Kaikki aineistot
Lisää
The intake of computer science faculty has rapidly increased with simultaneous reductions to course personnel. Presently, the economy is recovering slightly, and students are entering the working life already during their studies. These reasons have fortified demands for flexibility to keep the target graduation time the same as before, even shorten it. Required flexibility is created by increasing distance learning and MOOCs, which challenges students’ self-regulation skills. Teaching methods and systems need to evolve to support students’ progress. At the curriculum design level, such learning analytics tools have already been taken into use. This position paper outlines a next-generation, course-scope analytics tool that utilises data from both the learning management system and Gitlab, which works here as a channel of student submissions. Gitlab provides GitOps, and GitOps will be enhanced with machine learning, thereby transforming as MLOps. MLOps that performs learning analytics, is called here LAOps. For analysis, data is copied to the cloud, and for that, it must be properly protected, after which models are trained and analyses performed. The results are provided to both teachers and students and utilised for personalisation and differentiation of exercises based on students’ skill level.
Interest in and demand for micro-credentials in higher education institutions is on the rise. Although the concept of micro-credentials is still evolving, they can be seen as short learning opportunities that are accompanied by digital credentials that capture the proofs of the learning. These digital proofs of learning range from skills and competences acquired to information whether such skills were acquired via formal or non-formal learning activities. Micro-credential platforms are used for multiple purposes including issuing, viewing, and storing the digital credentials. Despite the growth in the number of micro-credential platforms in the recent years, literature is limited on the features offered by the platforms and how they are helpful for higher education institutions and learners. To address this gap in research, we employed a qualitative approach by semi-structured interviews and group discussions with platform providers and education experts. Our findings resulted in 38 features that can help higher education institutions, learners, and providers understand what kind of features are emphasized in micro-credential platforms and how they can be helpful for different use purposes. As practical implications, the findings of this study can help higher education institutions in considering adoption and usage of micro-credential platform.
Although logic is considered central to mathematics and computer science, there is evidence that teaching logic has not been a great success. We identify three issues where what is typically taught conflicts with what is needed by those who are supposed to apply logic. First, what is taught about the notion of implication often disagrees with human intuition. We argue that in some cases human intuition is wrong, and in some others teaching is to blame. Second, the formal concepts of logical consequence, logical equivalence and tautology are not the similar concepts that everyday mathematicians and computer scientists need. The difference is small enough to go unnoticed but big enough to cause confusion. Third, how to deal with undefined operations such as division by zero is left informal and perhaps fuzzy. These problems also harm development of computer tools for education. We present suggestions about how to address them in teaching.