المؤلفون: Yuni Susanti, Takenobu Tokunaga, Hitoshi Nishikawa

المصدر: Research and Practice in Technology Enhanced Learning, Vol 15, Iss 1, Pp 1-22 (2020)

مصطلحات موضوعية: Automatic question generation, Computerised adaptive test, English vocabulary question, Multiple-choice question, Information technology, T58.5-58.64, Education

الوصف: Abstract The present study focuses on the integration of an automatic question generation (AQG) system and a computerised adaptive test (CAT). We conducted two experiments. In the first experiment, we administered sets of questions to English learners to gather their responses. We further used their responses in the second experiment, which is a simulation-based experiment of the AQG and CAT integration. We proposed a method to integrate them with a predetermined item difficulty that enables to integrate AQG and CAT without administering the items in a pretesting. The result showed that all CAT simulations performed better than the baseline, a linear test, in estimating the test taker’s true proficiency.

وصف الملف: electronic resource

Relation: http://link.springer.com/article/10.1186/s41039-020-00132-w; https://doaj.org/toc/1793-7078

URL الوصول: https://doaj.org/article/59e9de99f7f6454ebf520d280c78573a

المؤلفون: Yuni Susanti, Takenobu Tokunaga, Hitoshi Nishikawa, Hiroyuki Obari

المصدر: Research and Practice in Technology Enhanced Learning, Vol 13, Iss 1, Pp 1-16 (2018)

مصطلحات موضوعية: Distractor, English vocabulary question, Automatic distractor generation, Multiple-choice question, Information technology, T58.5-58.64, Education

الوصف: Abstract The use of automated systems in second-language learning could substantially reduce the workload of human teachers and test creators. This study proposes a novel method for automatically generating distractors for multiple-choice English vocabulary questions. The proposed method introduces new sources for collecting distractor candidates and utilises semantic similarity and collocation information when ranking the collected candidates. We evaluated the proposed method by administering the questions to real English learners. We further asked an expert to judge the quality of the distractors generated by the proposed method, a baseline method and humans. The results show that the proposed method produces fewer problematic distractors than the baseline method. Furthermore, the generated distractors have a quality that is comparable with that of human-made distractors.

وصف الملف: electronic resource

Relation: http://link.springer.com/article/10.1186/s41039-018-0082-z; https://doaj.org/toc/1793-7078

URL الوصول: https://doaj.org/article/064f8c798ea44fcabe4e0e1a39f96a38

المؤلفون: Yuni Susanti, Takenobu Tokunaga, Hitoshi Nishikawa, Hiroyuki Obari

المصدر: Research and Practice in Technology Enhanced Learning, Vol 12, Iss 1, Pp 1-16 (2017)

مصطلحات موضوعية: Item difficulty, English vocabulary question, Automatic question generation, Multiple-choice question, Information technology, T58.5-58.64, Education

الوصف: Abstract The present study investigates the best factor for controlling the item difficulty of multiple-choice English vocabulary questions generated by an automatic question generation system. Three factors are considered for controlling item difficulty: (1) reading passage difficulty, (2) semantic similarity between the correct answer and distractors, and (3) the distractor word difficulty level. An experiment was conducted by administering machine-generated items to three groups of English learners. The groups were determined based on their standardised English test scores. In total, 120 items, generated using combinations of the above three factors, were tested. The results reveal that the distractor word difficulty level had the greatest impact on item difficulty, but this tendency changed depending on the proficiency of the test takers. These results will be of use when implementing a fully automatic system for administrating tests.

وصف الملف: electronic resource

Relation: http://link.springer.com/article/10.1186/s41039-017-0065-5; https://doaj.org/toc/1793-7078

URL الوصول: https://doaj.org/article/afc5a40bf6a140f3944a6532fbfcf753

المؤلفون: Hideya Mino, Kazutaka Kinugawa, Hitoshi Ito, Isao Goto, Ichiro Yamada, Takenobu Tokunaga

المصدر: 自然言語処理. 29(No. 4):1082-1105

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3a77dcb22fe1a44acea50939959a44af
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100884314

المؤلفون: Takenobu Tokunaga, Jan Wira Gotama Putra, Kana Matsumura, Simone Teufel

المصدر: Language Resources and Evaluation. :1-25

مصطلحات موضوعية: Structure (mathematical logic), Linguistics and Language, Argumentative, business.industry, Process (engineering), Computer science, Library and Information Sciences, computer.software_genre, Language and Linguistics, Education, Argumentation theory, Annotation, Artificial intelligence, Computational linguistics, business, computer, Interactive visualization, Natural language processing, Sentence

