Learning is an integral part of being human. How people learn has long been discussed, revealed in many learning theories, investigated in numerous studies, and demonstrated in extensive practices. ...The goal of this article is to rethink how people learn from four fundamental perspectives, that is, learning by interaction with content (C), learning by interaction with other people (O), learning by interaction with self (S), and learning by interaction with tasks or practices (T), so-called COST model. This framework offers a high-level view of human learning and the role of technology in human learning. Moreover, it serves as a guide for effective design of learning experiences, learning environments, and learning approaches, where technology has become a crucial component.
With the fast development of artificial intelligence and emerging technologies, automatic recognition of students’ facial expressions has received increased attention. Facial expressions are a kind ...of external manifestation of emotional states. It is important for teachers to assess students’ emotional states and adjust teaching activities accordingly. However, existing methods for automatic facial expression recognition have the limitations of low accuracy of recognition and poor feature extraction. To address the problem, this study proposed a novel deep learning model called DenseNetX-CBAM to improve facial expression recognition by utilizing a variant of densely connected convolutional networks (DenseNet) to reduce unnecessary parameters and strengthen the reuse of expression features between networks; moreover, convolutional block attention module (CBAM) was integrated to allow the networks to focus on important special regions and important channels when representing features. The proposed model was tested using 217 video clips of 33 students in an online course. The results demonstrated promising effects of the method in improving the accuracy of facial expression recognition, which can help teachers to accurately recognize students’ emotions and provide real-time adjustment in online learning environments.
Many university students have been struggling with multiple challenges that may cause mental fatigue. Exposure to the natural environment is found to have restorative effects on mental fatigue, which ...can be explained by its benefits in physiological, psychological, and cognitive aspects. While the natural environment contains both visual and auditory elements, research on the effects of auditory elements, such as nature sounds, is underdeveloped and limited to laboratory settings. It remains unclear what are the effects of exposure to nature sounds in daily life settings. The study was conducted with 71 students from a university, who were randomly assigned to the experimental group using a nature-sound mobile application in daily life and the control group not using the application. After a 4-week exposure to the intervention, the students in the experimental group outperformed their counterparts in the control group on psychological well-being reflected in positive affect, as well as cognitive performance reflected in flow state, attention (in terms of alerting) and working memory (in terms of accuracy and reaction time). The findings reveal the positive impact of exposure to relaxing nature sounds on university students' psychological well-being and cognitive performance, as well as the potential of mobile applications to provide easy exposure to nature sounds.
Technological advancements, particularly in the field of artificial intelligence (AI) have played an increasingly important role in transforming education. More recently, ground-breaking AI ...applications like ChatGPT have demonstrated the potential to bring radical changes to the educational landscape due to their capability to understand complex questions, generate plausible responses and human-like writing, and assist with the completion of complex tasks. However, ChatGPT has limitations in the quality of its output, such as the inclusion of inaccurate, fabricated and biased information and the lack of critical thinking and in-depth understanding. The combinations of these capabilities and limitations along with external factors (e.g., the growing demand for personalized learning support, the irresponsible and unethical use of AI) presents a range of opportunities and challenges to the potential use of ChatGPT in education. This paper presents a thorough SWOT (strength, weakness, opportunity, threat) analysis of ChatGPT, based on which we propose how ChatGPT can be properly integrated into teaching and learning practice to harness its potential in education.
Concept mapping has been employed as a promising tool to facilitate group learning and interaction mainly in the classroom. Computer- and web-based applications provide plenty of opportunities to ...extend concept mapping mediated group learning to online environments. Nevertheless, the effects of concept mapping on group learning and interaction may vary with the nature of group tasks and other factors. This study investigated the effects of web-based collaborative concept mapping on group interaction in two task situations: concept-oriented task and design-oriented task. Web-based collaborative concept mapping was used to mediate small group learning among college students in an online environment. The findings revealed that there were differences in the effects of collaborative concept mapping on group interaction between the two task situations; collaborative concept mapping functioned more effectively in facilitating group interaction in the concept-oriented task situation than in the design-oriented task situation in several ways.
•Web-based collaborative concept mapping supports interaction in group learning.•Concept mapping is effective in mediating group interaction in a conceptual task.•Concept mapping is ineffective in facilitating group interaction in a design task.
Sarcopenia greatly reduces the quality of life of the elderly, and iron metabolism plays an important role in muscle loss. This study aimed to investigate the association between iron status and ...sarcopenia. A total of 286 adult patients hospitalized between 2019 and 2021 were included in this study, of which 117 were diagnosed with sarcopenia. Serum iron, total iron binding capacity (TIBC), transferrin, and transferrin saturation levels were compared between groups with and without sarcopenia and were included in the logistic analyses, with significant variables further included in the logistic regression model for the prediction of sarcopenia. Serum iron, TIBC, and transferrin levels decreased significantly in the sarcopenia group (p < 0.05), and were negatively associated with handgrip strength, relative skeletal muscle index, and multiple test performances (p < 0.05). Multivariate logistic analysis showed that sex, age, body mass index (BMI), and serum iron level were independent risk factors for sarcopenia. In the final logistic regression model, male sex (odds ratio OR 3.65, 95% confidence interval CI 1.67-7.98), age > 65 years (OR 5.40, 95% CI 2.25-12.95), BMI < 24 kg/m
(OR 0.17, 95% CI 0.08-0.36), and serum iron < 10.95 μmol/L (OR 0.39, 95% CI 0.16-0.93) were included. Our study supported the impact of iron metabolism on muscle strength and performance.
