There are two different ways to improve teaching and learning at university. The traditional way is teaching orientated: This way involves optimizing university seminars by improving the teachers' instruction. A second, complimentary way is to encourage students to use learning strategies, which help them to learn more from the teachers' instruction. For the latter purpose, we have developed a computer-based, adaptive learning environment for freshmen students to train their learning strategies. Our online learning-strategy training aims to: 1) teach declarative knowledge about learning strategies; 2) consolidate this knowledge; 3) support students to apply these learning strategies when working on the university course. We conducted several experimental studies to optimize this learning environment with respect to how motivating it is, how the declarative knowledge about learning strategies can be effectively consolidated, and how the formation of effective intentions for applying the learning strategies (Implementation Intentions) can best be prompted. We found that motivation while working with the learning environment can be fostered by using sketched explanation videos (i.e. video containing sketched symbols and human hands e.g. simpleshow). For consolidating students' knowledge about learning strategies, a retrieval practice-based arrangement that uses different types of test questions for learners with different prior knowledge levels is best. This prior knowledge is assessed in the learning environment. The learning environment automatically adapts the type of questions so that they are most beneficial for the individual learner. Finally, we found that it is important to guide the students to form very specific Implementation Intentions for applying learning strategies. A contrasting cases guidance was most efficient. We implement our strategy training presently in a freshman courses on a long-term basis.
Keywords: learning strategies, computer-based learning, retrieval practice, adaptivity, motivation;