Quincy Jia
American Association for Applied Linguistics (AAAL) 2026 Conference, Chicago
One of the most valuable experiences during my conference attendance was being matched with my AAAL mentor, Oksana Moroz, and having the opportunity to engage in a deeply meaningful mentoring conversation with her. What made this experience especially significant was that it went far beyond general networking or academic advice; it provided rare, personalized guidance at a pivotal stage of my doctoral journey.
During our meeting, Dr Moroz generously shared her own professional trajectory, reflecting on her growth from PhD student to assistant professor. She spoke candidly about the challenges, uncertainties, and decisions that shaped her path, which made her advice both practical and inspiring. In particular, she helped me think more clearly about my own post-PhD career planning, an area where I had been experiencing considerable uncertainty. Through our discussion, I gained a much stronger understanding that academic career development is not defined by research alone, but by the integration of research, teaching, and service. This broader perspective was transformative for me.
Another especially valuable insight was her emphasis on professional service. She encouraged me to become more actively involved in AAAL committees and to participate in the association not only as a conference presenter, but also as a contributing member of the scholarly community. This helped me recognize that service is not peripheral to academic development; rather, it is integral to building professional identity, expanding networks, and contributing meaningfully to the field. This mentoring exchange was the most valuable experience of the conference because it gave me clarity, confidence, and a more holistic vision of academic life. It transformed the conference from a venue for presenting research into a space for professional growth, and it offered guidance that I believe will shape my long-term career development.
During our meeting, Dr Moroz generously shared her own professional trajectory, reflecting on her growth from PhD student to assistant professor. She spoke candidly about the challenges, uncertainties, and decisions that shaped her path, which made her advice both practical and inspiring. In particular, she helped me think more clearly about my own post-PhD career planning, an area where I had been experiencing considerable uncertainty. Through our discussion, I gained a much stronger understanding that academic career development is not defined by research alone, but by the integration of research, teaching, and service. This broader perspective was transformative for me.
Another especially valuable insight was her emphasis on professional service. She encouraged me to become more actively involved in AAAL committees and to participate in the association not only as a conference presenter, but also as a contributing member of the scholarly community. This helped me recognize that service is not peripheral to academic development; rather, it is integral to building professional identity, expanding networks, and contributing meaningfully to the field. This mentoring exchange was the most valuable experience of the conference because it gave me clarity, confidence, and a more holistic vision of academic life. It transformed the conference from a venue for presenting research into a space for professional growth, and it offered guidance that I believe will shape my long-term career development.
Phoebe Liao
American Association for Applied Linguistics (AAAL) 2026 Conference, Chicago
The most valuable experience during this conference was not a single session, but the opportunity to observe how different scholars approach research and academic life. Being immersed in this environment felt like stepping behind the curtain of academia, where I could see not only the final “polished performances” of research, but also the attitudes, struggles, and commitments that shape them.
One particularly meaningful aspect was witnessing the diversity of academic attitudes. Some scholars approached research with strong critical and activist orientations, aiming to challenge dominant narratives, while others emphasized methodological rigor or theoretical innovation. This made me realize that there is no single “correct” way to do research; rather, academic work is shaped by one’s values, positioning, and goals. This insight helped me reflect more deeply on what kind of researcher I want to become.
Another valuable element was the guidance and support from senior scholars and mentors (and my supervisor, of course). Through both formal feedback and informal conversations, I received constructive suggestions on how to refine my research focus and strengthen my theoretical framework. These interactions made the research process feel less isolating and more collaborative.
Equally important was the chance to connect with other doctoral students. Talking with peers who are at similar stages of their academic journey creates a sense of shared experience. We exchanged ideas, discussed challenges, and reflected on our research trajectories, which helped me feel more grounded and motivated. Overall, this experience was valuable because it reshaped my understanding of academia, strengthened my research identity, and inspired me to move forward with greater clarity and confidence.
One particularly meaningful aspect was witnessing the diversity of academic attitudes. Some scholars approached research with strong critical and activist orientations, aiming to challenge dominant narratives, while others emphasized methodological rigor or theoretical innovation. This made me realize that there is no single “correct” way to do research; rather, academic work is shaped by one’s values, positioning, and goals. This insight helped me reflect more deeply on what kind of researcher I want to become.
Another valuable element was the guidance and support from senior scholars and mentors (and my supervisor, of course). Through both formal feedback and informal conversations, I received constructive suggestions on how to refine my research focus and strengthen my theoretical framework. These interactions made the research process feel less isolating and more collaborative.
Equally important was the chance to connect with other doctoral students. Talking with peers who are at similar stages of their academic journey creates a sense of shared experience. We exchanged ideas, discussed challenges, and reflected on our research trajectories, which helped me feel more grounded and motivated. Overall, this experience was valuable because it reshaped my understanding of academia, strengthened my research identity, and inspired me to move forward with greater clarity and confidence.
