Search Results (41)

Large language models (LLMs) offer new opportunities for lesson planning, remediation, and personalized practice, but deploying them in real educational settings remains challenging for two reasons. First, direct use of learner interaction traces can expose sensitive information about student knowledge states and behavioral patterns. Second, unconstrained generation can produce recommendations that are pedagogically inconsistent with the adopted curriculum, such as skipping prerequisite concepts or drifting outside the prescribed textbook scope. We propose PrivPath, a stage–subject–textbook-aligned framework for privacy-preserving curriculum planning that explicitly separates on-device learner modeling from server-side content generation. Its core module, Tri-Index Private Path Planning (TIPP), first restricts planning to a scoped curriculum graph defined by the target educational context, then privatizes learner mastery summaries under local differential privacy before transmission, and finally computes a curriculum-feasible instructional path that is coupled with evidence-grounded constrained generation. This design preserves personalization while reducing reliance on raw student traces and improving controllability of the generated teaching sequence. Experiments on three educational interaction datasets paired with open-textbook curriculum graphs show that PrivPath substantially improves structural validity and privacy robustness. In particular, it raises graph feasibility from 82.5% to 99.2% relative to TriIndex-RAG, improves the offline pedagogical utility proxy $\Delta$AUC from 0.013 to 0.018, and lowers membership inference AUC from 0.74 to 0.52 at ${\epsilon }_{\mathrm{loc}}=1.0$. These results suggest that curriculum-aligned path planning, privacy-preserving learner adaptation, and practically useful LLM-based educational generation can be achieved within a unified framework. Full article

Teacher shortages have become a global phenomenon, affecting educational systems across many countries. However, the strategies adopted to address it differ considerably. This study gives a first, detailed account of the reasons and effects of teacher shortages in Austria. For this purpose, a number of documents were analysed: 120 newspaper reports (to mirror the public debate), 43 parliamentary questions and ministerial responses (to mirror the policy debate), and relevant national statistics (to mirror the current situation and remedial measures by quantitative indicators). This allows a first comprehensive synthesis of public debate, policy developments, and research—comparable to country reports for other countries but currently missing for Austria. The findings of these multiple sources reveal that, following a period in the early 2000s with sufficient applicants for teaching positions, Austria gradually experienced an emerging teacher shortage. Initial responses were ad hoc, relying on measures such as increased overtime and the employment of underqualified teaching staff. More comprehensive strategies were introduced only in 2022, including a public image campaign for the teaching profession, reforms in teacher education, and new pathways for career changers. The study concludes by discussing implications for the teaching profession, school practice, and the teacher education system. Full article

Background: Lifestyle challenges such as prolonged sitting, irregular dietary habits, high stress levels, and lack of physical activity have become increasingly common among working professionals. All these factors contribute to the risk of chronic diseases such as diabetes, heart disease, obesity, and high blood pressure, which in turn result in reduced work performance and quality of life and may further affect health services access through increase healthcare needs. The teaching environment, like many other work environments, is mentally, emotionally, and practically demanding, and it puts extra pressure on those who work in it. Academicians, who devote themselves to guiding young minds, often make unhealthy daily choices and face significant work-related stress, which can lead to serious long-term health problems. This review highlights that health and well-being are shaped not by a single factor such as diet, work patterns, or habits, but by their combined effect. Methods: A study of around 113 studies has highlighted that academicians usually feel drained and physically exhausted. Result: The factors like prolonged fasts, insufficient water intake, long-standing hours, long and continuous talking, and extended periods in the sitting position have added to their stress levels at the workplace. The most critical finding is that these factors do not affect in isolation but impact as a combined interaction. These issues influence each other, thus increasing the vulnerability to lifestyle disorders. Conclusions: This critical problem can be addressed with a Multimodal Assessment Framework that integrates teachers’ data on dietary habits, workplace ergonomics, sleep quality, and levels of physical activity. The presented work also proposes a statistical technique with an Artificial Intelligence (AI) model, and generates Vulnerability Quotient (VQ) that show lifestyle disease-related exposure of the teachers, which may be further used to provide remedial interventions. These insights can further guide institutions and policymakers to design healthier, supportive, and sustainable teaching environments. Full article

