Using the Inquiry-based Learning Approach to Enhance Student Innovativeness: A Conceptual Model

Individual innovativeness has become one of the most important employability skills for university graduates. In this paper, we focus on how students could be better prepared to be innovative in the workplace, and we argue that inquiry-based learning (IBL) – a pedagogical approach in which students follow the inquiry-based processes used by scientists to construct knowledge – can be effective for this purpose. Drawing on research which examines the social and cognitive micro-foundations of innovative behaviour, we develop a conceptual model that links IBL and student innovativeness, and introduce three teacher-controlled design elements that can influence the strength of this relationship, namely whether an inquiry is open or closed, discovery-focused or information focused and individual or teambased. We argue that an open, discovery-focused and team-based inquiry offers the greatest potential for enhancing students’ skills in innovation. This paper has several implications for higher education research and practice

Determination of plasticity following deformation and welding of austenitic stainless steel

Intergranular strain has been associated with high-temperature cracking of welded pipework in 316H austenitic stainless steel material used in nuclear power plant heat exchangers. In this study, neutron diffraction has been used to study the development of intergranular strains in plastically-deformed and welded 316H stainless steel. Measurements have been made of the intergranular strain evolution with increasing plastic strain in base material, and correlated with further measurements made in samples extracted from welded pipes, where the pipes were welded following plastic deformation to different levels of plastic strain. Strong tensile strain evolution was seen on the compliant 200 grain family. The results were correlated with various proxy measures of plastic strain, including hardness and diffraction peak width, and excellent agreement was obtained

A New Model for Crowdsourcing Innovation

On paper, crowdsourced innovation makes a lot of sense: If two heads are better than one, why not 20,000? Surely, some of those outsiders will have fresh solutions to your problem. But in practice, such programs have often not worked out as well as hoped. More often than not, even the best crowdsourced ideas disappear in a Bermuda Triangle of logistical difficulties, internal politics, and professional insecurity. The International Committee of the Red Cross has developed a new collaborative approach to crowdsourcing ideas that limits the competition to teams. It designed its Enable Makeathon project not only to generate good ideas of products to help people with disabilities but also to make sure those ideas reach the market

Predicted Adoption Rates of Contact Tracing App Configurations - Insights from a choice-based conjoint study with a representative sample of the UK population

Widespread adoption of a contact tracing app by the UK public is an important part of safely easing or lifting the lockdown. In this context, it is essential to understand how adoption rates are influenced by different configurations of a proposed contact tracing app. There are many implementation options that can impact app adoption. For example, which institution should be responsible for and have oversight of the app? What type of data is collected? Does it matter how long it is stored? This whitepaper provides data-driven insights into these and other questions to guide app implementation choices

Customer empowerment in the digital age

The Internet and advances in digital technologies fundamentally are transforming marketing. Armed with an abundance of information and opportunities, consumers no longer accept the role of passive recipients of marketing communication. This is turning traditional communication approaches upside down and forcing brands to interact with individual customers quickly, openly, and continuously. In the digital age, customer engagement is more important than ever. The Marketing Science Institute, for example, has identified understanding how marketing activities create engagement as one of its top research priorities for 2014–2016. More and more brands are using social-media platforms to connect with their customers by creating engaging content so that consumers can interact (e.g., sharing an interesting and current Tweet) and/or by initiating dialog with them (e.g., responding to a customer comment or complaint). These steps undoubtedly are very important in connecting with customers, but they are not sufficient. Most visionary brands not only interact with customers but also empower them. Consider Lego, which enables its customers to create and vote for new product designs on a “Lego Ideas” platform. The designs that receive considerable votes from other customers (i.e., 10,000 “supports”) are then reviewed formally. Those that pass the review are transformed into products to be sold all over the world. The initiative of Lego not only involves the emotional, cognitive, and behavioral engagement of customers—characteristics of a successful customer engagement initiative—but also shifts the power and control of the company's product development to its customers

Effect of industrial wastewater ontotal protein and the peroxidase activity in plants

