scholarly journals Am I getting through? Surveying students on what messages they recall from the first day of STEM classes

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Clara L. Meaders ◽  
Lillian G. Senn ◽  
Brian A. Couch ◽  
A. Kelly Lane ◽  
Marilyne Stains ◽  
...  
Keyword(s):  
Learning Environments ◽  
Classroom Environment ◽  
Student Motivation ◽  
Social Dynamics ◽  
Classroom Observation ◽  
Observation Data ◽  
Student Relationships ◽  
Course Structure ◽  
Course Retention

Abstract Background The first day of class helps students learn about what to expect from their instructors and courses. Messaging used by instructors, which varies in content and approach on the first day, shapes classroom social dynamics and can affect subsequent learning in a course. Prior work established the non-content Instructor Talk Framework to describe the language that instructors use to create learning environments, but little is known about the extent to which students detect those messages. In this study, we paired first day classroom observation data with results from student surveys to measure how readily students in introductory STEM courses detect non-content Instructor Talk. Results To learn more about the instructor and student first day experiences, we studied 11 introductory STEM courses at two different institutions. The classroom observation data were used to characterize course structure and use of non-content Instructor Talk. The data revealed that all instructors spent time discussing their instructional practices, building instructor/student relationships, and sharing strategies for success with their students. After class, we surveyed students about the messages their instructors shared during the first day of class and determined that the majority of students from within each course detected messaging that occurred at a higher frequency. For lower frequency messaging, we identified nuances in what students detected that may help instructors as they plan their first day of class. Conclusions For instructors who dedicate the first day of class to establishing positive learning environments, these findings provide support that students are detecting the messages. Additionally, this study highlights the importance of instructors prioritizing the messages they deem most important and giving them adequate attention to more effectively reach students. Setting a positive classroom environment on the first day may lead to long-term impacts on student motivation and course retention. These outcomes are relevant for all students, but in particular for students in introductory STEM courses which are often critical prerequisites for being in a major.

scholarly journals EFL Learners’ Affect, Engagement, Misbehaviours, and Achievement: A Classroom Observation Perspective

2021 ◽  
Vol 11 (4) ◽  
pp. 12
Author(s):  
Bo Yang ◽  
Christo Moskovsky
Keyword(s):  
Classroom Environment ◽  
Classroom Observation ◽  
Video Recording ◽  
Northwest China ◽  
Influential Factors ◽  
Reciprocal Relationship ◽  
Special Focus ◽  
Observation Data ◽  
College English ◽  
Efl Learners

Most previous research examining the correlation between affect and achievement of learners of English as a foreign language (EFL) has relied on questionnaire and/or interview data. The current study, conducted in a Chinese EFL context, chose to explore this relationship on the basis of quantitative and qualitative classroom observation data, with a special focus on learners’ classroom engagement and misbehaviours. The participant sample involved the EFL learners and teachers in six classes at a key and a non-key university in Northwest China. Data in relation to participants’ affect, engagement, and misbehaviours were collected via classroom observations, including some video-recording. The participating students’ College English Test-Band 4 (CET-4) scores were used as a measurement of EFL achievement. Participants’ affect, engagement, and achievement formed a reciprocal relationship; the latter was negatively connected with misbehavious. Rather than gender, type of school (key vs. non-key university) had significant effects on the variables being examined. Data revealed that teachers, peers, and classroom environment were also influential factors in explaining the differences in the relationship between the identified variables.

scholarly journals A global association between Covid-19 cases and airborne particulate matter at regional level

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Angelo Solimini ◽  
F. Filipponi ◽  
D. Alunni Fegatelli ◽  
B. Caputo ◽  
C. M. De Marco ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Negative Binomial ◽  
Numerical Models ◽  
Regional Level ◽  
Pollution Level ◽  
Observation Data ◽  
Cumulative Number ◽  
Mixed Effect

