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Optimization algorithms have many general practical applications, such as investigating network flows, managing project timetables, and solving assignment-related problems. The network, node supply and demand, edge capacity and cost, and the minimum feasible transportation cost for a set of commodities across a capacitated network are all illustrated using fuzzy numbers. We can then determine the most cost-effective means of transporting the products. There is a singular emphasis in all of this team's studies. The Robust ranking technique is being applied to the transportation problem by representing fuzzy demand and supply information with trapezoidal fuzzy numbers. When it comes to solving real transportation problems, this approach is clear, simple, and has no learning curve. [ABSTRACT FROM AUTHOR]

Over the past few years, Decentralized Finance (DeFi) has emerged as a transformative force in the financial industry, offering users a range of new and innovative ways to access financial services. Studies show that DeFi is not just a trend or a niche but a paradigm shift in the financial system, which can change traditional finance. Removing intermediaries helps reduce costs, increase accessibility and accessibility, and improve the efficiency of financial services. DeFi technology has the potential to democratize the financial industry by giving individuals more control over their financial assets and transactions, irrespective of location, wealth, or background. However, the complexity, high volatility, technical barriers, and the steep learning curve make it difficult to enter the DeFi space for many users. Existing challenges like Impermanent Loss (IL) deter people willing to invest in the DeFi space. To tackle these issues, this paper introduces the "Algosage Backtesting Engine" - an advanced tool for backtesting investment strategies for Liquidity Providers (LPs). It compares them against the backtesting engines for Automated Market Makers (AMMs) currently in the market. [ABSTRACT FROM AUTHOR]

Teleoperation of mobile manipulators within a home environment can significantly enhance the independence of individuals with severe motor impairments, allowing them to regain the ability to perform self-care and household tasks. There is a critical need for novel teleoperation interfaces to offer effective alternatives for individuals with impairments who may encounter challenges in using existing interfaces due to physical limitations. In this work, we iterate on one such interface, HAT (Head-Worn Assistive Teleoperation), an inertial-based wearable integrated into any head-worn garment. We evaluate HAT through a 7-day in-home study with Henry Evans, a non-speaking individual with quadriplegia who has participated extensively in assistive robotics studies. We additionally evaluate HAT with a proposed shared control method for mobile manipulators termed Driver Assistance and demonstrate how the interface generalizes to other physical devices and contexts. Our results show that HAT is a strong teleoperation interface across key metrics including efficiency, errors, learning curve, and workload. Code and videos are located on our project website. [ABSTRACT FROM AUTHOR]

A learning curve is a powerful tool for companies producing large lots or cutting-edge products, enabling them to negotiate cost savings. New products and services are crucial for the growth of any business, particularly in the technology sector. However, they also come with inherent risks. One of these challenges is the learning curve associated with new offerings. Companies can assess the cost savings of acquiring new skills by applying the learning curve. A common mistake is to price new products solely based on their initial manufacturing costs. However, if businesses utilize the learning curve effectively, it can be a valuable tool for estimating costs, improving productivity, and achieving long-term profitability. Understanding and implementing the learning curve empowers companies to make informed pricing, resource allocation, and project management decisions. It allows them to optimize their processes and identify opportunities for cost reduction and improved performance. The study aims to determine the learning rate for emerging or exceptionally large-scale products where traditional learning curve theory may not readily apply. This research will show how large corporations and defense organizations can effectively use the learning curve to manage extensive projects involving emerging products and services. [ABSTRACT FROM AUTHOR]

Learning is critical for individuals to increase their performance. However, this benefit of learning is not always realized. Previous studies have distinguished different classifications of learning approaches and reached inconsistent results. Therefore, this study further refines the classification of learning approaches in an open innovation community and explore the individual's learning curve from a dynamic perspective. Specifically, we focus on whether and under what conditions learning can increase individual's performance, and how individual's learning curve changes over the tenure. To examine our hypotheses, we collect a dataset includes 48,820 game mods developed by 6,141 creators spanning 7-years from an open game innovation community. The results not only show the significant curve relationship between the four learning approaches and performance, but also demonstrate individual's learning curve evolves over the tenure. This paper provides valuable suggestions and implications for individuals to choose appropriate learning approaches and obtain better performance under different tenures. [ABSTRACT FROM AUTHOR]

Base intuition tells us that if you don't keep practicing a given skill set, it will continue to degrade the longer it goes unused. What does this mean for a skill set that only gets used infrequently? How can one be assured that when they need their skills, that they will be in a state that is reliable? This point becomes even more important when the skills set belongs to a technically skilled worker, within a maintenance facility. Not only does this affect the quality of the work produced, but also the time taken to perform the task. In this study, learning curve theory is applied to the workforce of a military maintenance facility to firstly, identify the changes to job task time that can be expected due to knowledge and skill degradation, and secondly, to determine training intervention types that address the loss of knowledge and/or skill. Through the use of computational experimentation based on Discrete Event Simulation maintenance model output, it was observed that without refresher training intervention, job completion times increased between 14% and 27%. With intervention applied, this increase in completion time can be reduced and maintained at levels as low as 4.14%. [ABSTRACT FROM AUTHOR]

