23 research outputs found
Multi-Objective Big Data Optimization with jMetal and Spark
Big Data Optimization is the term used to refer to optimization problems which have to manage very large amounts of data. In this paper, we focus on the parallelization of metaheuristics with the Apache Spark cluster computing system for solving multi-objective Big Data Optimization problems. Our purpose is to study the influence of accessing data stored in the Hadoop File System (HDFS) in each evaluation step of a metaheuristic and to provide a software tool to solve these kinds of problems. This tool combines the jMetal multi-objective optimization framework with Apache Spark. We have carried out experiments to measure the performance of the proposed parallel infrastructure in an environment based on virtual machines in a local cluster comprising up to 100 cores. We obtained interesting results for computational e ort and propose guidelines to face multi-objective Big Data Optimization
problems.Universidad de Málaga. Campus de Excelencia Internacional AndalucĂa Tech
Exploring the impact of cumulative testing on academic performance of undergraduate students in Spain
The final publication is available at Springer via http://dx.doi.org/10.1007/s11092-014-9208-zFrequent testing provides opportunities for students to receive regular feedback and to increase their motivation. It also provides the instructor with valuable information on how course progresses, thus making it possible to solve the problems encountered before it is too late. Frequent tests with noncumulative contents have been widely analysed in the literature with inconclusive results. However, cumulative testing methods have hardly been reported in higher education courses. This paper analyses the effect of applying an assessment method based on frequent and cumulative tests on student performance. Our results show that, when applied to a microeconomics course, students who were assessed by a frequent, cumulative testing approach largely outperformed those assessed with a single final exam.Doménech I De Soria, J.; Blázquez Soriano, MD.; De La Poza, E.; Muñoz Miquel, A. (2015). Exploring the impact of cumulative testing on academic performance of undergraduate students in Spain. Educational Assessment, Evaluation and Accountability. 27(2):153-169. https://doi.org/10.1007/s11092-014-9208-zS153169272Adelman, HS, & Taylor, L. (1990). Intrinsic motivation and school misbehaviour some intervention implications. Journal of Learning Disabilities, 23, 541–550.Biggs, J, & Tang, C. (2007). Teaching for quality learning at university 3rd edn. Open University Press.Boston, C. (2002). The concept of formative assessment. Practical Assessment Research & Evaluation 8.Brown, GA, Bull, J, Pendlebury, M. (1997). Assessing Student Learning in Higher Education, 1st edn. Routledge.Cano, MD. (2011). Students’ involvement in continuous assessment methodologies: a case study for a distributed information systems course. IEEE Transactions on Education, 54, 442–451.Casem, ML (2006). Active learning is not enough. Journal of College Science Teaching, 35.Chen, J, & Lin, TF. (2008). Class attendance and exam performance a randomized experiment. The Journal of Economic Education, 39, 213–227.Chickering, AW, & Gamson, ZF. (1987). Seven principles for good practice in undergraduate education. American Association for Higher Education Bulletin, 39, 3–7.Crooks, TJ. (1988). The impact of classroom evaluation practices on students. Review of Educational Research, 58, 438–481.De Paola, M, & Scoppa, V. (2011). Frequency of examinations and student achievement in a randomized experiment. Economics of Education Review, 30, 1416–1429.Deck, W. (1998). The effects of frequency of testing on college students in a principles of marketing course, PhD thesis, Virginia Polytechnic Institute and State University. Virginia: Blacksburg.Dempster, FN. (1991). Synthesis of research on reviews and tests. Educational Leadership, 48, 71–76.Dochy, F. (2008). The Edumetric Quality of New Modes of Assessment: Some Issues and Prospects. Assessment, Learning and Judgement in Higher Education. Dordrecht: Springer Netherlands.Eikner, AE, & Montondon, L. (2001). Evidence on factors associated with success in intermediate accounting I. Accounting Educators’ Journal 13.Emerson, TLN, & Mencken, KD. (2011). Homework to require or not? online graded homework and student achievement Perspectives on Economic Education Research 7.Fulkerson, F, & Martin, G. (1981). Effects of exam frequency on student performance, evaluations of instructor, and test anxiety. Teaching of Psychology, 8, 90–93.Furnham, A, & Chamorro-Premuzic, T. (2005). Individual differences and beliefs concerning preference for university assessment methods. Journal of Applied Social Psychology, 35, 1968–1994.Gibbs, G, & Simpson, C. (2005). Conditions under which assessment supports students’ learning Learning and Teaching in Higher Education 1 (August 5, 2011)3–31.Haberyan, KA. (2003). Do weekly quizzes improve student performance on general biology exams?. The American Biology Teacher, 65, 110–114.Kling, N, McCorkle, D, Miller, C, Reardon, J. (2005). The impact of testing frequency on student performance in a marketing course. Journal of Education for Business, 81, 67–72.Kuh, GD (2003). What we’re learning about student engagement from NSSE Change 35.Kuo, T, & Simon, A. (2009). How many tests do we really need. College Teaching, 57, 156–160.Leeming, FC. (2002). The exam-a-day procedure improves performance in psychology classes. Teaching of Psychology, 29, 210–212.Lumsden, KG, Scott, A, Becker, WE. (1987). The economics student reexamined Male-female differences in comprehension. Journal of Economic Education, 18, 365–375.Marriott, P. (2009). Students’ evaluation of the use of online summative assessment on an undergraduate financial accounting module. British Journal of Educational Technology, 40, 237–254.Marriott, P, & Lau, A. (2008). The use of on-line summative assessment in an undergraduate financial accounting course. Journal