AbstractEvidences of an association between air pollution and Covid-19 infections are mixed and inconclusive. We conducted an ecological analysis at regional scale of long-term exposure to air-borne particle matter and spread of Covid-19 cases during the first wave of epidemics. Global air pollution and climate data were calculated from satellite earth observation data assimilated into numerical models at 10 km resolution. Main outcome was defined as the cumulative number of cases of Covid-19 in the 14 days following the date when > 10 cumulative cases were reported. Negative binomial mixed effect models were applied to estimate the associations between the outcome and long-term exposure to air pollution at the regional level (PM10, PM2.5), after adjusting for relevant regional and country level covariates and spatial correlation. In total we collected 237,749 Covid-19 cases from 730 regions, 63 countries and 5 continents at May 30, 2020. A 10 μg/m3 increase of pollution level was associated with 8.1% (95% CI 5.4%, 10.5%) and 11.5% (95% CI 7.8%, 14.9%) increases in the number of cases in a 14 days window, for PM2.5 and PM10 respectively. We found an association between Covid-19 cases and air pollution suggestive of a possible causal link among particulate matter levels and incidence of COVID-19.

scholarly journals Evaluations of Surface PM10 Concentration and Chemical Compositions in MERRA-2 Aerosol Reanalysis over Central and Eastern China

2021 ◽  
Vol 13 (7) ◽  
pp. 1317
Author(s):  
Xiaodan Ma ◽  
Peng Yan ◽  
Tianliang Zhao ◽  
Xiaofang Jia ◽  
Jian Jiao ◽  
...  
Keyword(s):  
Eastern China ◽  
Mainland China ◽  
Chemical Components ◽  
Chemical Compositions ◽  
Observation Data ◽  
Causative Factors ◽  
Routine Sampling ◽  
Aerosol Compositions ◽  
Modern Era

The chemical composition dataset of Aerosol Reanalysis of NASA’s Modern-Era Retrospective Analysis for Research and Application, version 2 (MERRAero) has not been thoroughly evaluated with observation data in mainland China due to the lack of long-term chemical components data. Using the 5-year data of PM10 mass concentrations and chemical compositions obtained from the routine sampling measurements at the World Meteorological Organization the Global Atmosphere Watch Programme regional background stations, Jing Sha (JS) and Lin’An (LA), in central and eastern China, we comprehensively evaluate the surface PM10 concentrations and chemical compositions such as sulfate (SO42−), organic carbon (OC) and black carbon (BC) derived from MERRAero. Overall, the concentrations of PM10, SO42−, OC and BC from the MERRAero agreed well with the measurements, despite a slight and consistent overestimation of BC concentrations and a moderate and persistent underestimation of PM10 concentrations throughout the study period. The MERRAero reanalysis of aerosol compositions performs better during the summertime than wintertime. By considering the nitrate particles in PM10 reconstruction, MERRAero performance can be significantly improved. The unreasonable seasonal variations of PM10 chemical compositions at station LA by MERRAero could be causative factors for the larger MERRAero discrepancies during 2016–2017 than the period of 2011–2013.

scholarly journals Long-Term Observations of Beach Variability at Hasaki, Japan

2020 ◽  
Vol 8 (11) ◽  
pp. 871
Author(s):  
Masayuki Banno ◽  
Satoshi Nakamura ◽  
Taichi Kosako ◽  
Yasuyuki Nakagawa ◽  
Shin-ichi Yanagishima ◽  
...  
Keyword(s):  
Morphological Change ◽  
High Frequency ◽  
Climate Changes ◽  
Wave Climate ◽  
Time Interval ◽  
Observation Data ◽  
Beach Profile ◽  
Water Level Variations ◽  
Monthly Variations

