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Objective To investigate the suicide risk factors among caregivers of individuals with depression who may develop suicidal ideation due to the ongoing challenges of managing the patient's mood fluctuations. Methods This cross-sectional study enrolled dyads of patients with depression and their caregivers from a medical centre. The assessment included a psychiatric diagnostic interview, the Hospital Anxiety and Depression Scale, the List of Threatening Experiences, Benefit Finding Scale, Numerical Pain Rating Scale, Stigma Subscale of the Explanatory Model Interview Catalogue, Big Five Inventory-10, the Family APGAR Index and the Suicide Assessment Scale. Univariate and multivariate regression analysis were used to explore the interrelationship between the mental health of patients and caregivers. Results Among the 125 caregivers, 60.0% ( n = 75) were females. The most common psychiatric diagnoses were depressive disorders (33 of 125; 26.4%), followed by anxiety disorders (21 of 125; 16.8%) and insomnia disorder (19 of 125; 15.2%). There was a significant association between the stressful life events of depressive patients and the suicide risk of their caregivers. The severity of anxiety and depression in caregivers was significantly associated with the suicide risk among the caregivers. Conclusion A relationship may exist between the psychological well-being of patients with depression and their caregivers.

Abstract Background The COVID-19 Vaccine Introduction and deployment Costing (CVIC) tool was developed to assist countries to estimate incremental financial costs to roll out COVID-19 vaccines. This article describes the purposes, assumptions and methods used in the CVIC tool and presents the estimated financial costs of delivering COVID-19 vaccines in the Lao People’s Democratic Republic (Lao PDR). Methods From March to September 2021, a multidisciplinary team in Lao PDR was involved in the costing exercise of the National Deployment and Vaccination Plan for COVID-19 vaccines to develop potential scenarios and gather inputs using the CVIC tool. Financial costs of introducing COVID-19 vaccines for 3 years from 2021 to 2023 were projected from the government perspective. All costs were collected in 2021 Lao Kip and presented in United States dollar. Results From 2021 to 2023, the financial cost required to vaccinate all adults in Lao PDR with primary series of COVID-19 vaccines (1 dose for Ad26.COV2.S (recombinant) vaccine and 2 doses for the other vaccine products) is estimated to be US$6.44 million (excluding vaccine costs) and additionally US$1.44 million and US$1.62 million to include teenagers and children, respectively. These translate to financial costs of US$0.79–0.81 per dose, which decrease to US$0.6 when two boosters are introduced to the population. Capital and operational cold-chain costs contributed 15–34% and 15–24% of the total costs in all scenarios, respectively. 17–26% went to data management, monitoring and evaluation, and oversight, and 13–22% to vaccine delivery. Conclusions With the CVIC tool, costs of five scenarios were estimated with different target population and booster dose use. These facilitated Lao PDR to refine their strategic planning for COVID-19 vaccine rollout and to decide on the level of external resources needed to mobilize and support outreach services. The results may further inform inputs in cost-effectiveness or cost–benefit analyses and potentially be applied and adjusted in similar low- and middle-income settings.

Virtual Reality (VR) has demonstrated significant advantages in various educational fields as it allows learners to actively learn in high interactivity and realism under their learning pace. However, for low-achieving students, VR learning environments may introduce some challenges, which are problems encountered during their learning process, which lead to difficulties in self-regulating their learning progress and becoming disoriented in the lack of guidance. This study aims to explore the improvement of self-regulated VR learning environment based on the Cognitive Theory of Multimedia Learning and enhance the performance of low-achieving students. We designed a VR course on electronic circuit hardware and programming, providing participants with a series of learning aids in the VR learning environment, including feedback, hints and guidance. Feedback aids provide correct or incorrect feedback after each task or test, guidance aids display progress following each task or test and hint aids offer guidance when inactivity is detected. A quasi-experiment was conducted by using questionnaires and practical tasks to assess the participants' cognitive levels, practical hands-on skills, self-regulated learning abilities and learning engagement after VR learning. The results demonstrated significant improvements in all learning indicators for low-achieving students.

