The WiSo Faculty develops innovative ideas and teaching concepts that break new ground and improve the quality of teaching. There are deliberately no limits on the range of possible ideas - except that they must be related to teaching. A selection of current projects is described below.
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Further teaching innovations at the WiSo Faculty
E-PLUS: Crowdsourcing-based, individual learning
The project was initiated by Prof. Dr. Detlef Schoder (Department of Information Systems and Information Management and Academic Programme Director for Information Systems). It will be applied for the first time in the 2017/18 winter term as part of the “Core Module Information Systems” course (for students of Business Administration). Based on the concept of crowdsourcing, students design tasks and solutions relating to the content of the lectures they are taking in the current term, and then evaluate and correct them in a peer review process. The students are thus actively involved in the course and improve their learning success by regularly working on the learning content in this form. The activities are organised via the ILIAS e-learning platform, which is used to present the tasks, facilitate mutual evaluation and help students research questions in a wiki set up especially for this purpose.
This innovative project focuses on achieving an individualised, active learning process. By contributing their own – individual – tasks, the students create a broadly diversified pool of tasks, which results in a large number of different mock e-exams for extensive practice. The content can thus be internalised even more as the students receive direct feedback on each exercise and can thus reflect on and adapt their level of learning. In addition, by evaluating the tasks submitted and the answers given in the mock exams, lecturers can identify any weaknesses and then address them and provide further explanations in class.
The exams take the form of individualised e-exams, which, theoretically, can be taken by the students at any time. This evens out the exam schedule and eases the workload both in terms of the conducting and the administration of the examinations.
Individual e-homework assignments with immediate feedback
This interdisciplinary project aims to develop a new e-learning tool for regular, voluntary homework (e-homework assignments). The project manager is Prof. Dr. Jörg Breitung (Institute of Econometrics and Statistics), supported by project coordinator Dr. Christoph Scheicher (Institute of Econometrics and Statistics). With this tool, the students receive completely individually composed exercises with different numbers and functions, which they have to solve. The tool ensures that the assignments do not overlap and students cannot copy others’ answers. This approach requires the students to actively engage with the content of the course, thus contributing to better understanding and a continuous process of preparation for the exams.
After submitting their e-homework assignments, the students receive direct and individual feedback on their current level of learning, which promotes self-assessment of their previous ability and, if necessary, indicates what further action is necessary.
The e-homework assignment tool also uses, if available, a bonus point system, which could have a positive effect on the mark for the final examination if the assignments are completed successfully. This increases student motivation and leads to lower fail and drop-out rates.
The e-homework assignment tool will be used by and by from winter semester 2017/18 on the following bachelor courses: "Basic Module Mathematics", "Basic Module Microeconomics", "Basic Module Statistics","Advanced Module Statistics" and "Basic Module Fundamentals of Economics". In the long term, the plan is to expand the project both within the Faculty and University-wide to take in other courses in which quantitative mathematical or statistical methods are applied.
AufbaU: Tasks in Business Administration classes
The aim of the project - led by Prof. Dr. Matthias Pilz, holder of the Chair for Business and Economic Education and Training - is to optimise application-oriented learning tasks on the mass bachelor degree programme in Business Administration and to expand lecturers’ task-construction skills.
In contrast to pure exercises, these learning tasks not only allow students to revise and practise what they have learned in the lectures, but also to develop new competencies, based on the application of the acquired knowledge to solve real problems.
As part of this project, the first step in the 2017 summer term was to analyse the existing learning tasks in selected courses of the bachelor degree in Business Administration. Based on this, the students and teachers involved in these courses were asked about their experiences and thoughts with regard to the learning tasks used and the teaching of the content, the aim being to then evolve and optimise these aspects. Finally, a manual was written which can be used by lecturers to develop their own learning tasks and support them in their implementation of teaching and methodological approaches. The manual is to be continuously developed and optimised by means of recurring surveys and analyses.
From "Statistics A for Social Scientists" to Data Science
Prof. Dr. Merlin Schaeffer from the Institute for Sociology and Social Psychology (ISS) uses empirical, raw data in his lectures, enabling students to learn to apply the theoretical statistical knowledge acquired in the lectures by processing real empirical data in accompanying online exercises. The students are confronted with the challenge of processing, evaluating and drawing conclusions from the almost always incomplete, faulty and poorly coded data.
Since the 2016/17 winter term, the data has been processed as part of online exercises via the ILIAS e-learning platform. Students can thus solve tasks on a weekly basis, in parallel with the lectures, and receive automated but individual feedback. In addition, tutorials are offered, in which the online tasks are discussed in detail and questions can be asked.
The students work with real data from the European Social Survey (ESS) and quantified party programmes from the Manifesto project - two of the most important and most frequently used data sets in the social sciences.