A support system for mentors of novice entrepreneurs

In this study we present online software to rapidly assess the impact of mentoring techniques on a novice entrepreneur. We have built a prototype that collects data from team members in less than five minutes and that automatically returns a diagnostic analysis to the mentor. Between 2012 and 2015 we have tested three versions of our prototype with longitudinal analyses of teams attending startup weekend competitions, to confirm that our prototype supports mentors with few and yet relevant information. The results of our studies open several avenues of research regarding rapid diagnostic of project teams, whereas, from a practical point of view, our prototype entirely done with Google Docs can be easily used by anyone interested in entrepreneurship education. Keywords: Entrepreneurship education, effectuation, mentoring, decision support, design science.

Scientific writing: a randomized controlled trial comparing standard and on-line instruction.

BACKGROUND: Writing plays a central role in the communication of scientific ideas and is therefore a key aspect in researcher education, ultimately determining the success and long-term sustainability of their careers. Despite the growing popularity of e-learning, we are not aware of any existing study comparing on-line vs. traditional classroom-based methods for teaching scientific writing. METHODS: Forty eight participants from a medical, nursing and physiotherapy background from US and Brazil were randomly assigned to two groups (n = 24 per group): An on-line writing workshop group (on-line group), in which participants used virtual communication, google docs and standard writing templates, and a standard writing guidance training (standard group) where participants received standard instruction without the aid of virtual communication and writing templates. Two outcomes, manuscript quality was assessed using the scores obtained in Six subgroup analysis scale as the primary outcome measure, and satisfaction scores with Likert scale were evaluated. To control for observer variability, inter-observer reliability was assessed using Fleiss's kappa. A post-hoc analysis comparing rates of communication between mentors and participants was performed. Nonparametric tests were used to assess intervention efficacy. RESULTS: Excellent inter-observer reliability among three reviewers was found, with an Intraclass Correlation Coefficient (ICC) agreement = 0.931882 and ICC consistency = 0.932485. On-line group had better overall manuscript quality (p = 0.0017, SSQSavg score 75.3 +/- 14.21, ranging from 37 to 94) compared to the standard group (47.27 +/- 14.64, ranging from 20 to 72). Participant satisfaction was higher in the on-line group (4.3 +/- 0.73) compared to the standard group (3.09 +/- 1.11) (p = 0.001). The standard group also had fewer communication events compared to the on-line group (0.91 +/- 0.81 vs. 2.05 +/- 1.23; p = 0.0219). CONCLUSION: Our protocol for on-line scientific writing instruction is better than standard face-to-face instruction in terms of writing quality and student satisfaction. Future studies should evaluate the protocol efficacy in larger longitudinal cohorts involving participants from different languages.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

Systematic review and metasummary of attitudes toward research in emergency medical conditions

Emergency departments are challenging research settings, where truly informed consent can be difficult to obtain. A deeper understanding of emergency medical patients' opinions about research is needed. We conducted a systematic review and meta-summary of quantitative and qualitative studies on which values, attitudes, or beliefs of emergent medical research participants influence research participation. We included studies of adults that investigated opinions toward emergency medicine research participation. We excluded studies focused on the association between demographics or consent document features and participation and those focused on non-emergency research. In August 2011, we searched the following databases: MEDLINE, EMBASE, Google Scholar, Scirus, PsycINFO, AgeLine and Global Health. Titles, abstracts and then full manuscripts were independently evaluated by two reviewers. Disagreements were resolved by consensus and adjudicated by a third author. Studies were evaluated for bias using standardised scores. We report themes associated with participation or refusal. Our initial search produced over 1800 articles. A total of 44 articles were extracted for full-manuscript analysis, and 14 were retained based on our eligibility criteria. Among factors favouring participation, altruism and personal health benefit had the highest frequency. Mistrust of researchers, feeling like a 'guinea pig' and risk were leading factors favouring refusal. Many studies noted limitations of informed consent processes in emergent conditions. We conclude that highlighting the benefits to the participant and society, mitigating risk and increasing public trust may increase research participation in emergency medical research. New methods for conducting informed consent in such studies are needed.

