research-article

Data-driven design pattern production: a case study on the ASSISTments online learning system

Authors:

Paul Salvador Inventado,

Peter ScupelliAuthors Info & Claims

EuroPLoP '15: Proceedings of the 20th European Conference on Pattern Languages of Programs

Article No.: 14, Pages 1 - 13

https://doi.org/10.1145/2855321.2855336

Published: 08 July 2015 Publication History

Abstract

Recently, online learning systems such as cognitive tutors, online courses, and massive open online courses (MOOCS) increased in popularity in various domains. 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 students' learning gains and affective states, which are indirect measures of system quality. Analysis of online learning system data can uncover linkages between particular design choices made and student learning. In this paper, we describe the data-driven design pattern production (3D2P) methodology to prospect, mine, write, and evaluate design patterns for online learning systems from collected data. Design patterns are high quality solutions for recurring problems in a particular context. Patterns identified with 3D2P can guide the addition of new content and the modification of system designs to maintain the quality of online learning systems. A case study on the ASSISTments math online learning system is presented to demonstrate the 3D2P methodology and discuss its benefits and limitations.

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Data-driven design pattern production: a case study on the ASSISTments online learning system

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EuroPLoP '15: Proceedings of the 20th European Conference on Pattern Languages of Programs

July 2015

714 pages

ISBN:9781450338479

DOI:10.1145/2855321

Conference Chair:
Claudius Link,
Program Chair:
Veli-Pekka Eloranta

Copyright © 2015 ACM.

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Published: 08 July 2015

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EuroPLoP 2015: 20th European Conference on Pattern Languages of Programs

July 8 - 12, 2015

Kaufbeuren, Germany

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Papageorgiou GSarlis VTjortjis C(2024)Evaluating the effectiveness of machine learning models for performance forecasting in basketball: a comparative studyKnowledge and Information Systems10.1007/s10115-024-02092-966:7(4333-4375)Online publication date: 1-Jul-2024
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