The core purpose of integrating inquiry-based learning strategies into STEM activities is to create a challenging learning environment that stimulates students' active learning, thereby effectively enhancing their interest in learning, thinking skills, and practical application abilities. To achieve these goals, developing more technology-assisted tools and platforms to improve teaching efficiency and enrich the learning experience becomes crucial. Therefore, this research developed InquiryGPT, which guides students through the POEE inquiry process by imposing limitations, facilitating dialogue, and providing feedback, while avoiding over-reliance on ChatGPT. This promotes the cultivation of higher-order thinking skills through interactions with InquiryGPT, thereby enhancing students' knowledge construction and understanding. This study, based on the Technology Acceptance Model (TAM), examined the effectiveness of InquiryGPT. The results showed no significant difference between InquiryGPT and ChatGPT in terms of perceived usefulness and perceived ease of use. Additionally, through analysis of covariance (ANCOVA), the study further analyzed the impact of InquiryGPT on students' higher-order thinking skills and learning scores, proving that it significantly enhances students' creativity, problem-solving abilities, critical thinking, and knowledge construction.

Learning in a virtual environment has been found to foster students' affective responses, indicating the importance of exploring the factors which affect students' learning when engaged in a virtual game. This study aimed to explore the relationships among students' epistemic curiosity, situational interest, and learning engagement in an exploratory 3D virtual game environment. A virtual game was designed for elementary school students to learn concepts of evaporation and condensation in real-life situations. Data were collected using questionnaires from a total of 121 sixth-grade elementary school students, and were analyzed using partial least square structural equation modeling (PLS-SEM). The reliability and validity of the instruments employed in this study were verified. The structural relationships showed that I-type epistemic curiosity showed a stronger influence on the design of the virtual game environment compared to D-type epistemic curiosity. Challenge was found to be negatively predicted by I-type epistemic curiosity, but positively predicted by D-type epistemic curiosity. Instant enjoyment was also found to play a significant mediating role between I-type epistemic curiosity and emotional engagement. It is suggested that future research should consider providing students with interesting contexts and challenging tasks as a critical approach to designing virtual game learning environments.

Background/purpose: In 2017, Long-Fa Temple, an illegal religious asylum in Taiwan, was forced to shut down. Hundreds of chronic mentally ill patients were incarcerated there but provided with no modern psychiatric treatment. This study investigated the effectiveness of providing psychiatric intervention for patients subsequently transferred from Long-Fa Temple to a medical center. Methods: In total, 88 patients (mean age: 57.2 years, 52.3% male) who had been incarcerated at Long-Fa Temple were transferred to a southern medical center. The patients underwent comprehensive biological, psychological, and social treatment for 18 months. The patients were evaluated once a month in terms of their psychotic symptoms, self-care, nutrition status, cognitive function, occupational function, and family function. Results: Regarding the patients' length of stay, 18.2% were incarcerated in Long-Fa Temple for less than 10 years, 21.6% for 10–20 years, and 60.2% for more than 20 years. In terms of psychiatric diagnosis, 98.9% of the patients had been diagnosed with a schizophrenia spectrum disorder. During the 18-month treatment period, negative symptoms decreased significantly, while the patients’ self-care ability, nutrition status, cognition, occupational function, and family function all significantly improved over time. Patients who had been incarcerated for less than 10 years demonstrated better improvements in psychotic symptoms, self-care, nutrition status, and cognitive function. Conclusion: Contemporary psychiatric intervention is beneficial for chronically untreated mentally ill patients, and the patients who had a shorter duration of illness had a better reserve of recovery. These findings can serve as an important reference for psychiatric intervention in developing countries.

Background: The treatment goals for patients with schizophrenia are to address subjective well-being, quality of life, and recovery in recent decades. Loneliness is a negative subjective feeling and related to social isolation, which is thought to be a barrier to recovery. Few research exist to study loneliness in-depth in patients with schizophrenia. Methods: In this review, the authors intend to address the issues of the prevalence, the impacts, the associated factors, and the interventions of loneliness in patients with schizophrenia. Results: Studies showed that patients with schizophrenia have a greater degree of loneliness than those without. The physical and mental health problems associated with loneliness in patients with schizophrenia include hypertension, high blood level of glycated hemoglobin, activated hypothalamus–pituitary–adrenal axis, poor subjective quality of life, depression, anxiety, suicide, use of addictive substances, high perceived stress, low self-esteem, low sense of pleasure, pessimism, and low resilience. From an ecological approach, loneliness in patients with schizophrenia is associated with several personal disease factors, personal cognitive factors, personal socioeconomic factors, community integration, and residence. Social prescribing projects, cognitive behavioral therapy, mindfulness, and positive psychology interventions have been used to reduce loneliness in patients with schizophrenia. Conclusion: Loneliness is an important indicator of the physical and mental health in patients with schizophrenia. Several factors associated with loneliness in patients with schizophrenia have been identified in the past studies. Further intervention research are required for establish effective methods to reduce loneliness in patients with schizophrenia.

