National, inter-institutional, graduate modules – blended learning approaches for PhD education in Ireland

This paper is a case study that describes the design and delivery of national PhD lectures with 40 PhD candidates in Digital Arts and Humanities in Ireland simultaneously to four remote locations, in Trinity College Dublin, in University College Cork, in NUI Maynooth and NUI Galway. Blended learning approaches were utilized to augment traditional teaching practices combining: face-to-face engagement, video-conferencing to multiple sites, social media lecture delivery support – a live blog and micro blogging, shared, open student web presence online. Techniques for creating an effective, active learning environment were discerned via a range of learning options offered to students through student surveys after semester one. Students rejected the traditional lecture format, even through the novel delivery method via video link to a number of national academic institutions was employed. Students also rejected the use of a moderated forum as a means of creating engagement across the various institutions involved. Students preferred a mix of approaches for this online national engagement. The paper discusses successful methods used to promote interactive teaching and learning. These included Peer to peer learning, Workshop style delivery, Social media. The lecture became a national, synchronous workshop. The paper describes how allowing students to have a voice in the virtual classroom they become animated and engaged in an open culture of shared experience and scholarship, create networks beyond their institutions, and across disciplinary boundaries. We offer an analysis of our experiences to assist other educators in their course design, with a particular emphasis on social media engagement.

CEO Humility: Development of an Unobtrusive Measure and Strategic Implications

Over the past 30 years, the Upper Echelons perspective of strategic management has sought to explain a given organization’s strategies and effectiveness as a reflection of the differences in personality, background, and other characteristics of the senior executives that guides each organization. An important stream of research within this field has linked a firm’s strategy to the grandiose way that executives are often thought to view themselves – namely through examining the narcissism, core self-evaluations (CSE), and hubris of Chief Executive Officers (CEOs). In this dissertation, I focus on understanding the strategic impact of CEO humility – a trait that has often been erroneously thought of to represent a poor view of oneself. Consistent with ancient writings and recent research, humility is defined herein as a multi-faceted trait that is the common core of four dimensions: self-awareness, developmental orientation/teachability, appreciation of others' strengths and contributions, and low self-focus. In the first essay, I explore the conceptual relevance and various potential implications of executive humility. Drawing on existing empirical research about the humility construct and general behavioral implications of humility, I argue that executive humility is a critical avenue toward a more rich and nuanced understanding of the delicate interplay and implications of executive self-concept. In essay two, I develop and validate an unobtrusive measure of CEO humility. Ten indicators of humility are suggested and then validated using a self-reported survey administered to a sample of 30 U.S. and Canadian CEOs. Two behaviors were found to be significantly positively related to self-reported humility: CEOs who volunteered some of their time for non-profit organizations and CEO’s who reported that part of their own firm’s success was due to the help of the board of directors. In essay three, I examine the relationship between the level of CEO humility and four firm-level outcomes. Employing a sample of 163 CEOs appointed to S&P 500 firms between 2005-2008, I show that firms led by humble CEOs (measured by the unobtrusive indicators) tend to outperform others in regards to corporate social performance, while at the same time showing that their financial performance is generally no better or worse.

Imputing accelerometer non-wear time when assessing children's moderate-to-vigorous physical activity

BACKGROUND: Moderate-to-vigorous physical activity (MVPA) is an important determinant of children’s physical health, and is commonly measured using accelerometers. A major limitation of accelerometers is non-wear time, which is the time the participant did not wear their device. Given that non-wear time is traditionally discarded from the dataset prior to estimating MVPA, final estimates of MVPA may be biased. Therefore, alternate approaches should be explored. OBJECTIVES: The objectives of this thesis were to 1) develop and describe an imputation approach that uses the socio-demographic, time, health, and behavioural data from participants to replace non-wear time accelerometer data, 2) determine the extent to which imputation of non-wear time data influences estimates of MVPA, and 3) determine if imputation of non-wear time data influences the associations between MVPA, body mass index (BMI), and systolic blood pressure (SBP). METHODS: Seven days of accelerometer data were collected using Actical accelerometers from 332 children aged 10-13. Three methods for handling missing accelerometer data were compared: 1) the “non-imputed” method wherein non-wear time was deleted from the dataset, 2) imputation dataset I, wherein the imputation of MVPA during non-wear time was based upon socio-demographic factors of the participant (e.g., age), health information (e.g., BMI), and time characteristics of the non-wear period (e.g., season), and 3) imputation dataset II wherein the imputation of MVPA was based upon the same variables as imputation dataset I, plus organized sport information. Associations between MVPA and health outcomes in each method were assessed using linear regression. RESULTS: Non-wear time accounted for 7.5% of epochs during waking hours. The average minutes/day of MVPA was 56.8 (95% CI: 54.2, 59.5) in the non-imputed dataset, 58.4 (95% CI: 55.8, 61.0) in imputed dataset I, and 59.0 (95% CI: 56.3, 61.5) in imputed dataset II. Estimates between datasets were not significantly different. The strength of the relationship between MVPA with BMI and SBP were comparable between all three datasets. CONCLUSION: These findings suggest that studies that achieve high accelerometer compliance with unsystematic patterns of missing data can use the traditional approach of deleting non-wear time from the dataset to obtain MVPA measures without substantial bias.

