119,977 research outputs found

    Authentication of Students and Students’ Work in E-Learning : Report for the Development Bid of Academic Year 2010/11

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    Global e-learning market is projected to reach $107.3 billion by 2015 according to a new report by The Global Industry Analyst (Analyst 2010). The popularity and growth of the online programmes within the School of Computer Science obviously is in line with this projection. However, also on the rise are students’ dishonesty and cheating in the open and virtual environment of e-learning courses (Shepherd 2008). Institutions offering e-learning programmes are facing the challenges of deterring and detecting these misbehaviours by introducing security mechanisms to the current e-learning platforms. In particular, authenticating that a registered student indeed takes an online assessment, e.g., an exam or a coursework, is essential for the institutions to give the credit to the correct candidate. Authenticating a student is to ensure that a student is indeed who he says he is. Authenticating a student’s work goes one step further to ensure that an authenticated student indeed does the submitted work himself. This report is to investigate and compare current possible techniques and solutions for authenticating distance learning student and/or their work remotely for the elearning programmes. The report also aims to recommend some solutions that fit with UH StudyNet platform.Submitted Versio

    Designing and evaluating the usability of a machine learning API for rapid prototyping music technology

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    To better support creative software developers and music technologists' needs, and to empower them as machine learning users and innovators, the usability of and developer experience with machine learning tools must be considered and better understood. We review background research on the design and evaluation of application programming interfaces (APIs), with a focus on the domain of machine learning for music technology software development. We present the design rationale for the RAPID-MIX API, an easy-to-use API for rapid prototyping with interactive machine learning, and a usability evaluation study with software developers of music technology. A cognitive dimensions questionnaire was designed and delivered to a group of 12 participants who used the RAPID-MIX API in their software projects, including people who developed systems for personal use and professionals developing software products for music and creative technology companies. The results from the questionnaire indicate that participants found the RAPID-MIX API a machine learning API which is easy to learn and use, fun, and good for rapid prototyping with interactive machine learning. Based on these findings, we present an analysis and characterization of the RAPID-MIX API based on the cognitive dimensions framework, and discuss its design trade-offs and usability issues. We use these insights and our design experience to provide design recommendations for ML APIs for rapid prototyping of music technology. We conclude with a summary of the main insights, a discussion of the merits and challenges of the application of the CDs framework to the evaluation of machine learning APIs, and directions to future work which our research deems valuable

    Tracking the dynamic nature of learner individual differences: Initial results from a longitudinal study

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    Individual differences (IDs) have long been considered one of the most important factors explaining variable rates and outcomes in second language acquisition (Dewaele, 2013). While traditional operationalizations of IDs have, explicitly or implicitly, assumed that IDs are static traits that are stable through time, more recent research inspired by complex dynamic systems theory (Larsen-Freeman, 1997, 2020) demonstrates that many IDs are dynamic and variable through time and across contexts, a theme echoed throughout the current issue. This study reports the initial semester of a diachronic project investigating the dynamicity of four learner IDs: motivation, personality, learning and cognitive styles, and working memory. In the initial semester, data from 323 participants in their first year of university-level Spanish were collected and analyzed to determine what type of variability may be present across learners with respect to the four IDs studied at one time point and to discern possible learner profiles in the data or patterns via which the data may be otherwise meaningfully described. The results revealed four types of learner profiles present in the dataset

    The words of the body: psychophysiological patterns in dissociative narratives

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    Trauma has severe consequences on both psychological and somatic levels, even affecting the genetic expression and the cell\u2019s DNA repair ability. A key mechanism in the understanding of clinical disorders deriving from trauma is identified in dissociation, as a primitive defense against the fragmentation of the self originated by overwhelming experiences. The dysregulation of the interpersonal patterns due to the traumatic experience and its detrimental effects on the body are supported by influent neuroscientific models such as Damasio\u2019s somatic markers and Porges\u2019 polyvagal theory. On the basis of these premises, and supported by our previous empirical observations on 40 simulated clinical sessions, we will discuss the longitudinal process of a brief psychodynamic psychotherapy (16 sessions, weekly frequency) with a patient who suffered a relational trauma. The research design consists of the collection of self-report and projective tests, pre-post therapy and after each clinical session, in order to assess personality, empathy, clinical alliance and clinical progress, along with the verbatim analysis of the transcripts trough the Psychotherapy Process Q-Set and the Collaborative Interactions Scale. Furthermore, we collected simultaneous psychophysiological measures of the therapeutic dyad: skin conductance and hearth rate. Lastly, we employed a computerized analysis of non-verbal behaviors to assess synchrony in posture and gestures. These automated measures are able to highlight moments of affective concordance and discordance, allowing for a deep understanding of the mutual regulations between the patient and the therapist. Preliminary results showed that psychophysiological changes in dyadic synchrony, observed in body movements, skin conductance and hearth rate, occurred within sessions during the discussion of traumatic experiences, with levels of attunement that changed in both therapist and the patient depending on the quality of the emotional representation of the experience. These results go in the direction of understanding the relational process in trauma therapy, using an integrative language in which both clinical and neurophysiological knowledge may take advantage of each other

    Visual BFI: an Exploratory Study for Image-based Personality Test

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    This paper positions and explores the topic of image-based personality test. Instead of responding to text-based questions, the subjects will be provided a set of "choose-your-favorite-image" visual questions. With the image options of each question belonging to the same concept, the subjects' personality traits are estimated by observing their preferences of images under several unique concepts. The solution to design such an image-based personality test consists of concept-question identification and image-option selection. We have presented a preliminary framework to regularize these two steps in this exploratory study. A demo version of the designed image-based personality test is available at http://www.visualbfi.org/. Subjective as well as objective evaluations have demonstrated the feasibility of image-based personality test in limited questions
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