Artificial Intelligence, Computational Tools for Data Science, Human-Computer Interaction

Barbara Jane Ericson

School of Information


Electrical Engineering and Computer Science, College of Engineering

I have been creating free and interactive ebooks for introductory computing courses on the open-source Ruenstone platform and analyzing the clickstream data from those courses to improve the ebooks and instruction. In particular, I am interested in using educational data mining to close the feedback loop and improve the instructional materials. I am also interested in learner sourcing to automatically generate and improve assessments. I have been applying principles from educational psychology such as worked examples plus low cognitive load practice to improve instruction. I have been exploring mixed-up code (Parsons) problems as one type of practice. I created two types of adaptation for Parsons problems: intra-problem and inter-problem. In intra-problem adaptation, if the learner is struggling to solve the current problem it can dynamically be made easier. In inter-problem adaptation the difficulty of the next problem is based on the learner’s performance on the previous problem.