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Revisiting Initial Perspectives: From Principles to Practice

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Revisiting Initial Perspectives: From Principles to Practice

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At the start of this course, my thinking was grounded in the foundational ideas of Chun et al. (2016), emphasizing that developing technology-capable language teachers depends on principles rather than specific tools. I saw technology as an evolving landscape where teachers need openness, flexibility, and critical awareness—qualities necessary to adapt to unpredictable future innovations. My early response reflected a commitment to empowering teachers to analyze how technologies shape language and culture, rather than reacting to technological trends superficially.

However, as the course progressed, I realized that these principles are not abstract ideals but dynamic processes deeply embedded in the day-to-day realities of teaching and learning. The course readings challenged me to move beyond conceptual agreement toward understanding the micro-level interactions between teachers, students, and technologies. I began to see technology not just as a medium but as an active agent that transforms language use, classroom interaction, and even identity construction.

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Throughout the course, I found myself challenging conventional separations between “language,” “technology,” and “education.” Early on, I viewed these as intersecting but distinct domains. Now, I envision them as entangled, co-constitutive forces shaping each other in fluid ways. For instance, when analyzing course readings on multimodality and digital literacies, I began to appreciate that language itself transforms when mediated through different technologies—text messaging, video conferencing, social media—all bring unique cultural codes and communicative norms.

This realization disturbed my previous mental map where language was a static system to be transmitted, and technology was a neutral channel. Instead, I now see language as performative and technology as ideological, shaping what counts as “literacy” in diverse contexts. This has profound implications for my teaching education: preparing technology-capable teachers means cultivating my ability to critically interrogate these shifting boundaries and to facilitate student agency in navigating them.

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Looking Forward: Embracing Complexity and Uncertainty

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Looking Forward: Embracing Complexity and Uncertainty

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Reflecting on this transformation, I am realizing that I am okay with ambiguity and the complexity in the intersections of language, technology, and education. Rather than seeking predictive certainty, I embrace a posture of inquiry and responsiveness, grounded in critical principles but open to emergent possibilities. This mindset aligns with Chun et al.’s call for teachers to prepare students for “whatever new technologies they encounter,” but it also acknowledges the ongoing labor and reflexivity required from teachers themselves.

This course has transformed my understanding from a conceptual framework to a process-oriented vision of technology-capable language teaching. It has reshaped how I see the interconnections among languages, technologies, and education—not as static categories but as living, shifting ecosystems demanding creative, critical engagement at every level.

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Disturbing Conventional Boundaries: Language, Technology, and Learner Agency

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Disturbing Conventional Boundaries: Language, Technology, and Learner Agency

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Throughout the course, I came to see language, technology, and education not as distinct spheres but as a dynamic ecosystem of interrelations. Kasch’s study highlighted how assistive multimodal designs scaffold not only comprehension but also learners’ self-efficacy and intrinsic motivation—a triad often overlooked in traditional tech integration narratives.

This disturbed my earlier mental map where language was a stable system and technology a neutral conduit. Instead, technologies actively reconfigure language learning by enabling “reading-plus” strategies—multisensory integration, lexical hypothesis testing, and self-regulation—that transform how learners experience and produce language.

As a teacher myself, the learners’ diverse strategies with the UDL e-book (e.g., switching between English and Danish retelling, using pictorial glosses first, or testing pronunciation with text-to-speech) disrupted any simplistic notion of linear or uniform language acquisition. Technology, then, becomes not a “boon or threat” but a complex mediator that amplifies diversity, agency, and variability in learning trajectories.

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Deepening Understanding of Affordances and Digital Equity

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Deepening Understanding of Affordances and Digital Equity

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Module 2’s focus on digital equity and access pushed me to confront the uneven realities behind technology use. Kasch’s research provided a textured view of how UDL-guided scaffolds can mitigate adverse Matthew effects by supporting struggling readers and below-average learners through multimodal inputs and scaffolding that respect learner diversity.

I was struck by the learners’ delight in having “all the functions” at their disposal, which fostered task persistence and positive self-regulation even among those previously frustrated by reading tasks. Yet, the study also surfaced “misaffordances”—cases where learners feared over-reliance on scaffolds might undercut their own learning or where interface design posed barriers for learners with dyslexia or OCD-like behaviors.

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Exploring AI’s Language Affordances: Personalization, Cognitive Load, and Ethical Dimensions

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Exploring AI’s Language Affordances: Personalization, Cognitive Load, and Ethical Dimensions

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Module 3 expanded my perspective by introducing AI-based oral and written language tools, focusing on their affordances and ethical complexities. The study on AI KAKU (Gayed et al., 2022) particularly resonated. It demonstrated how AI-powered word suggestions and reverse translation functions can reduce cognitive load for L2 writers struggling with “tip-of-the-tongue” retrieval and translation bottlenecks.

This detailed exploration helped me see AI not merely as a convenience but as a pedagogical instrument that can scaffold higher-level writing processes like syntactic complexity and fluency. The quantitative and qualitative data showed promise for AI tools to support lexical diversity and sentence fluency, though results also cautioned about factors like insufficient user training and potential biases embedded in language models.