Standardization in the Pre-Columbian Pottery from El Caño, Panama: Specialization, Productivity and Consumption

The pottery found in the burials of El Cano is uniform in style to these made in the coclesanos valleys between 700 and 1000 AD. The coefficient of variability of the different pottery forms, evidence diverse standardizations values for polychrome and non-polychrome ceramics. Moreover, data of funerary contexts from the Cano recently excavated, suggest that elite has controlled ceramic production. This control over the production of certain goods reveals that these were important in the support or proper operational of the chiefdoms in Panama and mark the phase of splendour of this culture.

The role of learning design and learning analytics in MOOCs

The last couple of years there has been a lot of attention for MOOCs. More and more universities start offering MOOCs. Although the open dimension of MOOC indicates that it is open in every aspect, in most cases it is a course with a structure and a timeline within which learning activities are positioned. There is a contradiction there. The open aspect puts MOOCs more in the non-formal professional learning domain, while the course structure takes it into the formal, traditional education domain. Accordingly, there is no consensus yet on solid pedagogical approaches for MOOCs. Something similar can be said for learning analytics, another upcoming concept that is receiving a lot of attention. Given its nature, learning analytics offers a large potential to support learners in particular in MOOCs. Learning analytics should then be applied to assist the learners and teachers in understanding the learning process and could predict learning, provide opportunities for pro-active feedback, but should also results in interventions aimed at improving progress. This paper illustrates pedagogical and learning analytics approaches based on practices developed in formal online and distance teaching university education that have been fine-tuned for MOOCs and have been piloted in the context of the EU-funded MOOC projects ECO (Elearning, Communication, Open-Data: http://ecolearning.eu) and EMMA (European Multiple MOOC Aggregator: http://platform.europeanmoocs.eu).

Capturing and indexing rehearsals: the design and usage of a digital archive of performing arts

Preserving the cultural heritage of the performing arts raises difficult and sensitive issues, as each performance is unique by nature and the juxtaposition between the performers and the audience cannot be easily recorded. In this paper, we report on an experimental research project to preserve another aspect of the performing arts—the history of their rehearsals. We have specifically designed non-intrusive video recording and on-site documentation techniques to make this process transparent to the creative crew, and have developed a complete workflow to publish the recorded video data and their corresponding meta-data online as Open Data using state-of-the-art audio and video processing to maximize non-linear navigation and hypervideo linking. The resulting open archive is made publicly available to researchers and amateurs alike and offers a unique account of the inner workings of the worlds of theater and opera.

Non-Symbolic Fragmentation

This paper reports on the use of non-symbolic fragmentation of data for securing communications. Non-symbolic fragmentation, or NSF, relies on breaking up data into non-symbolic fragments, which are (usually irregularly-sized) chunks whose boundaries do not necessarily coincide with the boundaries of the symbols making up the data. For example, ASCII data is broken up into fragments which may include 8-bit fragments but also include many other sized fragments. Fragments are then separated with a form of path diversity. The secrecy of the transmission relies on the secrecy of one or more of a number of things: the ordering of the fragments, the sizes of the fragments, and the use of path diversity. Once NSF is in place, it can help secure many forms of communication, and is useful for exchanging sensitive information, and for commercial transactions. A sample implementation is described with an evaluation of the technology.

