Paper presentation @ EuroPLoP 2015 writer’s workshop
Peter Scupelli and Paul Inventado presented “Data-Driven Design Pattern Production: A Case Study on the ASSISTments Online Learning System” in a writing workshop 20th European Conference on Pattern Languages of Programs (EuroPLoP) 2015 in Bavaria, Germany.
Online learning systems popularity increased rapidly in recent decades in multiple domains such as cognitive tutors, online courses, and massive open online courses (MOOCS). The design quality of online learning systems is difficult to maintain. Multiple stakeholders are involved (e.g., software developers, interaction designers, learning scientists, teachers), the system is complex, there are rapid changes in software, platforms (e.g., mobile, tablet, desktop) and learning subject content, and so forth. Many existing online learning systems collect a significant amount of data that describe learning outcomes and student behaviors, which are indirect measures of system quality. Data analysis on online learning systems data can uncover linkages between particular design choices made and student learning outcomes. In this paper, we describe the Data-Driven Design Patterns Production (3D2P) methodology to prospect, mine, write and evaluate design patterns for online learning systems. Pattern prospecting helps designers decide what type of possible meaningful outcomes and features to scan for in the data and helps to focus on specific data subsets to limit the search space for pattern mining. Design patterns identified with 3D2P methodology can guide the addition of new content and the modification of system designs to maintain the online learning system’s quality. We present a case study of the ASSISTments math online learning system to illustrate the 3D2P methodology and discuss its benefits and limitations.