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.
Communication between healthcare professionals and deaf patients has been particularly challenging during the COVID-19 pandemic. We have explored the possibility to automatically translate phrases that are frequently used in the diagnosis and treatment of hospital patients, in particular phrases related to COVID-19, from Dutch or English to Dutch Sign Language (NGT). The prototype system we developed displays translations either by means of pre-recorded videos featuring a deaf human signer (for a limited number of sentences) or by means of animations featuring a computer-generated signing avatar (for a larger, though still restricted number of sentences). We evaluated the comprehensibility of the signing avatar, as compared to the human signer. We found that, while individual signs are recognized correctly when signed by the avatar almost as frequently as when signed by a human, sentence comprehension rates and clarity scores for the avatar are substantially lower than for the human signer. We identify a number of concrete limitations of the JASigning avatar engine that underlies our system. Namely, the engine currently does not offer sufficient control over mouth shapes, the relative speed and intensity of signs in a sentence (prosody), and transitions between signs. These limitations need to be overcome in future work for the engine to become usable in practice.
The current study investigates the effects of the school lockdowns during school years 2019–2020 and 2020–2021 on the achievement scores of primary school students during the COVID-19 pandemic. We analyzed scores for spelling, reading fluency (i.e., decoding speed), reading comprehension, and mathematics from standardized student tracking systems for 5125 students from 26 primary schools in the urban region of The Hague, the Netherlands. Results showed that students in grades 1 through 3 had significant learning delays after the first lockdown. However, results after the second lockdown showed that most students were able to catch up, compared to students from corresponding grades of cohorts before COVID-19. The magnitude of these positive effects was mostly close to the negative effect of the first lockdown. Apparently, during the second lockdown, schools seemed better prepared and able to deliver more effective home schooling and online instruction. The hypothesis that students’ learning from a low SES home environment will suffer most from the school lockdowns could only partly be confirmed. SES effects at the individual level tended to be mitigated by negative effects of SES at the school level, making SES-related differences between schools less profound. The findings of this study offer a broader perspective to evaluate the effects of long-term school closures. Implications for educational practice and issues of inequality between students are discussed.
