GAMETRAPP project in progress: Designing a virtual escape room to enhance skills in research abstract post-editing (2025)

Abstract: The “App for post-editing neural machine translation using gamification” (GAMETRAPP) project (TED2021-129789B-I00), funded by the Spanish Ministry of Science and Innovation (2022–2025) and led by the University of Málaga, has been in progress for two and a half years. The project is developing a web application that incorporates a gamified environment, specifically a virtual escape room, to bring post-editing practice closer to scholars. This paper outlines the methodological process followed and provides a brief description of the virtual escape room.

## introduction the breakthrough of artificial intelligence (ai) has significantly impacted the development and advancement of language technologies, including neural machine translation (nmt). this advancement has also led to a greater reliance on post-editing (pe), which has garnered increasing attention from scholars. previous research has explored the implementation of pe, particularly in academic contexts, focusing on first language (l1) to second or foreign language (l2) translation @xcite . against the backdrop of scientific dissemination in english as l2, the gametrapp project (toledo-báez & noriega-santiáñez, 2024) is developing a web application that incorporates a gamified environment, specifically a virtual escape room, to enhance the pe of research abstracts translated from iberian spanish to american english (l1 to l2). while other applications, such as kaninjo @xcite , have been developed to train users in pe, gametrapp ## analyzing nmt and pe to design the gamified environment the methodological process of the gametrapp project was carried out in four phases, which are outlined as follows: 244 spanishlanguage abstracts were selected from spanish journals ranked in quartiles 1 and 2 (representing the top 50% of journals) in the scientific journal & country ranking 2022. of these, only 126 abstracts met the following three criteria: a) published in 2023; b) following the iamrac 1 structure; c) authored by scholars affiliated with spanish universities and/or research centers. google translate was selected as the nmt engine because, according to a previous questionnaire conducted to assess the spanish scholars' needs, it was the most widely used nmt engine. the 126 abstracts were, on the one hand, translated into english by a professional translator, and, on the other hand, machine-translated with google translate and then post-edited into english by a professional post-editor (both of whom had english as their l1). then, the translated and postedited abstracts were analyzed, identifying nmt and pe errors and kudos using two metrics. on the one hand, the multidimensional quality metrics was used to detect and classify nmt errors across the following categories: terminology, accuracy, terminology, accuracy, linguistic conventions, style, locale conventions, audience appropriateness, and design and markup. on the other hand, the post-edit me! metric @xcite was used to detect and classify edits into four categories: value adding/successful edits, unnecessary edits, incomplete edits, or unsuccessful/error introducing/missing edits. this dual analysis not only helped identify some of the most frequent nmt errors in machine-translated research abstracts but also revealed specific @xmath0. the analysis results provided the foundation for the design of the gamified exercises, as the linguistic material was adapted to create the activities. these activities were organised into three parts: part 1 focused on detecting nmt errors, part 2 centered on pe, and part 3 aimed at identifying successful and unsuccessful edits of pe. an example of each type of activity is provided below: part 1: identify the error in the following nmt output: -no hay datos recientes que recojan su adaptación durante la pandemia por la covid-19. -there is no recent data that reflect their adaptation during the covid-19 pandemic. part 2: correct the error in the nmt output: -la lucha contra la radicalización gana protagonismo.