This study aims to address the challenges junior high school students often encounter when learning abstract spatial vector concepts. By developing and implementing a virtual robotic system, this research intends to improve students’ spatial reasoning, deepen their conceptual understanding, and increase engagement through an interactive, visual, and experiential learning environment that remedies the shortcomings of traditional teaching methods. The system was developed with the Unity Game Engine to deliver 3D visualization, interactive manipulation, and real-time feedback, thereby enhancing conceptual learning. In addition, the instructional design employed the ADDIE model (Analysis, Design, Development, Implementation, Evaluation) to enhance students’ understanding of spatial vector concepts. A quasi-experimental design was conducted involving 60 eighth-grade students divided evenly into experimental and control groups. Pre- and post-tests—including achievement assessments, learning attitude questionnaires, and cognitive load scales—were administered to evaluate learning outcomes. The main findings are as follows: (1) The experimental group demonstrated significantly higher learning achievement compared to the control group. (2) Both groups showed improvements in mathematics learning attitudes, with the experimental group exhibiting greater gains in practicality and confidence. (3) Although the experimental group experienced a slightly higher cognitive load, this difference was not statistically significant. (4) The experimental group reported high satisfaction with the system, especially in perceived usefulness. This study demonstrates that integrating virtual reality with the ADDIE model can substantially enhance learners’ conceptual understanding and motivation. Full article

Background/Objective: The use of artificial intelligence to assist in medical applications is an emerging area of investigation and discussion. The researchers studied whether there was a difference between homeopathy guidance provided by artificial intelligence (AI) (automated) and live professional practitioners (live) for acute illnesses. Additionally, the study explored the practical challenges associated with validating AI tools used for homeopathy and sought to generate insights on the potential value and limitations of these tools in the management of acute health complaints. Method: Randomly selected cases at a homeopathy teaching clinic (n = 100) were entered into a commercially available homeopathic remedy finder to investigate the consistency between automated and live recommendations. Client symptoms, medical disclaimers, remedies, and posology were compared. The findings of this study show that the purpose-built homeopathic remedy finder is not a one-to-one replacement for a live practitioner. Result: In the 100 cases compared, the automated online remedy finder provided between 1 and 20 prioritized remedy recommendations for each complaint, leaving the user to make the final remedy decision based on how well their characteristic symptoms were covered by each potential remedy. The live practitioner-recommended remedy was included somewhere among the auto-mated results in 59% of the cases, appeared in the top three results in 37% of the cases, and was a top remedy match in 17% of the cases. There was no guidance for managing remedy responses found in live clinical settings. Conclusion: This study also highlights the challenge and importance of validating AI remedy recommendations against real cases. The automated remedy finder used covered 74 acute complaints. The live cases from the teaching clinic included 22 of the 74 complaints. Full article

The Chickahominy T.R.U.T.H. (Trust, Research, Understand, Teach, and Heal) Project investigates water quality concerns, including potential contamination from a nearby landfill, and their corresponding health implications among residents of rural Charles City County, Virginia. This rural, majority-racial-minority county includes citizens of the Chickahominy Indian tribe. The T.R.U.T.H. Project utilizes a community-based participatory research approach and environmental justice-focused lens to study water quality and health; the present study represents the first comprehensive analysis of the drinking water quality of homes with domestic groundwater wells. We collected water samples from 121 participants located within a four-mile radius of the landfill, analyzing over 200 potential analytes that may affect water quality. Among the measured analytes, water pH, aluminum, iron, manganese, and hardness as CaCO₃ were most frequently identified as having ratings outside of established EPA limits (“Bad”). Logistic regression models demonstrated that proximity to streams near the landfill was associated with significantly greater odds of worse water quality for several analytes. Specifically, residing within a mile of these streams was associated with greater odds of “Fair” or worse turbidity (OR = 4.31, 95% CI 1.31–19.53) and zinc levels (OR = 2.63, 95% CI 1.23–5.86). Additionally, residing within half a mile of a proximate stream was linked with “Poor” or worse hardness ratings (OR = 10.71, 95% CI 1.64–86.96); residing within a mile of the landfill was associated with “Bad” water pH levels (OR = 10.50, 95% CI 1.16–95.68). Though many tested analytes did not have concerning ratings or were not significantly associated with proximity to the landfill or streams, the above findings suggest that anthropogenic factors, particularly landfill proximity, may influence water quality with regard to specific analytes. Therefore, addressing water quality through enhanced monitoring, contaminant remediation, and community education is crucial for restoring trust in drinking water and improving public health outcomes. Full article