Ethical considerations emerged vividly: AI’s reliance on large-scale web data introduces biases, and its non-discriminatory generation of language can produce problematic outputs, necessitating teacher oversight. This layered understanding disturbed simplistic techno-optimism and underscored the importance of critical digital literacy among both educators and learners.

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In module 2, the authors don’t present UDL scaffolding as a panacea but rather as a dynamic, sometimes contradictory force. They wrestle with balancing empowerment and autonomy—ensuring scaffolds enhance learning without fostering dependence or frustration. This tension invites ongoing reflection on design practices that must be inclusive yet adaptable, addressing both cognitive and emotional learner needs. The research’s findings prompt a critical stance that sees technology neither as inherently enabling nor limiting but as a landscape shaped by design choices, learner perceptions, and diverse contexts.

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Disturbing Conventional Representations: Toward an Entangled, Emergent View

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Disturbing Conventional Representations: Toward an Entangled, Emergent View

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Reflecting on the course as a whole, I now reject neat separations between “language,” “technology,” and “education.” Instead, I envision these domains as mutually constitutive and emergent, forming a complex ecosystem where meaning, identity, and power are continuously negotiated. Language use reshapes technology (e.g., through user input and adaptation), technology reframes language practices (e.g., through multimodal affordances and AI-mediated writing), and education situates these interactions within cultural and ethical dimensions.

This perspective unsettles traditional metaphors of technology as a mere “tool” or “channel” and invites embracing ambiguity, creativity, and critical inquiry. It foregrounds the lived experiences of learners and teachers as co-constructors of evolving literacies in digitally mediated contexts.

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Looking Ahead: Embracing Complexity, Creativity, and Criticality in Future Teaching

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Looking Ahead: Embracing Complexity, Creativity, and Criticality in Future Teaching

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This course has transformed my view from seeking fixed strategies to nurturing adaptive expertise and critical digital literacy. Future teaching must balance principled flexibility, ethical vigilance, and ongoing research engagement. Teachers are not just implementers but designers, ethnographers, and learners themselves—tasked with navigating the tensions and possibilities technology brings to language education.

My journey has been one of deepening complexity and integration—moving from foundational principles to detailed, situated understandings of how technology reshapes language learning and teaching. It has equipped me to think creatively and critically about emerging technologies and their roles in fostering equitable, dynamic, and meaningful language education.

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From Conceptual Curiosity to Embodied Interaction: Shifting My View on Technology’s Role

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From Conceptual Curiosity to Embodied Interaction: Shifting My View on Technology’s Role

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Module 4’s deep dive into Robot-Assisted Language Learning (RALL), especially through Huang and Moore’s (2023) comprehensive review, radically expanded that view. Here, technology is no longer an abstract medium but a physically embodied social actor capable of multimodal interaction—speech, gestures, movement—that transforms not only how language is taught but how learners emotionally and cognitively engage.

This shift disturbed my earlier mental map that saw technology as largely disembodied digital tools. Instead, social robots bring language learning into the realm of complex human-robot interaction (HRI), where physical presence, embodied gestures, and emotional expressiveness can enhance motivation and memorization in ways tablets or computers cannot.

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Navigating the Complexities: The Process of Human-Robot Interaction in Language Learning

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Navigating the Complexities: The Process of Human-Robot Interaction in Language Learning

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The detailed exploration of robot types—autonomous, teleoperated, and hybrid—and forms—zoomorphic, cartoon-like, humanoid—highlighted the intricate design decisions shaping RALL’s affordances. For instance, teleoperated robots like South Korea’s Engkey compensate for current limitations in speech recognition for non-native speakers, allowing more flexible, context-aware interaction. The process of integrating robots into classrooms is thus a delicate balance—teachers must scaffold interactions, manage learner emotions, and align robot functions with pedagogical goals. This complex choreography goes far beyond simply “using a tool” and involves co-constructing learning experiences with human and robotic agents.

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Integrating Course Insights: From Affordances to Adaptive Expertise

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Integrating Course Insights: From Affordances to Adaptive Expertise

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Reflecting across course modules, I now see the connections among technologies, languages, and education as a dynamic ecosystem of affordances, learner agency, and sociocultural context. Kasch’s (2019) work on Universal Design for Learning (UDL) multimodal scaffolds parallels RALL’s embodied multimodality, both emphasizing relational affordances shaped by learner diversity and interaction patterns. The course has transformed my understanding from viewing technology as a neutral delivery platform to seeing it as a socially and culturally situated participant in language learning ecosystems. Robots exemplify this complexity: their physicality and social affordances invite new pedagogical possibilities while raising unresolved technical, ethical, and emotional challenges.

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Mobile Assisted Language Learning (MALL): Evidence-Based Insights on Speaking Skill Development

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Mobile Assisted Language Learning (MALL): Evidence-Based Insights on Speaking Skill Development

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What stood out to me in module 5 is the evidence that MALL applications like WhatsApp and WikiTalki, often used outside formal classrooms, promote collaborative, learner-centered, and self-regulated practice. This expanded my view of language learning environments beyond institutional walls. Yet, the caution that learners require training in self-monitoring and motivation management reminded me that technology alone is insufficient—effective teacher guidance remains essential.