The objective of simple assembly line balancing problem type1 is to minimize the number of workstations organized to perform tasks with precedence constraints. Assembly lines, which require a lot of manual labor, are an example of a manufacturing environment where learning effect influences the operation. In this case, when the minimal number of workstations is determined, the change of task times as a consequence of learning must be considered. This paper investigates the effects of two exponential learning curves on the minimal number of workstations when a simple assembly line balancing problem is solved. A modified simple assembly line balancing model incorporating the learning effect is formulated, and a sample problem to illustrate the application of the model is provided. Some general conclusions related to the type of learning curve function applied and to the change of learning rates are also presented. [ABSTRACT FROM AUTHOR]

Computer laboratories are met with tedious and time-consuming tasks. Significantly, these tasks affect students' learning curves. Therefore, this research aims to solve time-consuming, repetitive methods by developing digital classroom management software; Horace. A software evaluation survey was done. It is for teachers that are teaching non-computer-related subjects. On the software evaluation, the functionality (...=3.15, σ=0.33) of the software gained the highest approval among the participants to be followed by efficacy (...=3.11, σ=0.31), Usability (...=3.08, σ=0.28), and Reliability (...=3.05, σ=0.18). Moreover, all factors gained a descriptive interpretation of Agree. In conclusion, the software is effective and efficient in terms of their teaching in computer laboratories, assisting the teachers and the students in an effective transfer of knowledge towards achieving the desired goal and competencies. [ABSTRACT FROM AUTHOR]

Wireless embedded systems assist us in collecting data from the physical world, through sensor data analysis, such systems allow us to understand our environment. However, deploying wireless embedded systems and analyzing the collected data remains significantly challenging. This is due to the steep learning curve required to implement custom machine-learning models and other algorithms for data analysis. Furthermore, it is also challenging to program individual embedded devices. The diversity of the available platforms and their capabilities further compounds this problem. In response, we introduce an end-to-end system, called the Otter. It facilitates simple sensor data collection using commodity-embedded platforms. Moreover, it employs a large language model to design a natural language interface for the analysis and extraction of useful information from the sensor data. We present our preliminary work on prototyping this system, applying it to a specific use case of hand gesture detection. Otter represents one of the first systems to leverage the enhanced capabilities of large language models for simplifying wireless embedded system deployments. [ABSTRACT FROM AUTHOR]

Testing Technical Debt (TTD) occurs due to shortcuts (non-optimal decisions) taken about testing; it is the test dimension of technical debt. R is a package-based programming ecosystem that provides an easy way to install third-party code, datasets, tests, documentation and examples. This structure makes it especially vulnerable to TTD because errors present in a package can transitively affect all packages and scripts that depend on it. Thus, TTD can effectively become a threat to the validity of all analysis written in R that rely on potentially faulty code. This two-part study provides the first analysis in this area. First, 177 systematically-selected, open-source R packages were mined and analysed to address quality of testing, testing goals, and identify potential TTD sources. Second, a survey addressed how R package developers perceive testing and face its challenges (response rate of 19.4%). Results show that testing in R packages is of low quality; the most common smells are inadequate and obscure unit testing, improper asserts, inexperienced testers and improper test design. Furthermore, skilled R developers still face challenges such as time constraints, emphasis on development rather than testing, poor tool documentation and a steep learning curve. [ABSTRACT FROM AUTHOR]

This article attempts to describe challenges and opportunities for teaching work measurement in developing countries using the Japanese art of origami (paper folding). I initially present background information about the challenges of teaching work measurement to students from developing countries. Next, I suggest that origami-based instruction is related to Problem Based Learning (PBL) and can be used to teach work measurement, or other industrial engineering concepts, without depending on laboratories. Specifically, I present an origami-based project and its implementation by students from a Bolivian university. The basic strategy of the project is for students to put their hands to work to shape origami figures, and thus develop intuitions about work measurement for the calculation of average, normal, and standard times. Moreover, this strategy can also be used to teach students other industrial engineering concepts, such as learning curves, work standards, workplace cleanliness, poka-yokes, etc. As a consequence, origami-based instruction offers new opportunities for the development of practical, cheap, and environmentally friendly learning experiences. Therefore, industrial engineering students will discover the joy of product creation by their own hands, where the possibility of creation from a paper is infinite. [ABSTRACT FROM AUTHOR]

The article presents the results of an experimental construction and quantitative analysis of the learning curve (LC) obtained from individuals learning a foreign language. The experiment was conducted at the Ural Federal University named after the first President of Russia B.N. Yeltsin. Three types of LC were constructed for different level of English skills of the subjects: Pre-Intermediate, Intermediate and Upper-Intermediate. Comparison of these curves demonstrates that the subject’s knowledge acquisition keeps running for 14 hours after the flash memory session. The paper presents two dependencies for constructing an approximation of the learning curve: logarithmic and polynomial. Based on a comparison of the approximation of the experimental LCs with functions of various types, we suggest that they all provide satisfactory results. Based on the results plans for further study of the problem were proposed. [ABSTRACT FROM AUTHOR]

