New publication in eLearning Papers #42

June 15, 2015 7:56 PM

Paul Salvador Inventado and Peter Scupelli’s paper entitled “Towards an open, collaborative repository for online learning system design patterns” has been published in eLearning Papers #42.

Abstract:

Design patterns are high-quality solutions to known problems in a specific context that guide design decisions. Typically, design patterns are mined and evaluated through four methods: expert knowledge, artifact analysis, social observations, and workshops. For example, experts discuss: knowledge, interpretations of artifacts, social patterns, and clarity of patterns. In this paper, we introduce a fifth method, a data-driven design pattern production (3D2P) method to produce design patterns and conduct randomized controlled trials as a means to evaluate applied design patterns. We illustrate the 3D2P method in the context of online learning systems (OLSs) that are difficult to create, update and maintain. To overcome such challenges, we propose an open repository for OLS design patterns, evaluation data, and implementation examples. On the repository, researchers can collaborate in the six stages of the pattern lifecycle (i.e., prospecting, mining, writing, evaluation, application, applied evaluation). The repository provides five benefits: researchers from different backgrounds can (a) collaborate on design pattern production; (b) perform distributed tasks in parallel; (c) share results for mutual benefit; (d) test patterns across varied systems and domains to explore pattern generalizability and robustness; and (e) promote design patterns to elevate OLS quality.

Last updated: 7:56 pm

Data-driven Design Pattern Development (3DPD) Workshop @ PLoP 2014

July 8, 2014 5:05 PM

Peter Scupelli and Paul Inventado facilitated the Data-driven Design Pattern Development (3DPD) Workshop which was  held in conjunction with the 21st Conference on Pattern Languages of Programs (PLOP 2014).

Abstract:

Workshop description: Increasingly, outside of the design pattern community, big data is being used to validate design decisions. For example, A/B testing and simple randomized experiments with two variants are used to validate design decisions in online settings such as web-design, social media, and so forth. Likewise, in online math tutor systems, data-driven approaches are used to identify math problems that confuse and frustrate students or are linked to positive learning outcomes. Big data and measurable outcomes can help to identify problems and confirm high-quality solutions. Design patterns provide a very effective way to describe known design problems and design solutions. In this workshop, we propose to explore the role of data-driven processes in the development of design patterns, such that data-driven exploration may help authors uncover problems and high-quality solutions. In the workshop, we explore domains where data-driven approaches may be appropriate to develop design patterns, methodologies for collecting data, techniques for pre-processing data, approaches for analyzing data and utilizing its results to facilitate the design pattern development process. Participants will have the opportunity to experience the data-driven design pattern development approach through group discussions and simulations.

Last updated: 5:05 pm