Pedagogical methods in web-based language teaching-mapping

The purpose of this presentation is to introduce the research project progress in “the mapping of pedagogical methods in web-based language teaching" by Högskolan Dalarna (Dalarna University). This project will identify the differences in pedagogical methods that are used for online language classes. The pedagogical method defined in this project is what the teachers do to ensure students attain the learning outcomes, for example, planning, designing courses, leading students, knowing students' abilities, implementing activities, etc. So far the members of this project have analyzed the course plans (in the language department at Dalarna University) and categorized the learning outcomes. A questionnaire was constructed based on the learning outcomes and then either sent out remotely to teachers or completed face to face through interviews. The answers provided to the questionnaires enabled the project to identify many differences in how language teachers interact with their students but also, the way of giving feedback, motivating and helping students, types of class activities and materials used. This presentation introduces the progress of the project and identifies the challenges at the language department at Dalarna University. Finally, the advantages and problems of online language proficiency courses will be discussed and suggestions made for future improvement.

The Power of the Synthetic Control Method

The synthetic control method (SCM) is a new, popular method developed for the purpose of estimating the effect of an intervention when only one single unit has been exposed. Other similar, unexposed units are combined into a synthetic control unit intended to mimic the evolution in the exposed unit, had it not been subject to exposure. As the inference relies on only a single observational unit, the statistical inferential issue is a challenge. In this paper, we examine the statistical properties of the estimator, study a number of features potentially yielding uncertainty in the estimator, discuss the rationale for statistical inference in relation to SCM, and provide a Web-app for researchers to aid in their decision of whether SCM is powerful for a specific case study. We conclude that SCM is powerful with a limited number of controls in the donor pool and a fairly short pre-intervention time period. This holds as long as the parameter of interest is a parametric specification of the intervention effect, and the duration of post-intervention period is reasonably long, and the fit of the synthetic control unit to the exposed unit in the pre-intervention period is good.