Abstract Parkinson's disease (PD) is an incapacitating neurodegenerative disease. Patients with PD and their caregivers may have interactive effects on each other’s psychological well-being. This study aimed to assess the dyadic dynamics of resilience, fatigue, and suicidal ideation on the depression severity of PD patients and their caregivers. In total, 175 PD patients and 175 caregivers were recruited at a medical center from August 2018 to May 2020. Structural equation modeling (SEM) was used to examine the actor/partner effects on the psychological well-being of both the PD patients and their caregivers. The most common psychiatric diagnoses of both the PD patients (28.6%) and their caregivers (11.4%) were depressive disorders. The PD patients’ and their caregivers’ fatigue, suicidal ideation, and lack of resilience were significantly associated with the severity of their depression, respectively. Interactive effects existed between psychological well-being of individuals with PD and their caregivers. Clinicians must be aware of, and manage, these contributing factors between PD patients and their caregivers in order to prevent them from worsening each other’s depression.

This article presents a narrative inquiry of a Chinese heritage mother to theorize and explicate how historical, relational, and spatial processes impacted her negotiation with power and agency in relation to her own heritage language (HL) identity development. A narrative approach enables us to draw on participant counter-stories against master narratives that erase experiences of marginalization of Asians in Asian language education in the United States. We do this through a model of HL identity development (Zhou & Liu, 2022) supplemented by an AsianCrit lens (Iftikar & Museus, 2018). We show the importance of normalizing Chinese as a HL outside of the home in terms of language maintenance as well as the impact such normalization has on the development of an affirmative Chinese HL identity. We add that spaces for such identity development are deeply associated with language programs like dual language bilingual education (DLBE), especially as the number of DLBE opportunities grow in number and in popularity. Thus, language programs, including DLBE, have a responsibility to ensure that the language education they provide address the interests and investments of families with respect to their HL in order to decenter a primary focus on the interests of ethnolinguistic majoritized families.

Abstract Background Neurocognitive dysfunction is a common symptom of various major psychiatric disorders, including schizophrenia, major depressive disorder (MDD), and bipolar I disorder (BD). In this study, we investigated whether cognitive profiles and daily skill functioning could effectively differentiate between patients with schizophrenia, MDD, and BD. Method In this cross-sectional study, we recruited a total of 63 patients with schizophrenia, 55 patients with MDD, 43 patients with BD, and 92 healthy control subjects. We evaluated participants’ cognitive functions and functional capacity using the Brief Assessment of Cognition in Schizophrenia (BACS) and the UCSD Performance-based Skills Assessment, Brief Version (UPSA-B), respectively. Multivariate analysis of covariance was then adopted to determine inter-group differences in BACS and UPSA-B performance. Results The BACS was capable of differentiating patients with a major psychiatric disorder (schizophrenia, MDD, and BD) from healthy subjects. Furthermore, schizophrenia patients had poorer motor speed performance than patients with affective disorders. The UPSA-B, particularly the financial portion, was able to distinguish schizophrenia patients from other groups. However, we did not observe any differences in UPSA-B performance between patients with mood disorders and the healthy controls. No significant difference between patients with BD and those with MDD were observed in either cognitive function or in functional capacity. The performances of the BACS and the UPSA-B were positively correlated, particularly in the MDD group. Conclusion Considering overall performance, the BACS and the UPSA-B characterize different endophenotyping profiles in the aforementioned four participant groups. Therefore, the results support the need for comprehensive assessments that target both cognitive function and functional capacity for patients with major psychiatric disorders.

