5 research outputs found
Investigating the effects of gender and scaffolding in developing preschool children’s computational thinking during problem-solving with Bee-Bots
The research community has embraced computational thinking as an essential skill to develop in school and academic settings. Many researchers argue that computational thinking should be developed in the context of programming and robotic activities in all educational levels of education, starting from early childhood education. However, the factors related to developing computational thinking in preschool education are still under study. Furthermore, not too many empirical investigations provide evidence about the development of computational thinking in young children. The present study examined the effects of scaffolding and gender in developing young children’s sequencing and decomposition skills - two of the five skills that constitute computational thinking. The results indicated statistically significant effects about the type of scaffolding on children’s computational thinking in favor of the children assigned to the experimental groups. Lastly, boys outperformed girls on all occasions, indicating that gender effects exist. The authors conclude that researchers need to design teaching interventions in such a way so they have mathemagenic outcomes for all learners irrespective of gender. Finally, the authors conclude with implications and future research directions
On the Creation of Sustainable Design Patterns of ICT Integration in the Classroom
The paper focuses on the methodology of making observations that account for the actual use of ICT infrastructure and tools in the classroom. The observational study is part of a project that focuses on scenario feasibility as an enabler of ICT usage. In particular, the observations provide input on pattern mining with the aim to help teachers and other stakeholders in the decision-making process of selecting suitable ICT facilities
Educational robotics: platforms, competitions and expected learning outcomes
Summarization: Motivated by the recent explosion of interest around Educational Robotics (ER), this paper attempts to re-approach this area by suggesting new ways of thinking and exploring the related concepts. The contribution of the paper is fourfold. First, future readers can use this paper as a reference point for exploring the expected learning outcomes of educational robotics. From an exhaustive list of potential learning gains, we propose a set of six learning outcomes that can offer a starting point for a viable model for the design of robotic activities. Second, the paper aims to serve as a survey for the most recent ER platforms. Driven by the growing number of available robotics platforms, we have gathered the most recent ER kits. We also propose a new way to categorize the platforms, free from their manufacturers' vague age boundaries. The proposed categories, including No Code, Basic Code, and Advanced Code, are derived from the prior knowledge and the programming skills that a student needs to use them efficiently. Third, as the number of ER competitions, and tournaments increases in parallel with ER platforms' increase, the paper presents and analyses the most popular robotic events. Robotics competitions encourage participants to develop and showcase their skills while promoting specific learning outcomes. The paper aims to provide an overview of those structures and discuss their efficacy. Finally, the paper explores the educational aspects of the presented ER competitions and their correlation with the six proposed learning outcomes. This raises the question of which primary features compose a competition and achieve its' pedagogical goals. This paper is the first study that correlates potential learning gains with ER competitions to the best of our knowledge.Presented on: IEEE Acces
Assessing Lidar Ratio Impact on CALIPSO Retrievals Utilized for the Estimation of Aerosol SW Radiative Effects across North Africa, the Middle East, and Europe
North Africa, the Middle East, and Europe (NAMEE domain) host a variety of suspended particles characterized by different optical and microphysical properties. In the current study, we investigate the importance of the lidar ratio (LR) on Cloud-Aerosol Lidar with Orthogonal Polarization–Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIOP-CALIPSO) aerosol retrievals towards assessing aerosols’ impact on the Earth-atmosphere radiation budget. A holistic approach has been adopted involving collocated Aerosol Robotic Network (AERONET) observations, Radiative Transfer Model (RTM) simulations, as well as reference radiation measurements acquired using spaceborne (Clouds and the Earth’s Radiant Energy System-CERES) and ground-based (Baseline Surface Radiation Network-BSRN) instruments. We are assessing the clear-sky shortwave (SW) direct radiative effects (DREs) on 550 atmospheric scenes, identified within the 2007–2020 period, in which the primary tropospheric aerosol species (dust, marine, polluted continental/smoke, elevated smoke, and clean continental) are probed using CALIPSO. RTM runs have been performed relying on CALIOP retrievals in which the default and the DeLiAn (Depolarization ratio, Lidar ratio, and Ångström exponent)-based aerosol-speciated LRs are considered. The simulated fields from both configurations are compared against those produced when AERONET AODs are applied. Overall, the DeLiAn LRs leads to better results mainly when mineral particles are either solely recorded or coexist with other aerosol species (e.g., sea-salt). In quantitative terms, the errors in DREs are reduced by ~26–27% at the surface (from 5.3 to 3.9 W/m2) and within the atmosphere (from −3.3 to −2.4 W/m2). The improvements become more significant (reaching up to ~35%) for moderate-to-high aerosol loads (AOD ≥ 0.2)