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This article describes the outcome of the studies aimed at development of methods for obtaining the learning curve (LC) for foreign language learning. It also suggests ways for the use of the learning curves. Two types of LC were obtained: short-term and medium-term memorization. Comparative analysis of the two curves suggests that the subject continues learning for up to 14 hours after the completion of a flash memory session since medium-term memorization tests readings are consistently higher than those for the short-term memorization. The paper presents various approximations of the learning curve and the functions that fit best the LC for foreign language learning. Based on a comparison of the results of the approximations of the experimental LC by functions of various types a conclusion has been drawn that all of them provide satisfactory results, with logarithmic and polynomial approximations slightly better than the others. Based on these findings, forecasts for subsequent learning achievements and proposals for further studies are made. [ABSTRACT FROM AUTHOR]

Historically, ASEAN countries are dependent on conventional energy resources due to their abundance, which in turn explains renewable energy's slow progress. With the existing government plans, various reports predict that only 17% renewable energy share can be achieved by 2025. Geothermal, Hydro and Bioenergy being limited to regional availability and with the declining cost of Solar PV, it is important to predict future Levelized Cost of Electricity (LCOE) for Solar PV systems in this region. Hence, unlike earlier research articles this paper focuses on evaluating Levelized Cost of Electricity (LCOE) for PV (equal 1 MW) technology across selected five ASEAN member states, i.e. Indonesia, Malaysia, Thailand, Vietnam and Philippines till 2040 while considering capital cost of sub-system components within a typical PV system, i.e. PV module, Inverter, Mounting Structure and Balance of System (BoS) distinctly to generate unique Learning Curves (LCs) for individual countries. Sensitivity analysis was conducted with regard to discount rate, solar irradiation and CAPEX to identify impact on LCOE values and attainment of grid parity. [ABSTRACT FROM AUTHOR]

The learning curve represents an important area of study within industrial engineering, administration, training and development of the workforce within an organization. The objective of this research is to make a theoretical approach to the topics of the learning curve and the role it plays within industrial engineering, as well as to present the preliminary results of simulated industrial work days in laboratory conditions. The results are exposed through the quantity of products made and the time elapsed during the elaboration of each one. The music factor is included in this research as the main factor whose effect is considered beneficial at the time of performing the activities. The conclusions and recommendations of the study show important possibilities for research within this area and many more. [ABSTRACT FROM AUTHOR]

The learning curve represents an important area of study within industrial engineering, administration, training and development of the workforce within an organization. The objective of this research is to make a theoretical approach to the topics of the learning curve and the role it plays in industrial engineering, as well as to present the preliminary results of simulated industrial work days surrounded by controlled laboratory conditions. The results are exposed through the quantity of products made and the time elapsed in the elaboration of each one. The music factor is not included in the investigation. The conclusions and recommendations of the study show important possibilities for research within this area and many more. [ABSTRACT FROM AUTHOR]

The main objective of this research is to present a solid foundation of capex projections for the major solar energy technologies until the year 2030 for further analyses. The experience curve approach has been chosen for this capex assessment, which requires a good understanding of the projected total global installed capacities of the major solar energy technologies and the respective learning rates. A literature survey has been conducted for CSP tower, CSP trough, PV and Li-ion battery. Based on the literature survey a base case has been defined for all technologies and low growth and high growth cases for further sensitivity analyses. All results are shown in detail in the paper and a comparison to the expectation of a potentially major investor in all of these technologies confirmed the derived capex projections in this paper. [ABSTRACT FROM AUTHOR]

The objective of this study is to investigate the effects of heliostat size on the levelized cost of electricity (LCOE) for power tower plants. These effects are analyzed in a power tower with a net capacity of 100 MWe, 8 hours of thermal energy storage and a solar multiple of 1.8 in Upington, South Africa. A large, medium and a small size heliostat with a total area of 115.56 m2, 43.3 m2 and 15.67 m2 respectively are considered for comparison. A radial-staggered pattern and an external cylindrical receiver are considered for the heliostat field layouts. The optical performance of the optimized heliostat field layouts has been evaluated by the Hermite (analytical) method using SolarPILOT, a tool used for the generation and optimization of the heliostat field layout. The heliostat cost per unit is calculated separately for the three different heliostat sizes and the effects due to size scaling, learning curve benefits and the price index is included. The annual operation and maintenance (O&M) costs are estimated separately for the three heliostat fields, where the number of personnel required in the field is determined by the number of heliostats in the field. The LCOE values are used as a figure of merit to compare the different heliostat sizes. The results, which include the economic and the optical performance along with the annual O&M costs, indicate that lowest LCOE values are achieved by the medium size heliostat with an area of 43.3 m2 for this configuration. This study will help power tower developers determine the optimal heliostat size for power tower plants currently in the development stage. [ABSTRACT FROM AUTHOR]