The vaccination of all children may be one of the most important public health measures for preventing a wider spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the community. Therefore, the purpose of this study was to investigate the attitude, intention, decision making, and psychological well-being among the caregivers of children who received SARS-CoV-2 vaccination in Taiwan. The caregivers of children (98 preschool children, 191 school-age children, and 154 adolescents) who received COVID-19 vaccination were invited to fill in the following questionnaires: Adopting Self-Protective Behavior Scale, Drivers of COVID-19 Vaccination Acceptance Scale, Impact of Event Scale, Chinese Health Questionnaire, and Parental Bonding Instrument. Compared to the caregivers of adolescents, the caregivers of preschool children exhibited more protective behaviors toward the COVID-19 pandemic. The caregivers of preschool children also displayed a higher emotional impact than those of adolescents and took a greater interest in the family’s opinion about vaccination. Finally, we found that COVID-19 ideological invasion and protective parenting style were significantly related to the prevalence of mental illness among caregivers. The results of this study can be used as an important reference for vaccination health care and policy formulation for adolescents with regard to COVID-19.

Buergeria frog tadpoles exhibit high thermal tolerance and are occasionally found in water pools that temporarily exceed 40°C. With the aim of understanding how they can cope with the severe heat stress, we performed RNA-seq of three heat-treated (38°C) and three control (25°C) tadpoles and compared their transcriptomic profiles. We identified 382 differentially expressed transcripts. A protein-protein interaction (PPI) network analysis of these transcripts further identified hub proteins involved in protein degradation, stress granule assembly, and global suppression of DNA transcription and mRNA translation. Along with the avoidance behavior against high water temperature, these endurance mechanisms potentially support tadpoles to survive in high temperatures for short periods of time. Similar mechanisms may exist in many other amphibian species whose habitats are prone to high temperatures.

Objective Depression is a common comorbidity in cancer patients. This study aimed to compare the prevalence and associated factors of depressive disorder between patients with head and neck cancer (HNC) and those with lung cancer (LC).Design This study used a cross-sectional design with consecutive sampling.Setting A medical centre (Kaohsiung Chang Gung Memorial Hospital, Taiwan).Participants Patients for the study were recruited from the HNC and LC outpatient clinic and inpatient ward from March 2016 to February 2018. Patients with HNC and LC were enrolled and assessed using the Mini International Neuropsychiatric Interview (MINI).Primary and secondary outcome measures The primary outcome was psychiatric diagnoses assessed using the MINI. The secondary outcomes were psychological well-being assessed using the Beck Anxiety Inventory, Taiwanese Depression Questionnaire, Brief Fatigue Inventory, Numeric Pain Rating Scale and the List of Threatening Experiences Questionnaire.Results In total, 113 HNC patients and 104 LC patients were recruited for the study. The most common psychiatric comorbidity of HNC patients was alcohol use disorder (49.6%), followed by adjustment disorder (20.4%) and depressive disorder (11.5%). The most common psychiatric comorbidity of LC patients was depressive disorder (25.0%), followed by adjustment disorder (17.3%), alcohol use disorder (3.8%) and insomnia disorder (3.8%). Among HNC patients, a self-harm history was positively associated with depression (OR=11.91; 95% CI, 1.47 to 96.83), and a higher educational level was negatively associated with depression (OR=0.77; 95% CI, 0.66 to 0.91). Among LC patients, severity of stressor (OR=2.78; 95% CI, 1.50 to 5.15) and severity of anxiety (OR=1.18; 95% CI, 1.04 to 1.34) were two significant factors associated with depression.Conclusion We reported the prevalence and associated factors of depression between patients with HNC and those with LC. Clinicians should be aware of this comorbidity and the associated risk factors, and conduct intervention programmes to prevent these cancer patients from developing depression.

In the WHO Western Pacific Region, traditional medicine has extensively been used by communities as part of primary health care which is critical foundation for achieving universal health coverage (UHC). This paper conceptualizes integration of traditional and complementary medicine (T&CM) into national health systems and explores how such integration can contribute to pathways toward UHC. Integration has been variously conceptualized at health system, service delivery, and consumer levels. Integration can be conceptualized based on the level of institutionalization of T&CM in national health systems (i.e. regulation of T&CM, education system, monitoring and health financial scheme). According to it, countries and areas of the Region can be categorized: countries with: ‘well-established integration strategies’; ‘in-process of developing and implementing integration policies’; ‘mixed-level of integration’; or ‘indigenous traditional medicine practiced outside the national healthcare system’. Integration of T&CM may offer pathways to advance five health system attributes essential to achieve UHC, namely: quality; efficiency; equity; accountability; and sustainability and resilience. It can contribute to improving quality of healthcare services through regulation of T&CM products, practitioners and services used by communities; meeting population needs in ageing population and managing non-communicable diseases; improving equitable access to care through health insurance coverage of T&CM; improving accountability by monitoring and use of data for informed-policy decisions on T&CM; and strengthening sustainability and resilience through maximizing potentials of T&CM in managing outbreaks of infectious diseases and disasters. Depending on the level of integration, actions to move forward integration of T&CM as a pathway toward UHC will be various.

