Dialogic education, historical thinking and epistemic beliefs: a design-based research study of teaching in Taiwanese classrooms

The study reported in this dissertation explored: (1) teachers’ use of dialogue to facilitate students’ historical thinking and (2) the trajectory of historical personal epistemology through a design-based approach. Empirical evidence emerging in previous decades has acknowledged that good quality classroom dialogue could have a positive impact on students’ learning. Through dialogic teaching, it has been argued that teachers could probe and promote students’ higher thinking skills. However, how dialogue is being used in history classes as well as the cultural context of dialogic education in East Asia was a salient gap in current research. The first research aim was to explore both teachers’ and students’ epistemic beliefs regarding the domain of history, which has been largely neglected in this field of study. The aim of this research was also to propose a new perspective on dialogic education that might not only bridge the dichotomy of the monologic and dialogic forms of teaching, but also address the pedagogical dilemma in history education raised by the latest Taiwanese national curriculum reform. Finally, another major aim of the research was to design a teacher professional development programme to change teachers’ epistemic beliefs and their teaching practice towards dialogic history education for promoting historical thinking. Adopting the notion of design-based research, a teaching professional programme was designed and administered throughout the one-academic year to 7 high school teachers. Three students of each participating teacher were chosen for semi-structured interviews to explore their personal epistemology, which were later analysed with an innovative discourse analysis method: Epistemic Network Analysis (ENA). Data concerning classroom dialogue was collected from monthly class observations and then analysed with a reconceptualised coding framework adapted from the Teacher’s Scheme for Educational Dialogue Analysis (T-SEDA, Hennessy, et al., 2021) and an observational instrument for historical thinking (Gestsdóttir, et al., 2018). In regard to personal epistemology, the findings reported a mixture of results with only a few students seeing a significant change in their epistemic beliefs after the programme. However, a pattern-based model for analysing historical epistemic beliefs reported from this study, has been generated resulting in four major patterns of beliefs being identified. In terms of classroom dialogue, the results found a positive increase in teachers’ use of dialogue. A hybrid form of dialogue informed by current dialogic theories synthesised with Confucianism and Taoism allowed dialogue to transgress away from the dichotomy of structural forms of monologue and dialogue was also put forward and characterised from the analysis. The contributions of this present study are discussed in terms of theoretical, methodological and practical uses

Detecting and Ranking Causal Anomalies in End-to-End Complex System

With the rapid development of technology, the automated monitoring systems of large-scale factories are becoming more and more important. By collecting a large amount of machine sensor data, we can have many ways to find anomalies. We believe that the real core value of an automated monitoring system is to identify and track the cause of the problem. The most famous method for finding causal anomalies is RCA, but there are many problems that cannot be ignored. They used the AutoRegressive eXogenous (ARX) model to create a time-invariant correlation network as a machine profile, and then use this profile to track the causal anomalies by means of a method called fault propagation. There are two major problems in describing the behavior of a machine by using the correlation network established by ARX: (1) It does not take into account the diversity of states (2) It does not separately consider the correlations with different time-lag. Based on these problems, we propose a framework called Ranking Causal Anomalies in End-to-End System (RCAE2E), which completely solves the problems mentioned above. In the experimental part, we use synthetic data and real-world large-scale photoelectric factory data to verify the correctness and existence of our method hypothesis

Prognostic Factors Influencing the Patency of Hemodialysis Vascular Access: Literature Review and Novel Therapeutic Modality by Far Infrared Therapy

In Taiwan, more than 85% of patients with end-stage renal disease undergo maintenance hemodialysis (HD). The native arteriovenous fistula (AVF) accounts for a prevalence of more than 80% of the vascular access in our patients. Some mechanical factors may affect the patency of hemodialysis vascular access, such as surgical skill, puncture technique and shear stress on the vascular endothelium. Several medical factors have also been identified to be associated with vascular access prognosis in HD patients, including stasis, hypercoagulability, endothelial cell injury, medications, red cell mass and genotype polymorphisms of transforming growth factor-β1 and methylene tetrahydrofolate reductase. According to our previous study, AVF failure was associated with a longer dinucleotide (GT)n repeat (n ≥ 30) in the promoter of the heme oxygenase-1 (HO-1) gene. Our recent study also demonstrated that far-infrared therapy, a noninvasive and convenient therapeutic modality, can improve access flow, inflammatory status and survival of the AVF in HD patients through both its thermal and non-thermal (endothelial-improving, anti-inflammatory, antiproliferative, antioxidative) effects by upregulating NF-E2-related factor-2-dependent HO-1 expression, leading to the inhibition of expression of E-selectin, vascular cell adhesion molecule-1, and intercellular adhesion molecule-1