Long-term memory plays a crucial role in learning mechanisms. We start to build up a probability model of learning (ENKI) ten years ago based on findings of micro genetics published in [1]. We accomplished a number of experiments in our department to testify the validity of the model with success. We described ENKI in detail here, giving the general mathematical formula of the learning curve. This paper pointed out that the model ENKI can detect its own strategy of learning in the brain as well as the simulation of the process of learning that will lead to the development of this method using its own strategy. [ABSTRACT FROM AUTHOR]

Photovoltaics started its success story by predicting the cost degression depending on cumulated installed capacity. This so-called learning curve was published and used for predictions for PV modules first, then predictions of system cost decrease also were developed. This approach is less sensitive to political decisions and changing market situations than predictions on the time axis. Cost degression due to innovation, use of scaling effects, improved project management, standardised procedures including the search for better sites and optimization of project size are learning effects which can only be utilised when projects are developed. Therefore a presentation of CAPEX versus cumulated installed capacity is proposed in order to show the possible future advancement of the technology to politics and market. However from a wide range of publications on cost for CSP it is difficult to derive a learning curve. A logical cost structure for direct and indirect capital expenditure is needed as the basis for further analysis. Using derived reference cost for typical power plant configurations predictions of future cost have been derived. Only on the basis of that cost structure and the learning curve levelised cost of electricity for solar thermal power plants should be calculated for individual projects with different capacity factors in various locations. [ABSTRACT FROM AUTHOR]

E-Book readers are changing the way people read books in many ways. Unlike traditional books, E-Book Reader (Kindle, iBook etc.) can produce very valuable assessment and information of reading habits from the natural reading activity in a natural environment. It is possible to track minutes per page to understand reading behavior for individual readers and to find the most popular pages among books across several readers as well. Words that readers look up while reading a book can be collected and analyzed. We believe that this data can be effectively used for assessment of reading levels as well as the source for possible educational and fun activities. By processing the data, many valuable services could be provided back to readers, parents (teachers), authors, and publishers. This paper introduces the Smart Reader project whose ultimate goal is to develop a reading model to understand various readers' reading comprehension and their learning experience. We attempt to analyze readers' natural reading behavior and study their reading patterns along with developing new tools to aid the readers. [ABSTRACT FROM AUTHOR]

Apparel manufacturing is a labour intensive industry which is characterized by rapid product changes. Each time such changeover of product type occurs, it demands operator learning for the process to reach a steady-state. Higher the number of product type changes, higher the adverse impact of learning on the production performance. Purpose of this paper is to analyse and model this learning process in batch assembly (sewing) lines to improve the accuracy of forecasting, production planning and inventory control. For this purpose, empirical data of daily production efficiency is collected from a large scale apparel manufacturer in Sri Lanka over a period of 8 months. Product types or styles are categorized as "Repeat Styles" or "New Styles" based on whether the operators have prior experience in assembling the product type or not. Modelling of learning curves for above two categories of styles was carried out separately, using nonlinear regression analysis. This analysis indicates that the hyperbolic learning curve models are the best fitted learning curve for both style categories with different parameter estimates. Models were validated for both style categories using a separate set of daily efficiency data from same sewing lines. [ABSTRACT FROM AUTHOR]

Each domain and its underlying communities evolve in time and each period is centered on specific topics that emerge from textual sources that characterize the domain. Our analysis represents an extension of other researches performed on the same corpora that were focusing more on evaluating co-citations between the articles in order to compute their importance score (Grauwin and Jensen [1]). Our approach presents a general perspective of the domain by performing semantic comparisons between article abstracts using natural language processing techniques such as Latent Semantic Analysis, Latent Dirichlet Allocation or semantic distances in lexicalized ontologies, i.e. WordNet. Moreover, graph visual representations are generated using Gephi in order to highlight the keywords of each paper and of the domain, the document similarity view or the table of keyword-abstract overlap score. The purpose of the views is to minimize the learning curve of the domain and to facilitate the research process for someone interested in a particular subject. Also, in order to further argue the benefits of our approach, some potential refinements of the methods for classification that can be performed as future improvements are presented. [ABSTRACT FROM AUTHOR]

When first year students enter a new program that fundamentally differs from their past educational experiences, new types of pressures may impact both students and their families. To identify some of the pressures that should be anticipated when introducing a new program, this exploratory case study focused on the hopes, concerns, and fears of the first cohort of students enrolled in the first semester of a pilot program at the Purdue Polytechnic Institute - a new multidisciplinary, hands-on, competency-based program. Since students do not act in isolation, additional considerations are given to expectations and concerns of their parents, and faculty response to those concerns. Students and parents were surveyed, and in-depth interviews were conducted with both students and faculty. Qualitative and quantitative analyses found that while the majority of students and parents were excited about the hands-on, student-centered approach, concerns were raised about employability, the ability to seamlessly transfer back to traditional programs, and ability to develop the same skills and knowledge as students in traditional technology programs would. The use of badges instead of grades caused further confusion and distress among students, especially during the first few weeks of the program. Program faculty attempted to ameliorate these concerns through transparency and by providing additional structure, with mixed success. Along with the findings, potential implications for similar programs and areas for future research are discussed. [ABSTRACT FROM AUTHOR]

