成人学习与教育提升健康与幸福,促进社会和谐发展——专访联合国教科文组织终身学习研究所亚历山德鲁·盖纳博士

世界各国均已认识到,成人学习与教育在促进健康和幸福、劳动力市场、社会包容和共同体生活等方面发挥着重要作用.与此同时,全球公民一致认为教育是一种人权,自身也存在一种价值.成人学习与教育能给个体公民、家庭和共同体带来好处.成人学习与教育帮助公民在公民社会和政治生活中变得更加活跃、多样性包容、更多环境问题意识.它还能促进从艺术到精神层面的文化发展,帮助公民在塑造社会的过程中更加多才多艺和足智多谋.我们有幸对联合国教科文组织终身学习研究所亚历山德鲁·盖纳(Alexandru Gaina)博士进行了专访,分享其对成人学习与教育方面的思考与见解.亚历山德鲁·盖纳博士满腔热情地关注健康、幸福和跨领域问题,特别强调成人学习和教育在这些领域的作用,促成全球、区域和国家层面的利益相关者协同解决全球关注的问题,实现共同目标.目前,盖纳博士是联合国教科文组织终身学习研究所成人学习和教育团队成员,其主要任务之一是组织第六届成人教育国际大会的中期回顾会议(Mid-Term Review of the Sixth International Conference on Adult Learning and Education,CONFINTEA-VI Mid-Term Review).     

The Development of the Motivation for Critical Reasoning in Online Discussions Inventory (MCRODI)

Abstract

This study was conducted to develop an inventory that measures students' motivation to engage in critical reasoning in online discussions. Inventory items were developed based on theoretical frameworks and then tested on 168 participants. Using exploratory factor analysis, test–retest reliability, and internal consistency, twenty-two items were selected for the Motivation for Critical Reasoning in Online Discussions Inventory. Six motivational constructs were supported: Interest and Enjoyment, Normative Goals, Outcome Goals, Implicit Theories, Self-Efficacy Perception, and Finishing Requirements. The inventory can be used by other researchers or online instructors to collect students' motivational data to investigate strategies to promote student motivation in online discussions.     

The Effects of Exercise on Muscle Tension and Subsequent Muscle Relaxation Training

Abstract

This investigation examined the effects of physical exercise on muscle tension and subsequent muscle relaxation training. Twenty college students participated in the first phase of the study, which included a 10-minute EMG baseline, 30 minutes of pedalling on a bicycle ergometer, followed by EMG measurements on the frontalis muscle for up to 3 hours after the end of exercise. The same subjects from Phase I went on to Phase II, which included eight 32-minute EMG biofeedback training (BFT) sessions, utilizing the frontalis muscle. Ten subjects randomly assigned to the experimental group received BFT following an acute exercise bout, while the 10 subjects in the control group received no treatment. The greatest decrease in muscle tension in Phase I occurred 90 minutes after the end of the exercise. This finding was not significantly different from the baseline, indicating that there was no relaxation effect as a result of exercise. In Phase II, significant differences between pre and post-test measurements in both groups indicated that learning of relaxation did occur. However, no significant differences were found between the two groups, indicating that physical exercise did not enhance the learning of EMG BFT.     

The influence of self-efficacy and metacognitive prompting on math problem-solving efficiency

A regression design was used to test the unique and interactive effects of self-efficacy beliefs and metacognitive prompting on solving mental multiplication problems while controlling for mathematical background knowledge and problem complexity. Problem-solving accuracy, response time, and efficiency (i.e. the ratio of problems solved correctly to time) were measured. Students completed a mathematical background inventory and then assessed their self-efficacy for mental multiplication accuracy. Before solving a series of multiplication problems, participants were randomly assigned to either a prompting or control group. We tested the motivational efficiency hypothesis, which predicted that motivational beliefs, such as self-efficacy and attributions to metacognitive strategy use are related to more efficient problem solving. Findings suggested that self-efficacy and metacognitive prompting increased problem-solving performance and efficiency separately through activation of reflection and strategy knowledge. Educational implications and future research are suggested.     

Measuring the perceived quality of an AR-based learning application: a multidimensional model

Augmented reality (AR) technologies could enhance learning in several ways. The quality of an AR-based educational platform is a combination of key features that manifests in usability, usefulness, and enjoyment for the learner. In this paper, we present a multidimensional model to measure the quality of an AR-based application as perceived by students. The model is specified by a second-order factor (perceived quality) and three dimensions: ergonomic quality, learning quality, and hedonic quality. The purpose of this model is to embody previous research into a coherent framework for the evaluation of AR-based educational platforms and to provide guidance for researchers and practitioners. The model was empirically validated on a Chemistry learning scenario and the results confirm the importance of both the learning and hedonic quality.     