Component-wise gradient boosting and false discovery control in survival analysis with high-dimensional covariates.

MOTIVATION: Technological advances that allow routine identification of high-dimensional risk factors have led to high demand for statistical techniques that enable full utilization of these rich sources of information for genetics studies. Variable selection for censored outcome data as well as control of false discoveries (i.e. inclusion of irrelevant variables) in the presence of high-dimensional predictors present serious challenges. This article develops a computationally feasible method based on boosting and stability selection. Specifically, we modified the component-wise gradient boosting to improve the computational feasibility and introduced random permutation in stability selection for controlling false discoveries. RESULTS: We have proposed a high-dimensional variable selection method by incorporating stability selection to control false discovery. Comparisons between the proposed method and the commonly used univariate and Lasso approaches for variable selection reveal that the proposed method yields fewer false discoveries. The proposed method is applied to study the associations of 2339 common single-nucleotide polymorphisms (SNPs) with overall survival among cutaneous melanoma (CM) patients. The results have confirmed that BRCA2 pathway SNPs are likely to be associated with overall survival, as reported by previous literature. Moreover, we have identified several new Fanconi anemia (FA) pathway SNPs that are likely to modulate survival of CM patients. AVAILABILITY AND IMPLEMENTATION: The related source code and documents are freely available at https://sites.google.com/site/bestumich/issues. CONTACT: yili@umich.edu.

Muscle Logic: New Knowledge Resource for Anatomy Enables Comprehensive Searches of the Literature on the Feeding Muscles of Mammals.

BACKGROUND: In recent years large bibliographic databases have made much of the published literature of biology available for searches. However, the capabilities of the search engines integrated into these databases for text-based bibliographic searches are limited. To enable searches that deliver the results expected by comparative anatomists, an underlying logical structure known as an ontology is required. DEVELOPMENT AND TESTING OF THE ONTOLOGY: Here we present the Mammalian Feeding Muscle Ontology (MFMO), a multi-species ontology focused on anatomical structures that participate in feeding and other oral/pharyngeal behaviors. A unique feature of the MFMO is that a simple, computable, definition of each muscle, which includes its attachments and innervation, is true across mammals. This construction mirrors the logical foundation of comparative anatomy and permits searches using language familiar to biologists. Further, it provides a template for muscles that will be useful in extending any anatomy ontology. The MFMO is developed to support the Feeding Experiments End-User Database Project (FEED, https://feedexp.org/), a publicly-available, online repository for physiological data collected from in vivo studies of feeding (e.g., mastication, biting, swallowing) in mammals. Currently the MFMO is integrated into FEED and also into two literature-specific implementations of Textpresso, a text-mining system that facilitates powerful searches of a corpus of scientific publications. We evaluate the MFMO by asking questions that test the ability of the ontology to return appropriate answers (competency questions). We compare the results of queries of the MFMO to results from similar searches in PubMed and Google Scholar. RESULTS AND SIGNIFICANCE: Our tests demonstrate that the MFMO is competent to answer queries formed in the common language of comparative anatomy, but PubMed and Google Scholar are not. Overall, our results show that by incorporating anatomical ontologies into searches, an expanded and anatomically comprehensive set of results can be obtained. The broader scientific and publishing communities should consider taking up the challenge of semantically enabled search capabilities.

Una experiencia de trabajo colaborativo en sesiones virtuales y presenciales con estudiantes de grado undécimo para la superación del obstáculo geométrico ligado al concepto de límite de una función

El concepto de límite es importante en la educación media, dado que es relevante para introducir otros conceptos como continuidad, derivada, integral, entre otras; de igual manera, sabemos desde diversos autores y desde nuestra experiencia con el aprendizaje de límites, que su enseñanza ha sido algorítmica y tradicional, por lo tanto, se hace necesario replantear este tratamiento y proponer una forma dinámica, para que el estudiante pueda superar algunos de los obstáculos propuestos por Sierpinska (1987). Para esto, proponemos diseñar actividades que busca tratar y/o superar el obstáculo geométrico referido al concepto de límite, basado en un trabajo colaborativo que tendrá lugar en sesiones virtuales en horarios extraclase, que estarán apoyadas por sesiones presenciales (dentro del aula).

