Updated on 2024/03/28

写真a

 
GAYED, John Maurice
 
Affiliation
Affiliated organization, Global Education Center
Job title
Assistant Professor(tenure-track)
Degree
PhD ( 2023.03 Tokyo Institute of Technology )

Research Experience

  • 2023.05
    -
    Now

    Waseda University   Global Education Center   Assistant Professor

Research Areas

  • Educational technology
 

Papers

  • Exploring an AI-based writing Assistant's impact on English language learners

    John Maurice Gayed, May Kristine Jonson Carlon, Angelu Mari Oriola, Jeffrey S. Cross

    Computers and Education: Artificial Intelligence   3  2022.01

     View Summary

    The increasing use of English as a Lingua Franca (ELF) worldwide has brought attention to tools that can assist English as a Foreign Language (EFL) learners in their journey to fluency. Much research has shown that EFL learners often do not have sufficient latitude to output at a satisfactory level when writing in a second language. In addition, cognitive (working memory) resources are spent on low-level writing tasks (word production, translation) at the expense of time being allocated to higher-level writing tasks such as organization and revision. The researcher's laboratory developed an AI-based web application called “AI KAKU” to assist EFL learners in reducing the cognitive barriers they face when producing written text in English. While there has been much research and discussion on Automated Writing Evaluation (AWE) technologies or older technologies such as spell check and grammar check, few studies have attempted to use AI-based tools as learning instruments outside assessments. This study recruited adult EFL participants in a counter-balanced experiment to evaluate the potential impact of AI KAKU on student writing. Preliminary results indicate that this is a potentially useful tool for English language learners who need more structured assistance than traditional word processors.

    DOI

    Scopus

    38
    Citation
    (Scopus)
  • Impact on Second Language Writing via an Intelligent Writing Assistant and Metacognitive Training

    John Maurice Gayed, May Kristine Jonson Carlon, Jeffrey Scott Cross

    Proceedings - Frontiers in Education Conference, FIE   2022-October  2022

     View Summary

    This Research to Practice Full Paper investigates second language learners' writing output using an online next-word prediction writing tool after exposure to training and metacognitive prompts to improve their critical thinking. Engineering graduates' writing skills are often deemed lacking by industry standards; this can be even more challenging for English as a foreign language (EFL) learners. This study employs a randomized control trial with university-level participants using an internally developed writing aid with next-word prediction, reverse translation support, and metacognitive prompts. EFL participants were given question prompts in the TOEFL iBT independent writing task style, and the outputs were assessed (machine and human) using several measures for writing quality. All participants were shown short explanatory videos for TOEFL writing advice and metacognition training. The treatment group, exposed to the next-word prediction writing aid and metacognitive prompts, performed better than the control group even though both received the same training and writing opportunities. This study indicates there is value in providing writing support and metacognitive thinking practice to improve writing skills and, ultimately, writing output quality. This study's implications can be applied not only to EFL learners but also to engineering-related fields using English as a lingua franca.

    DOI

    Scopus

  • Educational Assistant Wireframe for the Elderly to Mitigate Urban Climate Health Risks

    May Kristine Jonson Carlon, Alvin Christopher Galang Varquez, Eden Mariquit Andrews, John Maurice Gayed

    30th International Conference on Computers in Education Conference, ICCE 2022 - Proceedings   2   638 - 640  2022.11

     View Summary

    The climate in urban centers can differ significantly from the immediate surrounding areas; this can pose health risks to the elderly who have spent much of their lives in urban centers and then move to more rural areas for retirement. Therefore, there is a need to develop educational software applications for the elderly that needs to account for their life experiences aside from physiological restrictions. This research created a connected wireframe for an educational assistant to make the elderly aware of the climate differences between their urban and rural residences. To address the difficulty of recruiting vulnerable subjects, especially during the COVID-19 pandemic, we evaluated our wireframe using a combination of heuristic evaluation and a variation of the Delphi process, an expert consensus-building tool typically used for market forecasting.

