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Dissertation:conception_and_evaluation_of_e-learning_units_regarding_motivation_and_acquired_competencies_for_theoretical_computer_science_at_university_level

Conception and Evaluation of E-Learning Units Regarding Motivation and Acquired Competencies for Theoretical Computer Science at University Level (Dissertation)

Referenz

Wilhelm-Weidner, Arno: Conception and Evaluation of E-Learning Units Regarding Motivation and Acquired Competencies for Theoretical Computer Science at University Level. Dissertation, Technische Universität Berlin, 2020

Publikation

Zusammenfassung

Theoretical computer science is an essential part of computer science study programmes. Many articles from different countries can be found, which are concerned with the high levels of frustration amongst students, motivational problems, and high failure rates in courses on theoretical computer science. There are even indications that theoretical computer science is one of the reasons for the high dropout rates of computer science study programmes.

This dissertation presents a design-based research approach, aiming to improve the learning in university courses on theoretical computer science. For this approach, the author created interactive Learning Units in the learning management system Moodle. As theoretical basis, the cognitive load theory, the cognitive theory of multimedia learning and the cognitive-affective theory of learning with media as well as the Felder-Silverman model of learning styles were analyzed. All these theories were used to derive design recommendations for the Learning Units. Furthermore, existing approaches concerning e-learning in the area of theoretical computer science and meta-analyses on e-learning and blended learning in general were taken into account.

The created Learning Units use text and video as presentation forms and exercises on the content. Students can follow different learning paths on the content. On these paths, they can choose whether they want to be presented with simple examples introducing a new subject before its actual explanation. Another possible choice at several points is to follow a further extension on the content of the explanation if they are more deeply interested.

These Learning Units were intended for self-studying and self-testing using exercises. One pair of Learning Units were created for a course on formal languages and automata, typically attended at the beginning of the study programme, and another pair for a more advanced course on reactive systems. In both cases, the Learning Units were intended as a supplement to be used with otherwise unchanged university courses. Additionally, an evaluation instrument was created for these Learning Units, concentrating on student motivation and competencies. The Learning Units were evaluated in six studies at RWTH Aachen University, Technische Universität Berlin, Universität Duisburg-Essen, Universität Potsdam and Universität Salzburg. Even though participation levels were low in the studies, the Learning Units were seen as helpful by many participants, and the overall results on competencies indicate positive tendencies. Overall, the results on motivation were ambiguous, but suggest possibilities for further research.

After these studies were finished, the created Learning Units were opened for public use. Additionally, they were made available for students in two courses at Universität Duisburg-Essen and Technische Universität Berlin in the summer term 2019. These two approaches were taken to ensure the sustainability of this work. Additionally, the dissertation discusses the possibilities for reusability of the approach for further Learning Units, not only for theoretical computer science but for different areas as well.

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