29 research outputs found

    Smartphone application in postgraduate clinical psychology training: trainees’ perspectives

    Get PDF
    M-learning refers to the learning that takes advantage of mobile technologies. Although research shows enhanced educational outcomes from m-learning in some Asian countries, the generalizability to postgraduate clinical psychology training in Singapore remains unclear. Current professional standards in clinical psychology training emphasize the importance of attainment of clinical competencies in trainees. Although learning theories indicated potential for m-learning to be incorporated into the local clinical psychology curriculum, trainees’ perspectives have not been adequately explored on m-learning. The study aimed to address this gap by exploring the use of m-learning via a novel smartphone application in clinical psychology training using mixed-methods design. Eight clinical psychology trainees between the ages of 26 to 43 years old (mean age of 31.75, SD = 5.49) enrolled in a relevant coursework subject were recruited. Participants were randomly allocated to the experimental and control groups. The experimental group accessed the novel application weekly, from week 1 to week 6, and participants in the control group accessed the application after week 6. Participants from both groups completed a brief demographic questionnaire, and the following scales New General Self-Efficacy Scale adapted for Education (NGSES-E) and self-reported scale of learning outcomes (SLO). The qualitative study explored how participants perceived and experienced the novel application. Participants from the experimental group were invited to provide open-ended responses about the novel application. Data were analyzed using thematic analysis. Results from the qualitative analysis yielded four themes of: Convenience, preferred learning style, building confidence, and putting theory into practice. Findings from the qualitative study were consistent with previous studies about advantages of m-learning: That the e-platform was convenient, the learning style was engaging, which helped to build confidence, and facilitate practical learning of skills. The qualitative results were helpful in understanding the users’ perspectives and experience of the novel application, indicating that future research in this innovative area is necessary. However, the quantitative outcomes were not significant, limitations would be discussed, and recommendations made for future research

    Neutron structure function and inclusive DIS from H-3 and He-3 at large Bjorken-x

    Get PDF
    A detailed study of inclusive deep inelastic scattering (DIS) from mirror A = 3 nuclei at large values of the Bjorken variable x is presented. The main purpose is to estimate the theoretical uncertainties on the extraction of the neutron DIS structure function from such nuclear measurements. On one hand, within models in which no modification of the bound nucleon structure functions is taken into account, we have investigated the possible uncertainties arising from: i) charge symmetry breaking terms in the nucleon-nucleon interaction, ii) finite Q**2 effects neglected in the Bjorken limit, iii) the role of different prescriptions for the nucleon Spectral Function normalization providing baryon number conservation, and iv) the differences between the virtual nucleon and light cone formalisms. Although these effects have been not yet considered in existing analyses, our conclusion is that all these effects cancel at the level of ~ 1% for x < 0.75 in overall agreement with previous findings. On the other hand we have considered several models in which the modification of the bound nucleon structure functions is accounted for to describe the EMC effect in DIS scattering from nuclei. It turns out that within these models the cancellation of nuclear effects is expected to occur only at a level of ~ 3%, leading to an accuracy of ~ 12 % in the extraction of the neutron to proton structure function ratio at x ~ 0.7 -0.8$. Another consequence of considering a broad range of models of the EMC effect is that the previously suggested iteration procedure does not improve the accuracy of the extraction of the neutron to proton structure function ratio.Comment: revised version to appear in Phys. Rev. C; main modifications in Section 4; no change in the conclusion

    A Robust Parser-Interpreter for Jazz Chord Sequences

    Get PDF
    Hierarchical structure similar to that associated with prosody and syntax in language can be identified in the rhythmic and harmonic progressions that underlie Western tonal music. Analysing such musical struc-ture resembles natural language parsing: it requires the derivation of an underlying interpretation from an un-structured sequence of highly ambiguous elements— in the case of music, the notes. The task here is not merely to decide whether the sequence is grammati-cal, but rather to decide which among a large number of analyses it has. An analysis of this sort is a part of the cognitive processing performed by listeners familiar with a musical idiom, whether musically trained or not. Our focus is on the analysis of the structure of ex-pectations and resolutions created by harmonic progres-sions. Building on previous work, we define a theory of tonal harmonic progression, which plays a role analo-gous to semantics in language. Our parser uses a formal grammar of jazz chord sequences, of a kind widely used for natural language processing (NLP), to map music, in the form of chord sequences used by performers, onto a representation of the structured relationships between chords. It uses statistical modelling techniques used for wide-coverage parsing in NLP to make practical pars-ing feasible in the face of considerable ambiguity in the grammar. Using machine learning over a small corpus of jazz chord sequences annotated with harmonic anal-yses, we show that grammar-based musical interpreta-tion using simple statistical parsing models is more ac-curate than a baseline HMM. The experiment demon-strates that statistical techniques adapted from NLP can be profitably applied to the analysis of harmonic struc-ture
    corecore