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The purpose of this paper is to provide an overview of a commissioned research study that analyzed a schooling initiative with the ambitious goal of transforming learning environments across the district by advancing innovative, inquiry-driven pedagogical practices combined with 1:1 iPad distribution. The paper explores impacts of the initiative on pedagogical innovation, twenty-first century learning, and related impacts on professional learning, collaboration, and culture change in the pilot schools analyzed in the study.

A multi-dimensional case study approach was used to analyze how the initiative was implemented, and to what extent teaching, learning, and professional cultures were transformed, based on action plan inputs and “change drivers”. Research methods included structured, open-ended interviews conducted with randomly selected teachers and key informants in leadership roles, focus groups held with students, as well as analysis of policy documents, student work samples, and other data sources.

The authors found evidence of a synergistic relationship between innovations in inquiry-driven pedagogy and professional learning cultures, with evidence of increased collaboration, deepened engagement and persistence, and a climate of collegiality and risk-taking at both classroom and organizational levels. Based on initiative inputs, the authors found that innovations in collaborative technology/pedagogy practices in classrooms paralleled similar innovations and transformations in professional learning cultures and capacity-building networks.

This initiative analyzed in this paper provides a case study in large-scale system change, offering a compelling model for transformative policies and initiatives where interwoven innovations in pedagogy and technology mobilization are supported by multiple drivers for formal and informal professional learning/development and networked collaboration. Challenges and recommendations are highlighted in the concluding discussion.

The transformative initiative analyzed in this paper provides a very timely case-model for innovations in twenty-first century learning and, specifically, for enacting and sustaining large-scale system change where inquiry-driven learning and technology tools are being mobilized to support “deep learning”, “new learning partnerships”, and multilevel transformations in professional learning (Fullan and Donnelly, 2013). This research advances scholarly work in the areas of twenty-first century learning, identifying relationships between technology/pedagogy innovation and professional capital building (Hargreaves and Fullan, 2012).

Technologically-enhanced language education has shifted from computer-assisted language learning (CALL) to mobile-assisted language learning (MALL), including the use of conversational digital agents, and more recently, towards the use of generative artificial intelligence (AI) large language model (LLM) programmes for language learning purposes. This paper aims to explore the interplay between such posthuman communication and posthumanist applied linguistics, and between digital agents and human agency in response to the increasing permeation of AI in life and learning.

A core team of four researchers investigated how digital agents could be leveraged to support immersive target language learning and practice, focusing specifically on the conversational AI that pervaded digitally-mediated communication prior to the release of generative AI. Each researcher engaged in a digital autoethnography using conversational agents found in the digital wilds to learn a target second language via digital immersion.

Through qualitative data analysis of autoethnographic narratives using NVIVO, four key thematic codes characterizing the learning journeys emerged: context, language learning, posthuman engagement and technological parameters. The posthuman learning experiences conflicted with the multisensory, embodied and embedded ethos of posthumanist applied linguistics, indicating that informed human pedagogical agency must crucially be exercised to benefit from the learning potential of posthuman agents. Interactions with conversational agents did provide small-scale, just-in-time learning opportunities, but these fell short of immersive learning.

The methodology and findings offer a unique and valuable lens on the language learning potential of emerging LLM-based generative agents that are rapidly infusing conversational practices.