Eighteen years after the introduction of the graphing calculator in national examinations in the Netherlands, much has been learned about the use of technology in education. One of the key lessons was that integrating ICT as a tool for learning math is a complex task, and this complexity is often underestimated. In this article we give a current view of the use of ICT in learner practice in the Netherlands and in particular in the discipline of mathematics. Some of the topics covered include the type of technologies and learning materials used and the curriculum guidelines for math and assessment. Reflecting on experiences and challenges of the last few years is given an idea of future priorities. Directions for improving the integration of technology in mathematics education include the need to understand their role in learning and developing students' mathematical knowledge and reasoning, an investment in teacher training, the quality of digital learning materials and in more forms evaluation
The potential of software tools to support learning mathematics is widely acknowledged, but their use can be hindered for many reasons. When teaching future mathematics teachers, we observed that these students were unmotivated to use such tools. This lack of motivation was caused by two concerns held by the students. Firstly, expected difficulty with the software interface (`handling equations with computer interfaces is cumbersome') and secondly, having to do time-consuming exercises on top of the regular pen-and-paper material. To circumvent these concerns, we developed and deployed a set of exercises, categorized in seven different types, that required little effort in terms of equation `writing' with the computer interface but still covered the core mathematical principles taught in the lessons. To allow for sufficient training opportunities, the software automatically created new randomized versions of the same question type. In this paper, we present an exploratory study that discusses the potential of this approach and provides insight on the effectiveness of question types used.
Over the past three years we have built a practice-oriented, bachelor level, educational programme for software engineers to specialize as AI engineers. The experience with this programme and the practical assignments our students execute in industry has given us valuable insights on the profession of AI engineer. In this paper we discuss our programme and the lessons learned for industry and research.
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