Background Cognitive impairments in patients with depressive disorders have a negative impact on their daily skill functioning and quality of life. In this study, we evaluated the cognitive profiles and associated factors of patients with depressive disorders with the Brief Assessment of Cognition in Affective Disorders (BAC-A). Methods This cross-sectional study consisted of 75 patients with depressive disorders (56 patients with major depressive disorder (MDD) and 19 patients with depressive disorder NOS or dysthymic disorder (non-MDD)). We evaluated the participants’ cognitive functions at euthymic status using the BAC-A. The BAC-A includes six subtests derived from the Brief Assessment of Cognition in Schizophrenia (BAC-S) and Affective Processing Tests. The current severity of depressive symptoms was assessed with the 17-item Hamilton Depression Rating Scale (HAMD-17), and we recorded any psychotropic drugs being used by the patients. Results We observed no differences in cognitive profiles in the MDD group and non-MDD group after adjusting for educational levels, severity of depression, and psychotropic drugs. Instead, the HAMD-17 scores were negatively correlated to cognitive performance in working memory, motor speed, verbal fluency, attention and processing speed, executive function, composite score, and the six indexes of the Affective Processing Test measured by the BAC-A. A longer illness duration was associated with worse performance of four indexes of the Affective Processing Test. Furthermore, benzodiazepine use was associated with a worse performance of verbal memory, and antidepressant use was associated with better motor speed performance. Conclusion The current severity of depressive symptoms and psychotropic drugs being taken, not the diagnosis category, are associated with cognitive impairments in patients with depressive disorders. Clinicians should pay particular attention to managing residual depressive symptoms and prescribing adequate psychotropic drugs in order to eliminate depressive patients’ cognitive deficits.

The rise of precision education has encouraged teachers to use intelligent diagnostic systems to understand students' learning processes and provide immediate guidance to prevent students from giving up when facing learning difficulties. However, current research on precision education rarely employs multimodal learning analytics approaches to understand students' learning behaviors. Therefore, this study aims to investigate the impact of teachers intervene based on different modalities of learning analytics diagnosing systems on students' learning behaviors, learning performance, and motivation in STEM collaborative learning activities. We conducted a quasi-experiment with three groups: a control group without any learning analytics system assistance, experimental group 1 with a unimodal learning analytics approach based on image data, and experimental group 2 with a multimodal learning analytics approach based on both image and voice data. We collected students' image or voice data according to the experimental design and employed artificial intelligence techniques for facial expression recognition, eye gaze tracking, and speech recognition to identify students' learning behaviors. The results of this research indicate that teacher interventions, augmented by learning analytics systems, have a significant positive impact on student learning outcomes and motivation. In experimental group 2, the acquisition of multimodal data facilitated a more precise identification and addressing of student learning challenges. Relative to the control group, students in the experimental groups exhibited heightened self-efficacy and were more motivated learners. Moreover, students in experimental group 2 demonstrated a deeper level of engagement in collaborative processes and the behavior associated with constructing knowledge.

Background: Virtual reality (VR) offers significant potential for hands-on learning environments by providing immersive and visually stimulating experiences. Interacting with such environments can bring numerous benefits to learning, including enhanced engagement, knowledge construction, and higher-order thinking. However, many current VR studies in hands-on learning tend to utilise one-way learning materials, limiting participants' ability to interact with and reflect on their actions and learning experiences. Moreover, these studies often neglect to assess learners' capacity to transfer their skills from VR learning to real-world scenarios. Therefore, this study aims to investigate participants' engagement, learning outcomes, higher-order thinking, and their ability to apply acquired skills in real-world contexts. Method and Objective: Participants were immersed in a hands-on learning environment in VR, where they received feedback and engaged in reflection during the learning process. This study recruited 68 university students to participate in the experiment, employing a quasi-experimental design. Participants experienced learning units both with and without reflection on the feedback. The theme of these learning units was related to embedded systems, encompassing topics such as the assembly of embedded components and Python programming. The investigation aimed to assess whether reflection in VR could enhance cognitive levels, engagement, real-world hands-on tasks abilities, and higher-order thinking. Results: The research results indicate that in the VR hands-on learning environment, participants engage in reflection through the provided feedback, effectively enhancing their engagement, cognitive levels, and hands-on task abilities. Simultaneously, it also successfully assists participants in developing problem-solving skills and critical thinking in higher-order thinking. Conclusions: Participants actively engaged in reflection on their own learning tasks and actions within the hands-on learning environment, enabling them to develop a deeper understanding of the learning material and enhance their real-world hands-on tasks abilities, we encourage the integration of reflection strategies in VR learning environments for hands-on learning, as they can yield positive benefits for learners.