A common challenge in teaching sustainable design is the need to incorporate knowledge and skills from multiple areas of expertise. This paper describes an approach taken to meet this challenge with a collaborative learning experience that combines students from two institutions. Students from CVEEN 6460 Sustainable Urban Water Engineering at the University of Utah were teamed with students from CIVE 6670/8670 Life Cycle Engineering at the University of Toledo in a semester project experience. The design project required the students to complete the design of a rainwater harvesting project, servicing an institutional building, based on technical, economic, environmental, and social performance criteria. The project was setup to include seven deliverables, each of which included a report submission and a team presentation update at both institutions. Each deliverable encouraged collaborative learning since student teams were required to make a presentation at each institution; therefore, teammates had to help teach across institutions to cover the content of the projects not taught in their respective courses. Student performance was assessed based on the quality of each deliverable, instructor reflection, an opinion survey, and a post-course assessment of student learning. The authors conclude the paper with a discussion of the perceived benefits of the CICL approach and provide suggestions for future implementation. [ABSTRACT FROM AUTHOR]

Cellular pathologists are doctors who diagnose disease by using a microscope to examine glass slides containing thin sections of human tissue. These slides can be digitised and viewed on a computer, promising benefits in both efficiency and safety. Despite this, uptake of digital pathology for diagnostic work has been slow, with use largely restricted to second opinions, education, and external quality assessment schemes. To understand the barriers and facilitators to the introduction of digital pathology, we have undertaken an interview study with nine consultant pathologists. Interviewees were able to identify a range of potential benefits of digital pathology, with a particular emphasis on easier access to slides. Amongst the barriers to use, a key concern was lack of familiarity, not only in terms of becoming familiar with the technology but learning how to adjust their diagnostic skills to this new medium. The findings emphasise the need to ensure adequate training and support and the potential benefit of allowing parallel use of glass slides and digital while pathologists are on the learning curve. [ABSTRACT FROM AUTHOR]

Delays often occur in real-world software development projects and may cause significant monetary penalties to software companies. Meanwhile, industry lessons have shown that adding inexperienced employees would cause further delays due to the learning curve and communication overhead. However, if employees with same or similar skills and domain knowledge can be rescheduled from other concurrent projects to help with the delayed projects, it may be possible to reduce or even eliminate delay penalties without requesting extra employees. Here, the big challenge is how to conduct employee rescheduling without having employees working overtime, which is an NP hard problem in nature. To address such a problem, this paper proposes a novel employee rescheduling strategy based on improved ant colony optimization algorithm. Specifically, three generic rules are proposed to improve the effectiveness in generating valid solutions. Preliminary results on benchmark projects show that our strategy can achieve much better effectiveness than its genetic algorithm based counterpart in reducing the overall delay penalty of multiple software projects. [ABSTRACT FROM AUTHOR]

Universities around the world have implemented competitive programming as an approach to teach computer science courses. They have empirically validated this approach as a successful pedagogical tool. However, there are no conclusive results that describe the degree in which competitive programming affects the learning process of the students. In this paper, we report on the learning curves obtained from analyzing ten years of TopCoder algorithm competitions. We discuss on how these learning curves apply to university courses and can help us explain the influence of competitive programming in a class. [ABSTRACT FROM AUTHOR]

The present study aims at defining effectiveness of digital game-based learning (DGBL) in the context of social cognitive theory. More specifically, a user requirements analysis was conducted gauging for anticipated or desired outcomes of DGBL, serving as a benchmark against which to judge effectiveness. Three stakeholder groups were considered: the operational working area (game designers and DGBL researchers), containing business (potential adopters) and wider environment (governmental level). Accordingly, three focus groups were organized (one for each stakeholder group). Our results showed that seven elements of DGBL can be identified: attaining of learning goals (i.e., as defined by the game designer or the client who ordered the game), time management (i.e., saving time for teaching certain content in comparison to other methods), transfer of learning (i.e., application of learned content to real world situations), game experience (i.e., playing the game should be an enjoyable experience), motivation towards the learning content (i.e., increased interest in the subject), motivation towards the instructional tool (i.e., whether or not the learners are motivated to learn the content through the game) and cost effectiveness (i.e., cost of implementing a DGBL intervention with respect to the number of learners that can be reached). The level of importance that is attributed to each of these elements is dependent of the context in which the game is implemented. For instance, cost-effectiveness is found more important in a corporate context than in a school context. In conclusion, this study has shown that effectiveness of DGBL is a multidimensional construct, where not only improved knowledge, skills, attitude or behavior is considered as a decisive factor in the implementation of DGBL. The elements of DGBL effectiveness brought forward by this study can thus guide game designers in the development of DGBL, providing them with stakeholders' requirements about outcomes of effective DGBL. Moreover, these elements can guide researchers conducting DGBL effectiveness studies in their study design, touching upon these outcomes considered relevant for stakeholders which should be considered as factors to assess. [ABSTRACT FROM AUTHOR]

