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The growing interest in applying gamified designs in higher education is challenged by mixed results in terms of student acceptance. Different players are attracted to games for different reasons and game design elements, and a better understanding of how each learner will connect to different game mechanics provides valuable input for game design and evaluation. In this paper, we present and validate a scale to measure the affinity of each player with different game elements. First, a theoretical review was carried out on three profile classifications and six motivational theoretical models, proposing a taxonomy for twelve player profiles based on three axes: relational, competence and motivational. Then, a pilot test was carried out with 54 subjects, analysing content and comprehension validity through the judgment of six experts and construct validity through an exploratory factorial analysis. Subsequently, with a sample of 1010 subjects, a confirmatory factor analysis was performed. The scale was made up of 30 items, with a Cronbach's alpha of 0.822; three main components were obtained: dominators, interactors and trackers. The results show the validity of the scale, with high levels of confidence. It provides an understanding of the player's profile in a playful context, their motivational orientation and their affinity with the specific game design. This can be used to improve the design of gamified experiences in higher education. [ABSTRACT FROM AUTHOR]

This paper explores the possibilities offered by new Artificial Intelligence tools when applied with Error Analysis to English as a Foreign Language (EFL) teachers to design assessments that improve their students’ written proficiency in the context of a university course at the B2 level of the Common European Framework of Reference (CEFR). A comparative corpus study was designed to evaluate the impact of integrating both disciplines, in which half of the productions were evaluated with artificial intelligence tools. Relevant conclusions were obtained, as new intelligent technologies bring new perspectives that effectively help EFL learners produce more appropriate written texts. Among other findings, error elimination was observed in more than 70% of the cases and a better application of grammatical rules in more than 75%. [ABSTRACT FROM AUTHOR]