Modeling Data From Collaborative Assessments: Learning in Digital Interactive Social Networks.

Saved in:

Bibliographic Details
Title:	Modeling Data From Collaborative Assessments: Learning in Digital Interactive Social Networks.
Authors:	Wilson, Mark¹ MarkW@berkeley.edu, Gochyyev, Perman¹ perman@berkeley.edu, Scalise, Kathleen² kscalise@uoregon.edu
Source:	Journal of Educational Measurement. Spring2017, Vol. 54 Issue 1, p85-102. 18p.
Subject Terms:	Collaborative learning, Cognitive learning, Learning strategies, Assessment of education, *Students, Problem solving methodology
Abstract:	This article summarizes assessment of cognitive skills through collaborative tasks, using field test results from the Assessment and Teaching of 21st Century Skills (ATC21S) project. This project, sponsored by Cisco, Intel, and Microsoft, aims to help educators around the world enable students with the skills to succeed in future career and college goals. In this article, ATC21S collaborative assessments focus on the project's 'ICT Literacy-Learning in digital networks' learning progression. The article includes a description of the development of the learning progression, as well as examples and the logic behind the instrument construction. Assessments took place in random pairs of students in a demonstration digital environment. Modeling of results employed unidimensional and multidimensional item response models, with and without random effects for groups. The results indicated that, based on this data set, the models that take group into consideration in both the unidimensional and the multidimensional analyses fit better. However, the group-level variances were substantially higher than the individual-level variances. This indicates that a total individual estimate of group plus individual is likely a more informative estimate than individual alone but also that the performances of the pairs dominated the performances of the individuals. Implications are discussed in the results and conclusions. [ABSTRACT FROM AUTHOR]
	Copyright of Journal of Educational Measurement is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database:	Education Research Complete

Description
Abstract:	This article summarizes assessment of cognitive skills through collaborative tasks, using field test results from the Assessment and Teaching of 21st Century Skills (ATC21S) project. This project, sponsored by Cisco, Intel, and Microsoft, aims to help educators around the world enable students with the skills to succeed in future career and college goals. In this article, ATC21S collaborative assessments focus on the project's 'ICT Literacy-Learning in digital networks' learning progression. The article includes a description of the development of the learning progression, as well as examples and the logic behind the instrument construction. Assessments took place in random pairs of students in a demonstration digital environment. Modeling of results employed unidimensional and multidimensional item response models, with and without random effects for groups. The results indicated that, based on this data set, the models that take group into consideration in both the unidimensional and the multidimensional analyses fit better. However, the group-level variances were substantially higher than the individual-level variances. This indicates that a total individual estimate of group plus individual is likely a more informative estimate than individual alone but also that the performances of the pairs dominated the performances of the individuals. Implications are discussed in the results and conclusions. [ABSTRACT FROM AUTHOR]
ISSN:	00220655
DOI:	10.1111/jedm.12134