problems (like catching terrorists or identifying huge hidden trends) is not a question of finding the right algorithm, but rather the right symbiotic relationship between computation and human creativity."