ENGINEERING DIGITAL SHARING PLATFORM TO CREATE SOCIAL CONTAGION: EVIDENCE FROM LARGE SCALE RANDOMIZED FIELD EXPERIMENTS

Peer-to-peer information sharing has fundamentally changed customer decision-making process. Recent developments in information technologies have enabled digital sharing platforms to influence various granular aspects of the information sharing process. Despite the growing importance of digital information sharing, little research has examined the optimal design choices for a platform seeking to maximize returns from information sharing. My dissertation seeks to fill this gap. Specifically, I study novel interventions that can be implemented by the platform at different stages of the information sharing. In collaboration with a leading for-profit platform and a non-profit platform, I conduct three large-scale field experiments to causally identify the impact of these interventions on customers’ sharing behaviors as well as the sharing outcomes. The first essay examines whether and how a firm can enhance social contagion by simply varying the message shared by customers with their friends. Using a large randomized field experiment, I find that i) adding only information about the sender’s purchase status increases the likelihood of recipients’ purchase; ii) adding only information about referral reward increases recipients’ follow-up referrals; and iii) adding information about both the sender’s purchase as well as the referral rewards increases neither the likelihood of purchase nor follow-up referrals. I then discuss the underlying mechanisms. The second essay studies whether and how a firm can design unconditional incentive to engage customers who already reveal willingness to share. I conduct a field experiment to examine the impact of incentive design on sender’s purchase as well as further referral behavior. I find evidence that incentive structure has a significant, but interestingly opposing, impact on both outcomes. The results also provide insights about senders’ motives in sharing. The third essay examines whether and how a non-profit platform can use mobile messaging to leverage recipients’ social ties to encourage blood donation. I design a large field experiment to causally identify the impact of different types of information and incentives on donor’s self-donation and group donation behavior. My results show that non-profits can stimulate group effect and increase blood donation, but only with group reward. Such group reward works by motivating a different donor population. In summary, the findings from the three studies will offer valuable insights for platforms and social enterprises on how to engineer digital platforms to create social contagion. The rich data from randomized experiments and complementary sources (archive and survey) also allows me to test the underlying mechanism at work. In this way, my dissertation provides both managerial implication and theoretical contribution to the phenomenon of peer-to-peer information sharing.

Recomendr-entity recommendation based on ad-hoc dimensions

The growing availability and popularity of opinion rich resources on the online web resources, such as review sites and personal blogs, has made it convenient to find out about the opinions and experiences of layman people. But, simultaneously, this huge eruption of data has made it difficult to reach to a conclusion. In this thesis, I develop a novel recommendation system, Recomendr that can help users digest all the reviews about an entity and compare candidate entities based on ad-hoc dimensions specified by keywords. It expects keyword specified ad-hoc dimensions/features as input from the user and based on those features; it compares the selected range of entities using reviews provided on the related User Generated Contents (UGC) e.g. online reviews. It then rates the textual stream of data using a scoring function and returns the decision based on an aggregate opinion to the user. Evaluation of Recomendr using a data set in the laptop domain shows that it can effectively recommend the best laptop as per user-specified dimensions such as price. Recomendr is a general system that can potentially work for any entities on which online reviews or opinionated text is available.

Crowdfunding for non-commercial initiatives

Organizations and individuals dealing with non-commercial initiatives are in permanent search for funding. Crowdfunding is an alternative way of collecting funds from general public through Internet-based platforms, which is currently gaining popularity all over the world. There are several research initiatives in that field that show the influence of different factors on the success of campaigns, both with commercial and non-commercial objectives. Non-profit nature of the project is named among key predictors of positive outcome. In this context, the purpose of this work is to check whether the tendencies detected by scholars are valid for non-commercial initiatives, especially those having socially aware objectives, posted on the Belarusian crowdfunding platform Ulej. The method used for validation of the research hypotheses is binary logistic regression and statistical test. The results showed that the dependent variable success is influenced by such independent variables as the funding goal, the sum collected, the number of sponsors and the average pledge. On the other hand, the effect of the duration period is not significant. Inferential analysis shows that there is no difference in the level of success between commercial and non-commercial projects and that social orientation does not increase the likelihood of meeting financial goals. The findings are opposite to those provided in literature. However that could be explained by the short period of functioning of platform and the small number of projects.

Capturing and indexing rehearsals: the design and usage of a digital archive of performing arts

Preserving the cultural heritage of the performing arts raises difficult and sensitive issues, as each performance is unique by nature and the juxtaposition between the performers and the audience cannot be easily recorded. In this paper, we report on an experimental research project to preserve another aspect of the performing arts—the history of their rehearsals. We have specifically designed non-intrusive video recording and on-site documentation techniques to make this process transparent to the creative crew, and have developed a complete workflow to publish the recorded video data and their corresponding meta-data online as Open Data using state-of-the-art audio and video processing to maximize non-linear navigation and hypervideo linking. The resulting open archive is made publicly available to researchers and amateurs alike and offers a unique account of the inner workings of the worlds of theater and opera.