The aim of this study is to investigate the effects of industrial wastewaters on protein and the peroxidase activity in Lycopersicon esculentum Mill., Capsicum annuum L., Phaseolus vulgaris L. and Vicia faba L. Industrial wastewaters were taken from Dardanel Fisheries Company, Tekel alcoholicdrinks companies’ wastewater treatment plants and from one station which is located in the middle of the Sarýçay River. Wastewaters were applied to 6 weeks old plants with directly irrigation water. Physiological changes in the plants were observed by the means of measuring the protein and enzyme activity. The largest increase in protein was observed as 190.9 and 136.3% in V. faba treated with Sarýçay River water and Tekel wastewater, respectively. In P. vulgaris which was treated with Dardanelwastewater, the total protein amount increased by 84% compared to control plants. After the wastewater treatment, the peroxidase activity decreased in all plants. The largest peroxidase decrease was 80% in L. esculentum treated with Tekel wastewater. In P. vulgaris, peroxidase decreased by 59 and 51% when treated with Dardanel wastewater and Sarýçay River water, respectively. It was concluded that the increase in total protein amount and the decrease in peroxidase activity demonstrated theindustrial wastewater’s blocking effects on plants defense systems

Individual differences as antecedents of leader behavior: Towards an understanding of multi-level outcomes

The leadership research on individual differences is going through a period of revival. However, due to the substantial number of variables in this area and the different knowledge bases they are associated with (e.g., psychology, endocrinology, genetics), the literature is also becoming highly fragmented as it grows. This fragmentation is preventing different literature streams from effectively communicating with each other and synthesizing the rapidly expanding body of knowledge. Consequently, the continued growth of the individual differences literature is at risk. Therefore, we believe that classifying the relevant literature streams and reviewing the key variables in those streams will be beneficial. We do so by organizing this review and research agenda of the leadership literature on individual differences around the recent model developed by Antonakis, Day, and Schyns (2012). In doing so, we hope to unify some of the future research efforts around a recent and recognized conceptual model, and in turn facilitate communication between these different streams of literature. Moreover, insights from this literature also allow us to propose additions and refinements to the model of Antonakis, Day, and Schyns (2012) that may help scholars by indicating other fruitful areas for future research on individual differences

Investigations of spinodal dynamics in asymmetric nuclear matter within a stochastic relativistic model

Cataloged from PDF version of article.Early development of spinodal instabilities and density correlation functions in asymmetric nuclear matter are investigated in the stochastic extension of the Walecka-type relativistic mean field including coupling with rho meson. Calculations are performed under typical conditions encountered in heavy-ion collisions and in the crusts of neutron stars. In general, growth of instabilities occur relatively slower for increasing charge asymmetry of matter. At higher densities around rho = 0.4 rho(0) fluctuations grow relatively faster in the quantal description than those found in the semi-classical limit. Typical sizes of early condensation regions extracted from density correlation functions are consistent with those found from dispersion relations of the unstable collective modes

Regressor-based adaptive infinite impulse response filtering

Superior performance of fast recursive least squares (RLS) algorithms over the descent-type least mean square (LMS) algorithms in the adaptation of FIR systems has not been realized in the adaptation of IIR systems. This is the result of having noisy observations of the original system output resulting in significantly biased estimates of the system parameters when this noisy signal is used in the adaptive system. Here, we propose an adaptive IIR system structure consisting of two parts: a two-channel FIR adaptive filter whose parameters are updated by the rotation-based multichannel least squares lattice (QR-MLSL) algorithm, and an adaptive régresser that provides more reliable estimates to the original system output based on previous values of the adaptive system output and noisy observation of the original system output. Two different regressors are investigated, and robust ways of adaptation of the régresser parameters are proposed. The performances of the proposed algorithms are compared with composite régresser (CR) and bias remedy least mean square equation error (BRLE) algorithms that are LMS-type successful adaptation algorithms, and it is found that in addition to the expected convergence speedup, the proposed algorithms provide better estimates to the system parameters at low SNR value. In addition, the extended Kaiman filtering approach is tailored to our application. Comparison of the proposed regressor-based algorithms with the extended Kaiman filter approach revealed that the proposed approaches provide improved estimates in systems with abrupt parameter changes. ©1993 IEEE