Search

The Ministry of Education has reemphasized the implementation of higher order thinking skills (HOTS) in science and mathematics curriculum in 2014. In relation to this, a research was carried out to analyse students’ ability in thinking skills (ATS), and to construct a model that estimates their ATS. The study involved 300 students of engineering and science foundation programme from a university. A Scientific Reasoning Test was used as instrument. Binary logistic regression is used to categorize the students’ level of thinking skills. Results show that 51.7% of students are categorized as having higher order thinking skills (HOTS) and 48.3% having lower order thinking skill (LOTS). More male students at HOTS level (57.1%) compared to LOTS (42.9%), while more female students at LOTS level (52.7%) compared to HOTS (47.3%). Higher percentage of boarding school students (55.4%) at HOTS level compared to daily school students. There is a significant correlation between ATS with students’ performance in mathematics course in foundation programme (MAT093) and performance in mathematics subject in SPM (MAT). A binary logistic model was constructed to estimate students’ ATS. The findings implicate that teaching method through inquiry and mind-mapping in i-Think process which has been implemented in schools since 2015 seems to give an impact in enhancing and developing students’ thinking skills. Key Words: Higher order thinking skill (HOTS); Scientific thinking skills; Scientific Reasoning Test; Binary logistic regression model; Mathematics achievement Kementerian Pendidikan Malaysia telah memberi penekanan semula terhadap penerapan kemahiran berfikir aras tinggi (KBAT) di dalam kurikulum sains dan matematik pada tahun 2014. Sehubungan itu, satu kajian dijalankan untuk menganalisis keupayaan kemahiran berfikir (KKB) pelajar dan membina model untuk telahan kemahiran berfikir mereka. Kajian ini melibatkan 300 pelajar Asasi program kejuruteraan dan sains dari sebuah universiti. Ujian Penaakulan Saintifik digunakan sebagai instrumen. (MAT) dan Matematik Tambahan (ADMAT) dalam SPM. Regresi Logistik Binari digunakan untuk menentukan kategori tahap kemahiran berfikir pelajar. Hasil kajian mendapati 51.7% pelajar berada pada kemahiran berfikir aras tinggi (KBAT) dan 48.3% berada pada kemahiran berfikir aras rendah (KBAR). Lebih banyak pelajar lelaki berada pada aras KBAT (57.1%) daripada aras KBAR (42.9%), manakala lebih banyak pelajar perempuan berada pada aras KBAR (52.7%) berbanding aras KBAT (47.3%). Lebih pelajar berasrama penuh berada pada aras KBAT (55.4%) berbanding pelajar sekolah harian. Terdapat korelasi yang signifikan antara KKB dengan pencapaian dalam kursus matematik matrikulasi (MAT093) dan pencapaian Matematik SPM (MAT). Sebuah model logistik binari telah dibina untuk telahan KKB pelajar. Dapatan mengimplikasikan bahawa kaedah pengajaran yang berbentuk inkuiri dan peta minda dalam proses i-Think yang telah diperkenalkan di sekolah pada tahun 2015 adalah berpotensi dan berkemampuan untuk mengembangkan aras kemahiran pemikiran pelajar. Kata Kunci: Kemahiran berfikir aras tinggi (KBAT); Kemahiran berfikiran saintifik; Ujian Penaakulan Saintifik; Model Regresi logistik binary; Pencapaian matematik

In regression analysis, missing covariate data has been a common problem. Many researchers use ad hoc methods to overcome this problem due to the ease of implementation. However, these methods require assumptions about the data that rarely hold in practice. Model-based methods such as Maximum Likelihood (ML) using the expectation maximization (EM) algorithm and Multiple Imputation (MI) are more promising when dealing with difficulties caused by missing data. Then again, inappropriate methods of missing value imputation can lead to serious bias that severely affects the parameter estimates. The main objective of this study is to provide a better understanding regarding missing data concept that can assist the researcher to select the appropriate missing data imputation methods. A simulation study was performed to assess the effects of different missing data techniques on the performance of a regression model. The covariate data were generated using an underlying multivariate normal distribution and the dependent variable was generated as a combination of explanatory variables. Missing values in covariate were simulated using a mechanism called missing at random (MAR). Four levels of missingness (10%, 20%, 30% and 40%) were imposed. ML and MI techniques available within SAS software were investigated. A linear regression analysis was fitted and the model performance measures; MSE, and R-Squared were obtained. Results of the analysis showed that MI is superior in handling missing data with highest R-Squared and lowest MSE when percent of missingness is less than 30%. Both methods are unable to handle larger than 30% level of missingness.

Quality of life (QoL) refers to the degree of satisfaction, or the sense of well being, people experience in organizations including universities. The quality of life students experience in a university increases when they believe their needs are aligned with the goals of the university because they perceive that the university is responsive to their needs. Quality of University Life (QuL) refers to the students' ability to stabilize their life regarding social activities, academic performance, health and spiritual. A study was undertaken to investigate the accountability of Universiti Teknologi MARA (UiTM), Malaysia, in terms of teaching and learning. The objective of this paper is to identify and evaluate the determinants of QoL and QuL measurement models. Data from 788 students who responded to a set of questionnaire were collected from nine faculties. Factor analysis performed on the data resulted in six determinants for QuL; friendly, skills, satisfaction, interest, learning and feeling. Only two det...

Prostate cancer is a disease facing the male which has shown a significant increase worldwide and is ranked sixth globally. In Malaysia, prostate cancer is ranked sixth as the leading cause of death among male cancer patients. The breakthrough in technology has shown that the robotic-assisted radical prostatectomy (RARP) is a treatment of choice compared to the traditional open surgery. This study focuses on the effectiveness of the RARP as this procedure benefits the patients including faster return of urinary continence, erectile function and cancer control. Even though studies have shown that the RARP has resulted in quick recovery and better functional outcome, yet post surgeries by RARP have shown patients have a full return of urinary continence while a few others do not. This study was conducted to investigate the association among the potential risk factors and the effectiveness of the RARP and the association with the demographic as confounding factors. This study used the secondary data obtained from the Urology Department at Hospital Kuala Lumpur. The summary and descriptive statistics were performed to explain the demographic profile of the patients. The chi-square test was used to determine the association among the potential risk factors. The result indicates that all potential risk factors are not significantly associated with the effectiveness of the RARP except for detection of cancer. In addition it was found that Indians with margin location at apex has a chance of grade 2 effectiveness of RARP.