With the emergence of MOOCs, there is a growing interest in prediction research. Most existing predictive models do not consider the context for which they are intended, thus resulting in limited impact. Learning design (LD) can provide a contextual understanding for the design of predictive models in collaboration with the instructors, maximizing their potential for supporting learning. This paper presents the findings of a mixed-methods research that explored the potentials emerging from aligning LD and LA during the design of a predictive analytics solution and from involving the instructors in the design process. The context was a past MOOC, where the learner data and the instructors were accessible for posterior analysis and additional data collection. Through a close collaboration with the instructors, the details of the prediction task were identified, including the learning activity to focus on, the target variable to predict, and the practical constraints to consider. Later, two predictive models were built for the prediction task identified: LD-specific model, in which the features were based on the LD and pedagogical intentions, and a generic model, which was based on cumulative features, not informed by the LD. Although the LD-specific predictive model did not outperform the generic one, some features derived from the LD and pedagogical intentions were predictive. The quantity and the power of such features were associated with the degree to which the students acted as guided by the LD and pedagogical intentions. The leading instructor's opinion about the importance of the learning activities in the LD was compared with the results of the feature importance analysis. This comparison helped identify the parts of the LD that need improvement. That is, the results of the LA informed back the LD, where the instructor was a mediator. The implications for improving the LD are discussed.

Despite the success of MOOCs to promote open leaning, they are usually criticized for their high drop-out rates and behaviorist pedagogical approach. Some active learning strategies, such as collaboration and gamification, have shown their potential to overcome some of these problems at low scale. However, the design and implementation of such strategies in MOOCs is still a challenge, which is being studied by several researchers, who tend to focus specially on the enactment of MOOCs. Therefore, there is a need for research studies exploring the design processes of MOOCs including active strategies. In this paper, we describe a co-redesign process in which an economic translation course conceived as a MOOC but finally implemented in Moodle for blended learning, was redesigned to include collaboration and gamification to implement it in Canvas Network (a MOOC platform). During the redesign process we found severe difficulties related to the scale, which were mainly caused by the initial implementation in a typical LMS.

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RESUMENEn el presente artículo se analiza el uso de los dispositivos y aplicaciones móviles por parte de los estudiantes de Grado en Traducción e Interpretación de las universidades españolas durante su proceso formativo a partir de los datos obtenidos en una encuesta. La muestra se compone de un total de 280 estudiantes de diferentes cursos de grado de 13 universidades. ABSTRACTThis paper presents the results of a survey that describes the use of mobile devices and apps by Translation and Interpreting students in Spain during their learning process. The sample consists of a total of 280 undergraduate students from 13 different Spanish universities.

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