A multivariate causality test of carbon dioxide emissions, energy consumption and economic growth in China.

a b s t r a c t This paper uses multivariate co-integration Granger causality tests to investigate the correlations between carbon dioxide emissions, energy consumption and economic growth in China. Some researchers have argued that the adoption of a reduction in carbon dioxide emissions and energy consumption as a long term policy goal will result in a closed-form relationship, to the detriment of the economy. Therefore, a perspective that can make allowances for the fact that the exclusive pursuit of economic growth will increase energy consumption and CO 2 emissions is required; to the extent that such growth will have adverse effects with regard to global climate change

LLM4TS: Two-Stage Fine-Tuning for Time-Series Forecasting with Pre-Trained LLMs

In this work, we leverage pre-trained Large Language Models (LLMs) to enhance time-series forecasting. Mirroring the growing interest in unifying models for Natural Language Processing and Computer Vision, we envision creating an analogous model for long-term time-series forecasting. Due to limited large-scale time-series data for building robust foundation models, our approach LLM4TS focuses on leveraging the strengths of pre-trained LLMs. By combining time-series patching with temporal encoding, we have enhanced the capability of LLMs to handle time-series data effectively. Inspired by the supervised fine-tuning in chatbot domains, we prioritize a two-stage fine-tuning process: first conducting supervised fine-tuning to orient the LLM towards time-series data, followed by task-specific downstream fine-tuning. Furthermore, to unlock the flexibility of pre-trained LLMs without extensive parameter adjustments, we adopt several Parameter-Efficient Fine-Tuning (PEFT) techniques. Drawing on these innovations, LLM4TS has yielded state-of-the-art results in long-term forecasting. Our model has also shown exceptional capabilities as both a robust representation learner and an effective few-shot learner, thanks to the knowledge transferred from the pre-trained LLM

Dual task measures in older adults with and without cognitive impairment: Response to simultaneous cognitive-exercise training and minimal clinically important difference estimates

BACKGROUND: Responsiveness and minimal clinically important difference (MCID) are critical indices to understand whether observed improvement represents a meaningful improvement after intervention. Although simultaneous cognitive-exercise training (SCET; e.g., performing memory tasks while cycling) has been suggested to enhance the cognitive function of older adults, responsiveness and MCID have not been established. Hence, we aimed to estimate responsiveness and MCIDs of two dual task performance involving cognition and hand function in older adults with and without cognitive impairment and to compare the differences in responsiveness and MCIDs of the two dual task performance between older adults with and without cognitive impairment. METHODS: A total of 106 older adults completed the Montreal Cognitive Assessment and two dual tasks before and after SCET. One dual task was a combination of Serial Sevens Test and Box and Block Test (BBT), and the other included frequency discrimination and BBT. We used effect size and standardized response mean to indicate responsiveness and used anchor- and distribution-based approaches to estimating MCID ranges. When conducting data analysis, all participants were classified into two cognitive groups, cognitively healthy (Montreal Cognitive Assessment ≥ 26) and cognitively impaired (Montreal Cognitive Assessment \u3c 26) groups, based on the scores of the Montreal Cognitive Assessment before SCET. RESULTS: In the cognitively healthy group, Serial Seven Test performance when tasked with BBT and BBT performance when tasked with Serial Seven Test were responsive to SCET (effect size = 0.18-0.29; standardized response mean = 0.25-0.37). MCIDs of Serial Seven Test performance when tasked with BBT ranged 2.09-2.36, and MCIDs of BBT performance when tasked with Serial Seven Test ranged 3.77-5.85. In the cognitively impaired group, only frequency discrimination performance when tasked with BBT was responsive to SCET (effect size = 0.37; standardized response mean = 0.47). MCIDs of frequency discrimination performance when tasked with BBT ranged 1.47-2.18, and MCIDs of BBT performance when tasked with frequency discrimination ranged 1.13-7.62. CONCLUSIONS: Current findings suggest that a change in Serial Seven Test performance when tasked with BBT between 2.09 and 2.36 corrected number (correct responses - incorrect responses) should be considered a meaningful change for older adults who are cognitively healthy, and a change in frequency discrimination performance when tasked with BBT between 1.47 and 2.18 corrected number (correct responses - incorrect responses) should be considered a meaningful change for older adults who are cognitively impaired. Clinical practitioners may use these established MCIDs of dual tasks involving cognition and hand function to interpret changes following SCET for older adults with and without cognitive impairment. TRIAL REGISTRATION: NCT04689776, 30/12/2020