The effectiveness of technology-supported personalised learning in low- and middle-income countries: A meta-analysis

AbstractDigital technology offers the potential to address educational challenges in resource‐poor settings. This meta‐analysis examines the impact of students' use of technology that personalises and adapts to learning level in low‐ and middle‐income countries. Following a systematic search for research between 2007 and 2020, 16 randomised controlled trials were identified in five countries. Studies involved 53,029 learners aged 6–15 years. Coding examined learning domain (mathematics and literacy); personalisation level and delivery; technology use; and intervention duration and intensity. Overall, technology‐supported personalised learning was found to have a statistically significant—if moderate—positive effect size of 0.18 on learning (p = 0.001). Meta‐regression reveals how more personalised approaches which adapt or adjust to learners' level led to significantly greater impact (an effect size of 0.35) than those only linking to learners' interests or providing personalised feedback, support, and/or assessment. Avenues for future research include investigating cost implications, optimum programme length, and teachers' role in making personalised learning with technology effective. Practitioner notesWhat is already known about this topic? Promoting personalised learning is an established aim of educators. Using technology to support personalised learning in low‐ and middle‐income countries (LMICs) could play an important role in ensuring more inclusive and equitable access to education, particularly in the aftermath of COVID‐19. There is currently no rigorous overview of evidence on the effectiveness of using technology to enable personalised learning in LMICs. What this paper adds? The meta‐analysis is the first to evaluate the effectiveness of technology‐supported personalised learning in improving learning outcomes for school‐aged children in LMICs. Technology‐supported personalised learning has a statistically significant, positive effect on learning outcomes. Interventions are similarly effective for mathematics and literacy and whether or not teachers also have an active role in the personalisation. Personalised approaches that adapt or adjust to the learner led to significantly greater impact, although whether these warrant the additional investment likely necessary for implementation at scale needs to be investigated. Personalised technology implementation of moderate duration and intensity had similar positive effects to that of stronger duration and intensity, although further research is needed to confirm this. Implications for practice and/or policy: The inclusion of more adaptive personalisation features in technology‐assisted learning environments can lead to greater learning gains. Personalised technology approaches featuring moderate personalisation may also yield learning rewards. While it is not known whether personalised technology can be scaled in a cost‐effective and contextually appropriate way, there are indications that this is possible. The appropriateness of teachers integrating personalised approaches in their practice should be explored given ‘supplementary’ uses of personalised technology (ie, additional sessions involving technology outside of regular instruction) are common. </jats:sec

Impact of Obesity on Metabolic Syndrome among Adolescents as Compared with Adults in Korea

PURPOSE: This study aimed to estimate the prevalence of metabolic syndrome (MetS) in adolescents and adults and to compare the impact of body mass index (BMI) on MetS between adolescents and adults in Korea. MATERIALS AND METHODS: Data were used from 6,186 subjects aged 10 years or more who representatively participated in the Third Korean National Health and Nutrition Examination Survey. Body composition, blood test, and health behavioral factors were measured. We used the definition of MetS from the modified the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) for adolescents and the NCEP-ATP Ⅲ for adults. RESULTS: The prevalence of MetS was 6.4 (95% CI 4.5-8.4) and 22.3 (95% CI 20.8-23.8) in adolescents and adults, respectively. The prevalence of MetS among normal, overweight and obese body types for both adolescents and adults differed significantly (p<0.001). After adjustment for covariates, the odds ratios (ORs) of obese and overweight body types on MetS compared with normal BMI in adolescents were 28.1 (95% CI 11.4-69.1) and 8.7 (95% CI 2.3-33.1), respectively. The ORs of obesity on MetS were 32.0 (95% CI 7.5-136.9), 32.2 (95% CI 12.8-80.8), 16.2 (95% CI 9.4-27.9), 7.6 (95% CI 4.7-12.2) and 9.9 (95% CI 6.8-14.6) for subjects in their 20's, 30's, 40's, 50's and older than 60, in order. CONCLUSION: We found that the prevalence of MetS increased with age and was more prevalent in males. Moreover, the group younger than 39 years of age had a higher chance of having MetS than the group older than 40 years of age. Weight control is more vital in the earlier stages of life for the prevention and management of MetS.ope

Financing intersectoral action for health: a systematic review of co-financing models.

