Digital natives,better learners? Students’ beliefs about how the Internet influenced their ability to learn

In the literature students are sometimes assumed to feel empowered with respect to learning because of their familiarity with and access to ICT. However, after interviewing 25 students from post-elementary schools, it was found that the majority of the students, although they use the Internet and other ICT for school purposes, believed that their generation is not as good at learning as the pre-ICT generation. Several students explained the situation in terms of the school’s failure to build on their abilities. Nonetheless, the majority believed that the Internet over-simplifies schoolwork (perceived primarily as the traditional processing of textual sources), which in turn diminishes learning abilities. These results carry important implications regarding school, given that low self-efficacy might make students less likely to apply themselves to learning.     

A survey on deep learning in medicine: Why,how and when?

New technologies are transforming medicine, and this revolution starts with data. Health data, clinical images, genome sequences, data on prescribed therapies and results obtained, data that each of us has helped to create. Although the first uses of artificial intelligence (AI) in medicine date back to the 1980s, it is only with the beginning of the new millennium that there has been an explosion of interest in this sector worldwide. We are therefore witnessing the exponential growth of health-related information with the result that traditional analysis techniques are not suitable for satisfactorily management of this vast amount of data. AI applications (especially Deep Learning), on the other hand, are naturally predisposed to cope with this explosion of data, as they always work better as the amount of training data increases, a phase necessary to build the optimal neural network for a given clinical problem. This paper proposes a comprehensive and in-depth study of Deep Learning methodologies and applications in medicine. An in-depth analysis of the literature is presented; how, where and why Deep Learning models are applied in medicine are discussed and reviewed. Finally, current challenges and future research directions are outlined and analysed.     

An AlphaSmart for each student: Do teaching and learning change with full access to word processors?

Research shows that regular use of computers for writing over an extended period of time can have a positive impact on the quantity and quality of student writing. The lack of large numbers of computers in schools and in classrooms presents a major impediment to providing students with regular access to computers. The introduction of laptops and/or portable writing devices such as AlphaSmarts into classrooms provides opportunities for teachers to increase student access to word processing tools. This article examines how teaching and learning change when three fourth-grade classrooms are equipped with one AlphaSmart for each student. Findings are based on observations conducted before and after full access to AlphaSmarts was provided on, student and teacher interviews, and on students’ depictions of themselves working in the classroom. The general findings include increased use of AlphaSmarts by students for writing in all subject areas, increased student ownership of and fluency with technology, changes in teachers’ policies regarding technology use in the classroom, increased ease in managing the use of technology in the classroom, increased peer-to-peer and teacher-to-student conferencing, and improvements in the quality of student writing.     

The passport control problem or how to keep a dynamic service system load balanced?

In many real life situations (such as department stores, or passport control booths in airports) parallel queues are formed in front of control stations. Typically, some of the stations are manned while others are not. Classical queuing theory considers the configuration constant, and concentrates on the arrival process. This work explores a new line of research—the case in which the configuration is dynamic, and the customers can plan to cope with anticipated changes. Specifically, as the queues build up, management assigns additional officers to the unmanned stations. When this happens—some people move to the newly manned queues from nearby busy queues. In anticipation, people may prefer to line up in busy queues next to unmanned ones.Mathematically we discuss the problem of dynamic arrangement of the queues in a service system where at any time each server can be in either an active or an inactive mode. A balancing strategy determines how customers will be reallocated when a station becomes active. Given a balancing strategy, we seek a partition of customers to queues that minimizes the maximum wait time of a customer in each of the active stations, thereby keeping the system balanced at all times. We study two balancing strategies that we call Split and Trim. For the Split strategy we discuss a special case (the stations are ordered on a line and a single unmanned station is at one end). We show how an optimal partition can be calculated recursively. We then give partitions that approximate the minimal expected wait time within a factor of 1+O(1/N), under each of these strategies, where N is the number of stations. We obtain similar bounds (to within factor 2) for the case, where the number of active servers can be any 1⩽n⩽N−1, and the balancing strategy is Trim.     

To var or not to var: how do C# developers use and misuse implicit and explicit typing?

When implicit typing with the “var” keyword was introduced into C#, it prompted contradictory opinions among developers. This paper starts by explaining the difference between implicit and explicit typing and then provides an overview of developers’ opinions and guidelines that are available online. This paper then reports on the results of a study that investigated how C# developers use and misuse implicit and explicit typing. This study involved analyzing the source code of 10 different open-source software projects including more than 16,500,000 lines of code and more than 930,000 variables. This study investigated to what extent developers use a form of typing that affects the readability of a variable’s type and the length of its declaration. It also investigated whether or not there is an adoption of a consistent set of guidelines in general and across each software project. A tool called “Code Analysis and Refactoring Engine for C#” (Care#) was developed and used to conduct the code analysis for this study.