Discussions about the quality of business education and its adaptability to the rapidly changing business environment have brought providers of business education - business schools - more sharply into focus. Business schools are specific organizations which in terms of ownership may be both privately and publicly owned. Notwithstanding the ownership form, a precondition for business schools to cope with the challenges they are facing is constant development and improvement of their organization, which presumes learning capacity from the organization. According to Peter Lorange, organizational learning should be a strategic development component of the BS. Lorange points out that organizational learning can be expected to be a key driver for any leading BS which wants to advance and to respond to the customers. The key of structural changes is in the hands of managers. It is primarily a business school leader's responsibility to ensure that the structures and systems are in place to maximise the opportunity for organizational learning (Willcoxson 2001). The authors of this paper have been dealing with both theoretical and practical problems of measuring organizational learning at business schools as organizations for years. They have developed a special learning rate measurement instrument for business schools - Business School Learning Organization Questionnaire, BSLOQ - (Voolaid, Ehrlich 2011), which has also been used for measuring the learning rate of business schools worldwide (Voolaid, Ehrlich 2012). The current study continues the authors' work in the area of organizational learning of business schools and analyses the organizational learning characteristics related to the management of business schools. The business schools worldwide survey conducted by the authors pointed out that the organisational learning rate of BSs depends on ownership (Voolaid, Ehrlich 2012). The learning rate of private capital based BSs are as a rule higher than that of public BSs. In this paper the authors find out that the learning rate difference in private and state/public BSs depends on the management of a business school. The empirical part of the paper presents a survey of business schools worldwide and the analysis of their management-related organizational learning dimensions, as well as focus group interviews with the employees of private and public business schools in Estonia to specify the learning rate dependence on the business school management, and discuss the importance of individual characteristics of BSLOQ. The authors compare which of the management features of the learning organization conduce to the learning of a business school. The study defines the management features which restrain the organizational learning capacity at public and private business schools, and identifies the management aspects which cause different learning rates in public and private universities. The study also provides suggestions on how to improve the management of business schools in order to make the learning rate increase. [ABSTRACT FROM AUTHOR]

In this paper we analyse two cases where BL courses have been run since the summer 2012 (Teachers' and the radiography educational programmes at University College North in Denmark (UCN). In this study it was clear that the majority of students preferred face-to-face instructions and interaction over the implemented BL approach and they felt more disrupted and disturbed when required to work more online and from home. In the paper we therefore discuss how disruptions and disturbances have an influence on students' study and learning activities in a BL environment. We argue how disturbances are related to students' embodied experiences and habitual and spatial orientation, and how they play a role in students' perceptions of different learning spaces. Based in Simonsen's (2007) 'geography of human practice' and an ecological understanding of 'orientations' developed by Jander (1975) we analyse and discuss how students' orientation in different learning environments influence their navigation, and how disruptions and disturbances affect their orientation. The findings illustrate and discuss students' challenges of adapting to the BL approach and how students' prior experiences and habits challenge their learning activities outside the educational institutions. Based in these findings the concluding discussion presents new perspectives on students' orientation in BL environment to take into consideration in BL programmes. [ABSTRACT FROM AUTHOR]

This paper reports our experience using Microsoft testing tools in both graduate and undergraduate Software Testing courses for four semesters. In particular, we used Microsoft Visual Studio Ultimate 2010 (including Microsoft Test Manager 2010) and Microsoft Team Foundation Server 2010, which together offer an integrated and comprehensive environment for the application lifecycle management, including test planning, authoring, automation, execution, tracking, monitoring and managing. We assessed our experience in using the tools from the student's and the teacher's points of view. Based on students' feedback, we found that students not only consider they learned a lot from the labs (where Microsoft tools were used) but also deem the tools easy to use, relevant to the course (supported the learning of course concepts), and valuable for their professional career. On the other hand, based on the teacher assessment, Microsoft tools provide support for the application of many different concepts studied along the course within an integrated environment, reducing the learning curve for students, while offering the added value of an industrial-level tool. [ABSTRACT FROM AUTHOR]

Lean manufacturing is one of the popular concepts among the manufacturers nowadays in Sri Lanka. One of the main objectives of Lean manufacturing is to reduce different forms of wastes available in manufacturing. Time waste is one of them. Even the organizations with lean background find it difficult to reduce time wastage, since it is difficult to identify. In order to identify time waste, every activity has to be observed sharply and it is turn out to be a costly and time consuming procedure. In this study, it is proposed to visualize the process in real-time with the assistance of virtual lookup. For the sake of practical convenience, real time process visualization of apparel manufacturing plant will be given the priority. This will assist to identify and troubleshoot particular work stations which waste time easily. The main advantage of this is its ability to make the best decision out of the accurate information available. In this application, each and every operation in a module of a garment factory will be tracked and acquire data to a central monitoring system. Then it will be visualized through an interface with the assistance of Yamazumi chart and Learning curve. [ABSTRACT FROM AUTHOR]

