Event Details

How can teachers sustain effective formative assessment when resources are limited? This talk reconceptualizes teacher readiness as an enacted regulatory practice, drawing on evidence from mobile-assisted language learning in low-resource settings.

Beyond Possession: Teacher Readiness as Enacted Regulatory Practice in Mobile- Assisted Language Learning

Teacher readiness in language education is commonly conceptualized as knowledge, competence, or disposition that precedes practice. While this informs research on teacher preparation and cognition, it explains little about how readiness is enacted when teaching must be sustained under constraint. This becomes visible in low-resource mobile-assisted language learning (MALL) settings, where teachers maintain formative assessment without purpose-built systems. A teacher who understands formative assessment but cannot enact it through available means is not yet ready in any practical sense.

This study reconceptualizes teacher readiness as an enacted metacognitive regulatory practice, observable through how teachers plan, monitor, and adjust activity. Rather than locating readiness in what teachers know or in what tools make possible, it argues that coherence depends on how teachers organize and adapt the resources they have. It proposes repurposing as a mechanism through which teachers reorganize general-purpose digital affordances into structured formative assessment. The argument draws on a multi-case study of teachers sustaining formative assessment on Telegram in low-resource settings, where regulatory work recurs across cases without teachers framing it as assessment.

A Note for This Meeting:

My work reads regulation on the teacher's side of the interaction, through its traces in action, where much of the cognition research here reads the learner's side, often, I assume, in real time, though you would know far better than I do. What strikes me is that these are not simply two parallel readings. When teachers detect a signal in learner output, diagnose what lies behind it, and adjust, they are modeling learner cognition, and much of their regulatory work is driven by that model. Anticipatory regulation is the stronger case, since the teacher acts on a prediction about learner processing before any signal arrives. Whether those models are accurate is a question my design cannot answer.

I would welcome discussion of one question in particular: What would it take to test the accuracy of teachers' inferences about learner processing, without flattening either side of the interaction?

To join remotely via Teams, please click this link.