Effects of tutor-related behaviours on the process of problem-based learning

Tutors in a Problem-Based Learning (PBL) curriculum are thought to play active roles in guiding students to develop frameworks for use in the construction of knowledge. This implies that both subject-matter expertise and the ability of tutors to facilitate the learning process must be important in helping students learn. This study examines the behavioural effects of tutors in terms of subject-matter expertise, social congruence and cognitive congruence on students’ learning process and on their final achievement. The extent of students’ learning at each PBL phase was estimated by tracking the number of relevant concepts recalled at the end of each learning phase, while student achievement was based on students’ ability to describe and elaborate upon the relationship between relevant concepts learned. By using Analysis of Covariance, social congruence of the tutor was found to have a significant influence on learning in each PBL phase while all of the tutor-related behaviours had a significant impact on student achievement. The results suggest that the ability of tutors to communicate informally with students and hence create a less threatening learning environment that promotes a free flow exchange of ideas, has a greater impact on learning at each of the PBL phases as compared to tutors’ subject-matter expertise and their ability to explain concepts in a way that is easily understood by students. The data presented indicates that these tutor-related behaviours are determinants of learning in a PBL curriculum, with social congruence having a greater influence on learning in the different PBL phases

The impact of climatic risk factors on the prevalence, distribution, and severity of acute and chronic trachoma.

BACKGROUND AND OBJECTIVES: Trachoma is the most common cause of infectious blindness. Hot, dry climates, dust and water scarcity are thought to be associated with the distribution of trachoma but the evidence is unclear. The aim of this study was to evaluate the epidemiological evidence regarding the extent to which climatic factors explain the current prevalence, distribution, and severity of acute and chronic trachoma. Understanding the present relationship between climate and trachoma could help inform current and future disease elimination. METHODS: A systematic review of peer-reviewed literature was conducted to identify observational studies which quantified an association between climate factors and acute or chronic trachoma and which met the inclusion and exclusion criteria. Studies that assessed the association between climate types and trachoma prevalence were also reviewed. RESULTS: Only eight of the 1751 papers retrieved met the inclusion criteria, all undertaken in Africa. Several papers reported an association between trachoma prevalence and altitude in highly endemic areas, providing some evidence of a role for temperature in the transmission of acute disease. A robust mapping study found strong evidence of an association between low rainfall and active trachoma. There is also consistent but weak evidence that the prevalence of trachoma is higher in savannah-type ecological zones. There were no studies on the effect of climate in low endemic areas, nor on the effect of dust on trachoma. CONCLUSION: Current evidence on the potential role of climate on trachoma distribution is limited, despite a wealth of anecdotal evidence. Temperature and rainfall appear to play a role in the transmission of acute trachoma, possibly mediated through reduced activity of flies at lower temperatures. Further research is needed on climate and other environmental and behavioural factors, particularly in arid and savannah areas. Many studies did not adequately control for socioeconomic or environmental confounders

Mixed methods evaluation of a primary eye care training programme for primary health workers in Morogoro Tanzania

Background: There are 285 million people with visual impairment (VI) worldwide including 39 million who are blind; 15 % of those with VI live in Africa, and around 80 % of VI is preventable or treatable with the right equipment, information and skills. The scarcity of human resources for eye health, particularly in Sub-Saharan Africa, is a key challenge towards achieving this goal. Therefore training primary health workers (PHW) in providing eye-care services has been seen by some authors as a way to improve access to eye-care services in remote communities. However, the package of interventions which could be effectively delivered for eye-care at the primary-care level or the set of skills and competencies that PHWs need has not yet been delineated. The aim of the study was to evaluate the effectiveness of a four day training programme of PHWs in primary eye-care conducted in Morogoro, Tanzania in 2010/2011. Methods: A mixed methods study using pre- and immediate post-training knowledge assessment of 60 trainees, and in-depth face to face interviews with 20 PHWs and 8 service managers 2 to 3 years after the training. Results: Pre-and immediate post-training assessments indicated improvement in health worker knowledge about eye-care in the short term. Qualitative investigations 2 to 3 years after the training showed that although staff could make the correct management decisions when presented with eye-health problems, they often could not make a correct diagnosis. PHWs and managers reported satisfaction with the content of the training but some of the less well qualified staff found it overwhelming. Theoretical teaching was appreciated by most participants but almost all suggested increasing the time spent on acquiring skills. The training manual was accepted by many and some improvements were recommended. All interviewed PHWs were keen to improve their skills and knowledge. Acquired skills and knowledge were used for identification, referral of patients and for eye-health promotion. Conclusion: The training program in Morogoro was considered by PHWs as broadly successful and satisfying in terms of content, methods and duration of training. However, any future programme needs to be considered within the context of strengthening wider health systems

Self-reflection and academic performance: is there a relationship?