Contenidos transversales y aprendizaje de la matemática: haciendo uso de la tecnología (software libre)

El trabajo trata de mostrar los logros en el aprendizaje de la matemática –área de Geometría– a través del contenido transversal Educación para la gestión de riesgos y la conciencia ambiental, usando recursos tecnológicos como Google Maps y Google Earth. El tema desarrollado para tal fin fue el problema sismológico en el Perú. Finalmente, se señalan temas de geometría involucrados, así como temas anexos a través del uso de contenidos de Estadística, Geografía y Ciencias Naturales. La experiencia se hizo con un grupo de 50 alumnas del Tercer año de Educación Secundaria de una escuela pública del Perú.

Relational dimensions of corporate governance in translation: networked governance in China and India

The effectiveness of corporate governance mechanisms has been a subject of academic research for many decades. Although the large majority of corporate governance studies prior to mid 1990s were based on data from developed market economies such as the U.S., U.K. and Japan, in recent years researchers have begun examining corporate governance in transition economies. A comparison of China and India offers a unique environment for analyzing the effectiveness of corporate governance. First, both countries state-owned enterprise (SOE) reform strategies hinges on the Modern Enterprise System characterized by the separation of ownership and control. Ownership of an SOE’s assets is distributed among the government, institutional investors, managers, employees, and private investors. Effective control rights are assigned to management, which generally has a very small, or even nonexistent ownership stake. This distinctive shareholding structure creates conflict of interest not only between management (insiders) and outside investors but also between large shareholders and minority investors. Moreover, because both governments desire to retain some control—in part through partial retained ownership of commercialized SOEs, further conflicts arise between politicians and firms. Second, directors in publicly listed firms in both countries are predominantly drawn from institutions with significant non-market objectives: the government and other state enterprises, particularly in China, and extended families, particularly in India. As a result, the effectiveness of internal governance mechanisms, such as the number of independent directors on the board and the number of independent supervisors on the supervisory committee, are likely to be quiet limited, although this has yet to be fully evaluated. Third, because of the political nature of the privatization process itself, typical external governance mechanisms, such as debt (in conjunction with appropriate bankruptcy procedures), takeover threats, legal protection of investors, product market competition, etc., have not been effective. Bank loans have traditionally been viewed as grants from the state designed to bail out failing firms. State-owned banks retain monopoly or quasi-monopoly positions in the banking sector and profit is not their overriding objective. If political favor is deemed appropriate, subsidized loans, rescheduling of overdue debt or even outright transfer of funds can be arranged with SOEs (soft budget constraints). In addition, a market for private, non-bank debt is limited in India and has yet to be established China. There is no active merger or takeover activity in Chinese stock markets to discipline management. Information available in the capital markets is insufficient to keep at arm’s length of the corporate decisions. In light of the above peculiarities, China and India share many of the typical institutional characteristics as a transition economy, including poor legal protection of creditors and investors, the absence of an effective takeover market, an underdeveloped capital market, a relative inefficient banking system and significant interference of politicians in firm management. Su (2005) finds that the extent of political interference, managerial entrenchment and institutional control can help explain corporate dividend policies and post-IPO financing choices in this situation. Allen et al. (2005) demonstrate that standard corporate governance mechanisms are weak and ineffective for publicly listed firms while alternative governance mechanisms based on reputation and relationship have been remarkably effective in the private sector. Because the peculiarities are significant in this context, the differences in the political-economies of the two countries are likely to be evident in such relational terms. In this paper we explore the peculiarities of corporate governance in this transitional environment through a systematic examination of certain aspects of these reputational and relationship dimensions. Utilising the methods of social network analysis we identify the inter-organisational relationships at board level formed by equity holdings and by shared directors. Using data drawn from the Orbis database we map these relations among the 3700 largest firms in India and China respectively and identify the roles played in these relational networks by the particularly characteristic institutions in each case. We find greatly different social network structures in each case with some support in these relational dimensions for their distinctive features of governance. Further, the social network metrics allow us to considerably refine proxies for political interference, managerial entrenchment and institutional control used in earlier econometric analysis.

