Malai Hayati Sheikh Hamid

Online Learning: trends, issues and challenges in the Big Data Era

Nowadays, many students access online resources using their mobile devices, substituting this for traditional learning interactions. However, the new concept of ‘big data’ in recent ICT discussions extends the promising research direction on online learning and big data integration. Big data promises content that can be tailored for each student based on the context and Internet behaviour of users in online learning. This study examines recent Internet activities and literacy in Brunei Darussalam (Brunei) relating to the Internet behaviour and online learning of residents. The study highlights milestones in terms of recent issues, challenges, and trends in Internet activities, focusing on online learning and its potential in the big data era. An extensive nationwide survey was conducted to ensure the reliability of the data. The survey revealed that people in Brunei expect and demand better learning services and experiences through an online learning system to improve literacy as well as the quality and ef ciency of learning. Regardless of the limitations of the survey, the general public has shown great support for online learning systems. The results of the survey provide a solid argument for further research on big data in online learning by developing a framework incorporating the expectations of the people. Finally, the study provides a baseline for future studies of Internet adoption in Brunei.

Recidivism in Brunei Inmates â Estimating the Rates and PredictingReoffending

The survey investigated the recidivism problem in a random sample of Brunei prisoners (N = 64) representing both genders. Overall, there were more recidivists than firsttime offenders on all the three major crimes (theft, drugs, and sex offenses). The relapse cases were overrepresented in the 36-40 age-group. Offending and re-offending occurred almost at the same rate in married and non-married inmates. Both groups cited the need to support dependent relatives as one of the main reasons for stealing. Four variables (interpersonal-sensitivity, lifestyle, parents’ marital status, and obsessive-compulsive disorder) were significantly related to recidivism, all at p<0.05 level. Of these, the best predictor of recidivism was interpersonal-sensitivity (OR = 1.199; 95% CI for OR = 1.028 - 1.398; p<0.05). Inmates who scored high on the interpersonalsensitivity variable (lack of sensitivity when dealing with other people) were 1.2 times more likely to reoffend and be re-imprisoned upon release. Sex offenses were 28 times more likely to be repeated by perpetrators upon release. The likelihood of drug and stealing offenses to recurr was 10.9 and 7.4 times respectively. Preventive, community-based, and in-prison interventions were recommended to address the convicts’ recidivism, labeling, stigma, and discrimination problems to facilitate reintegration. Large-scale mixed-methods research was suggested to gain additional insights and solutions.

Contributions of sociodemographic factors to criminal behavior.

We explored the extent to which prisoner sociodemographic variables (age, education, marital status, employment, and whether their parents were married or not) influenced offending in 64 randomly selected Brunei inmates, comprising both sexes. A quantitative field survey design ideal for the type of participants used in a prison context was employed to investigate the problem. Hierarchical multiple regression analysis with backward elimination identified prisoner marital status and age groups as significantly related to offending. Furthermore, hierarchical multinomial logistic regression analysis with backward elimination indicated that prisoners’ age, primary level education, marital status, employment status, and parental marital status as significantly related to stealing offenses with high odds ratios. All 29 nonrecidivists were false negatives and predicted to reoffend upon release. Similarly, all 33 recidivists were projected to reoffend after release. Hierarchical binary logistic regression analysis revealed age groups (24–29 years and 30–35 years), employed prisoner, and primary level education as variables with high likelihood trends for reoffending. The results suggested that prisoner interventions (educational, counseling, and psychotherapy) in Brunei should treat not only antisocial personality, psychopathy, and mental health problems but also sociodemographic factors. The study generated offending patterns, trends, and norms that may inform subsequent investigations on Brunei prisoners.