  • The Matthew effect in CALL: Examining the equity of a novel intelligent writing assistant as English language support

    John Gayed, May Kristine Jonson Carlon, Jeffrey Cross

    Proceedings of the XXIst International CALL Research Conference     80 - 93  2022.07

     View Summary

    As practitioners introduce new educational technologies into their classrooms, the potential for unintended outcomes from their use might arise. One such potential negative artifact is an increase in the achievement gaps between learners, where high performers tend to benefit more from newly introduced educational technologies than their peers. This phenomenon is commonly referred to as the Matthew effect. In this study, we leverage natural language processing (NLP) based transformers to introduce English language support to English as a Foreign Language (EFL) learners while they are in the writing process. A web-based application was created that uses next-word prediction and automatic reverse translation to help EFL participants in their writing.Adult English language learners from professional development language schools participated in a counterbalanced repeated measures study. To understand the presence of the Matthew effect, learners were grouped based on their self-reported EIKEN scores. Their performance according to two writing factors as well as their perceived cognitive load while using the tool were measured to establish which groups benefit the most from using the tool. This research sets the stage for understanding how emerging tools cansupport learning without exacerbating Matthew effects. These effects should beconsidered in both the development and application of educational technology.

    DOI

  • Educational Nonlinear Stories with Twine

    May Kristine Jonson Carlon, Donn Emmanuel Gonda, Eden Mariquit Andrews, John Maurice Gayed, Robert Anthony Olexa, Jeffrey Scott Cross

    L@S 2022 - Proceedings of the 9th ACM Conference on Learning @ Scale     248 - 251  2022.06

     View Summary

    Multiple studies have hinted at the positive effects of educational games on learner engagement. However, some games, if they exist, may not be readily usable for some lessons even though the same topics are covered. In this workshop, the participants will be introduced to Twine, an open-source development environment for nonlinear stories that requires little to no coding. Tips and tricks to making engaging stories that target desired learning outcomes derived from existing research will be shared. The participants will have the opportunity to apply these insights through a group activity where they create their stories for a lesson. They will then individually create games for their stories and share their works to the rest of the group. An online community will be created after the workshop for the participants to continue exchanging ideas or creations afterwards.

    DOI

    Scopus

    3
    Citation
    (Scopus)
  • Long-Term Effects of Short-Term Intervention Using MOOCs for Developing Cambodian Undergraduate Research Skills

    Cheyvuth Seng, May Kristine Jonson Carlon, John Maurice Gayed, Jeffrey S. Cross

       2021  [International journal]

    DOI

  • Examining The Impact Of Grammarly On The Quality Of Mobile L2 Writing

    Gilbert Dizon, John M. Gayed

    JALT CALL Journal   17 ( 2 ) 74 - 92  2021

     View Summary

    While the use of automated writing evaluation software has received much attention in CALL literature, as Frankenberg-Garcia (2019) notes, empirical research on predictive text and intelligent writing assistants is lacking. Thus, this study addressed this gap in the literature by examining the impact of Grammarly, an intelligent writing assistant that incorporates predictive text technology, on the mobile writing quality of Japanese L2 English students. Specifically, the study explored if Grammarly had a significant effect on the grammatical accuracy, lexical richness, writing fluency, or syntactic complexity of L2 students’ writing when compared to unassisted mobile writing. A total of 31 university EFL students participated in the 8-week study which utilized a counterbalanced design. Participants took part in weekly guided freewriting tasks under each writing condition (non-Grammarly and Grammarly) over the duration of the study. The descriptive statistics and results from t-tests showed that when students wrote with the assistance of Grammarly, they produced fewer grammatical errors and wrote with more lexical variation. These findings highlight the potential of predictive text and real-time corrective feedback as a way to support L2 writing, particularly among novice writers who may struggle to write effectively in the L2.

    DOI

    Scopus

    13
    Citation
    (Scopus)
  • Development of Open-Response Prompt-Based Metacognitive Tutor for Online Classrooms

    May Kristine Jonson Carlon, John Maurice Gayed, Jeffrey S. Cross

    TALE 2021 - IEEE International Conference on Engineering, Technology and Education, Proceedings     151 - 158  2021

     View Summary

    Metacognition, a set of skills essential to succeed in online learning environments, spans three distinct phases: planning, monitoring, and evaluating. An existing metacognitive tutor for developing knowledge of cognition and regulation of cognition at different problem-solving phases previously shown to be effective in an experimental setting was revisited in this research. The tool was optimized to be usable in learning management systems (LMS), which are frequently used in blended and online learning environments. It was then tested in a hybrid online class on electrical engineering offered to first-year undergraduate students. The students rated the tool while using it in an LMS and found it to be usable and improved cognition regulation significantly. The tool is cognitive domain agnostic; thus, it can be a convenient means of tutoring metacognition in online learning environments.

    DOI

    Scopus

    1
    Citation
    (Scopus)

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Research Projects

  • Investigating an AI-based writing assistant's impact on English language learners' writing proficiency

    日本学術振興会  科学研究費助成事業 基盤研究(C)

    Project Year :

    2022.04
    -
    2025.03
     

    ガイエド ジョンモリース, クロス ジェフリーS