Making Data Science Count In and For Education

Rosenberg, Joshua M.; Lawson, Michael J.; Anderson, Daniel John; Jones, Ryan Seth; Rutherford, Teomara

doi:10.4324/9780429260919-7

Cited by 12 publications

(11 citation statements)

References 38 publications

(46 reference statements)

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“…These micro-level interactions elide with Fischer et al’s (2020) description of how sentiment analysis as a method provides a meso-level account of the valence of an expression through an analysis of its linguistic features. Educational data science studies draw on techniques related to statistics, knowledge about education, and the power of computation and computer programming (Rosenberg, Lawson, et al, 2020). In this way, the use of advanced statistical or machine learning methods are not necessarily, alone, constitute educational data science.…”

Section: Using Social Media To Explore Public Sentiment About Educational Reformmentioning

confidence: 99%

Understanding Public Sentiment About Educational Reforms: The Next Generation Science Standards on Twitter

Rosenberg¹,

Borchers

Dyer

et al. 2021

AERA Open

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System-wide educational reforms are difficult to implement in the United States, but despite the difficulties, reforms can be successful, particularly when they are associated with broad public support. This study reports on the nature of the public sentiment expressed about a nationwide science education reform effort, the Next Generation Science Standards (NGSS). Through the use of data science techniques to measure the sentiment of posts on Twitter about the NGSS (N = 565,283), we found that public sentiment about the NGSS is positive, with only 11 negative posts for every 100 positive posts. In contrast to findings from past research and public opinion polling on the Common Core State Standards, sentiment about the NGSS has become more positive over time—and was especially positive for teachers. We discuss what this positive sentiment may indicate about the success of the NGSS in light of opposition to the Common Core State Standards.

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Section: Using Social Media To Explore Public Sentiment About Educational Reformmentioning

confidence: 99%

Understanding Public Sentiment About Educational Reforms: The Next Generation Science Standards on Twitter

Rosenberg¹,

Borchers

Dyer

et al. 2021

AERA Open

Self Cite

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“…What values are programmed into the apps, ed tech platforms, and repurposed social media sites that are being used in (and out of) classrooms all over the world? Do those who retrieve data from these platforms for dataintensive educational research (e.g., Baker & Siemens, 2015;Kimmons & Veletsianos, 2017;Rosenberg et al, 2021) look for miseducational values embedded in these "big data" or assume them to be objective (see D'Ignazio & Klein, 2020) and inherently educational? Is the design of a platform discriminatory and miseducative (Benjamin, 2019;Noble, 2018)?…”

Section: Studying Social Media As Designed Platforms Not Neutral Learning Spacesmentioning

confidence: 99%

Gab, Parler, and (Mis)educational Technologies: Reconsidering Informal Learning on Social Media Platforms

Greenhalgh¹,

Krutka²,

Oltmann³

2021

JAID

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Alternative" social media platforms like Parler and Gab-on which hate speech and conspiracy theories often exist unchecked-present an opportunity for instructional designers and other education professionals to revisit assumptions about informal learning on social media. Employing a conceptual framework that distinguishes education from miseducation, we use these controversial platforms to argue that educators should more fully consider: 1) the miseducation happening in learning spaces, 2) how the design of educational technologies may amplify miseducation, and 3) the importance that formal education resist miseducation.

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“…What values are programmed into the apps, ed tech platforms, and repurposed social media sites that are being used in (and out of) classrooms all over the world? Do those who retrieve data from these platforms for dataintensive educational research (e.g., Baker & Siemens, 2015;Greenhalgh et al, 2021;Kimmons & Veletsianos, 2017;Rosenberg et al, 2021) look for miseducational values embedded in these "big data" or assume them to be objective (see D'Ignazio & Klein, 2020) and inherently educational? Is the design of a platform discriminatory and miseducative Noble, 2018)?…”

Section: Studying Social Media As Designed Platforms Not Neutral Learning Spacesmentioning

confidence: 99%

Untitled

2021

JAID

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This journal will provide a peer-reviewed format for the publication of scholarly articles in the field of applied instructional design. The journal recognizes the role of the practitioner in the work environment and realizes that outside constraints may limit the data collection and analysis process in applied settings. The limitations of real-world instructional design of the practitioner can still provide valuable knowledge for the field. Sponsoring OrganizationJAID is a publication of the Association for Educational Communications and Technology (AECT).

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Making Data Science Count In and For Education

Abstract: T. (2020). Making data science count in and for education. In E. Romero-Hall (Ed.), Research Methods in Learning Design & Technology (pp. 94-110). Routledge.

Cited by 12 publications

References 38 publications

Understanding Public Sentiment About Educational Reforms: The Next Generation Science Standards on Twitter

Understanding Public Sentiment About Educational Reforms: The Next Generation Science Standards on Twitter

Gab, Parler, and (Mis)educational Technologies: Reconsidering Informal Learning on Social Media Platforms

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