Valuable assets : a general formal investigation into the role and status of classroom assistants in Scotland's primary school

Based on the earlier pilot research conducted by SCER, the EOC instigated a General Formal Investigation (GFI) of the role and status of classroom assistants in Scotland's primary schools. As part of the GFI, SCER was commissioned to conduct a national survey of classroom assistants, teachers and head teachers. Primary data was generated from a Scotland-wide, large scale survey sent to over 1000 primary schools. Interviews were also conducted with Directors of Education and the Scottish Executive Education Department

An evaluation of identity in online social networking: distinguishing fact from fiction

Online social networks are understood to replicate the real life connections between people. As the technology matures, more people are joining social networking communities such as MySpace (www.myspace.com) and Facebook (www.facebook.com). These online communities provide the opportunity for individuals to present themselves and maintain social interactions through their profiles. Such traces in profiles can be used as evidence in deciding the level of trust with which to imbue individuals in making access control decisions. However, online profiles have serious implications over the reality of identity disclosure. There are many reasons why someone may choose not to reveal their true self, which sometimes leads to misidentification or deception. On one hand, the structure of online profiles allows anonymity, which gives users the opportunity to create a persona that may not represent their true identity. On the other hand, we often play multiple identities in different contexts where such behaviour is acceptable. However, realizing the context for each identity representation depends on the individual. As a result, some represented identities will be essentially real, if edited for public view, some will be disguised, and others will be fictitious or humorous. The millions of social network profiles, and billions of connections between them, make it difficult to formalize an automated approach to differentiate fact from fiction in online self-described identities. How can we be sure with whom we are interacting, and whether these individuals or groups are being truthful with the online identities they present to the rest of the community? What tools and techniques can be used to gather, organize, and explore the available data for informing the level of honesty that should be entrusted to an individual? Can we verify the validity of the identity automatically, based on the available information online? We aim to evaluate identity representation online and examine how identity can be verified in a less trusted online community. We propose a personality classifier model to identify a user‟s personality (such as expressive, valid, active, positive, popular, sociable and traceable) using traces of 2.2 million profile features collected from MySpace. We use data mining techniques and social network analysis to extract significant patterns in the data and network structure, and improve the classifier during the cycle of development. We evaluate our classifier model on profiles with known identities such as „real‟ and „fake‟. Our results indicate that by utilizing people‟s online, self-reported information, personality, and their network of friends and interactions, we are able to provide evidence for validating the type of identity in a manner that is both accurate and scalable

Reading the Source Code of Social Ties

Though online social network research has exploded during the past years, not much thought has been given to the exploration of the nature of social links. Online interactions have been interpreted as indicative of one social process or another (e.g., status exchange or trust), often with little systematic justification regarding the relation between observed data and theoretical concept. Our research aims to breach this gap in computational social science by proposing an unsupervised, parameter-free method to discover, with high accuracy, the fundamental domains of interaction occurring in social networks. By applying this method on two online datasets different by scope and type of interaction (aNobii and Flickr) we observe the spontaneous emergence of three domains of interaction representing the exchange of status, knowledge and social support. By finding significant relations between the domains of interaction and classic social network analysis issues (e.g., tie strength, dyadic interaction over time) we show how the network of interactions induced by the extracted domains can be used as a starting point for more nuanced analysis of online social data that may one day incorporate the normative grammar of social interaction. Our methods finds applications in online social media services ranging from recommendation to visual link summarization.Comment: 10 pages, 8 figures, Proceedings of the 2014 ACM conference on Web (WebSci'14

A model to improve the Evaluation and Selection of Public Contest´s Candidates (Police Officers) based on AI technologies

Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business AnalyticsThe number of candidates applying to Public Contests is increasing compared to the number of Human Resources employees required for selecting them for Police Forces. This work intends to perceive how those Public Institutions can evaluate and select their candidates efficiently during the different phases of the recruitment process, and for achieving this purpose AI approaches will be studied. This paper presents two research questions and introduces a corresponding systematic literature review, focusing on AI technologies, so the reader is able to understand which are most used and more appropriate to be applied to Police Forces as a complementary recruitment strategy of the National Criminal Investigation Police agency of Portugal – Polícia Judiciária. Design Science Research (DSR) was the methodological approach chosen. The suggestion of a theoretical framework is the main contribution of this study in pair with the segmentation of the candidates (future Criminal Inspectors). It also helped to comprehend the most important facts facing Public Institutions regarding the usage of AI technologies, to make decisions about evaluating and selecting candidates. Following the PRISMA methodology guidelines, a systematic literature review and meta-analyses method was adopted to identify how can the usage and exploitation of transparent AI have a positive impact on the recruitment process of a Public Institution, resulting in an analysis of 34 papers published between 2017 and 2021. The AI-based theoretical framework, applicable within the analysis of literature papers, solves the problem of how the Institutions can gain insights about their candidates while profiling them; how to obtain more accurate information from the interview phase; and how to reach a more rigorous assessment of their emotional intelligence providing a better alignment of moral values. This way, this work aims to advise the improvement of the decision making to be taken by a recruiter of a Police Force Institution, turning it into a more automated and evidence-based decision when it comes to recruiting the adequate candidate for the place

Spotting The Elusive Prospect Customer: Exploratory Study Of A Web-Powered Customer Relationship Management Framework