Queeny Cheng
GaPI 2026 Conference, Hong Kong
The most valuable experience during the conference was my own presentation, as it was my first time being a presenter at a PolyU-hosted academic confernence. Presenting the learner-teacher-GenAI collaborative model to an audience of experts provided a level of rigorous peer review that is impossible to achieve in isolation.
The significance of this experience lies in the shift it prompted in my perspective. Previously, I viewed the GenAI interaction primarily as a tool for formative feedback and assessments, however, through refining my short paper and presentation preparation, the processes helped me realize that the most significant outcome of my study is the metacognitive development of the students, how they learn alongside GenAI.
This realization is vital for the future of my research. It validates the “transferable insights” my paper mentions, suggesting that the value of my work isn't just in the specific business leadership context, but in the creation of a blueprint for AI literacy that students can carry into their careers. This experience turned a localized teaching project into a broader philosophical inquiry into the future of work and education, making it the most significant and transformative part of the conference.
The significance of this experience lies in the shift it prompted in my perspective. Previously, I viewed the GenAI interaction primarily as a tool for formative feedback and assessments, however, through refining my short paper and presentation preparation, the processes helped me realize that the most significant outcome of my study is the metacognitive development of the students, how they learn alongside GenAI.
This realization is vital for the future of my research. It validates the “transferable insights” my paper mentions, suggesting that the value of my work isn't just in the specific business leadership context, but in the creation of a blueprint for AI literacy that students can carry into their careers. This experience turned a localized teaching project into a broader philosophical inquiry into the future of work and education, making it the most significant and transformative part of the conference.
Li Menglu
Convergence Conference 2026, online
The most valuable experience was the case study on machine translation trust management in medical translation. A translator, discovered critical terminology errors in MT output that risked misinforming patients. Rather than passively accepting the flawed post-editing workflow, she negotiated with peers and the client to switch to full human translation. This moved my thinking beyond a simple “trust or distrust” binary toward trust management that integrates technical knowledge, risk assessment and social communication. The case showed that practitioners have real agency to reshape technology use through evidence-based negotiation, countering the narrative that AI inevitably deskills human work. For my research, it provided a real-world scenario I can adapt into a teaching case or an experimental variable, and it reinforced that translation quality in the AI era depends as much on socio-technical process management as on linguistic accuracy. This insight now directly informs how I design my post-editing studies, ensuring they capture not just output quality but the human judgement that sustains it.
Zhao Qun
IEEE International Conference on Data Mining 2025, Washington DC
The most valuable experience at the ICDM conference was a critical conversation with a clinical psychologist following my presentation on the "Suicidal Comment Tree Dataset." While technical sessions were informative, this dialogue fundamentally reshaped my perspective on the very foundation of my research: data annotation quality.
The experience centered on the psychologist's probing question regarding the utility and credibility of our annotation work. He praised our use of the C-SSRS framework but highlighted a critical blind spot: "Your labels are the ground truth for the model, but how confident are the annotators in their judgments?" He pointed out that mental health expressions on social media are inherently ambiguous; a single post can contain mixed signals of despair and hope, placing annotators in a difficult position. His seminal suggestion was to introduce a new metric into the annotation process: annotator confidence. He proposed that for each label assigned, annotators should also rate their confidence level on a Likert scale, from "speculative" to "certain."
This insight was profoundly significant because it directly addresses the challenge of uncertainty in real-world data. Quantifying annotator confidence transforms a static, categorical label into a rich, nuanced data point. Samples with low confidence flags can be re-examined to refine annotation guidelines, identify edge cases, or be weighted differently during model training to improve robustness. This approach moves beyond treating the dataset as a perfect ground truth and instead acknowledges and models the inherent subjectivity of the task. This conversation was a masterclass in interdisciplinary rigor, providing a simple yet powerful methodological enhancement that will significantly increase the validity and reliability of my future research datasets, ensuring they are not just large, but truly insightful.
The experience centered on the psychologist's probing question regarding the utility and credibility of our annotation work. He praised our use of the C-SSRS framework but highlighted a critical blind spot: "Your labels are the ground truth for the model, but how confident are the annotators in their judgments?" He pointed out that mental health expressions on social media are inherently ambiguous; a single post can contain mixed signals of despair and hope, placing annotators in a difficult position. His seminal suggestion was to introduce a new metric into the annotation process: annotator confidence. He proposed that for each label assigned, annotators should also rate their confidence level on a Likert scale, from "speculative" to "certain."
This insight was profoundly significant because it directly addresses the challenge of uncertainty in real-world data. Quantifying annotator confidence transforms a static, categorical label into a rich, nuanced data point. Samples with low confidence flags can be re-examined to refine annotation guidelines, identify edge cases, or be weighted differently during model training to improve robustness. This approach moves beyond treating the dataset as a perfect ground truth and instead acknowledges and models the inherent subjectivity of the task. This conversation was a masterclass in interdisciplinary rigor, providing a simple yet powerful methodological enhancement that will significantly increase the validity and reliability of my future research datasets, ensuring they are not just large, but truly insightful.