Challenges in evaluating the EU’s lifelong learning policies

Since the early 1990s, lifelong learning has become a major policy concern for the European Union, being seen as a means for enabling individuals to be more competitive in social and economic contexts that are continually changing. After a series of white papers and strategies in the field of lifelong learning, the EU launched the Lifelong Learning Programme in 2007, which dealt with the most pressing issues in the field. In light on the complexity of this programme, we need to ask ourselves if traditional evaluation models and approaches are appropriate for evaluating complex educational policies and programmes in the educational field. Thus, the stake of this article is to explore the challenges which arise when evaluating the EU’s lifelong learning policies and programmes in general, and the Lifelong Learning Programme 2007–2013 in particular, as well as to propose several new directions for overcoming these challenges.     

A language modeling framework for expert finding

Statistical language models have been successfully applied to many information retrieval tasks, including expert finding: the process of identifying experts given a particular topic. In this paper, we introduce and detail language modeling approaches that integrate the representation, association and search of experts using various textual data sources into a generative probabilistic framework. This provides a simple, intuitive, and extensible theoretical framework to underpin research into expertise search. To demonstrate the flexibility of the framework, two search strategies to find experts are modeled that incorporate different types of evidence extracted from the data, before being extended to also incorporate co-occurrence information. The models proposed are evaluated in the context of enterprise search systems within an intranet environment, where it is reasonable to assume that the list of experts is known, and that data to be mined is publicly accessible. Our experiments show that excellent performance can be achieved by using these models in such environments, and that this theoretical and empirical work paves the way for future principled extensions.     

Indirect reference intervals for haematological parameters in capillary blood of pre-school children

IntroductionIndirect estimation of reference intervals (RIs) is straightforward and inexpensive procedure for determination of intra-laboratory RIs. We applied the indirect approach to assess RIs for haematological parameters in capillary blood of pre-school children, using results stored in our laboratory database.Materials and methodsWe extracted data from laboratory information system, for the results obtained by automatic haematology analyser in capillary blood of 154 boys and 146 girls during pre-school medical examination. Data distribution was tested, and logarithmic transformation was applied if needed. Reference intervals were calculated by the nonparametric percentile method.ResultsReference intervals were calculated for: RBC count (4.2-5.4 x10¹²/L), haemoglobin (114-146 g/L), MCH (25.0-29.4 pg), MCHC (321-368 g/L), RDW-SD (36.1-43.5 fL), WBC count (4.5-12.3 x10⁹/L), neutrophils count (1.7-6.9 x10⁹/L) and percentage (29.0-69.0%), lymphocytes count (1.6-4.4 x10⁹/L) and percentage (21.9-60.7%), PLT (165-459 x10⁹/L), MPV (8.1-11.4 fL) and PDW (9.2-14.4%). Gender specific RIs were calculated for monocytes count (male (M): 0.2-1.6 x10⁹/L; female (F): 0.1-1.4 x10⁹/L) and percentage (M: 2.5-18.3%; F: 1.8-16.7%), haematocrit (M: 0.34-0.42 L/L; F: 0.34-0.43 L/L), MCV (M: 73.4-84.6 fL; F: 75.5-84.2 fL) and RDW (M: 12.1-14.3%; F: 11.7-13.9%), due to observed gender differences in these parameters (P = 0.031, 0.028, 0.020, 0.012 and 0.001; respectively). Estimated RIs markedly varied from the literature based RIs that are used in the laboratory.ConclusionsIndirect method employed in this study enables straightforward assessment of RIs in pre-school children. Herein derived RIs differed from the literature-based ones, indicating the need for intra-laboratory determination of RIs for specific populations and sample types.     

Blog feed search with a post index

User generated content forms an important domain for mining knowledge. In this paper, we address the task of blog feed search: to find blogs that are principally devoted to a given topic, as opposed to blogs that merely happen to mention the topic in passing. The large number of blogs makes the blogosphere a challenging domain, both in terms of effectiveness and of storage and retrieval efficiency. We examine the effectiveness of an approach to blog feed search that is based on individual posts as indexing units (instead of full blogs). Working in the setting of a probabilistic language modeling approach to information retrieval, we model the blog feed search task by aggregating over a blogger’s posts to collect evidence of relevance to the topic and persistence of interest in the topic. This approach achieves state-of-the-art performance in terms of effectiveness. We then introduce a two-stage model where a pre-selection of candidate blogs is followed by a ranking step. The model integrates aggressive pruning techniques as well as very lean representations of the contents of blog posts, resulting in substantial gains in efficiency while maintaining effectiveness at a very competitive level.