     

A Necessary Condition about the Optimum Partition on a Finite Set of Samples and Its Application to Clustering Analysis

1IntroductionAsusedforclusteringanalysis,K-meansclusteringalgorithmhasbeenwidelyaPpliedindatacompression,characterextractionofpatternandcommunication-ConsideringthatK-meansclusteringalgorithmisadatacompressionmethodwithloss,wehopetominimizethelossundersomeconstraints,whichmaybringforththeoptimumdesigningofK-partition(orclusteringcenters).ThesequentialhardK-means(SHKM)isanoldclusteringapproach.TheMacQueen'sSHKMl1]algorithmwaspresentedin1967.Ref.[2]proposesamodifiedformtofindtheinitialclu…     

A Necessary Condition about the Optimum Partition on a Finite Set of Samples and Its Application to Clustering Analysis

This paper presents another necessary condition about the optimum partition on a finite set of samples.From this condition,a corresponding generalized sequential hard k-means (GSHKM) clustering algorithm is built and many well-known clustering algorithms are found to be included in it.Under some assumptions the well-known MacQueen;s SHKM (Sequential Hard K-Means) algorithm,FSCL(Frequency Sensitive Competitive Learning) algorithm and RPCL (Rival Penalized Competitive Learning) algorithm are derived.It is shown that FSCL in fact still belongs to the kind of GSHKM clustering algorithm and is more suitable for producing means of K-partition of sample data,which is illustrated by numerical experiment.Meanwhile,some improvements on these algorithms are also given.     

If online learning works for you,what about deaf students? Emerging challenges of online learning for deaf and hearing-impaired students during COVID-19: a literature review

Universal Access in the Information Society - With the coronavirus (COVID-19) outbreak, educational systems worldwide were abruptly affected and hampered, causing nearly total suspension of all...     

‘To play or not to play’: A cross-temporal investigation using hedonic and instrumental perspectives to explain user intentions to explore a technology

The present research extends prior work on the relationship between users and technology by examining users’ intention to explore a technology. Drawing on exploration and individual motivation theories, we developed and tested a model examining the effects of hedonic (i.e., personal innovativeness and cognitive absorption) and instrumental (i.e., performance expectancy and image enhancement) factors on individuals’ intentions to explore a technology over time. Based on a study of 94 users exposed to a new technology, with measurements taken at two points in time, we found that both instrumental and hedonic factors affect individuals’ intentions to explore, but their effects change over time such that as time goes by, the effect of personal innovativeness decreases and performance expectancy increases. In addition to our contributions and implications for research on technology acceptance, we present practical implications both for developers and managers, with a view toward helping the development and deployment of technologies that satisfy the evolution of users’ needs over time.     

A fuzzy random resource-constrained scheduling model with?multiple projects and its application to a working procedure in?a?large-scale water conservancy and hydropower construction project

The aim of this paper is to deal with resource-constrained multiple project scheduling problems (rc-mPSP) under a fuzzy random environment by a hybrid genetic algorithm with fuzzy logic controller (flc-hGA), to a large-scale water conservancy and hydropower construction project in the southwest region of China, whose main project is a dam embankment. The objective functions in this paper are to minimize the total project time (that is the sum of the completion time for all projects) and to minimize the total tardiness penalty of multiple projects, which is the sum of penalty costs for all the projects. After describing the problem of the working procedure in the project and presenting the mathematical formulation model of a resource-constrained project scheduling problem under a fuzzy random environment, we give some definitions and discuss some properties of fuzzy random variables. Then, a method of solving solution sets of fuzzy random multiple objective programming problems is proposed. Because traditional optimization techniques could not cope with the rc-mPSP under a fuzzy random environment effectively, we present a new approach based on the hybrid genetic algorithm (hGA). In order to improve its efficiency, the proposed method hybridized with the fuzzy logic controller (flc) concept for auto-tuning the GA parameters is presented. For the practical problems in this paper, flc-hGA is proved the most effective and most appropriate compared with other approaches. The computer generated results validate the effectiveness of the proposed model and algorithm in solving large-scale practical problems.     

Attitudes to telecare among older people,professional care workers and informal carers: a preventative strategy or crisis management?

This paper reports findings from an attitudinal survey towards telecare that emerged from 22 focus groups comprising 92 older people, 55 professional stakeholders and 39 carers. These were convened in three different regions of England as a precursor to telecare service development. The results from this study suggest that informants’ views were shaped by prior knowledge of conventional health and social care delivery in their locality, and the implication is that expectations and requirements with respect to telecare services in general are likely to be informed by wider perceptions about the extent to which community care should operate as a preventative strategy or as a mechanism for crisis management.

Where Is the Organization Looking in Order to Be Proactive about Safety? A Framework for Revealing whether It Is Mostly Looking Back,Also Looking Forward or Simply Looking Away

Despite the desire to utilize proactive safety metrics, research results indicate imbalances can arise between economic performance metrics and safety metrics. Imbalances can arise, first, because there are fewer proactive metrics available relative to the data an organization can compile to build reactive metrics. Second, there are a number of factors that lead organizations to discount proactive metrics when they conflict with shorter‐term and more definitive reactive metrics. This paper introduces the Q4‐Balance Framework to analyse economy‐safety trade‐offs. Plotting the sets of metrics used by an organization in the four‐quadrant visualization can be used to identify misalignments, overlap and false diversity. It results in a visualization of the set of metrics an organization uses and where these conflict or reinforce each other. The framework also provides a way to assess an organization's safety energy as a kind of analysis of an organization's capability to be proactive about safety.