{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T06:57:44Z","timestamp":1760597864661,"version":"build-2065373602"},"reference-count":17,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2018,12,19]],"date-time":"2018-12-19T00:00:00Z","timestamp":1545177600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>The Medi-test system we developed was motivated by the large number of resources available for the medical domain, as well as the number of tests needed in this field (during and after the medical school) for evaluation, promotion, certification, etc. Generating questions to support learning and user interactivity has been an interesting and dynamic topic in NLP since the availability of e-book curricula and e-learning platforms. Current e-learning platforms offer increased support for student evaluation, with an emphasis in exploiting automation in both test generation and evaluation. In this context, our system is able to evaluate a student\u2019s academic performance for the medical domain. Using medical reference texts as input and supported by a specially designed medical ontology, Medi-test generates different types of questionnaires for Romanian language. The evaluation includes 4 types of questions (multiple-choice, fill in the blanks, true\/false, and match), can have customizable length and difficulty, and can be automatically graded. A recent extension of our system also allows for the generation of tests which include images. We evaluated our system with a local testing team, but also with a set of medicine students, and user satisfaction questionnaires showed that the system can be used to enhance learning.<\/jats:p>","DOI":"10.3390\/data3040070","type":"journal-article","created":{"date-parts":[[2018,12,19]],"date-time":"2018-12-19T12:12:44Z","timestamp":1545221564000},"page":"70","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Medi-Test: Generating Tests from Medical Reference Texts"],"prefix":"10.3390","volume":"3","author":[{"given":"Ionu\u021b","family":"Pistol","sequence":"first","affiliation":[{"name":"Faculty of Computer Science, \u201cAlexandru Ioan Cuza\u201d University of Ia\u015fi, Ia\u0219i 700483, Romania"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9874-0642","authenticated-orcid":false,"given":"Diana","family":"Trandab\u0103\u021b","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, \u201cAlexandru Ioan Cuza\u201d University of Ia\u015fi, Ia\u0219i 700483, Romania"}]},{"given":"M\u0103d\u0103lina","family":"R\u0103schip","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, \u201cAlexandru Ioan Cuza\u201d University of Ia\u015fi, Ia\u0219i 700483, Romania"}]}],"member":"1968","published-online":{"date-parts":[[2018,12,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1017\/S1351324906004177","article-title":"A computer-aided environment for generating multiple-choice test items","volume":"12","author":"Mitkov","year":"2006","journal-title":"Nat. Lang. Eng."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Sumita, E., Sugaya, F., and Yamamoto, S. (2005, January 29). Measuring non-native speakers\u2019 proficiency of English by using a test with automatically-generated fill-in-the-blank questions. Proceedings of the Second Workshop on Building Educational Applications Using NLP, Ann Arbor, Michigan.","DOI":"10.3115\/1609829.1609839"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1162\/COLI_a_00206","article-title":"Towards topic-to-question generation","volume":"41","author":"Chali","year":"2015","journal-title":"Comput. Linguist."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Labutov, I., Basu, S., and Vanderwende, L. (2015, January 26\u201331). Deep questions without deep understanding. 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