A Theoretical Analysis of How Segmentation of Dynamic Visualizations Optimizes Students' Learning

This article reviews studies investigating segmentation of dynamic visualizations (i.e., showing dynamic visualizations in pieces with pauses in between) and discusses two not mutually exclusive processes that might underlie the effectiveness of segmentation. First, cognitive activities needed for dealing with the transience of dynamic visualizations impose extraneous cognitive load, which may hinder learning. Segmentation may reduce the negative effect of this load by dividing animations into smaller units of information and providing pauses between segments that give students time for the necessary cognitive activities after each of those units of information. Second, event segmentation theory states that people mentally segment dynamic visualizations during perception (i.e., divide the information shown in pieces). Segmentation of dynamic visualisation could cue relevant segments to students, which may aid them in perceiving the structure underlying the process or procedure shown

An integrated cell atlas of the lung in health and disease

Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP1 + profibrotic monocyte-derived macrophages in COVID-19, pulmonary fibrosis and lung carcinoma. Overall, the HLCA serves as an example for the development and use of large-scale, cross-dataset organ atlases within the Human Cell Atlas. </p

An integrated cell atlas of the lung in health and disease

Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP

An integrated cell atlas of the lung in health and disease

Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP1+ profibrotic monocyte-derived macrophages in COVID-19, pulmonary fibrosis and lung carcinoma. Overall, the HLCA serves as an example for the development and use of large-scale, cross-dataset organ atlases within the Human Cell Atlas

Investigating the use of sensor-based IoET to facilitate learning for children in rural Thailand

A novel sensor-based Internet of Educational Things (IoET) platform named OBSY was iteratively designed, developed and evaluated to support education in rural regions in Thailand. To assess the effectiveness of this platform, a study was carried out at four primary schools located near the Thai northern border with 244 students and 8 teachers. Participants were asked to carry out three science-based learning activities and were measured for improvements in learning outcome and learning engagement. Overall, the results showed that students in the IoET group who had used OBSY to learn showed significantly higher learning outcome and had better learning engagement than those in the control condition. In addition, for those in the IoET group, there was no significant effect regarding gender, home location (Urban or Rural), age, prior experience with technology and ethnicity on learning outcome. For learning engagement, only age was found to influence interest/enjoyment. The study demonstrated the potential of IoET technologies in underprivileged area, through a co-design approach with teachers and students, taking into account the local contexts

Confidence drives exploration strategies in interactive simulations

Maximising the benefits of digital learning environments requires understanding how students process what they are exposed to in these environments. Besides approaches based on examining information processing within the cognitive domain, the importance of including emotions has been recently addressed. This study aimed to explore emotional dynamics during discovery learning in an interactive simulation, with continuous measures of self-reported confidence and challenge. Interactions from participants were recorded and two groups were created according to the exploration strategy used: systematic or non-systematic. Visual exploration was also measured by eye tracking as well as knowledge at pre- and post-test. Results suggest that learners using a systematic exploration strategy ran significantly more simulation cycles than non-systematic learners. Moreover, the latter group reported to be significantly less challenged and more confident about understanding the material. These results emphasise the importance of student perceptions of their capabilities when learning in flexible, less structured digital environments

New optical technology for cold atom experiments

International audienceIn this proceeding we present a set of studies which are in progress in different labs and industrials. The aim of this project is to study the possibilities to design a very compact and reliable laser cooling bench for space and inboard applications

Iodine based reference laser for ground tests of LISA payload

International audienceWe report on the development of a transportable iodine frequency stabilized laser setup, based on compact-fibered frequency tripled Telecom laser, locked to the a10 hyperfine component of the 127I 2 line at 532.245 nm. Therefore, a tandem of Nd: YAG lasers are phase-locked to this reference laser and used for precise interferometry measurements as part of the French activities in the frame of LISA-France consortium, led by the French space agency (CNES). The frequency stability transfer from 1596 nm to the LISA nominal wavelength at 1064.49 nm is fulfilled in a simple manner [1], using the usual phase locking loop technique associated to a second harmonic generation process. The compact design of the whole setup will make it easily transportable and can be readily used on different sites