Many studies have demonstrated that student motivation is an important factor in student learning. The recently proposed General Model of Instructional Communication, however, does not include motivation. Based on the assumption that student motivation may be an important factor in student learning, particularly long-term learning and retention, the present research examined relationships of student motivation with the four primary teacher communication behaviors included in that model. Student motivation was also found to be highly associated with instructional outcomes (affect for course content and affect toward teacher) included in the General Model. Results indicate that student motivation should be added to that model. Potential problems associated with colinearity and halo effects are discussed.
There has been no empirical evidence about the health informatics workforce in Australia produced in the last ten years. This study reports the findings from an analysis of a subset of the 2018 Australian Health Informatics Workforce Census data. Analysing 420 responses that were identified as the occupational group Health Informatics, the results indicate that whilst most of the workforce is classified as aged (>45 years), many respondents are still relatively early in their health informatics careers. Furthermore, most do not possess any formal education in health informatics and almost a quarter undertake their health informatics role alongside another health-related role. The broad range of position titles and functions demonstrates the breadth within this workforce. Ongoing monitoring of this occupational group is required to inform workforce reform and renewal.
Encouraged by the success of pretrained Transformer models in many natural language processing tasks, their use for International Classification of Diseases (ICD) coding tasks is now actively being explored. In this study, we investigated two existing Transformer-based models (PLM-ICD and XR-Transformer) and proposed a novel Transformer-based model (XR-LAT), aiming to address the extreme label set and long text classification challenges that are posed by automated ICD coding tasks. The Transformer-based model PLM-ICD, which currently holds the state-of-the-art (SOTA) performance on the ICD coding benchmark datasets MIMIC-III and MIMIC-II, was selected as our baseline model for further optimisation on both datasets. In addition, we extended the capabilities of the leading model in the general extreme multi-label text classification domain, XR-Transformer, to support longer sequences and trained it on both datasets. Moreover, we proposed a novel model, XR-LAT, which was also trained on both datasets. XR-LAT is a recursively trained model chain on a predefined hierarchical code tree with label-wise attention, knowledge transferring and dynamic negative sampling mechanisms. Our optimised PLM-ICD models, which were trained with longer total and chunk sequence lengths, significantly outperformed the current SOTA PLM-ICD models, and achieved the highest micro-F1 scores of 60.8 % and 50.9 % on MIMIC-III and MIMIC-II, respectively. The XR-Transformer model, although SOTA in the general domain, did not perform well across all metrics. The best XR-LAT based models obtained results that were competitive with the current SOTA PLM-ICD models, including improving the macro-AUC by 2.1 % and 5.1 % on MIMIC-III and MIMIC-II, respectively. Our optimised PLM-ICD models are the new SOTA models for automated ICD coding on both datasets, while our novel XR-LAT models perform competitively with the previous SOTA PLM-ICD models.
The physical environments are often limited for fostering and enriching creativity and collaborative benefits, especially in the educational context. In general, students have limited opportunities to experience peer-to-peer and group collaborative learning. Gaining knowledge, understanding and group interaction skills from a collaborative learning experience in a classroom are often rare. This paper introduces how a virtual environment can be combined with a physical environment to achieve collaborative benefits. We observed an online homework submission system that facilitated this collaborative process. Although this is only one example of one class, these observed collaborative benefits and the way that the virtual and physical environments combine to produce them could be useful for other courses where collaborative skills are necessary or desired.
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