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Analyzing Dialogue in Technology-Enhanced Educational Settings

Thu, April 13, 4:40 to 6:10pm CDT (4:40 to 6:10pm CDT), Hyatt Regency Chicago, Floor: West Tower - Ballroom Level, Regency C

Abstract

Objectives and Framework

This presentation explores the mediating role digital technology can play in shaping communication between participants (Blake et al., 2013), in this case opening up a ‘dialogic space’ (Wegerif, 2007) that is productive for student learning. Building on sociocultural theory (e.g., Wertsch, 1998), the objective is to develop methods that researchers and teachers can use to understand the learning taking place in technology-enhanced settings involving multimodal interactions with digital knowledge artefacts. These interactions can support rich new forms of dialogue that highlight differences between perspectives, make ideas and reasoning more explicit and collectively scrutinise them (Authors, 2011; Pifarré, 2019), and thereby increase collaborative idea development (Muukkonen, Lakkala & Hakkarainen, 2005). The manipulable, provisional nature of artefacts means they constantly evolve, providing interim records of socio-cognitive activity and supportive devices for learners’ emerging thinking. Nonverbal interactions with them can themselves constitute turns in dialogue (Samuelsson et al., 2021).

Methods and Data

This work develops new methods by which researchers and practitioners can understand the learning happening through/with technology. It uses multimodal analysis (Norris, 2004) to capture communication through entangled modes, especially talk and gesture during manipulation of shared digital artefacts. Development of the core analytic tool extended our previous work on turn-level coding to create and systematically apply a specialised dialogue coding framework for technology-mediated contexts (TOOLNAME). Data sources comprised dialogic interactions across diverse technology uses by learners located face-to-face or remotely – adapted to particular instructional goals. Technologies included: online discussions, tablet apps, augmented reality, Knowledge Forum, Scratch programming, and interactive whiteboards. A further, emerging methodological tool is epistemic network analysis (ENA), a quantitative ethnographic method for quantifying, visualising, and interpreting thematic connections across datasets (Shaffer, 2017). Our ENA applications include teachers’ responses to student ideas before and after technology-enhanced professional development (PD) incorporating mixed-reality simulation. Quantitative ENA data or coding was triangulated with qualitative analysis.

Results and Significance

The findings illustrate how the coding framework charts the learning resulting through multimodal whole-class dialogue that exploits technology affordances. For example, inviting elaboration of others’ reasoning, revisiting, and comparing with a portrait annotated after spotlighting focused attention on key ideas, and built collective understanding of the Elizabethan era (Appendix D).

PD incorporating simulation technology assisted science teachers in Pakistan in responding to student talk and learning needs in the moment. ENA illustrated how teachers contingently responded to students by widening, deepening, maintaining, and shaping the dialogic space, including significant pre-post response pattern differences in live lessons. For example, Minahil’s pre-PD response pattern focused on initiate and feedback. (Appendix E). Post-PD, she maintained and widened dialogic space by following up students’ ideas (Appendix E).

The analytic tools helped identify teacher and student learning outcomes in technology-enhanced environments, offering important implications for researchers and practitioners. Comparing ENA networks informs researchers about learning and supports teachers’ reflective practice. The coding scheme extends one already used in hundreds of practitioner inquiries globally, again for assessing change and informing dialogic pedagogy development, now in technology-mediated contexts.

Authors