Intervention studies typically target a focused aspect of language learning that is studied over a relatively short time frame for a relatively small number of participants in a controlled setting. While for many research questions, this is effective, it can also limit the ecological validity and relevance of the results for real-life language learning. In educational science, large-scale randomized controlled field trials (RCTs) are seen as the gold standard method for addressing this challenge—yet they require intervention to scale to hundreds of learners in their varied, authentic contexts.We discuss the use of technology in support of large-scale interventions that are fully integrated in regular classes in secondary school. As an experimentation platform, we developed a web-based workbook to replace a printed workbook widely used in German schools. The web-based FeedBook provides immediate scaffolded feedback to students on form and meaning for various exercise types, covering the full range of constructions in the seventh-grade English curriculum.Following the conceptual discussion, we report on the first results of an ongoing, yearlong RCT. The results confirm the effectiveness of the scaffolded feedback, and the approach makes students and learning process variables accessible for the analysis of learning in a real-world context.

While immediate feedback on learner language is often discussed in the Second Language Acquisition literature (e.g., Mackey 2006), few systems used in real-life educational settings provide helpful, metalinguistic feedback to learners.In this paper, we present a novel approach leveraging task information to generate the expected range of well-formed and ill-formed variability in learner answers along with the required diagnosis and feedback. We combine this offline generation approach with an online component that matches the actual student answers against the pre-computed hypotheses.The results obtained for a set of 33 thousand answers of 7th grade German high school students learning English show that the approach successfully covers frequent answer patterns. At the same time, paraphrases and meaning errors require a more flexible alignment approach, for which we are planning to complement the method with the CoMiC approach successfully used for the analysis of reading comprehension answers .

Foreign language teaching achieves best learning outcomes when individual differences of learners are taken into account. While it is difficult for teachers to support internal differentiation in the classroom, digital tools can adaptively propose individual learning paths through activities so that students can practice with appropriately challenging exercises. But how can sufficiently varied, systematically parametrized exercises be provided to enable a system to match them to individual learner needs? We present an approach for high-variability exercise generation that transforms a single specification into a multitude of exercises varying in complexity. The approach is currently being evaluated in a randomized controlled study in regular German seventh grade English classes, facilitating a systematic empirical exploration of adaptive exercise complexity in relation to learning outcomes.