BACKGROUND: Addressing the social and other non-biological determinants of health largely depends on policies and programmes implemented outside the health sector. While there is growing evidence on the effectiveness of interventions that tackle these upstream determinants, the health sector does not typically prioritise them. From a health perspective, they may not be cost-effective because their non-health outcomes tend to be ignored. Non-health sectors may, in turn, undervalue interventions with important co-benefits for population health, given their focus on their own sectoral objectives. The societal value of win-win interventions with impacts on multiple development goals may, therefore, be under-valued and under-resourced, as a result of siloed resource allocation mechanisms. Pooling budgets across sectors could ensure the total multi-sectoral value of these interventions is captured, and sectors' shared goals are achieved more efficiently. Under such a co-financing approach, the cost of interventions with multi-sectoral outcomes would be shared by benefiting sectors, stimulating mutually beneficial cross-sectoral investments. Leveraging funding in other sectors could off-set flat-lining global development assistance for health and optimise public spending. Although there have been experiments with such cross-sectoral co-financing in several settings, there has been limited analysis to examine these models, their performance and their institutional feasibility. AIM: This study aimed to identify and characterise cross-sectoral co-financing models, their operational modalities, effectiveness, and institutional enablers and barriers. METHODS: We conducted a systematic review of peer-reviewed and grey literature, following PRISMA guidelines. Studies were included if data was provided on interventions funded across two or more sectors, or multiple budgets. Extracted data were categorised and qualitatively coded. RESULTS: Of 2751 publications screened, 81 cases of co-financing were identified. Most were from high-income countries (93%), but six innovative models were found in Uganda, Brazil, El Salvador, Mozambique, Zambia, and Kenya that also included non-public and international payers. The highest number of cases involved the health (93%), social care (64%) and education (22%) sectors. Co-financing models were most often implemented with the intention of integrating services across sectors for defined target populations, although models were also found aimed at health promotion activities outside the health sector and cross-sectoral financial rewards. Interventions were either implemented and governed by a single sector or delivered in an integrated manner with cross-sectoral accountability. Resource constraints and political relevance emerged as key enablers of co-financing, while lack of clarity around the roles of different sectoral players and the objectives of the pooling were found to be barriers to success. Although rigorous impact or economic evaluations were scarce, positive process measures were frequently reported with some evidence suggesting co-financing contributed to improved outcomes. CONCLUSION: Co-financing remains in an exploratory phase, with diverse models having been implemented across sectors and settings. By incentivising intersectoral action on structural inequities and barriers to health interventions, such a novel financing mechanism could contribute to more effective engagement of non-health sectors; to efficiency gains in the financing of universal health coverage; and to simultaneously achieving health and other well-being related sustainable development goals

Identification of Novel SNPs by Next-Generation Sequencing of the Genomic Region Containing the APC Gene in Colorectal Cancer Patients in China

We described an approach of identifying single nucleotide polymorphisms (SNPs) in complete genomic regions of key genes including promoters, exons, introns, and downstream sequences by combining long-range polymerase chain reaction (PCR) or NimbleGen sequence capture with next-generation sequencing. Using the adenomatous polyposis coli (APC) gene as an example, we identified 210 highly reliable SNPs by next-generation sequencing analysis program MAQ and Samtools, of which 69 were novel ones, in the 123-kb APC genomic region in 27 pair of colorectal cancers and normal adjacent tissues. We confirmed all of the eight randomly selected high-quality SNPs by allele-specific PCR, suggesting that our false discovery rate is negligible. We identified 11 SNPs in the exonic region, including one novel SNP that was not previously reported. Although 10 of them are synonymous, they were predicted to affect splicing by creating or removing exonic splicing enhancers or exonic splicing silencers. We also identified seven SNPs in the upstream region of the APC gene, three of which were only identified in the cancer tissues. Six of these upstream SNPs were predicted to affect transcription factor binding. We also observed that long-range PCR was better in capturing GC-rich regions than the NimbleGen sequence capture technique.MOST, Chin

Official report.

Description based on: June 15, 1982.Also issued as: Saint Louis (Mo.) Board of Education. Printed record.Mode of access: Internet