The high-fidelity and interactivity afforded by head-mounted displays (HMD) has a potential to improve learning in problem-solving contexts. However, there is a lack of studies with mixed findings on ...the efficacy of HMD in the development of problem-solving competence. Moreover, the integration of learning strategies with HMD supported learning is often overlooked. This study aimed to address the gap by investigating whether the simulation media (HMD or 2D simulation environments) and learning strategy (with or without planning) may influence student learning with problem-solving tasks. The results show that the HMD and planning groups outperformed other groups in simulated problem-solving tasks, and in transferring the competence to real-world tasks. Students using the HMD perceived a higher level of sense of presence, self-efficacy, and simulator acceptance; but they reported a higher level of mental workload and simulator sickness than those using the 2D simulation. Implications of the findings are also discussed.
The aim of this study is to prospectively evaluate whole-brain CT perfusion (CTP) on admission to predict delayed cerebral ischemia (DCI) in patients with aneurysmal subarachnoid hemorrhage (aSAH).
...All 252 consecutive patients with aSAH enrolled in this study underwent one-stop whole-brain CTP scan within 24 h after aneurysm rupture. The qualitative and quantitative CTP parameters and clinical data were compared between patients with and without DCI. Diagnostic performance of clinical data and mean and lowest CTP parameters were evaluated by receiver-operating characteristic (ROC) analyses. Logistic regression analysis was employed to determine predictors of DCI.
The study evaluated 191 of 252 consecutive patients, 57 of whom (29.8%) developed DCI during hospitalization. Patients with diffused hypoperfusion had the highest incidence rate of DCI (43%, 46/107). Mean TMax produced the largest area under the curve of 0.726 (95% confidence interval CI 0.638–0.814), and a cutoff value of 2.240 s provided sensitivity of 73.7% and specificity of 71.6% for early prediction of developing DCI. Glasgow Coma Scale score (odds ratio OR = 0.716, 95% CI 0.565–0.908, P = 0.006), cerebral vasospasm (OR = 6.117, 95% CI 1.427–26.223, P = 0.015), hydrocephalus (OR = 3.795, 95% CI 1.327–10.858, P = 0.013), and qualitative CTP analysis (OR = 3.383, 95% CI 1.686–6.789, P = 0.001) were all significant independent predictors of DCI.
Whole-brain CTP within 24 h of admission can qualitatively and quantitatively detect abnormal cerebral perfusion. It is possible to predict the risk of developing DCI after aSAH when the TMax value is larger than 2.240 s.
The rapid development of information and communication technology (ICT) has been increasingly changing the ways of teaching and learning and teacher development. While the literature shows a ...proliferation of studies exploring various issues of applying ICT in teacher development and teaching practice, there is a lack of overview of the literature in this field. This study aimed to address the gap by reviewing the literature in two themes: (1) ICT in teacher professional development (TPD), and (2) ICT in teaching practice. Six journals of a high impact in the field of teaching and teacher education were selected, from which 85 articles involving ICT applications and published from 2013 to 2019 were identified. Among them, 18 empirical articles highly relevant to the two themes were analysed. The content analysis of these publications identified a set of specific ICT applications in TPD and in teaching practice. Moreover, the analysis revealed the key features of these ICT applications in terms of their functions, their effects on teaching and teacher development, the factors influencing their applications, and the problems in existing applications.
Higher-order thinking is crucial to inquiry learning. It is important to investigate how students think in inquiry contexts. Given the tacit nature of higher-order thinking, cognitive maps (e.g., ...concept maps, reasoning maps) have been used to externalize thinking and have shown promising effects in terms of improving inquiry task performance. However, few studies have analyzed student-constructed maps that reflect the thinking underpinning students’ inquiry task performance. This study aimed to address this gap. Sixty-nine 11th grade students worked in small groups to explain a fish die-off phenomenon in a virtual ecosystem and collaboratively constructed an integrative cognitive map to facilitate thinking during the task. The map comprised a concept map (representing conceptual thinking about relevant subject knowledge) and a reasoning map (representing the reasoning process). Regression analyses showed that the quality of the student-constructed maps, particularly the reasoning maps, was a significant predictor of inquiry task performance assessed based on students’ written explanations of the phenomenon. Although the quality of the concept maps was not a significant predictor of inquiry task performance, it did predict the quality of the reasoning maps. Student thinking reflected in concept mapping and that reflected in reasoning mapping play different roles in inquiry learning.