We developed an application which allows learners to construct qualitative representations of dynamic systems to aid them in learning subject content knowledge and system thinking skills simultaneously. Within this application, we implemented a lightweight support function which automatically generates help from a norm-representation to aid learners as they construct these qualitative representations. This support can be expected to improve learning. Using this function it is not necessary to define in advance possible errors that learners may make and the subsequent feedback. Also, no data from (previous) learners is required. Such a lightweight support function is ideal for situations where lessons are designed for a wide variety of topics for small groups of learners. Here, we report on the use and impact of this support function in two lessons: Star Formation and Neolithic Age. A total of 63 ninth-grade learners from secondary school participated. The study used a pretest/intervention/post-test design with two conditions (no support vs. support) for both lessons. Learners with access to the support create better representations, learn more subject content knowledge, and improve their system thinking skills. Learners use the support throughout the lessons, more often than they would use support from the teacher. We also found no evidence for misuse, i.e., 'gaming the system', of the support function.
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What makes an educational game good? This paper describes three research directions that could provide insight in the underlying principles of effective educational games. These aspects are 1) The importance of distinguishing between types of to-be-learned knowledge, 2) the need to understand the relationship between game mechanics and learning goals, and 3) using research on intelligent tutoring systems to create more personalized learning experiences. Central in these directions is the concept of cognition and how it impacts the educational effectiveness of an educational game. This paper will give a short introduction on cognition and discuss why the research directions require further research.
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Robot tutors provide new opportunities for education. However, they also introduce moral challenges. This study reports a systematic literature re-view (N = 256) aimed at identifying the moral considerations related to ro-bots in education. While our findings suggest that robot tutors hold great potential for improving education, there are multiple values of both (special needs) children and teachers that are impacted (positively and negatively) by its introduction. Positive values related to robot tutors are: psychological welfare and happiness, efficiency, freedom from bias and usability. However, there are also concerns that robot tutors may negatively impact these same values. Other concerns relate to the values of friendship and attachment, human contact, deception and trust, privacy, security, safety and accountability. All these values relate to children and teachers. The moral values of other stakeholder groups, such as parents, are overlooked in the existing literature. The results suggest that, while there is a potential for ap-plying robot tutors in a morally justified way, there are imported stake-holder groups that need to be consulted to also take their moral values into consideration by implementing tutor robots in an educational setting. (from Narcis.nl)
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