In mathematics, sciences and economics, understanding and working with graphs are important skills. However, developing these skills has been shown to be a challenge in secondary and higher education as it involves high order thinking processes such as analysis, reflection and creativity. In this study, we present Interactive Virtual Math, a tool that supports the learning of a specific kind of graphs: dynamic graphs which represent the relation between at least two quantities that covary. The tool supports learners in visualizing abstract relations through enabling them to draw, move and modify graphs, and by combining graphs with other representations, especially interactive animations and textual explanations. This paper reports a design experiment about students’ learning graphs with this tool. Results show that students with difficulty in generating acceptable graphs improve their ability while working with the tool.
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In response to globalisation and internationalisation of both higher education and the job market, The Hague University of Applied Sciences (THUAS) has seen a considerable increase in English-medium courses, i.e. non-language subjects taught through English. Internationally, the rise of English-medium instruction (EMI) has led to research on, and discussion about the possible side-effects of a change in instructional language. More specifically, whether using a foreign language as the medium of instruction has a negative impact on teaching and learning. This paper reports the findings of a pilot research project into the implications of English-medium instruction (EMI) as perceived by students and teachers of the bachelor program Commercial Economics at the Faculty of Business, Finance and Administration at THUAS. Research methods used to collect data include face-to-face interviews with both students and lecturers involved in EMI subject courses, a student questionnaire, and lesson observations. Despite regular exposure to English and an adequate self-perceived English proficiency, results show that a considerable number of students, as well as teaching staff are experiencing difficulties with English-medium instruction and that for many EMI is not as efficient in transferring academic content as instruction in the mother tongue.
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The security of online assessments is a major concern due to widespread cheating. One common form of cheating is impersonation, where students invite unauthorized persons to take assessments on their behalf. Several techniques exist to handle impersonation. Some researchers recommend use of integrity policy, but communicating the policy effectively to the students is a challenge. Others propose authentication methods like, password and fingerprint; they offer initial authentication but are vulnerable thereafter. Face recognition offers post-login authentication but necessitates additional hardware. Keystroke Dynamics (KD) has been used to provide post-login authentication without any additional hardware, but its use is limited to subjective assessment. In this work, we address impersonation in assessments with Multiple Choice Questions (MCQ). Our approach combines two key strategies: reinforcement of integrity policy for prevention, and keystroke-based random authentication for detection of impersonation. To the best of our knowledge, it is the first attempt to use keystroke dynamics for post-login authentication in the context of MCQ. We improve an online quiz tool for the data collection suited to our needs and use feature engineering to address the challenge of high-dimensional keystroke datasets. Using machine learning classifiers, we identify the best-performing model for authenticating the students. The results indicate that the highest accuracy (83%) is achieved by the Isolation Forest classifier. Furthermore, to validate the results, the approach is applied to Carnegie Mellon University (CMU) benchmark dataset, thereby achieving an improved accuracy of 94%. Though we also used mouse dynamics for authentication, but its subpar performance leads us to not consider it for our approach.
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