Extracurricular university-based Business Plan Competitions [BPCs] assume a popular status in universities globally (Florin et al, 2007; Pittaway et al, 2011; Russell et al, 2008). Such competitions are assumed an entrepreneurial learning tool for those who participate, allowing the development of necessary entrepreneurial competencies (Hegarty, 2006; Russell et al, 2008). This principally attributable to their experiential nature and the opportunities afforded to the participant to engage in entrepreneurial activity within the competition context (McGowan and Cooper, 2008). However we lack appreciation of how learning motivates BPC participation from a participant perspective, notably the particular learning objectives which participants may have before participating and whether these are achieved through their participation. To explore this, the current qualitative paper draws insight from the participants of a regional university based BPC in the North-East of England. Participants were interviewed at the start and end of participation. Such an approach allowed the researcher to depict not only the learning objectives which may have guided their participation, but also capture whether these objectives were achieved through the competition experience. It was found that participants entered the competition perceiving there to be a competency 'gap' between the current statuses of their venture and where they wanted and were expected by others to be. The competition participation experience thus enlisted as a means of lessening this gap and gaining the competencies needed to take themselves and their venture forward. Competitors largely felt they had achieved their learning objectives and also appreciated that the competition had allowed the identification of further gaps in their competency base which would need to be addressed. These findings suggest a need to start dialogues with participants about what their learning objectives are so as to devise a means of supporting attainment of these through the competition. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to examine the relationship between knowledge and overcoming resistance to change in class projects at Firat University in Turkey. Resistance to change among departments is a major issue for individuals at organizations. It may cause stress and frustration at work environments. Even, the change can extend to layoffs which eventually destroy the overall work atmosphere within departments. Employees often set in their ways, and don't want to modify their routine. However, organizations need to change to continue delivering the right products and services on time and effectively due to emerging demands in industry. The major reason behind resistance to change is strongly correlated to knowledge management aspects. The lack of individual's knowledge in another field may fear him or her losing the job if an interchange occurs among departments. Because the employee is assigned to adopt a designated duty, it is unlikely to appoint the individual in another field that he or she is unfamiliar with. Thus, the learning curve for an existing experienced operator is much longer than a new employee. Besides organizations, the assignment changes in classroom project tasks may also create similar atmosphere among students. However, the causes of this hypothesis are firmly depending upon managing motivation and knowledge factors. Therefore, in this research, a matrix chart will be presented that evaluates students' performances at different in class projects at Firat University, which interprets how managing knowledge leverages the issues of resistance to change in order to increase productivity and decrease potential conflicts among students. [ABSTRACT FROM AUTHOR]

The article presents the paper entitled "Learning Analytics & FERPA: Issues of Student Privacy and New Boundaries of Student Data," discussed on the pnel discussion "The Temporal Dimension in the Study of Knowledge Bases: Approaches to Understanding Knowledge Creation and Representation Over Time." The paper discusses the ways Hammond University uses analytic technologies to analyze student data for the purposes of improving the educational experience of the students.

Serious Games are increasingly used as a tool for various applications contrary to the traditional entertainment purpose. Many game engines are available, and Unity3D is another example that presents some features such as rapid prototyping and an easy learning curve. The 3D space where action takes place is sometimes hard to map into a logical memory structure providing flexible access to that information. The problem of tracking players' path as well as their decisions in 3D environments arises when there is no previous knowledge of the scenario representation and the creation of a memory data structure poses an extra effort for the modeller. The proposed solution in this paper, albeit simple, is a straightforward way to track the location of the video game character and map it when he/she passes certain limits. This mechanism proved to represent a key step forward, addressing the important issue of tracking the decision-making process of players for future analysis and behaviour elicitation. [ABSTRACT FROM AUTHOR]

Nowadays as more and more teachers beside face-to-face education take online courses, at least partly in electronic learning environment, the usability of e-learning systems is one of the important questions in education. These e-learning systems accumulate a vast amount of information which is very valuable for analyzing students' behavior. However it is difficult to manage this kind of data manually. The paper describes educational data mining and student modeling as part of this area. We collected real educational data from programming courses in e-learning system Moodle. The objective is to preprocess the collected data and build a model, which will give the course facilitator information about possible course adaptation and learning recommendations based on the students learning behavior. [ABSTRACT FROM AUTHOR]

