Student Satisfaction with Online Learning during the COVID-19 Pandemic: A Study at State Universities in Sri Lanka

This quantitative study investigated the determinants of students’ satisfaction with their online learning experience at Sri Lankan universities during the COVID-19 pandemic. The data was collected from 1376 undergraduates enrolled in various courses in humanities and social sciences at three state-owned universities in the country. The results of the Structural Equation Modeling (SEM) revealed that the independent variables of the model, namely perceived learner motivation, perceived challenges of e-learning, and interaction significantly affected students’ satisfaction with their new online learning experience. Out of the three variables, learner motivation exerted the strongest effect on students’ satisfaction, implying the crucial role self-regulated learning—characterized by motivation—plays in online learning environments. The study has several implications for both creating and ensuring the long-term sustainability of productive and student-friendly online learning spaces in higher education

SCREENING OF WOODY AND SHRUB LEGUMES FOR AGRO-FORESTRY SYSTEMS BASED ON BIOMASS PRODUCTION, N YIELD AND BIOLOGICAL N2 FIXING CAPACITY

A field study was carried out to identify the suitable tree species for agrolorcstry systemsbased on their biomass production. N yield and Nrfixing capacity at the ExportAgriculture Research Station. Matalc for a period of 9 months. I'N isotope dilutionmethod was used for the assessment or the proportion of N2 derived through fixation (Pfix).Gl iricidi« spiurn (g+iric idia). Calliandra calothvrsus (calliandru). Lcucacna leucoccpha!a(lcucacna). Ervthrina suhumhrancc (Erythrina). Albizia [alraturi« (Albicia) and AI'(/Iiamangium (acacia) were used as N2-fixing species and SCIII/a siamea (siamca), SCI/I/aspettabilis (Spcctnhilis). both are non-nodulating legumes. and Michaella chantpaca(michalia) were used as non Ny-fixing reference species.Total dry matter yield of non Ns-Iixing reference crop spcctabilis was significantly (pO.05)higher than all the species. Among the fixing species. Calliandra produced the highestbiomass though the value is not significantly (p~O.O.'i) different from gliricidia, lcucacnaand siamca. Acacia and michaclia recorded the lowest yields.Highest leaf. twigs and root NIl,) was found in crythrina and the highest trunk N% wasassociated with gliricidia. Leaf NIYr,of spcctahilis was less than that of gliricidin andcrythrinu but total N yield of spcctabilis was the highest due to high biomass production.Among the six fixing species highest N yield was found with calliandra and the value isover two fold higher than that for gliricidia. Acacia and michaclia recorded the lowest nyields.Highest Pfix values for whole plant was found with alhizia followed by g liricidia,cnlliandra. crythrina, lcuccana and acacia. The trend is common for the values based onall the three reference crops. Total Ns-fix iug capacity 01" calliandra recorded the highestvalue followed by lcucacnn, gliricidia, albizia. crythrina, and acacia. Ny-Iixing valuescalculated based on siamea and spcctabilis revealed N-fixing species calliandra, lcucacnaand gliricidia have thc capacity to fix 19.51-23.11. 15.77-19.79 and 13.IO-l4.42g Nplant I. The values equivalent to 1<)5-231. 15X-19X and 13l-l44kg of N ha').S. spcctabilis. C calothyrsus, L. leucocephala and G. sepium produced higher biomassand higher N yields over the others. Total N fixing capacity of C calothvrsus. L.leucoccphal« and G. septum were superior to the other species. However, wheremaintenance of soil N status is considered further studies arc recommended to evaluate thelitter quality and N transferring ability before a firm recommendation is made.

Quantifying mangrove chlorophyll from high spatial resolution imagery

Lower than expected chlorophyll concentration of a plant can directly limit photosynthetic activity, and resultant primary production. Low chlorophyll concentration may also indicate plant physiological stress. Compared to other terrestrial vegetation, mangrove chlorophyll variations are poorly understood. This study quantifies the spatial distribution of mangrove canopy chlorophyll variation using remotely sensed data and field samples over the Rapid Creek mangrove forest in Darwin, Australia. Mangrove leaf samples were collected and analyzed for chlorophyll content in the laboratory. Once the leaf area index (LAI) of sampled trees was estimated using the digital cover photography method, the canopy chlorophyll contents were calculated. Then, the nonlinear random forests regression algorithm was used to describe the relationship between canopy chlorophyll content and remotely sensed data (WorldView-2 satellite image bands and their spectral transformations), and to estimate the spatial distribution of canopy chlorophyll variation. The imagery was evaluated at full 2 m spatial resolution, as well as at decreased resampled resolutions of 5 m and 10 m. The root mean squared errors with validation samples were 0.82, 0.64 and 0.65 g/m2 for maps at 2 m, 5 m and 10 m spatial resolution respectively. The correlation coefficient was analyzed for the relationship between measured and predicted chlorophyll values. The highest correlation: 0.71 was observed at 5 m spatial resolution (R2 = 0.5). We therefore concluded that estimating mangrove chlorophyll content from remotely sensed data is possible using red, red-edge, NIR1 and NIR2 bands and their spectral transformations as predictors at 5 m spatial resolution

Spatial Ecology of Mangrove Forests:A Remote Sensing Perspective

Over the past few decades, a diverse range of remote sensing data have been acquired over mangrove areas in different modes and with varying spatial resolutions and temporal frequencies, with these used to advance our understanding of mangrove ecosystems and their response to natural and human-induced change. Detailed information on the floristic composition, structure, biomass and growth stage of mangroves and changes in these attributes over time and at different scales of observation has been obtained and the knowledge gained has been to better inform on, for example, carbon dynamics, floral and faunal diversity, connectivity with adjacent environments, and responses to changing hydrological regimes and climate. Significant opportunities also exist for more effective use of these data for actively managing mangroves and the services they provide and ensuring that they are not overexploited and their integrity within the coastal environment is maintained. The benefits of including these data in mangrove characterization, mapping and monitoring programs are demonstrated using case studies from a wide range of locations, including in Australia, Southeast Asia and central America, and instruments such as radar, lidar and optical sensors. Local to global efforts aimed at monitoring mangrove dynamics using remote sensing data are also increasing, with these leading to more informed decisions in relation to conservation, management and sustainable use. The authors would like to acknowledge Jorg Hacker of Airborne Research Australia (ARA) for providing LIDAR data for the Gulf of Carpentaria and the Japanese Space Exploration Agency (JAXA) for access to Japanese L-band SAR data