Association for Learning Technology Annual Survey 2014 Data and Report

This is the first report from ALT’s new Annual Survey launched in December 2014. This survey was primarily for ALT members (individual or at an organisation which is an organisational member) it could however also be filled in by others, perhaps those interested in taking out membership. The report and data highlight emerging work areas that are important to the survey respondents. Analysis of the survey responses indicates a number of areas ALT should continue to support and develop. Priorities for the membership are ‘Intelligent use of learning technology’ and ‘Research and practice’, aligned to this is the value placed by respondent’s on by communication via the ALT Newsletter/News, social media and Research in Learning Technology. The survey also reveals ‘Data and Analytics’ and ‘Open Education’ are areas where the majority of respondents are finding are becoming increasingly important. As such our community may benefit from development opportunities ALT can provide. The survey is also a reminder that ALT has an essential role in enabling members to develop research and practice in areas which might be considered as minority interest. For example whilst the majority of respondents didn't indicate areas such as ‘Digital and Open Badges’, and ‘Game Based Learning’ as important there are still members who consider these areas are very significant and becoming increasingly valuable and as such ALT will continue to better support these groups within our community. Whilst ALT has conducted previous surveys of ALT membership this is the first iteration in this form. ALT has committed to surveying the sector on an annual basis, refining the core question set but trying to preserve an opportunity for longitudinal analysis.

D9.2 - RAGE website

This deliverable comprises the general description of the RAGE project public website – referred also as the RAGE website, accessible at http://www.rageproject.eu. The RAGE website main objectives are to raise awareness about the project activities as well as to incentivise engagement from targeted stakeholder communities. It integrates social media networks such as Twitter, Google+ and LinkedIn and has been developed using Wordpress as Content Management System (CMS). The RAGE website is constantly monitored for content management and technical support purposes.

Informal Learning in Online Knowledge Communities: Predicting Community Response to Visitor Inquiries

Nistor, N., Dascalu, M., Stavarache, L.L., Serafin, Y., & Trausan-Matu, S. (2015). Informal Learning in Online Knowledge Communities: Predicting Community Response to Visitor Inquiries. In G. Conole, T. Klobucar, C. Rensing, J. Konert & É. Lavoué (Eds.), 10th European Conf. on Technology Enhanced Learning (pp. 447–452). Toledo, Spain: Springer.

Chapter 2: Predicting Newcomer Integration in Online Knowledge Communities by Automated Dialog Analysis

Nistor, N., Dascalu, M., Stavarache, L.L., Tarnai, C., & Trausan-Matu, S. (2015). Predicting Newcomer Integration in Online Knowledge Communities by Automated Dialog Analysis. In Y. Li, M. Chang, M. Kravcik, E. Popescu, R. Huang, Kinshuk & N.-S. Chen (Eds.), State-of-the-Art and Future Directions of Smart Learning (Vol. Lecture Notes in Educational Technology, pp. 13–17). Berlin, Germany: Springer-Verlag Singapur

Visualization of polyphonic voices inter-animation in CSCL chats

Trausan-Matu, S., & Dascalu, M. (2015). Visualization of Polyphonic Voices Inter-animation in CSCL Chats. Revista Romana de Interactiune Om-Calculator, 8(4), 305–322.

ReaderBench: Automated evaluation of collaboration based on cohesion and dialogism

Dascalu, M., Trausan-Matu, S., McNamara, D.S., & Dessus, P. (2015). ReaderBench – Automated Evaluation of Collaboration based on Cohesion and Dialogism. International Journal of Computer-Supported Collaborative Learning, 10(4), 395–423. doi: 10.1007/s11412-015-9226-y