The purposes of the present study were two-fold: first, to evaluate whether reflection journal writing was effective in promoting self-reflection and learning, and whether students become better at self-reflection if they engage continuously in reflection journal writing. To that end, the reflection journals of 690 first-year applied science students at a local polytechnic were studied by means of an automated coding procedures using software. Data was collected twice, once at the beginning and again towards the end of an academic year. Outcomes of the textual content analyses revealed that students reflected on both the process and contents of their learning: critical review of past learning experiences, learning strategies and summaries of what was learned. Correlational analyses showed weak to moderate inter-relationship

The relationships between problem characteristics, achievement-related behaviors, and academic achievement in problem-based learning

This study investigated the influence of five problem characteristics on students' achievement-related classroom behaviors and academic achievement. Data from 5,949 polytechnic students in PBL curricula across 170 courses were analyzed by means of path analysis. The five problem characteristics were: (1) problem clarity, (2) problem familiarity, (3) the extent to which the problem stimulated group discussion, (4) self-study, and (5) identification of learning goals. The results showed that problem clarity led to more group discussion, identification of learning goals, and self-study than problem familiarity. On the other hand, problem familiarity had a stronger and direct impact on academic achievement

Synthesis and characterization of hybrid organic-inorganic materials based on sulphonated polyamideimide and silica

The preparation of hybrid organic–inorganic membrane materials based on a sulphonated polyamideimide resin and silica filler has been studied. The method allows the sol–gel process to proceed in the presence of a high molecular weight polyamideimide, resulting in well dispersed silica nanoparticles (<50 nm) within the polymer matrix with chemical bonding between the organic and inorganic phases. Tetraethoxysilane (TEOS) was used as the silica precursor and the organosilicate networks were bonded to the polymer matrix via a coupling agent aminopropyltriethoxysilane (APTrEOS). The structure and properties of these hybrid materials were characterized via a range of techniques including FTIR, TGA, DSC, SEM and contact angle analysis. It was found that the compatibility between organic and inorganic phases has been greatly enhanced by the incorporation of APTrEOS. The thermal stability and hydrophilic properties of hybrid materials have also been significantly improved

A new estimation of the recent tropospheric molecular hydrogen budget using atmospheric observations and variational inversion

This paper presents an analysis of the recent tropospheric molecular hydrogen (H2) budget with a particular focus on soil uptake and European surface emissions. A variational inversion scheme is combined with observations from the RAMCES and EUROHYDROS atmospheric networks, which include continuous measurements performed between mid-2006 and mid-2009. Net H2 surface flux, then deposition velocity and surface emissions and finally, deposition velocity, biomass burning, anthropogenic and N2 fixation-related emissions were simultaneously inverted in several scenarios. These scenarios have focused on the sensibility of the soil uptake value to different spatio-temporal distributions. The range of variations of these diverse inversion sets generate an estimate of the uncertainty for each term of the H2 budget. The net H2 flux per region (High Northern Hemisphere, Tropics and High Southern Hemisphere) varies between −8 and +8 Tg yr−1. The best inversion in terms of fit to the observations combines updated prior surface emissions and a soil deposition velocity map that is based on bottom-up and top-down estimations. Our estimate of global H2 soil uptake is −59±9 Tg yr−1. Forty per cent of this uptake is located in the High Northern Hemisphere and 55% is located in the Tropics. In terms of surface emissions, seasonality is mainly driven by biomass burning emissions. The inferred European anthropogenic emissions are consistent with independent H2 emissions estimated using a H2/CO mass ratio of 0.034 and CO emissions within the range of their respective uncertainties. Additional constraints, such as isotopic measurements would be needed to infer a more robust partition of H2 sources and sinks

Integrality gaps of integer knapsack problems

We obtain optimal lower and upper bounds for the (additive) integrality gaps of integer knapsack problems. In a randomised setting, we show that the integrality gap of a “typical” knapsack problem is drastically smaller than the integrality gap that occurs in a worst case scenario

Prediction of landing gear loads using machine learning techniques

This article investigates the feasibility of using machine learning algorithms to predict the loads experienced by a landing gear during landing. For this purpose, the results on drop test data and flight test data will be examined. This article will focus on the use of Gaussian process regression for the prediction of loads on the components of a landing gear. For the learning task, comprehensive measurement data from drop tests are available. These include measurements of strains at key locations, such as on the side-stay and torque link, as well as acceleration measurements of the drop carriage and the gear itself, measurements of shock absorber travel, tyre closure, shock absorber pressure and wheel speed. Ground-to-tyre loads are also available through measurements made with a drop test ground reaction platform. The aim is to train the Gaussian process to predict load at a particular location from other available measurements, such as accelerations, or measurements of the shock absorber. If models can be successfully trained, then future load patterns may be predicted using only these measurements. The ultimate aim is to produce an accurate model that can predict the load at a number of locations across the landing gear using measurements that are readily available or may be measured more easily than directly measuring strain on the gear itself (for example, these may be measurements already available on the aircraft, or from a small number of sensors attached to the gear). The drop test data models provide a positive feasibility test which is the basis for moving on to the critical task of prediction on flight test data. For this, a wide range of available flight test measurements are considered for potential model inputs (excluding strain measurements themselves), before attempting to refine the model or use a smaller number of measurements for the prediction