Long-term beach observation data for several decades are essential to validate beach morphodynamic models that are used to predict coastal responses to sea-level rise and wave climate changes. At the Hasaki coast, Japan, the beach profile has been measured for 34 years at a daily to weekly time interval. This beach morphological dataset is one of the longest and most high-frequency measurements of the beach morphological change worldwide. The profile data, with more than 6800 records, reflect short- to long-term beach morphological change, showing coastal dune development, foreshore morphological change and longshore bar movement. We investigated the temporal beach variability from the decadal and monthly variations in elevation. Extremely high waves and tidal anomalies from an extratropical cyclone caused a significant change in the long-term bar behavior and foreshore slope. The berm and bar variability were also affected by seasonal wave and water level variations. The variabilities identified here from the long-term observations contribute to our understanding of various coastal phenomena.

scholarly journals Using Long-Term Earth Observation Data to Reveal the Factors Contributing to the Early 2020 Desert Locust Upsurge and the Resulting Vegetation Loss

2021 ◽  
Vol 13 (4) ◽  
pp. 680
Author(s):  
Lei Wang ◽  
Wen Zhuo ◽  
Zhifang Pei ◽  
Xingyuan Tong ◽  
Wei Han ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Arabian Peninsula ◽  
Vegetation Coverage ◽  
Observation Data ◽  
Desert Locust ◽  
Meteorological Observations ◽  
Earth Observation Data ◽  
Vegetation Loss

Massive desert locust swarms have been threatening and devouring natural vegetation and agricultural crops in East Africa and West Asia since 2019, and the event developed into a rare and globally concerning locust upsurge in early 2020. The breeding, maturation, concentration and migration of locusts rely on appropriate environmental factors, mainly precipitation, temperature, vegetation coverage and land-surface soil moisture. Remotely sensed images and long-term meteorological observations across the desert locust invasion area were analyzed to explore the complex drivers, vegetation losses and growing trends during the locust upsurge in this study. The results revealed that (1) the intense precipitation events in the Arabian Peninsula during 2018 provided suitable soil moisture and lush vegetation, thus promoting locust breeding, multiplication and gregarization; (2) the regions affected by the heavy rainfall in 2019 shifted from the Arabian Peninsula to West Asia and Northeast Africa, thus driving the vast locust swarms migrating into those regions and causing enormous vegetation loss; (3) the soil moisture and NDVI anomalies corresponded well with the locust swarm movements; and (4) there was a low chance the eastwardly migrating locust swarms would fly into the Indochina Peninsula and Southwest China.

scholarly journals A SLR Pre-Processing Algorithm Based on Satellite Signature Effect

2021 ◽  
Vol 11 (19) ◽  
pp. 8880
Author(s):  
Bowen Guan ◽  
Cunbo Fan ◽  
Ning An ◽  
Ricardo Cesar Podesta ◽  
Dra Ana Pacheco ◽  
...  
Keyword(s):  
Mean Value ◽  
Observation Data ◽  
Short Term ◽  
Error Sources ◽  
Effect Model ◽  
The Mean ◽  
The Stability ◽  
First Time ◽  
Satellite Signature Effect

As one of the major error sources, satellite signature effect should be reduced or even erased from the distribution of the post-fit residuals to improve the ranging precision. A simulation of satellite signature effect removal process for normal point algorithm is conducted based on a revised model of satellite response, which fully considers the structural and distribution characteristics of retroreflectors. In order to eliminate both long-term and short-term satellite signature effect, a clipping method for SLR data processing is proposed by defining the clipping location as 5.6 mm away from the mean value of the long-term fit residuals to select effective returns for normal points. The results indicate that, compared to normal points algorithm, the RMS per NP of LAGEOS-1 observation data processed by the clipping method is reduced from 62.90 ± 9.9 mm to 56.07 ± 4.69 mm, and the stability of RMS is improved 53%. This study improves the satellite signature effect model and simulates the fluctuation of normal points caused by satellite signature effect for the first time. The new method based on the simulation of satellite signature effect has stronger robustness and applicability, which can further minimize the influence of satellite signature effect on the SLR production and significantly improve the data property.

