Together Research Archive for 2024 includes co-created articles, peer-reviewed submissions, and non-traditional thought and opinion pieces. This archive from 2024 not only showcases the cutting-edge work conducted across multiple disciplines but also emphasizes research with practical impact, aimed at improving societal well-being. This curated selection highlights rapid publications, ensuring timely access to relevant findings in the fast-evolving field of technology and beyond.
As education enters the era of agentic AI where tools act autonomously on behalf of students, leaders must grapple with both unprecedented opportunities and systemic risks. This paper draws on two decades of teaching experience and empirical research to frame a critical challenge: the automation abyss, a growing divide between learners who retain agency and those who rely entirely on automated systems. Using scenario planning, this study outlines plausible futures for education, the cognitive implications of AI overuse, and curricular implications. The results reveal that while AI adoption in education is accelerating rapidly, institutions can shape outcomes through strategic curriculum design. By implementing human checkpoints, redesigning learning to preserve inquiry, and establishing ethical frameworks for agentic AI, educational leaders can navigate this transition successfully. The core message: the trajectory of AI in education is not inevitable; it's a matter of strategic leadership, curriculum design, and ethical practice.
This book documents a field-level experiment in collaborative knowledge building for XR in education shaped by more than 40 core presenters and hundreds of active participants across linked events and working sessions. Through unconferencing, shared storytelling, and structured group synthesis, educators, researchers, developers, students, and administrators worked together to surface common challenges, examine real implementation constraints, and compare approaches across contexts. Contributions reflect wide geographic variety, including Asia, Europe, North America, and the Global South, with cases drawn from rural schools, urban universities, open universities, community labs, and national-scale deployments. Rather than advancing a single expert position, the work shows how collective analysis shaped understanding of technological, pedagogical, accessibility, and infrastructure issues as they are experienced in practice. The overall findings suggest that sustainable XR integration depends less on hardware or platforms than on institutional coordination, teacher agency, and shared design practices. The book is valuable because it captures how a field is actively being formed through dialogue, experimentation, and negotiated understanding rather than through theory alone.
Hawkinson, E., Banerjee, P., Alip, A. S., Garcia, J., Putman, S., Wuttisittikulkij, L., Mangubat, L., Klaphake, J., Black, S., Taylan, F., Saludadez, L. J., & Cabanes, R. V. (2025). World immersive learning labs community report 2025: Community-driven solutions for XR in education. Together Learning Research. https://doi.org/10.62883/ZHHV3484
In April 2025, researchers from the University of Zurich deployed AI bots on Reddit's r/changemyview subreddit without permission, discovering that AI-generated comments were six times more persuasive than human responses in changing users' views. While Reddit threatened legal action and condemned this as "psychological manipulation," this article argues that these researchers operated as academic "ethical hackers," exposing critical vulnerabilities in social media platforms. Drawing parallels to cybersecurity's white hat tradition, I examine how platforms like Reddit profit from selling user data to AI companies while restricting independent research that reveals manipulation risks.
This article explores the growing dependency on artificial intelligence in education and introduces the concept of the “automation abyss”, a new digital divide separating learners who retain agency from those who rely on AI-mediated experiences. Drawing on classroom observations, research on the Budding Botanist Paradox, and studies such as the Penn AI tutoring trial, the author argues that automation is not just improving efficiency but eroding core learning processes like struggle, inquiry, and human connection. Through examples from coursework and digital citizenship training, the article highlights a concerning feedback loop: teachers, students, and edtech companies increasingly use AI to replace, rather than support, authentic learning. To address this, the author proposes a framework centered on human checkpoints, critical reflection on automation, and self-awareness in technology use. Ultimately, the article calls for a shift toward “augmented pedagogy” that enhances rather than automates the learning experience.
This article explores the emerging field of AI-augmented memory, highlighting both its promise and its paradox. From everyday tools like smartphone contact lists and transcription software to advanced systems such as Microsoft’s Recall and brain-computer interfaces, technology is rapidly transforming how humans store, retrieve, and process information. In education and professional contexts, these systems hold the potential to revolutionize learning, training, and creativity by linking contextual information to places, objects, and experiences. Yet, alongside these opportunities come pressing challenges. The article emphasizes that forgetting is not a cognitive weakness but a crucial function for adaptability, emotional regulation, and creativity. Overreliance on AI memory aids risks cognitive rigidity, privacy violations, and the homogenization of thought. Drawing on research and global workforce studies, it argues that cognitive flexibility, critical thinking, and metacognition must be prioritized in this new era of learning. Ultimately, the author calls for a balanced approach—designing AI-augmented systems that complement rather than replace human memory but ensuring that technology enhances human growth, creativity, and resilience rather than constraining them.
This study examines the phenomenon of increased em dash usage in AI-generated text and its subsequent influence on human writing practices through the lens of technological determinism and social construction of technology (SCOT). Through analysis of recent empirical research, this paper addresses two primary research questions: (1) What computational and data-driven factors explain the prevalence of em dashes in major LLM outputs? and (2) How are educational institutions and writers responding to this phenomenon? The research reveals a complex dialectical relationship where computational factors including training data composition, tokenization processes, and reinforcement learning from human feedback—create distinctive punctuation patterns that subsequently influence human writing behavior. Educational institutions are adapting through comprehensive policy frameworks while writers are modifying their practices in response to AI-generated text characteristics. The findings support Marshall McLuhan's concept that "we shape our tools, and thereafter our tools shape us,"[11] demonstrating that AI writing tools represent neither pure technological determinism nor complete social construction, but rather an ongoing co-evolutionary process reshaping the fundamental nature of written communication.
Eric is a learning futurist, tinkering with and designing technologies that may better inform the future of teaching and learning. Eric's projects have included augmented tourism rallies, AR community art exhibitions, mixed reality escape rooms, and other experiments in immersive technology.
Roles
Professor - Kyoto University of Foreign Studies
Research Coordinator - MAVR Research Group
Founder - Together Learning
Designer - Reality Labo
Community Leader - Team Teachers
Chair - World Immersive Learning Labs
