Learning analysis of K-12 students' online problem solving: a three-stage assessment approach. Issue 2 (17th February 2017)

• Record Type: Journal Article
• Authors: Hu, Yiling; Wu, Bian; Gu, Xiaoqing
• Is Part Of: Interactive learning environments. Volume 25:Issue 2(2017)
• Page Start: 262
• Page End: 279
• Publication Date: 2017-02-17
• Subjects: Problem solving -- learning analytics -- large-scale assessment -- evidence-centered design -- cognitive diagnosis -- cluster analysis -- sequential data mining; Educational technology -- United States -- Periodicals; 371.33
• DOI: 10.1080/10494820.2016.1276080
• Languages: English
• ISSNs: 1049-4820

Abstract

ABSTRACT: Problem solving is considered a fundamental human skill. However, large-scale assessment of problem solving in K-12 education remains a challenging task. Researchers have argued for the development of an enhanced assessment approach through joint effort from multiple disciplines. In this study, a three-stage approach based on an evidence-centered design framework is proposed to analyze problem-solving behavior, abilities, and performance. The approach is applied to assess the online problem solving of 554 students in a Shanghai primary school. The study reveals four clusters with distinctive problem-solving behavior, abilities, and performance. The findings of this approach also corroborate the results of the Programme for International Student Assessment of Shanghai students' problem-solving performance. The implications and limitations of this study are also discussed.