scholarly journals The dyad is not enough

2021 ◽  
Vol 58 (3) ◽  
Author(s):  
Torbjörn Bildtgård ◽  
Marianne Winqvist ◽  
Peter Öberg
Keyword(s):  
Life Course ◽  
Exploratory Study ◽  
Social Dynamics ◽  
Intimate Partner ◽  
Life Course Perspective ◽  
Third Party ◽  
Older Parents ◽  
Biological Children ◽  
Over Time

The increasing prevalence of ageing stepfamilies and the potential of stepchildren to act as a source of support for older parents have increased the interest in long-term intergenerational step relationships. Applying a life-course perspective combined with Simmel’s theorizing on social dynamics, this exploratory study aims to investigate the preconditions for cohesion in long-term intergenerational step relationships. The study is based on interviews with 13 older parents, aged 66–79, who have raised both biological children and stepchildren. Retrospective life-course interviews were used to capture the development of step relationships over time. Interviews were analysed following the principles of analytical induction. The results reveal four central third-party relationships that are important for cohesion in intergenerational step relationships over time, involving: (1) the intimate partner; (2) the non-residential parent; (3) the bridge child; and (4) the stepchild-in-law. The findings have led to the conclusion that if we are to understand the unique conditions for cohesion in long-term intergenerational step relationships, we cannot simply compare biological parent–child dyads with step dyads, because the step relationship is essentially a mediated relationship.

scholarly journals Effects of Digital Storytelling in Mathematics Instruction on Academic Achievement and Examination of Teacher-Student Opinions on the Process

2017 ◽  
Vol 5 (10) ◽  
pp. 137 ◽  
Author(s):  
İlknur Özpinar ◽  
Semirhan Gökçe ◽  
Arzu Aydoğan Yenmez
Keyword(s):  
Academic Achievement ◽  
Learning Environments ◽  
Classroom Environment ◽  
Digital Storytelling ◽  
Daily Life ◽  
Learning Experience ◽  
Real Life ◽  
Control Group ◽  
Student Opinions ◽  
Digital Stories

Storytelling is a popular instrument used in every domain of natural and social interaction for human communication and commonly used in classrooms to enrich the learning experience. With the use of technological tools in every field of our daily lives, its use in educational environments has become inevitable and in parallel with the development of these tools, digital stories have started to replace traditional storytelling. Digital storytelling offers advantages such as providing diverse applications in the classroom environment, personalizing the learning experience, being interesting, helping difficult subjects explained, addressing real-life-related situations, supporting active learning, allowing for the creation of costless learning environments, and improving motivation and achievement. Materializing a course such as mathematics in which abstract concepts are given, helping students use the learned information with stories and associate it with daily life, developing activities to make learning environments enjoyable when learning and applying by taking students away from the traditional understanding of instruction are considered some of the most important duties of teachers in this process. In accordance with the related considerations, this study aims to investigate the effects of mathematics courses instructed by association with digital storytelling on 8th-grade students’ academic achievements and the teacher and student opinions on the application process. The study using the quasi-experimental method was conducted with 58 students. The Achievement Test, written opinion forms to receive student opinions and interview form for teacher were prepared by the researchers to this end. At the end of the study, although no statistically significant differences were found between the groups in the posttest and the delayed-posttest in terms of academic achievement score averages of the students in the experimental group were found to be higher than the score averages of the students in the control group. The results achieved in this study show that digital storytelling is a powerful instrument to create more interesting and enjoyable learning environments which facilitate association with daily life, allow for effective learning and participation. It was also stated that the students and the mathematics teacher had positive opinions on use of digital stories in the courses and its contribution to the courses.

scholarly journals Bird trends from long-term observation data at sites in the Hudson Bay Lowlands

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Rodney W. Brook ◽  
Lisa A. Pollock ◽  
Kenneth F. Abraham ◽  
Glen S. Brown
Keyword(s):  
Hudson Bay ◽  
Observation Data ◽  
Hudson Bay Lowlands ◽  
Long Term Observation
Sign in / Sign up

Export Citation Format

Share Document