Affordances of Narrative and Numerical Data for Data Teams: A Social-Semiotic Approach to Data Use

• In Event: 47.070 - Collaborative Data Use: Why, How, and When Does It (Not) Work?

Abstract

Purpose and theoretical framework
Research on data use in education is characterized by a pervasiveness of empirical studies and a corresponding lack of theorization (Prøitz, Mausethagen, & Skedsmo, 2017). The under-theorization has been explained as the result of the multiple origins and purposes of data use: as a component in evidence-based teacher inquiry (Earl & Katz, 2006), or as part of the accountability movement (Nichols & Harris, 2016). These different traditions influence what counts as data, users’ perceptions of data, and whether multiple forms of data are perceived to have equal weight in decision-making (Lai & Schildkamp, 2016). However, although teachers’ beliefs about and capacity for data use are considered central to the connection between data and instructional change (Datnow & Hubbard, 2016), the affordances of data is a critical but less discussed aspect of data use. Affordance is a term denoting the idea that meaning is made with different modes of signs, each with different potentials and limitations (Bezemer, Jewitt, & o’Halloran, 2016). This theoretical paper presents a social-semiotic perspective on the affordances of data, showing how they shape meaning-making processes and practitioner agency.

Mode of inquiry
Adopting concepts from social semiotics, we discuss how the affordances of narrative and numerical data affect data team interpretations of and interactions with data. Examples from interventions in Norway and New Zealand will illustrate how the affordances of data influence data use.



Data sources / Results and substantiated conclusions
Narrative data typically consist of units such as protagonists and opponents, tools, dramatic encounters, story arcs with conflicts, and often conclude with a resolution of the conflict (Polkinghorne, 1995; Riessman, 2008). Examples of narrative data include anecdotes of teaching experiences, learning processes, and successful or failed attempts at helping students achieve their goals. Narrative data often relate to other narratives; consequently, narrative data are important in continuous sense-making processes, but less suitable when a higher degree of precision is needed.

Numerical data are nested in mathematical discourse and are typically positioned epistemologically as part of the objectivist theory of knowledge. Statistical representation, the most common form of numeric data in data teams, often poses interpretive challenges for practitioners and may both enhance and hinder meaning-making. For example, a challenging feature is the fixed meaning of concepts such as means, medians, or population, and their implications.

The NZ literacy interventions capitalized on the affordances of narrative and numerical data, by using statistics to identify trends (for greater precision), and transcripts of teaching or anecdotes for sense-making and problem-solving. A focus on the numbers as part of a wider story of how to support students further served to bridge the two modes, while capitalizing on the literacy teachers’ inclination towards narratives. However, in Norway, teachers were comfortable with narrative data but struggled with or distrusted numerical data. This created discrepancies in what counted as data in decision-making processes.

Significance of the study
A critical understanding of the affordances of data will strengthen data teams’ design processes and practices that support decision-making and for instructional change.

Authors

• Henning Fjørtoft, The Norwegian University of Science and Technology

• Mei Kuin Lai, The University of Auckland