of Accounting Education, 26, 73–90.McNabb, R, Pal, S, Sloane, P. (2002). Gender differences in educational attainment. the case of university students in england and wales. Economica, 69, 481–503.Miller, F. (1987). Test frequency, student performance and teacher evaluation in the basic marketing class. Journal of Marketing Education, 9, 14–19.Nicol, DJ, & Macfarlane Dick, D. (2006). Formative assessment and self-regulated learning, A model and seven principles of good feedback practice. Studies in Higher Education, 31, 199–218.Nowell, C, & Alston, RM. (2007). I thought I got an A! Overconfidence across the economics curriculum. The Journal of Economic Education, 38, 131–142.Race, P (1995). The art of assessing 1 New Academic 4.Scriven, M. (1967). The Methodology of Evaluation, vol 1 (pp. 39–83). Chicago: Rand McNally.Skinner, BF. (1974). About behaviorism. New York: Alfred A Knopf.Taras, M. (2005). Assessment - summative and formative - some theoretical reflections. British Journal of Educational Studies, 53, 466–478.Trotter, E. (2006). Student perceptions of continuous summative assessment. Assessment & Evaluation in Higher Education, 31, 505–521.Yorke, M. (2003). Formative assessment in higher education: Moves towards theory and the enhancement of pedagogic practice. Higher Education, 45, 477–501
Maternal and child health interventions in Nigeria: a systematic review of published studies from 1990 to 2014
BACKGROUND: Poor maternal and child health indicators have been reported in Nigeria since the 1990s. Many interventions have been instituted to reverse the trend and ensure that Nigeria is on track to achieve the Millennium Development Goals. This systematic review aims at describing and indirectly measuring the effect of the Maternal, Newborn, and Child Health (MNCH) interventions implemented in Nigeria from 1990 to 2014.
METHODS: PubMed and ISI Web of Knowledge were searched from 1990 to April 2014 whereas POPLINE® was searched until 16 February 2015 to identify reports of interventions targeting Maternal, Newborn, and Child Health in Nigeria. Narrative and graphical synthesis was done by integrating the results of extracted studies with trends of maternal mortality ratio (MMR) and under five mortality (U5MR) derived from a joint point regression analysis using Nigeria Demographic and Health Survey data (1990-2013). This was supplemented by document analysis of policies, guidelines and strategies of the Federal Ministry of Health developed for Nigeria during the same period.
RESULTS: We identified 66 eligible studies from 2,662 studies. Three interventions were deployed nationwide and the remainder at the regional level. Multiple study designs were employed in the enrolled studies: pre- and post-intervention or quasi-experimental (n = 40; 61%); clinical trials (n = 6;9%); cohort study or longitudinal evaluation (n = 3;5%); process/output/outcome evaluation (n = 17;26%). The national MMR shows a consistent reduction (Annual Percentage Change (APC) = -3.10%, 95% CI: -5.20 to -1.00 %) with marked decrease in the slope observed in the period with a cluster of published studies (2004-2014). Fifteen intervention studies specifically targeting under-five children were published during the 24 years of observation. A statistically insignificant downward trend in the U5MR was observed (APC = -1.25%, 95% CI: -4.70 to 2.40%) coinciding with publication of most of the studies and development of MNCH policies.
CONCLUSIONS: The development of MNCH policies, implementation and publication of interventions corresponds with the downward trend of maternal and child mortality in Nigeria. This systematic review has also shown that more MNCH intervention research and publications of findings is required to generate local and relevant evidence
Academic Students’ Progress Indicators and Gender Gaps Based on Survival Analysis and Data Mining Frameworks
Thyroid hormone determines the start of the sensitive period of imprinting and primes later learning
Patient-reported and Physician-estimated Adherence to HAART: Social and Clinic Center-related Factors Are Associated with Discordance
OBJECTIVES: To evaluate the rate of discordance between patients and physicians on adherence to highly active antiretroviral therapy (HAART) and identify factors related to discordance in these two assessments. DESIGN: Prospective, multicenter, cohort study (AdICONA) nested within the Italian Cohort NaĂŻve Antiretrovirals (ICONA) study. SETTING: Tertiary clinical centers. PARTICIPANTS: The patients filled out a 16-item self-administered questionnaire on adherence to HAART. At the same time, physicians estimated the current HAART adherence of their patient. MAIN OUTCOME MEASURE: Discordance between patient and physician on adherence to antiretroviral therapy. RESULTS: From May 1999 to March 2000, 320 paired patient-physician assessments were obtained. Patients had a mean plasma HIV RNA of 315 copies/ml (64% had undetectable HIV RNA) and a mean CD4+ cell count of 577 cells Ă— 106/L. Nonadherence was reported by 30.9% of patients and estimated by physicians in 45.0% cases. In 111 cases (34.7%), patients and physicians were discordant on adherence to HAART. Kappa statistics was 0.27. Using patient-assessed adherence as reference, sensitivity, specificity, positive predictive value, and negative predictive value of physician-estimated adherence were 64.7%, 66.6%, 81.2%, and 45.8%, respectively. On multivariable analysis, low education level, unemployment, absence of a social worker in the clinical center, and unavailability of afternoon visits were significantly correlated with patient-physician discordance on adherence to antiretrovirals. CONCLUSIONS: Physicians did not correctly estimate patient-reported adherence to HAART in more than one third of patients. Both social variables and factors related to the clinical center were important predictors of discordance between patients and physicians. Interventions to enhance adherence should include strategies addressed to improve patient-physician relationship