Enhancing learning through cooperative learning: UTM experience

Lecture-based classes are the predominant teaching method in all levels of education. This teaching style, undoubtedly is able to deliver knowledge to students and produce graduates. However, this teaching technique is usually unable to invoke higher level of cognitive skills. With an ever-growing volume of knowledge that must be covered in engineering education, an alternative technique must be used to enhance learning. Co-operative learning is a proven teaching technique that is able to enhance students’ learning through active learning. This technique has been widely accepted in engineering education in the United States, Europe, United Kingdom and Australia. In UTM, lecturers from different faculties of engineering implement cooperative learning in their classes. The main aim is to induce better retention, in-depth understanding and mastery of knowledge among students. This paper shows how cooperative learning successfully enhance students' learning by looking at the performance of their grades in different engineering classes

A review and survey of Problem-Based Learning application in Engineering Education

This paper gives a review of Problem-Based Learning (PBL) applied in engineering courses worldwide, and a survey of academic staff who have implemented PBL in engineering classes in Universiti Teknologi Malaysia. The review of PBL application illustrates the extent of acceptance and success of PBL in schools of engineering in the international arena. The survey, on the other hand, illustrates the acceptance of PBL among engineering lecturers and the possibility of applying PBL in Malaysia. The main purpose of the survey is to obtain feedback on PBL regarding the impressions, set-backs and constraints faced, as well as innovations and tips for successful implementation from the faculty members involved

A new modification of the homotopy perturbation method

In this paper, a new modification of the homotopy perturbation method (HPM) is presented and applied to linear ordinary differential equations and nonlinear differential equations. A comparative study between the new modified homotopy perturbation method (MHPM) and the classical homotopy perturbation method (HPM) is conducted. Several illustrative examples are given to demonstrate the effectiveness and reliability of MHPM. The numerical results obtained from the MHPM and HPM are compared with the fourth-order Runge-Kutta method (RKM)

Process modelling of a PVC production plant

This paper presents the modelling of a Polyvinyl Chloride (PVC) resins manufacturing process with batch process simulator, SuperPro Designer V6.0. The simulation model has been developed based on the operating condition of a local PVC manufacturing plant. As the polymerisation process is carried out in batch operation mode, efforts have been made to document the scheduling details of each unit operation and results are presented in the Gantt chart. Cycle time for a complete polymerisation process is determined to be 14.28 hours. The model also reveals that approximately 17 batches of polymerisation reaction can be processed per day, which tallies the real operation of the PVC manufacturing plant

Optimization of nickel removal from electroless plating industry wastewater using response surface methodology

Optimum pH and coagulant dosage for chemical precipitation in wastewater treatment plants is conventionally obtained through repeated jar test. In this research, optimization of the performance of polyacrylamide in the treatment of industrial wastewater was carried out using response surface methodology. The individual linear and quadratic effect of coagulant dosage and pH on the degree of removals of nickel, total suspended solids, Chemical Oxygen Demand and turbidity were investigated. The optimum pH and polyacrylamide dosage were found to be 10.5 and 1.6 ml/L respectively and the optimum percentage nickel removal was 96.9%. The model used in predicting the precipitation process gave a good fit with the experimental variables and hence the suitability of response surface methodology for the optimization of polyacrylamide performanc

A review on gamma greenhouse as a chronic gamma irradiation facility for plant breeding and improvement program

The research on radiation induced mutation has been conducted as one of the promising method of plant breeding in Malaysia since 1980s. Nuclear Malaysia is leading research institute in Malaysia conducting plant mutation breeding research. Gamma Greenhouse facility located in Nuclear Malaysia is one of the irradiation facilities to serve as a chronic irradiation facility for inducing mutation in various organisms including plants, fungi and microbes. Chronic irradiation refers to the exposure of materials at a lower dose rate over a long period of time. Previous studies have shown that this type of irradiation can minimize radiation damages to living materials and produces a wider mutation spectrum, therefore is very useful for trait improvements in irradiated organisms. Experiments on induce mutation using Gamma Greenhouse facility for crop improvement program have been conducted since its first operation in 2009. Various plant species including ornamental and herbal plants, food crops and industrial crops have been irradiated to improve their traits such as higher yield and biomass, pest and disease tolerance, higher bioactive compounds, longer bloom time and many others. Most of these crop improvement programs were done through collaborations with other agencies in Malaysia such as universities, research institutes and government departments. A number of publications on crop improvement using Gamma Greenhouse have been published in local and international journals as well as seminar presentations at national and international levels. The outputs from induced mutation via chronic radiation using Gamma Greenhouse could be of great interest for plant breeders dealing with improvement and development of new cultivars. This paper discusses the activities and achievement in plant breeding and improvement using Gamma Greenhouse Facility in Malaysia

Anatomy education environment measurement inventory (AEEMI): a cross-validation study in Malaysian medical schools

Background: The Anatomy Education Environment Measurement Inventory (AEEMI) evaluates the perception of medical students of educational climates with regard to teaching and learning anatomy. The study aimed to cross-validate the AEEMI, which was previously studied in a public medical school, and proposed a valid universal model of AEEMI across public and private medical schools in Malaysia. Methods: The initial 11-factor and 132-item AEEMI was distributed to 1930 pre-clinical and clinical year medical students from 11 medical schools in Malaysia. The study examined the construct validity of the AEEMI using exploratory and confirmatory factor analyses. Results: The best-fit model of AEEMI was achieved using 5 factors and 26 items (χ 2 = 3300.71 (df = 1680), P < 0.001, χ 2/df = 1.965, Root Mean Square of Error Approximation (RMSEA) = 0.018, Goodness-of-fit Index (GFI) = 0.929, Comparative Fit Index (CFI) = 0.962, Normed Fit Index (NFI) = 0.927, Tucker–Lewis Index (TLI) = 0.956) with Cronbach’s alpha values ranging from 0.621 to 0.927. Findings of the cross-validation across institutions and phases of medical training indicated that the AEEMI measures nearly the same constructs as the previously validated version with several modifications to the item placement within each factor. Conclusions: These results confirmed that variability exists within factors of the anatomy education environment among institutions. Hence, with modifications to the internal structure, the proposed model of the AEEMI can be considered universally applicable in the Malaysian context and thus can be used as one of the tools for auditing and benchmarking the anatomy curriculum

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic