Boosting learning-by-teaching in virtual tutoring

Research has shown that students tend to engage in quality learning when they are asked to teach (i.e., learning-by-teaching). In this study, a web-based tutoring environment has been developed to enhance the learning of college students by their teaching others: the Virtual Tutee System (VTS). In the VTS, students take the role of tutor and teach a virtual character about what they learn from readings. The design of the VTS has been refined through several iterations of formative evaluation. The current study explored whether the recent improvements made in the VTS augmented the learning-by-teaching effects. The VTS was evaluated with regard to its' effects on students' reading engagement and reading performance. Results indicated that students were behaviorally and cognitively engaged in reading with use of the VTS. Also, the study found a significant improvement in students' emotional engagement in reading after using the VTS. Limited support was found for enhancement of reading performance with repeated use of the VTS. Implications of the study findings are discussed, and suggestions for future research are provided.     

Iterative augmentation of a medical training simulator: Effects of affective metacognitive scaffolding

Experiential training simulators are gaining increasing popularity for job-related training due to their potential to engage and motivate adult learners. They are designed to provide learning experiences that are directly connected to users' work environments and support self-regulated learning. Nevertheless, learners often fail to transfer the knowledge gained in the simulated environment to real-world contexts. The EU-funded ImREAL project aimed to bridge that gap by developing a suite of intelligent services designed to enhance existing training simulators. This paper presents work that was a subset of this research project, reporting the iterative development and evaluation of a scaffolding service, which was integrated into a simulator for training medical students to perform diagnostic interviews. The study comprises three evaluation phases, comparing the pure simulator to a first version with metacognitive scaffolding and then to a final version with affective metacognitive scaffolding and enriched user modelling. The scaffolding service provides the learner with metacognitive prompts; affective elements are realized by an integrated affect reporting tool and affective prompts. Using a mixed-method approach by analysing questionnaires (N = 106) and log-data (N = 426), the effects of the services were investigated with respect to real-world relevance, self-regulated learning support, learning experience, and integration. Despite some limitations, the outcomes of this study demonstrate the usefulness of affective metacognitive scaffolding in the context of experiential training simulators; significant post-simulation increases in perceived relevance of the simulator, reflective note-taking, overall motivation, and feeling of success could be identified. Perceived usability and flow of the simulation increased, whereas overall workload and frustration decreased. However, low response rates to specific functions of the simulation point to a need to further investigate how to raise users' awareness and understanding of the provided tools, to encourage interaction with the services, and to better convey the benefits of using them. Thus, future challenges concern not so much technological developments for personalizing learning experiences, but rather new ways to change user attitudes towards an open approach to learning systems that enables them to benefit from all offered features.     

Blending traditional teaching methods with learning environments: Experience,cyclical evaluation process and impact with MAgAdI

This paper reports the experiment carried out at the University of the Basque Country concerning the integration of the MAgAdI on-line system within traditional teaching/learning methods. MAgAdI is an adaptive web environment devoted to supporting the learning processes in overall contexts, in which several knowledge fields, courses and teachers are involved. So far, a three-year cyclical evaluation-improvement process has been developed on several subjects and participants (n = 80) of a Computer Science degree programme. This process embraced formative and summative evaluation phases with the aim of: discovering the implications of the blended-learning loop on the satisfaction of teachers and motivation of students confirming improvements in student learning; and testing the usability of the Student Workspace. Experimental data were collected by means of a combination of qualitative and quantitative methods. Results of this study detect improvements in the students' acquisition of knowledge in the three phases where it was evaluated (Wilcoxon-test, p = 0.02, p = 0.048, p = 0.044), which may be attributable to the use of MAgAdI. In addition, increments in student's motivation and teacher's satisfaction were also perceived. Thus, these results agree with previous findings of related works.     

Eye movements predict students' computer-based assessment performance of physics concepts in different presentation modalities

Despite decades of studies on the link between eye movements and human cognitive processes, the exact nature of the link between eye movements and computer-based assessment performance still remains unknown. To bridge this gap, the present study investigates whether human eye movement dynamics can predict computer-based assessment performance (accuracy of response) in different presentation modalities (picture vs. text). Eye-tracking system was employed to collect 63 college students' eye movement behaviors while they are engaging in the computer-based physics concept questions presented as either pictures or text. Students' responses were collected immediately after the picture or text presentations in order to determine the accuracy of responses. The results demonstrated that students' eye movement behavior can successfully predict their computer-based assessment performance. Remarkably, the mean fixation duration has the greatest power to predict the likelihood of responding the correct physics concepts successfully, followed by re-reading time in proportion. Additionally, the mean saccade distance has the least and negative power to predict the likelihood of responding the physics concepts correctly in the picture presentation. Interestingly, pictorial presentations appear to convey physics concepts more quickly and efficiently than do textual presentations. This study adds empirical evidence of a prediction model between eye movement behaviors and successful cognitive performance. Moreover, it provides insight into the modality effects on students' computer-based assessment performance through the use of eye movement behavior evidence.     

Unfriend or ignore tweets?: A time series analysis on Japanese Twitter users suffering from information overload

In recent years, with increased opportunities to post content on social media, a number of users are experiencing information overload in relation to social media use. This study addresses how Japanese Twitter users suffering from information overload cope with their stress, focusing on two actions: (1) The “unfriending” activities and (2) The changes in tweet processing methods. Objective data, such as numbers of friends, were collected through Twitter's open Application Programming Interfaces (APIs), and subjective data, such as perceived information overload and tweet processing methods, were collected through a web-based survey as a panel dataset (n = 778). The results demonstrated that although users experience information overload, they continue to increase their number of friends, and that the users who experience information overload modify their usage habits to avoid seeing all received tweets. In short, users do not choose a strategy to reduce the absolute number of received tweets, but only a strategy that involves changing the processing method of the received tweets.     

Impact of Internet gambling on problem gambling among adolescents in Italy: Findings from a large-scale nationally representative survey

AimsThe primary aim of the present study was to understand the impact of online gambling on gambling problems in a large-scale nationally representative sample of Italian youth, and to identify and then further examine a subgroup of online gamblers who reported higher rates of gambling problems.DesignData from the ESPAD^®Italia2013 (European School Survey Project on Alcohol and Other Drugs) Study were used for analyses of adolescent Internet gambling.SettingSelf-administered questionnaires were completed by a representative sample of high school students, aged 15–19 years.ParticipantsA total of 14,778 adolescent students.MeasurementsRespondents’ problem gambling severity; gambling behavior (participation in eight different gambling activities, the number of gambling occasions and the number of online gambling occasions, monthly gambling expenditure); Socio-demographics (e.g., family structure and financial status); and control variables were measured individually (i.e., use of the Internet for leisure activities and playing video games).FindingsRates of problem gambling were five times higher among online gamblers than non-online gamblers. In addition, factors that increased the risk of becoming a problem online gambler included living with non-birth parents, having a higher perception of financial family status, being more involved with gambling, and the medium preferences of remote gamblers (e.g., Internet cafes, digital television, and video game console).ConclusionsThe online gambling environment may pose significantly greater risk to vulnerable players. Family characteristics and contextual elements concerning youth Internet gambling (e.g., remote mediums) may play a key role in explaining problem online gambling among adolescents.     

Measuring the relation between computer use and reading literacy in the presence of endogeneity

This work studies the relation between computer use for reading activities and academic literacy in 15-year-old students in Chile, Uruguay, Spain, and Portugal. Data used is from the PISA 2009 test. Special attention is given to potential bias problems when the computer use is an endogenous variable. Few studies in this area address this issue: existing literature has shown that different types of computer use have different implications on performance. The limitations of observational data have also been emphasized to establish cause–effect relations between computer use and academic performance. It is important, however, to consider the computer use endogeneity hypothesis (above all at home) since students decide on the frequency of computer use at home. The results found show that by controlling for endogeneity, computer use for reading is not related to reading performance neither in digital or printed format, with the exception of Chile that shows a negative relation in the case of reading from a printed format. The results considering endogeneity differ considerably from results when endogeneity is not taken into account. The work shows the relevance of experimental type studies in order to make sound statements with regard to the computer use and academic performance relation. In turn, school reading activities in a digital environment are suggested that could have an impact on reading performance.     

Agro-ecosystem modeling can aid in the optimization of biomass feedstock supply

Recent European Directives promoted the development of biofuels, requesting mandatory limits to their emissions ot greenhouse gases (GHG). Second-generation biofuels based on lignocellulosic biomass are prime candidates but their GHG emissions are variable and uncertain. Agro-ecosystem modeling can capture them and the performance of biofuel feedstocks.This study aimed at optimizing feedstock supply for a bioethanol unit in France, from agricultural residues, annual and perennial crops. Their productivity and environmental impacts were modelled on a regional scale using geo-referenced data on soil properties, crop management, land-use and future weather data. Several supply scenarios were tested. Cereal straw was the most efficient feedstock but had a low availability, and only miscanthus could meet the bioethanol plant's demand. Sorghum combined poor yields and high GHG emissions compared by miscanthus and triticale. A mix of three biomass sources used less than 3% of the regional agricultural land while abating GHG emissions by 60%.     

Storytelling by a kindergarten social assistive robot: A tool for constructive learning in preschool education

Kindergarten Social Assistive Robotics (KindSAR) is a novel technology that offers kindergarten staff an innovative tool for achieving educational aims through social interaction. Children in a preschool setting have previously been shown to benefit from playing educational games with the KindSAR robot. The experiment presented here was designed to examine how KindSAR can be used to engage preschool children in constructive learning. The basic principle of constructivist education is that learning occurs when the learner is actively involved in a process of knowledge construction. In this study, storytelling was used as a paradigm of a constructive educational activity. An interactive robot served as a teacher assistant by telling prerecorded stories to small groups of children while incorporating song and motor activities in the process. Our results show that the children enjoyed interacting with the robot and accepted its authority. This study demonstrates the feasibility and expected benefits of incorporating KindSAR in preschool education.     

Activity theory as a framework for building adaptive e-learning systems: A case to provide empirical evidence

We apply activity theory (AT) to design adaptive e-learning systems (AeLS). AT is a framework to study human’s behavior at learning; whereas, AeLS enhance students’ apprenticeship by the personalization of teaching–learning experiences. AeLS depict users’ traits and predicts learning outcomes. The approach was successfully tested: Experimental group took lectures chosen by the anticipation AT principle; whilst, control group received randomly selected lectures. Learning achieved by experimental group reveals a correlation quite significant and high positive; but, for control group the correlation it is not significant and medium positive. We conclude: AT is a useful framework to design AeLS and provide student-centered education.     

Enablers and barriers to the use of ICT in primary schools in Turkey: A comparative study of 2005–2011

The purpose of this study was to reveal barriers encountered by Turkish primary school teachers in the integration of ICT, to propose potential enablers to overcome those barriers, and to compare the current status of ICT integration (in 2011) with the status of ICT integration in 2005. Part of the data for this comparison was gathered in 2005 as part of a doctoral study by Goktas (2006). A survey design was used to investigate the barriers and enablers. Data were collected from 1373 teachers from 52 schools in 39 provinces. The results indicate that ‘lack of hardware’, ‘lack of appropriate software materials’, ‘limitations of hardware’, ‘lack of in-service training’, and ‘lack of technical support’ were the most important barriers. The highest ranked enablers were ‘allocation of more budget’, ‘allocation of specific units for peer support’, ‘allocation of support offices and personnel for teachers’, and ‘offering higher quality pre-service training for ICT’. Other leading enablers were ‘supporting teachers to enable effective ICT use’, ‘having technology plans’, ‘offering higher quality and more quantity of in-service training’, and ‘designing appropriate course content/instructional programs’. Analysis of an independent t-test revealed that most barriers showed significant differences and most enablers showed moderate or low differences between teachers' perceptions of their situation in 2005 and in 2011.     

Stream flow predictions using nature-inspired Firefly Algorithms and a Multiple Model strategy – Directions of innovation towards next generation practices

Stream flow prediction is studied by Artificial Intelligence (AI) in this paper using Artificial Neural Network (ANN) as a hybrid of Multi-Layer Perceptron (MLP) with the Levenberg–Marquardt (LM) backpropagation learning algorithm (MLP-LM) and (ii) MLP integrated with the Fire-Fly Algorithm (MLP-FFA). Monthly stream flow records used in this prediction problem comprise two stations at Bear River, the U.S.A., for the period of 1961–2012. Six different model structures are investigated for both MLP-LM and MLP-FFA models and their results were analysed using a number of performance measures including Correlation Coefficients (CC) and the Taylor diagram. The results indicate a significant improvement is likely in predicting downstream flows by MLP-FFA over that by MLP-LM, attributed to identifying the global minimum. In addition, an emerging multiple model (ensemble) strategy is employed to treat the outputs of the two MLP-LM and MLP-FFA models as inputs to an ANN model. The results show yet another further possible improvement. These two avenues for improvements identify possible directions towards next generation research activities.     

Posture and lifting exposures for daycare workers

Daycare employees, specifically caregivers, are a distinct population that may experience increased risk of injury due to the high exposure to bent postures, lifting conditions and high stress associated with their work. The objectives of the study were to collect up to date data on daycare workers and to compare the data between groups working with children of different ages (Infant, Toddler and Preschool). The study consisted of two distinct phases: Phase 1 – Questionnaire distribution, Phase 2 – Observation and analysis involving three dimensional postural monitoring and video recording as well as an analysis of the low back forces and moments in lifting. Phase 1: Consisted of the distribution of questionnaires to all employees in each of the participating daycares (n = 73). Of the 73 questionnaires distributed 32 responses were obtained (44%). Of the 32 employees who completed the questionnaires, 19 caregivers volunteered to participate in Phase 2 of the study. An additional 5 caregivers participated in phase 2 of the study, but did not complete any questionnaires. The questionnaires indicated 81% of the workers have experienced low back pain. Phase 2: Observational data were collected on site in five local daycares, throughout the first half of each subject's shift (∼3.5 h). Caregivers from each of the three classroom age groups were recruited for participation in the direct observation (Infant: n = 7, Toddler: n = 7, Preschool: n = 8). Posture analysis revealed that on average, workers adopted trunk flexion angles greater than 55°, for 10% of the collection time, and greater than 70°, for 5% of the collection time. These postures correspond to both moderate and severe flexed postures respectively. The lifting analysis (completed using the data recorded in phase 2) revealed that workers lifted with frequencies of 0.25 lifts/minute, lifted a total weight of 501 kg (over 3.3 h) and experienced average compression and shear forces of 3323 N and 371 N, respectively. A between-group comparison showed that when compared to the Preschool group, the Infant (p = 0.008) and Toddler (p = 0.001) groups demonstrated higher relative flexed postures and lifting frequencies, and the Toddler group (p = 0.023) demonstrated higher total weight lifted. Results suggested that these employees experience an elevated risk of low back injury caused by their occupational tasks and thus, further research is required to determine appropriate worker accommodations and safe work practices to help mediate these risks for all daycare caregivers.Relevance to industryIt is thought that the results from this study could lead to the development of safe working and job sharing guidelines for daycare workers.     

Effects of heel cushioning elements in safety shoes on muscle–physiological parameters

Safety shoe designs are primarily based on safety requirements. But all-day comfort should not be luxury: Heel strike associated impact loads on joints need to be compensated by active muscular effort and safety shoes should support this protective function of muscle activation. In 10 healthy men, 12 trunk and leg muscles were analyzed with surface electromyography. Subjects walked on a walkway while wearing different safety shoes with the test shoes being equipped with exchangeable cushioning heel inserts according to individuals' body weight. While wearing the optimally cushioned shoes the cumulative muscle activity per distance travelled dropped clearly compared to the regular safety shoes, demonstrating reduced muscular effort. Also, the heel strike associated amplitude peak of back muscles occurred earlier within the stride while wearing the test shoes. Thus weight-balanced cushioning heel inserts in safety shoes proved able to reduce muscle strain, logically delaying muscular fatigue and extending muscular joint protection.Relevance to industryAdjustable heel inserts in safety shoes are suited to improve the health status of employees by reducing muscular effort so that active joint protection can be prolonged.     

Use of freely available datasets and machine learning methods in predicting deforestation

The range and quality of freely available geo-referenced datasets is increasing. We evaluate the usefulness of free datasets for deforestation prediction by comparing generalised linear models and generalised linear mixed models (GLMMs) with a variety of machine learning models (Bayesian networks, artificial neural networks and Gaussian processes) across two study regions. Freely available datasets were able to generate plausible risk maps of deforestation using all techniques for study zones in both Mexico and Madagascar. Artificial neural networks outperformed GLMMs in the Madagascan (average AUC 0.83 vs 0.80), but not the Mexican study zone (average AUC 0.81 vs 0.89). In Mexico and Madagascar, Gaussian processes (average AUC 0.89, 0.85) and structured Bayesian networks (average AUC 0.88, 0.82) performed at least as well as GLMMs (average AUC 0.89, 0.80). Bayesian networks produced more stable results across different sampling methods. Gaussian processes performed well (average AUC 0.85) with fewer predictor variables.     

A methodological approach to the design of optimising control strategies for sewer systems

This study focuses on designing an optimisation based control for sewer system in a methodological way and linking it to a regulatory control. Optimisation based design is found to depend on proper choice of a model, formulation of objective function and tuning of optimisation parameters. Accordingly, two novel optimisation configurations are developed, where the optimisation either acts on the actuators or acts on the regulatory control layer. These two optimisation designs are evaluated on a sub-catchment of the sewer system in Copenhagen, and found to perform better than the existing control; a rule based expert system. On the other hand, compared with a regulatory control technique designed earlier in Mollerup et al. (2015), the optimisation showed similar performance with respect to minimising overflow volume. Hence for operation of small sewer systems, regulatory control strategies can offer promising potential and should be considered along more advanced strategies when identifying novel solutions.     

Effect of body-borne equipment on injury of military pilots and aircrew during a simulated helicopter crash

Military helicopter pilots are expected to wear a variety of items of body-borne equipment during flight so as to be prepared for any situation that may arise in combat. Helicopter seats are designed to a specified weight range for an occupant with equipment. This paper investigates how distributing the equipment on the body affects injury potential during a helicopter crash. A finite element model representing a helicopter seat with a fully deformable 50th percentile Hybrid III carrying equipment was developed. The model was subjected to a standard military certification crash test. Various equipment configurations were investigated and analysed to determine its influence on the risk of injury. It was found that placing the equipment low on the torso, i.e. near the thighs, not only reduces the likelihood of injury in the lumbar, spinal region but also provides favourable results in neck and head injury risk when compared to other configurations investigated. In contrast, placing equipment high on the torso, i.e. close to the chin, increases the lumbar load and implicitly, the risk of head injury. A statistical analysis is carried out using the Wilcoxon Signed Rank Test to deliver probability of loads experienced within a certain interval. This study recommends an equipment configuration that improves survivability for an occupant seated on a fixed load energy absorbing seat which is subjected to Military Standard 58095A Test 4.     

Prevalence and personality correlates of Facebook bullying among university undergraduates

The purpose of the present study was to examine the prevalence of cyber-bullying through Facebook in a sample of 226 Greek university undergraduates, and to explore whether big five personality characteristics, narcissism, as well as attitudes toward Facebook, technological knowledge and skills were predictive of such behavior. Participants completed a self-report questionnaire measuring the above constructs. Results indicated that almost one third of the sample reported Facebook bullying engagement at least once during the past month, with male students reporting more frequent involvement than females. Bullying through Facebook was predicted by low Agreeableness and more time spent on Facebook only for males, whereas for females none of the studied variables predicted engagement in Facebook bullying. Findings are discussed in terms of prevention and intervention strategies.     

Electric vehicles charging control in a smart grid: A model predictive control approach

The paper presents an event driven model predictive control (MPC) framework for managing charging operations of electric vehicles (EV) in a smart grid. The objective is to minimize the cost of energy consumption, while respecting EV drivers' preferences, technical bounds on the control action (in compliance with the IEC 61851 standard) and both market and grid constraints (by seeking the tracking of a reference load profile defined by the grid operator). The proposed control approach allows “flexible” EV users to participate in demand side management (DSM) programs, which will play a crucial role in improving stability and efficiency of future smart grids. Further, the natural MPC formulation of the problem can be recast into a mixed integer linear programming problem, suitable for implementation on a calculator. Simulation results are provided and discussed in detail.     

Prototyping virtual reality serious games for building earthquake preparedness: The Auckland City Hospital case study

Enhancing evacuee safety is a key factor in reducing the number of injuries and deaths that result from earthquakes. One way this can be achieved is by training occupants. Virtual Reality (VR) and Serious Games (SGs), represent novel techniques that may overcome the limitations of traditional training approaches. VR and SGs have been examined in the fire emergency context; however, their application to earthquake preparedness has not yet been extensively examined.We provide a theoretical discussion of the advantages and limitations of using VR SGs to investigate how building occupants behave during earthquake evacuations and to train building occupants to cope with such emergencies. We explore key design components for developing a VR SG framework: (a) what features constitute an earthquake event; (b) which building types can be selected and represented within the VR environment; (c) how damage to the building can be determined and represented; (d) how non-player characters (NPC) can be designed; and (e) what level of interaction there can be between NPC and the human participants. We illustrate the above by presenting the Auckland City Hospital, New Zealand as a case study, and propose a possible VR SG training tool to enhance earthquake preparedness in public buildings.