Movement planning reflects skill level and age changes in toddlers

Kinematic measures of children's reaching were found to reflect stable differences in skill level for planning for future actions. Thirty-five toddlers (18-21 months) were engaged in building block towers (precise task) and in placing blocks into an open container (imprecise task). Sixteen children were retested on the same tasks a year later. Longer deceleration as the hand approached the block for pickup was found in the tower task compared with the imprecise task, indicating planning for the second movement. More skillful toddlers who could build high towers had a longer deceleration phase when placing blocks on the tower than toddlers who built low towers. Kinematic differences between the groups remained a year later when all children could build high towers.     

Mixed-methods exploration of students' motivation in using augmented reality in neuroanatomy education with prosected specimens

The use of augmented reality (AR) in teaching and studying neuroanatomy has been well researched. Previous research showed that AR-based learning of neuroanatomy has both alleviated cognitive load and was attractive to young learners. However, how the attractiveness of AR effects student motivation has not been discovered. Therefore, the motivational effects of AR were investigated in this research by the use of quantitative and qualitative methods. Motivation elicited by the GreyMapp-AR, an AR application, was investigated in medical and biomedical sciences students (n = 222; mean age: 19.7 ± 1.4 years) using the instructional measure of motivation survey (IMMS). Additional components (i.e., attention, relevance, confidence, and satisfaction) were also evaluated with motivation as measured by IMMS. Additionally, 19 students underwent audio-recorded individual interviews which were transcribed for qualitative analysis. Males regarded the relevance of AR significantly higher than females (P < 0.024). Appreciation of the GreyMapp-AR program was found to be significantly higher in students studying biomedical sciences as compared to students studying medicine (P < 0.011). Other components and scores did not show significant differences between student groups. Students expressed that AR was beneficial in increasing their motivation to study subcortical structures, and that AR could be helpful and motivating for preparing an anatomy examination. This study suggests that students are motivated to study neuroanatomy by the use of AR, although the components that make up their individual motivation can differ significantly between groups of students.     

Teacher Professional Growth on Assessment Literacy: A Case Study of Prevocational Geography Education in the Netherlands

Abstract

Teachers should have the necessary assessment knowledge and skills to contribute to students’ learning. This study provides insight into how a professional development program for teachers contributed to the achievement of higher mastery levels of assessment literacy. This study used Xu and Brown's TALiP (Teacher Assessment Literacy in Practice) framework to achieve these higher levels. To evaluate the extent to which teachers demonstrated professional growth regarding their assessment literacy, teachers’ practices were evaluated through a content analysis of summative assessments. Potential changes in teachers’ knowledge, skills, and beliefs were measured through questionnaires and interviews. The outcomes showed that reflection on educational goals and on teachers’ beliefs, collaborative practice, and peer feedback played an important role in fostering higher mastery levels in assessment literacy. The outcomes of this study support the value of the TALiP framework and support the idea that professional growth could be fostered via diverse growth pathways.     

Practical Application of a Synthetic Linking Function on Small-Sample Equating

The synthetic function is a weighted average of the identity (the linking function for forms that are known to be completely parallel) and a traditional equating method. The purpose of the present study was to investigate the benefits of the synthetic function on small-sample equating using various real data sets gathered from different administrations of tests from a licensure testing program. We investigated the chained linear, Tucker, Levine, and mean equating methods, along with the identity and the synthetic functions with small samples (N = 19 to 70). The synthetic function did not perform as well as did other linear equating methods because test forms differed markedly in difficulty; thus, the use of the identity function produced substantial bias. The effectiveness of the synthetic function depended on the forms' similarity in difficulty.     

Systematic reduction of leg muscle activity throughout a standard assessment of running footwear

Purpose:This study aimed to investigate whether there is a systematic change of leg muscle activity,as quantified by surface electromyography(EMG),throughout a standard running footwear assessment protocol at a predetermined running speed.Methods:Thirty-one physically active adults(15 females and 16 males) completed 5 testing rounds consisting of overground running trials at a speed of 3.5 m/s.The level of muscle activity from 6 major leg muscles was recorded using surface EMG.The variables asse...     

A dynamic analytic approach to national innovation systems: The IC industry in Taiwan

The paper attempts to develop a mathematical model of the national innovation system (NIS) of Taiwan, particularly with regard to its integrated circuit (IC) industry. The method utilised is that of system dynamics (SD). Drawing on both questionnaire/in-depth interviews and computer simulation, the paper aims to increase insights into the dynamic processes of the Taiwanese IC industry system of innovation and understand the interdependence and interaction among capital flows, human resource flows, knowledge and technology flows, and product flows in the NIS. The paper concludes with some simulations of policy alternatives confronting the IC industry and the Taiwanese government.     

Combined Approach to Multi-Informant Data Using Latent Factors and Latent Classes: Trifactor Mixture Model

Although collecting data from multiple informants is highly recommended, methods to model the congruence and incongruence between informants are limited. Bauer and colleagues suggested the trifactor model that decomposes the variances into common factor, informant perspective factors, and item-specific factors. This study extends their work to the trifactor mixture model that combines the trifactor model and the mixture model. This combined approach allows researchers to investigate the common and unique perspectives of multiple informants on targets using latent factors and simultaneously take into account potential heterogeneity of targets using latent classes. We demonstrate this model using student self-rated and teacher-rated academic behaviors (N = 24,094). Model specification and testing procedures are explicated in detail. Methodological and practical issues in conducting the trifactor mixture analysis are discussed.     

Detection and correction of incomplete duplicate 24-hour urine collections – theory and practical evidence

IntroductionThe intraindividual variability in urinary creatinine excretion is notoriously large. The aims of this study were to investigate the variability of duplicate consecutive 24-hour urinary creatinine excretions in patients and to develop a model for the detection and correction of discrepant creatinine excretions.Materials and methodsA group of 270 patients (82 men and 188 women) were included in the study. We collected the following data: urinary 24-hour volumes (volumetric/gravimetric) and urinary creatinine concentrations (Jaffé/enzymatic) on both collection days. We performed specific calculations to detect discrepant creatinine excretions.ResultsIn 60 patients (22%) discrepant collections were found. Among the remaining 78%, 22% of the patients collected very accurately (almost identical urinary creatinine excretions). In this subgroup the volume ratios and the creatinine concentration ratios behave inversely as in a dilution curve. A theoretical model and six collection scenarios were developed to detect, interpret and correct discrepant collections. Practical examples are given to illustrate the use of the model in successful correction of creatinine and other analytes for under- or overcollection.ConclusionsWe conclude that missed or overcollected urine volumes are the largest source of variation in creatinine excretion. Discrepancies in consecutive duplicate 24-hour creatinine excretions can be detected and corrected with specific calculations by means of the presented model. The effectiveness of these corrections is demonstrated with examples from daily practice. These calculations can be easily automated.     

Measuring Pupils’ Attitudes Towards Socioscientific Issues

Science & Education - This paper presents the results of a large-scale study to validate a questionnaire that measures pupils’ attitudes towards socioscientific issues (the PASSI...