Abstract Background Tardive akathisia (TA) is a subtype of tardive syndrome, and its etiology is still uncertain. Sevikar is an anti-hypertensive agent containing both amlodipine and olmesartan, and has never been reported to have an adverse reaction in patients with tardive syndrome. Case presentation A 57-year-old woman who took Sevikar for hypertension for 10 years developed TA one and a half years before receiving any psychiatric treatment. After switching from Sevikar to bisoprolol, she reported obvious improvement in her akathisia. Conclusions It is noteworthy that her TA developed before receiving any antidepressant medication, and that her TA improved after discontinuation of Sevikar. In light of these pharmacodynamic properties, it is therefore concluded that use of amlodipine and olmesartan might have caused TA in this patient. We reported this rare case to remind clinicians to be aware of possible akathisia when using amlodipine and olmesartan in combination as anti-hypertensive agents.

Virtual reality (VR) provides a unique platform for interactive learning experiences, enhancing learning, particularly in hands-on courses. However, the visual load of VR and the lack of guidance and interaction from physical teachers or peers can pose challenges for learners in self-regulated learning (SRL) and learning motivation. This study designed feedback in the VR learning environment based on the signaling principles of Cognitive Theory of Multimedia Learning (CTML) to investigate learners' SRL, learning motivation, cognitive levels, and their abilities to handle real-world scenarios. We developed a VR hands-on learning course on the Artificial Intelligence of Things (AIoT) and conducted two real-world AIoT hands-on tasks, implementing a quasi-experimental study with 71 university students. Participants were randomly assigned to either the experimental group or the control group. The experimental group received three types of feedback signals (gaze, progress, and decision) designed based on signaling principles, while the control group received no feedback. The results showed that the experimental group exhibited significantly higher levels of SRL and learning motivation compared to the control group after VR learning. The feedback group also performed better in terms of cognitive levels and real-world hands-on tasks.

While research has shown that students' epistemic beliefs can be a strong predictor of their academic performance, cognitive abilities, or self-efficacy, studies of this topic in computer education are rare. The purpose of this study was twofold. First, it aimed to validate a newly developed questionnaire for measuring students' epistemic beliefs about computer programming at middle school level. Second, the study aimed to understand how students' epistemic beliefs predict their computational thinking disposition and computer programming self-efficacy. A total of 406 middle school students completed a survey consisting of three research instruments: the Computer Programming Epistemic Belief Inventory (CPEBI), the Computational Thinking Scale (CTS), and the Computer Programming Self-Efficacy Scale (CPSES). The results indicated that the epistemic belief of "uncertainty" was a significant and positive predictor of the "abstraction" and "generalization" dimensions of computational thinking dispositions. In addition, the belief of "complexity" was an antecedent to three dimensions of computational thinking, namely, "algorithmic thinking," "evaluation," and "generalization." Only the "evaluation" dimension of CT disposition had significant and positive relationships with "programming self-efficacy." The roles of "uncertainty" and "complexity" of computer programming epistemic beliefs are discussed. Implications and suggestions for future computer programming education, especially for young students, are provided.

Research purposes and design: This study aimed to compare the effects of different explicit approaches used in modeling-based instruction on students' understanding of scientific models and modeling (USMM). In Study 1, a self-study approach was compared to a preliminary explicit approach. In Study 2, preliminary explicit approach and embedded explicit approach were compared. Methods: For the data analysis, t tests and analysis of covariance (ANCOVA) were used to compare students' USMM under the conditions of using different explicit approaches. Findings: Results showed that in the first study, no statistically significant difference was found between self-study approach and the preliminary explicit approach in any of the USMM subscales. In the second study, students who learned with the embedded explicit approach had better understandings in all subscales of USMM, but not in the "changing nature of scientific models" (CNM) subscale, than those who learned with the preliminary explicit approach. Through qualitative analysis of the data, categories and examples of the teacher's embedded epistemic guidance were illustrated. Suggestions for future professional development and research instrument design are provided. changing nature of scientific models