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Flipped Language Classrooms: Integrating Theory, Practice, and Tools for Active Learning

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Flipped Language Classrooms: Integrating Theory, Practice, and Tools for Active Learning

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Zou et al. (2022) provided a comprehensive, data-rich perspective on flipped classrooms, synthesizing theoretical foundations (self-regulated learning, TAM, gamification), learning activities (pre-, during-, after-class), and diverse e-tools (video platforms, interactive quizzes, online discussions). This systematic review enriched my understanding of flipped learning as a dynamic, scaffolded process promoting autonomy, motivation, and higher-order thinking.

The detailed breakdown of learning foci—listening and grammar pre-class, balanced multimodal engagement during class, productive skills after class—revealed how flipped classrooms orchestrate language skills development across time and space. The emphasis on teacher roles as facilitators, motivators, and feedback providers resonated with earlier themes on adaptive teacher expertise. However, the challenges highlighted—student readiness, workload, technical issues, and need for professional development—grounded my reflections in practical realities, emphasizing the importance of thoughtful design and scaffolding for successful flipped learning.

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Promotion of Collaborative Language Learning (through MALL)

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Promotion of Collaborative Language Learning (through MALL)

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The integration of mobile technology in teaching and learning a second language, while promising, is not without its challenges, particularly in bridging the technological gap between developed and developing countries (Mustaffa & Sailin, 2022). The importance of teacher guidance remains paramount in facilitating language acquisition, even in technology-rich environments. The challenge for educators and instructional designers lies in creating learning materials that are optimized for mobile devices across all educational levels.

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Looking Forward: Embracing Complexity and Pedagogical Innovation

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Looking Forward: Embracing Complexity and Pedagogical Innovation

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This course has transformed my thinking from seeking fixed recipes to cultivating adaptive expertise, critical digital literacy, and collaborative inquiry. Whether through embodied social robots, AI writing assistants, mobile learning apps, or flipped classroom designs, technology’s role is nuanced and context-dependent.

Future teaching demands openness to emergent technologies and learner diversity, commitment to ethical practice, and active participation in technology design and research. I am now more confident to navigate and contribute to this evolving landscape, fostering equitable, engaging, and meaningful language learning experiences.

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Disturbing Traditional Roles: Where Do Teachers and Robots Fit?

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Disturbing Traditional Roles: Where Do Teachers and Robots Fit?

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I was struck by the ethical and practical questions raised around robot-mediated pronunciation assessment. The insistence on native-like accuracy, often embedded in robot feedback, raises fairness concerns and questions about linguistic diversity and identity—how good is “good enough” pronunciation? This unsettled my assumptions about standardized language norms and highlighted the need for human-centered, transparent, and adaptive robot designs.

The variety of classroom contexts—from South Korea’s large-scale Engkey deployment to Japan’s Musio X with AI conversational engines and Europe’s NAO robot projects—illustrates how cultural, institutional, and technological factors shape RALL implementation. My role emerges as a critical mediator, adapting robot use to syllabus needs, learner profiles, and ethical considerations.

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Chun, D. M., Smith, B., & Kern, R. (2016). Technology in language use, language teaching, and language learning. The Modern Language Journal, 64–80. https://doi.org/10.1111/modl.12302

Gayed, J. M., Carlon, M. K. J., Oriola, A. M., & Cross, J. S. (2022). Exploring an AI-based writing Assistant's impact on English language learners. Computers and Education: Artificial Intelligence, 3, 100055. https://doi.org/10.1016/j.caeai.2022.100055

Huang, G., & Moore, R. K. (2023). Using social robots for language learning: Are we there yet? Journal of China Computer Assisted Language Learning, 3(1), 208-230. https://doi.org/10.1515/jccall-2023-0013

Kasch, H. (2019). Experimental studies of the affordances of assistive multimodal learning designs: Universal design for learning in modern language classrooms. JISTE, 23(2), 93-107.

Li, R. (2024). Effects of mobile-assisted language learning on foreign language learners' speaking skill development. Language Learning & Technology, 28(1), 1-26. https://hdl.handle.net/10125/73553

Mustaffa, N. U. C., & Sailin, S. N. (2022). A Systematic Review of Mobile-Assisted Language Learning Research Trends and Practices in Malaysia [Review of A Systematic Review of Mobile-Assisted Language Learning Research Trends and Practices in Malaysia]. International Journal of Interactive Mobile Technologies (iJIM), 16(5), 169. kassel university press. https://doi.org/10.3991/ijim.v16i05.28129

Unsplash. (n.d.). Best 100+ abstract pictures [HD]: Download free images on unsplash. Best 100+ Abstract Pictures [HD] | Download Free Images on Unsplash. https://unsplash.com/s/photos/abstract

Zou, D., Luo, S., Xie, H., & Hwang, G.-J. (2022). A systematic review of research on flipped language classrooms: theoretical foundations, learning activities, tools, research topics and findings. Computer Assisted Language Learning, 35(8), 1811-1837. https://doi.org/10.1080/09588221.2020.1839502