Research on how Web-Mining (WM) optimizes marketing, is sparse. Especially absent, is research on WM usefulness for Customer Relationship Management (CRM). The purpose of this research, is to propose a Web Mining-enabled knowledge acquisition framework for analytical CRM. An exploratory study consisting of eleven in-depth interviews with marketing scholars and practitioners revealed that, WM methods and techniques - currently available to practitioners - are well-suited for identifying the profile of web prospects according to their browsing behaviour and to classify them into homogeneous groups. Besides, the nascent technologies regarding opinion mining, sentiment analysis or natural language parsing, and which underlie WM, seem sufficient to acquire knowledge pertaining to attitudinal and other more psychometrically-based characteristics about web prospects. Such tools enable to better understand the so-often termed elusive prospects, by crafting fine-grained online marketing strategies to acquire those would-be customers. The authors discuss the managerial implications that derive from these findings

The Aesthetic Dimensions of U.S. and South Korean Responses to Web Home Pages: A Cross-Cultural Comparison

Culturally influenced preferences in website aesthetics is a topic often neglected by scholars in human-computer interaction. Kim, Lee, and Choi (2003) identified aesthetic design factors of web home pages that elicited particular responses in South Korean web users based on 13 secondary emotional dimensions. This study extends Kim et al.'s work to U.S. participants, comparing the original South Korean findings with U.S. findings. Results show that U.S. participants reliably applied translations of the emotional adjectives used in the South Korean study to the home pages. However, factor analysis revealed that the aesthetic perceptions of U.S. and South Korean participants formed different aesthetic dimensions composed of different sets of emotional adjectives, suggesting that U.S. and South Korean people perceive the aesthetics of home pages differently. These results indicate that website aesthetics can vary significantly between cultures

Customisable chatbot as a research instrument

Abstract. Chatbots are proliferating rapidly online for a variety of different purposes. This thesis presents a customisable chatbot that was designed and developed as a research instrument for online customer interaction research. The developed chatbot facilitates creation of different bot personas, data management tools, and a fully functional online chat user interface. Customer-facing bots in the system are rulebased, with basic input processing and text response selection based on best match. The system uses its own database to store user-chatbot dialogue history. Further, bots can be assigned unique dialogue scripts and their profiles can be customised concerning name, description and profile image. In the presented validation studies, participants completed a task by taking part in a conversation with different bots, as hosted by the system and invoked through distinct URL parameters. Second, the participants filled in a questionnaire on their experience with the bot, designed to reveal differences in how the bots were perceived. Our results suggest that the chatbot’s personality impacted how customers experienced the interactions. Therefore, the developed system can facilitate research scenarios that deal with investigating participant responses to different chatbot personas. Future work is necessary for a wider range of applications and enhanced response control.Personoitava chatbot tutkimustyökaluna. Tiivistelmä. Chatbotit yleistyvät nopeasti Internetissä ja niitä käytetään enenevissä määrin useissa eri käyttötarkoituksissa. Tämä diplomityö esittelee personoitavan chatbotin, joka on kehitetty tutkimustyökaluksi verkon yli tapahtuvaan vuorovaikutustutkimukseen. Kehitetty chatbot sisältää erilaisten bottipersoonien luonnin, apuvälineitä datan käsittelyn, ja itse botin käyttöliittymän. Järjestelmän käyttäjille vastailevat bottipersoonat ovat sääntöihin perustuvia, niiden syötteet käsitellään suoraviivaisesti ja vastaukseksi valitaan vertailun mukaan paras ennaltamääritellyn skriptin mukaisesti. Järjestelmä käyttää omaa tietokantaa tallentamaan käyttäjä-botti keskusteluhistorian. Lisäksi boteille voidaan asettaa uniikki dialogimalli, ja niiden profiilista voidaan personoida URL-parametrillä nimi, botin kuvaus ja profiilikuva. Chatbotin tekninen toiminta todettiin tutkimuksella, jossa osallistujat suorittivat annetun tehtävän seuraamalla osittain valmista käsikirjoitusta eri bottien kanssa. Tämän jälkeen osallistujat täyttivät käyttäjäkyselyn liittyen heidän kokemukseensa botin kanssa. Kysely oli suunniteltu paljastamaan mahdolliset eroavaisuudet siinä, kuinka botin käyttäytyminen miellettiin keskustelun aikana. Käyttäjätestin tulokset viittaavat siihen, että chatbotin persoonalla oli vaikutus käyttäjien kokemukseen. Kehitetty järjestelmä siis pystyy mahdollistamaan tutkimusasetelmia, joissa tutkitaan osallistujien reaktioita erilaisten chattibottien persooniin. Jatkotyö kehitetyn chatbotin yhteydessä keskittyy monimutkaisempien käyttötarkoitusten lisäämiseen ja botin vastausten parantamiseen edistyksellisemmän luonnollisen kielen käsittelyn avulla

Factors influencing learner driver experiences [Road Safety Grant Report 2009-003]

When compared with more experienced drivers, new drivers have a higher crash risk. This study examined the experiences of learner drivers in Queensland and New South Wales in order to develop an understanding of the factors that influenced them while learning to drive. This will enable the development of more effective licensing systems. The research was informed by a number of heoretical perspectives, particularly social learning theory. Participants were recruited from driver licensing centres as soon as they passed their practical driving test to attain a provisional licence. Of those approached, 392 new drivers from capital cities and regional locations in Queensland and New South Wales completed a 35 minute telephone interview that collected information on a range of personal, social, environmental and socio-demographic factors. Participants were obtaining their licence before several changes to the licensing systems in both Queensland and New South Wales were made in 2007. Several implications for countermeasure development resulted from this research. These included ensuring licensing authorities carefully consider mandating a minimum number of hour of practice as it may inadvertently suppress the amount of practice that some learners obtain. Licensing authorities should consider the use of logbooks for learner drivers, even if there is no minimum amount of supervised practice required as it may assist learners and their supervisors structure their practice more effectively. This research also found that the confidence of learner drivers increases between when they first obtain their learner licence and when they obtain their provisional licence. This is an important issue requiring further attention by licensing authorities