Science, Technology, Engineering, and Mathematics (STEM) education is essential for developing future-ready learners in both secondary and higher education levels. However, as students transition to higher education, many encounter challenges with independent learning and research. This can negatively impact their Higher-Order Thinking Skills (HOTS), engagement, and practical expertise. This study introduces a solution: Computational Thinking Scaffolding (CTS) in the Jupyter Notebook environment, designed to enhance STEM education at the tertiary level. CTS incorporates five phases: Decomposition, Pattern Recognition, Abstraction, Algorithm Design, and Evaluation. Utilizing a quasi-experimental method, we assessed the impact of CTS on the HOTS, engagement, and practical skills of undergraduate and postgraduate students. Our findings hold substantial relevance for university educators, academic advisors, and curriculum designers aiming to enhance students' HOTS and hands-on capabilities in STEM disciplines. The results validate the effectiveness of CTS in elevating tertiary STEM learning outcomes, and they spotlight the adaptability of the Jupyter Notebook as a valuable tool in higher education. In conclusion, our research underscores the merits of CTS for improving outcomes in higher STEM education and sets a benchmark for future endeavors in this domain.

In the evolving landscape of higher education, challenges such as the COVID-19 pandemic have underscored the necessity for innovative teaching methodologies. These challenges have catalyzed the integration of technology into education, particularly in blended learning environments, to bolster self-regulated learning (SRL) and higher-order thinking skills (HOTS). However, increased autonomy in blended learning can lead to learning disruptions if issues are not promptly addressed. In this context, OpenAI's ChatGPT, known for its extensive knowledge base and immediate feedback capability, emerges as a significant educational resource. Nonetheless, there are concerns that students might become excessively dependent on such tools, potentially hindering their development of HOTS. To address these concerns, this study introduces the Guidance-based ChatGPT-assisted Learning Aid (GCLA). This approach modifies the use of ChatGPT in educational settings by encouraging students to attempt problem-solving independently before seeking ChatGPT assistance. When engaged, the GCLA provides guidance through hints rather than direct answers, fostering an environment conducive to the development of SRL and HOTS. A randomized controlled trial (RCT) was employed to examine the impact of the GCLA compared to traditional ChatGPT use in a foundational chemistry course within a blended learning setting. This study involved 61 undergraduate students from a university in Taiwan. The findings reveal that the GCLA enhances SRL, HOTS, and knowledge construction compared to traditional ChatGPT use. These results directly align with the research objective to improve learning outcomes through providing guidance rather than answers by ChatGPT. In conclusion, the introduction of the GCLA has not only facilitated more effective learning experiences in blended learning environments but also ensured that students engage more actively in their educational journey. The implications of this study highlight the potential of ChatGPT-based tools in enhancing the quality of higher education, particularly in fostering essential skills such as self-regulation and HOTS. Furthermore, this research offers insights regarding the more effective use of ChatGPT in education.

Building on the long-standing tradition of challenging oppression and questioning whose interests are being served in the field of language education, we report on a study that involved a group of U.S.-based graduate students who collaborated with a ninth-grade English teacher in Nepal. The study comes out of a larger project that sought to internationalize the curriculum of a graduate educational linguistics course at a U.S. university. At the heart of this internationalizing curriculum endeavour was a commitment to expose graduate students in the U.S. to the issues of language teaching outside of the U.S. This was done through co-designing of a unit of lessons, with six graduate students meeting virtually with their teacher partner, Ditya, in Nepal over the course of a semester. The graduate students and Ditya constitute our research participants. The graduate student participants learned about the need to develop pedagogical materials that were relevant to the local context in Nepali classroom, and not attempt to transplant a Western-centric curriculum onto the Nepali classroom. In keeping with recent calls to decolonize higher education, we illustrate how critical theory in general and decolonizing pedagogy in particular can be infused into a U.S. graduate curriculum by drawing on the rich, indigenous knowledge and resources of a teacher collaborator from the Global South. We do this by reporting how this critical, decolonizing goal was realized through collaborative professionalism, which is characterized by the sharing of knowledge, skills, and experience to improve student achievement, reflection, dialogue and collective responsibility.