Data, Competition, and Consumer Privacy in Digital Markets

In digital markets personal information is pervasively collected by firms. In the first chapter I study data ownership and product customization when there is exclusive access to non rival but excludable data about consumer preferences. I show that an incumbent firm does not have an incentive to sell an exclusively held dataset with a rival firm, but instead it has an incentive to trade a customizing technology with the other firm. In the second chapter I investigate the effects of consumer information on the intensity of competition. In a two dimensional model of product differentiation, firms use information on preferences to practice price discrimination. I contrast a full privacy and a no privacy benchmark with a regime in which firms are able to target consumers only partially. When data is partially informative, firms are always better-off with price discrimination and an exclusive access to user data is not necessarily a competition policy concern. From a consumer protection perspective, the policy recommendation is that the regulator should promote either no privacy or full privacy. In the third chapter I introduce a data broker that observes either only one or both dimensions of consumer information and sells this data to competing firms for price discrimination purposes. When the seller exogenously holds a partially informative dataset, an exclusive allocation arises. Instead, when the dataset held is fully informative, the data broker trades information non exclusively but each competitor acquires consumer data on a different dimension. When data collection is made endogenous, non exclusivity is robust if collection costs are not too high. The competition policy suggestion is that exclusivity should not be banned per se, but it is data differentiation in equilibrium that rises market power in competitive markets. Upstream competition is sufficient to ensure that both firms get access to consumer information.

Generazione automatica di una knowledge base con applicazione ai Sustainable Development Goals

Questa tesi di laurea compie uno studio sull’ utilizzo di tecniche di web crawling, web scraping e Natural Language Processing per costruire automaticamente un dataset di documenti e una knowledge base di coppie verbo-oggetto utilizzabile per la classificazione di testi. Dopo una breve introduzione sulle tecniche utilizzate verrà presentato il metodo di generazione, prima in forma teorica e generalizzabile a qualunque classificazione basata su un insieme di argomenti, e poi in modo specifico attraverso un caso di studio: il software SDG Detector. In particolare quest ultimo riguarda l’applicazione pratica del metodo esposto per costruire una raccolta di informazioni utili alla classificazione di documenti in base alla presenza di uno o più Sustainable Development Goals. La parte relativa alla classificazione è curata dal co-autore di questa applicazione, la presente invece si concentra su un’analisi di correttezza e performance basata sull’espansione del dataset e della derivante base di conoscenza.

Aspectos da educação do corpo no curriculo de pedagogia

Universidade Estadual de Campinas . Faculdade de Educação Física

Fatores de risco e proteção para doenças crônicas não transmissíveis obtidos por inquérito telefônico - VIGITEL Brasil - 2009

OBJETIVO: Descrever os fatores de risco e proteção para doenças crônicas não transmissíveis resultantes do Sistema de Vigilância por Inquérito Telefônico (VIGITEL) em 2009. METODOLOGIA: Prevalências dos principais fatores de risco e proteção foram estimadas na população >18 anos a partir de entrevistas telefônicas em amostras probabilísticas da população coberta por telefonia fixa nas capitais de estados do Brasil e no Distrito Federal, segundo sexo, faixa etária e escolaridade. RESULTADOS: Foram realizadas 54.367 entrevistas. Fumantes e ex-fumantes corresponderam a 15,5e 22% da população adulta brasileira, respectivamente. O excesso de peso atinge 46,6% dos adultos; 33% relataram consumo de carne com gordura e 18,9% afirmaram consumir bebida alcoólica de forma abusiva. Tais fatores de risco são mais prevalentes em homens e em geral nos indivíduos jovens e de menor escolaridade. A prevalência de atividade física no lazer é de 18,8% (IC95% 17,4-20,1) em homens e de 11,3% (IC95% 10,6-12,0) nas mulheres. A inatividade física atinge 15,6% da população e aumenta com a idade. O consumo de frutas, legumes e verduras e a atividade física no lazer são mais frequentes em homens e mulheres com mais anos de estudo. Diagnóstico de hipertensão arterial foi referido por 21,1% (IC95% 19,6-22,5) dos homens e 27,2% (IC95% 25,8-28,5) das mulheres. A prevalência de diabetes foi de 5,8%. CONCLUSÃO: Os resultados apontaram comportamentos em saúde distintos de acordo com o sexo, idade e escolaridade da população e reforçam a tendência de queda do tabagismo e aumento no excesso de peso no Brasil.