ScholarSpace
ScholarSpace is an open-access, digital institutional repository for the University of Hawaiʻi at Mānoa community. ScholarSpace stores the intellectual works and unique collections of the UH at Mānoa academic community and also provides a permanent web location for those accessing these resources.
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Recent Submissions
The potential advantages of using an LLM-based chatbot for automated writing evaluation for English teaching practitioners
(University of Hawaii National Foreign Language Resource Center, 2025-05-05) Kim, Kyungmin; Lee, Jang Ho; Shin, Dongkwang
With the ever-increasing demand for assessing large amounts of student writing, Automated Writing Evaluation (AWE) has emerged as an efficient system to satisfy this demand. However, it has also been suggested that applying it in teachers’ writing classes may offer limited results. Given this, the present study developed an AWE chatbot based on ChatGPT 4.0-turbo, designed as an automated rater. A total of 465 narrative essays written by Korean high school EFL students were scored according to three criteria by the developed tool; these were then compared with the scores administered by two professional raters using various analytic measures. The results showed that the AWE chatbot’s scoring was strongly correlated with that of the human raters. Meanwhile, the many-facet Rasch model’s result indicated that the two human raters’ statistics demonstrated an excellent fit, whereas those of the developed AWE chatbot were slightly lower. The Coh-Metrix analysis suggested that the human raters’ scoring tendencies and GPT are largely aligned, indicating that both raters scored the essays similarly. Based on our findings, we suggest that the Large Language Model (LLM)-based AWE chatbot has great potential to assist teachers in EFL writing classrooms.
Comprehensibility of AI-generated and human simplified texts for L2 learners
(University of Hawaii National Foreign Language Resource Center, 2025-05-05) Murphy Odo, Dennis
There is currently limited investigation of readers’ comprehension of AI simplified text from the perspective of educators, but such research can help to more effectively address the specific needs and perspectives of language teachers and learners regarding the comprehensibility of AI simplified text. Therefore, the purpose of this study was to compare second language readers’ comprehension of an original reading passage, a version that was simplified by human experts, and a version that was automatically simplified by AI. Results showed that the AI and human simplified texts were not any easier to comprehend than the original version of the text when readers’ topic familiarity was taken into account in the analysis. These findings suggest that AI-generated simplified text does not yet improve L2 learners' comprehension. Thus, further study is needed on the effect of AI simplifications using learner-centered qualitative assessments like think aloud to assess the efficacy of simplified texts. These findings also serve as a reminder to researchers and teachers that they must carefully evaluate AI tools before attempting to apply them to instructional practice.
Flibl: A Tool to Ease Text Transfer Between ELAN and FLEx
(University of Hawaii Press, 2025-04) Amalia Skilton; Sunkulp Ananthanarayan; Sofia Gottlieb Pierson; Claire Bowern
Two of the most common software tools in language documentation are ELAN, for transcription, and FieldWorks Language Explorer (FLEx), for interlinearization. Many language documentarians use these tools together, and the transcribed output of ELAN is natural input to FLEx. Despite this, out of the box the two programs are not effectively interoperable. FLEx also does not allow users to display many data structures that are visible in ELAN and necessary for research purposes, such as speaker attributions. Therefore, we created Flibl [flɪbɫ]̩ , a software tool that automatically converts between the data formats used by ELAN and FLEx while keeping all ELAN information visible. This article offers a description and tutorial on the software. First, we describe our research motivations for creating Flibl, how researchers can use it and for what topics, and how the software works on the backend. Readers interested in using Flibl can download it from our stable repository at https://github.com/amaliaskilton/flibl.
FDA Regulation of Internet Pharmaceutical Communications: Strategies for Improvemen
(2000) Loza, Emile L.