الوصف: Discourse structure annotation aims at analysing how discourse units (e.g. sentences or clauses) relate to each other and what roles they play in the overall discourse. Several annotation tools for discourse structure have been developed. However, they often only support specific annotation schemes, making their usage limited to new schemes. This article presents TIARA 2.0, an annotation tool for discourse structure and text improvement. Departing from our specific needs, we extend an existing tool to accommodate four levels of annotation: discourse structure, argumentative structure, sentence rearrangement and content alteration. The latter two are particularly unique compared to existing tools. TIARA is implemented on standard web technologies and can be easily customised. It deals with the visual complexity during the annotation process by systematically simplifying the layout and by offering interactive visualisation, including clutter-reducing features and dual-view display. TIARA’s text-view allows annotators to focus on the analysis of logical sequencing between sentences. The tree-view allows them to review their analysis in terms of the overall discourse structure. Apart from being an annotation tool, it is also designed to be useful for educational purposes in the teaching of argumentation; this gives it an edge over other existing tools.

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab6620a6eceed4a0dbec7f46bc696a68
http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100863502

المؤلفون: Dolc¸a Tellols, Takenobu Tokunaga, Hilofumi Yamamoto, Hikaru Yokono

المصدر: Transactions of the Japanese Society for Artificial Intelligence. 38:B-M52_1

مصطلحات موضوعية: Artificial Intelligence, Software

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1428113aae5010cb927888fe023450d
https://doi.org/10.1527/tjsai.38-1_b-m52

المؤلفون: Takenobu, Tokunaga^Aff10, Tomofumi, Koyama^Aff10, Suguru, Saito^Aff11, Manabu, Okumura^Aff11

المساهمون: Goos, Gerhard, editor^Aff1, Hartmanis, Juris, editor^Aff2, van Leeuwen, Jan, editor^Aff3, Carbonell, Jaime G., editor^Aff4, Siekmann, Jörg, editor^Aff5, Rist, Thomas, editor^Aff6, Aylett, Ruth S., editor^Aff7, Ballin, Daniel, editor^Aff8, Rickel, Jeff, editor^Aff9

المصدر: Intelligent Virtual Agents : 4th International Workshop, IVA 2003, Kloster Irsee, Germany, September 15-17, 2003. Proceedings. 2792:127-135

المؤلفون: Dolça Tellols, Takenobu Tokunaga, Hikaru Yokono

المصدر: Proceedings of the 14th International Conference on Computer Supported Education.

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::dffdafdea6c59c680bfb38fa5c0bcfd1
https://doi.org/10.5220/0011046300003182

المؤلفون: Jan Wira Gotama Putra, Simone Teufel, Takenobu Tokunaga

المصدر: Tokyo Institute of Technology

مصطلحات موضوعية: FOS: Computer and information sciences, Computer Science - Computation and Language, Computation and Language (cs.CL)

الوصف: Argumentative structure prediction aims to establish links between textual units and label the relationship between them, forming a structured representation for a given input text. The former task, linking, has been identified by earlier works as particularly challenging, as it requires finding the most appropriate structure out of a very large search space of possible link combinations. In this paper, we improve a state-of-the-art linking model by using multi-task and multi-corpora training strategies. Our auxiliary tasks help the model to learn the role of each sentence in the argumentative structure. Combining multi-corpora training with a selective sampling strategy increases the training data size while ensuring that the model still learns the desired target distribution well. Experiments on essays written by English-as-a-foreign-language learners show that both strategies significantly improve the model's performance; for instance, we observe a 15.8% increase in the F1-macro for individual link predictions.
9 pages (excluding citations and appendix), 10 figures, 3 tables, the paper has been accepted (peer-reviewed) for publication at the 8th Workshop on Argument Mining (co-located with EMNLP 2021)

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c0f685a4bd73dcffa02ecb2e7ffeb8a6
http://arxiv.org/abs/2109.13067

المؤلفون: Mizuki Sango, Takenobu Tokunaga, Hitoshi Nishikawa

المصدر: Journal of Natural Language Processing. 26:483-508

مصطلحات موضوعية: Domain adaptation, Exophora, Structure analysis, First person, Computer science, Linguistics, Predicate (grammar)

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::c5c6674812b6921748b4094c70916520
https://doi.org/10.5715/jnlp.26.483