The fraction of nonconforming control scheme with learning effect consideration is presented. The learning curve (LC) is used to describe and forecast the progress in reducing the fraction of nonconforming (p). The reduction rate of p may be large during the initial stage of the quality improvement program, and influences the construction of p control chart. Based on average run lengths, the simulation is used to compare the shift-detecting performance of the Shewhart-p chart and modified-p chart, with- and without- consideration of LC in the order of production progress. Via simulation, The p charts with consideration of LC are more efficient than that without consideration of LC. The modified-p chart with consideration of LC performs best. [ABSTRACT FROM PUBLISHER]

Using a database of sixty-two different technologies, we study the issue of forecasting technological progress. We do so using the following methodology: pretending to be at a given time in the past, we forecast technology prices for years up to present day. Since our forecasts are in the past, we refer to it as hindcasting and analyze the predictions relative to what happened historically. We use hindcasting to evaluate a variety of different hypotheses for technological improvement. Our results indicate that forecasts using production are better than those using time. This conclusion is robust when analyzing randomly chosen subsets of our technology database. We then turn to investigating the interdependence of revenue and technological progress. We derive analytically an upper bound to the rate of technology improvement given the condition of increasing revenue and show empirically that all technologies fall within our derived bound. Our results suggest the observed advantage of using production models for forecasting is due in part to the direct relationship between production and revenue. [ABSTRACT FROM PUBLISHER]

During the learning process, understanding some specific topics of the subject's programme may present great difficulties. The solution to these problems may be more complex in a virtual environment if you just opt for strictly written feedback. Several actions are proposed in order to respond to this situation in a flexible way and to achieve three main objectives: (1) Defining the appropriate interactive tool to answer the questions proposed, according to the typology and characteristics of the question. (2) Elaborating answers in a more visual format to improve the comprehension by the students. (3) Making of a repository video with the answers based on the questions raised by students. For our purpose we've selected what we considered technology enhancing learning (TEL) tools. These are: video edited with Video Edit Magic (1), commented screencaptures with CamStudio (2) and commented video with screen-flash (3). The pilot test was carried out in various subjects at the Faculty of Economics and Business, of the Universitat Oberta de Catalunya. Specifically, this innovation has been applied to three subjects Statistics Essentials, Behaviour of Economic Aggregates (BEA) and Analysis of Financial Statements (AFS). For each subject we've chosen the tool- that fits better to the learning process and content of every one of them. In all cases, the usefulness of the tools used in the pilot has been positively evaluated by the students. In general, we can conclude that the video feedback versus written feedback improves the development of the students' learning process [ABSTRACT FROM AUTHOR]

Mathematical learning curve models can be used in construction for the prediction of the time cost required to perform a future repetitive activity. The time required to perform a given activity is fall in a repetitive construction work. In this paper we evaluate three mathematical models and four data presentation methods - average methods - of different learning curves for flat roof insulation reconstruction work of a building. Our evaluation is based on a survey done in 2009 spring in Budapest. The surveyed project was a reconstruction work of flat roofing. Several mathematical models are identified and each of these are used to estimate the real performance. The models are compared and evaluated to each other and to the measured data. Based on this study we can declare that if there is noise in the working conditions or a delay in working hours, most probably the best accuracy of estimating work performance using one of the average methods is better than using the unit data. [ABSTRACT FROM AUTHOR]

Learning curve has been known as a method to describe the learning capability of an organization. This paper will investigate the impact of learning to assembly line capacity. A case study has been conducted in one of major car manufacturers in Indonesia. It produces variants of products and implements a mixed model assembly line. The purposes of this research are to identify the learning curve model and investigate its impact to assembly line capacity. This paper applies log-linear model as a reference to construct the learning curve models and calculate their learning rate. It will be used to estimate the actual capacity of assembly line. The study shows that the actual capacity is lower than the designed capacity. [ABSTRACT FROM PUBLISHER]

Geometric variability arising from composite part forming or processing conditions can cause problems during assembly as the 'as manufactured' part forms can differ from the geometry used for any computer aided design (CAD) based, simulated build validation. In this paper finite element (FE) simulation methods are integrated with a digital manufacturing framework to illustrate how the current gap between part design and final assembly simulation can be covered for composite components and assemblies. A simple application example based on L shaped stiffeners, demonstrates the limitations of traditional assembly simulation using nominally sized, as designed CAD geometry to represent composite parts and how this can be overcome by enhancing a digital manufacturing simulation platform by using predicted, more realistic part forms. The main benefit of the method presented is that assembly process planning for composite products can be verified before any real part is manufactured thereby minimising the risk of non conformances as the material system, tooling geometry and processing conditions can be tailored to suit the required design geometry. The advantages of both digital manufacturing and advanced composite materials can be exploited using this approach resulting in a reduction in the learning curve as the application of advanced composite materials increases in future transport applications. [ABSTRACT FROM AUTHOR]

Role-play simulation games enable deep experiential learning but to do so effectively requires systematic congruence between learning objectives and game design that can be very time consuming. This paper discusses how this congruence can be achieved quickly and efficiently using the Fablusi Role-Play Simulation Generator software. [ABSTRACT FROM AUTHOR]