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Data in Discourse Analysis Konferenz: DATAFIED-Projekt

Spannende Diskussionen über Daten, Software, Diskurs, Macht und Wissen gab es am Mittwoch, den 18.02.2020,  auf der Data in Discourse Analysis Konferenz an der TU Darmstadt. Felicitas Macgilchrist reflektierte, unter anderem basierend auf  den im DATAFIED-Projekt mit Juliane Jarke erarbeiteten Analysen zur prädiktiven Analytik, wie sich der „Analysegegenstand“ von Diskursstudien mit der zunehmenden Datenerfassung in der Bildung verändert.

Sie beobachtet Veränderungen des Diskurses „über“ Bildung, des Diskurses „in“ Bildung und macht auf die Notwendigkeit aufmerksam, den in der Bildung „verschlüsselten“ Diskurs zu analysieren.

Hier dazu das Abstract des Papers in aktualisierter Form: 

Datafication, the increased transformation of information about education into digitally manipulable data, is a process occurring in educational practice and in (critical) discourse analytical research on education. In part one of this paper, I explore three ways in which ‘digital data’ have changed the way educational discourse studies perceives its object of analysis. First, ‘data about education’ flow abundantly. Schools are producing more numeric data about their students than ever before. Critical discourse studies have analysed, e.g., PISA, ICILS and other international assessments, the media reports about these assessments, and the networks of ‘experts’ from data science, who are increasingly working alongside government agencies to co-write educational policy. Critical analyses have traced these distributed policy networks, following how discursive elements move across sectors. Second, discourse analyses of classroom practices are investigating ‘data in education’. Studies observe how digital data are transformed into data visualisations, analysing, for instance, the uptake of data visualizations by teachers and students during class time. Third, we can observe ‘data encoded into education’. Here, I see the most substantial change for discourse studies. Algorithms written by specific teams in specific (primarily for-profit) contexts shape the software with which teachers and students engage. Discourse analysts begin to look at code, learning analytics, dashboard design, software documentation. In part two of the paper, a short “worked example” from predictive analytics walks through these three dimensions, reflecting on how data have changed the way discourse studies perceives its object of analysis. The paper ends by suggesting epistemological, political and practical questions for future research.

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