The advancement of artificial intelligence (AI) has attracted attention across disciplines. Different research has revealed the role of AI and the outcomes of AI in education (AIEd). However, teachers need to use AI to cater to learner diversities in mathematics education, which needs exploration. Therefore, how different AI tools assist mathematics teachers in developing teaching materials for students was investigated in this study. Teachers were invited to utilize AI techniques to develop their teaching and learning materials. The findings can be used to enhance the remedial and enrichment measures in teaching secondary mathematics and construct a framework to help teachers with learner diversities with AI tools. Full article

This article examines the teaching of civic engagement in academic settings, focusing on its role in generating new knowledge and fostering social and personal action. The article proposes regulatory remedies to ensure a fair and balanced curriculum supporting diverse worldviews and productive discourse, promoting student civic participation. The legal principle of equal protection, enshrined in the Fourteenth Amendment, serves as the foundation. The Fourteenth Amendment emphasizes equal treatment and opportunities for all, including access to a well-rounded education. By incorporating its principles into education, the article highlights the need to promote fair, civic education that empowers all students to participate actively in their communities. I recommend regulatory remedies to solidify education’s nature and foster a balanced curriculum. The proposed remedies ensure that various worldviews are embraced, promoting productive and amicable discourse among students. Creating an inclusive learning environment also allows students to engage in critical thinking and develop a deeper understanding of diverse perspectives, ultimately enhancing their civic participation. Furthermore, the article emphasizes the importance of regulatory safeguards against biased or exclusionary educational practices to ensure that all students have equal educational opportunities, regardless of their background or beliefs. By eliminating barriers and promoting a fair educational system, students can develop the necessary knowledge and skills to contribute to their communities actively. By incorporating the legal principle of equal protection with respect to perspectives represented on campus, the article advocates for legal and regulatory remedies to promote a fair and balanced curriculum that supports diverse worldviews. Full article

Clinical reasoning is an essential competence of veterinary graduands. Unfortunately, clinical reasoning and, therefore, the quality of provided veterinary medical services are prone to bias, difficulties, and errors. The literature on biases, difficulties, and errors in clinical reasoning in veterinary medical education is scarce or focused on theoretical rather than practical application. In this review, we address the practicality of learning and teaching biases, difficulties, and errors in clinical reasoning to veterinary learners utilizing a practical example of a cow with a prolapsed uterus complicated by hypocalcemia and hypomagnesemia. Learners should be guided through all of the stages of clinical reasoning as much as possible under direct supervision. The common clinical biases, difficulties, or errors in veterinary medical encounters may differ between stages of development of the learner, with more difficulties occurring in earlier stages (Observer, Reporter, ±Interpreter) but more heuristic biases occurring at later stages (Manager, Educator, ±Interpreter). However, clinical errors may occur at any learner development stage. Therefore, remediation of clinical biases, difficulties, and errors in veterinary medical encounters should use strategies that are tailored to the level of development of the learner, but also to the specific encounter (e.g., client, patient, and context). Full article

This article explores the historical and contemporary evolution of turbat al-ḥusayn, the sacred soil of Karbala, as a central element in shaping Shīʿī identity and ritual practices. From the early Islamic centuries, turbat al-ḥusayn has served not only as a symbol of healing and blessing but also as a key component of Shīʿī collective memory. The paper examines the development of turbat rituals across three significant periods: pre-Safavid, post-Safavid, and post-revolutionary Iran. During the pre-Safavid period, including the medieval Islamic centuries, the sanctification of turbat evolved through the efforts of Shīʿī Imams such as al-Bāqir and al-Ṣādiq, who integrated it into the theological framework of wilāyah (guardianship) and Shīʿī ritual practices. This period also witnessed the gradual codification of its ritualistic and medicinal uses in foundational Shīʿī texts. During the Safavid era, turbat became institutionalized as a marker of Shīʿī identity, with its economic significance expanding through the production of prayer tablets and rosaries. Following the 1979 Islamic Revolution in Iran, turbat was reinterpreted as a symbol of martyrdom and resistance, aligning with revolutionary ideologies and narratives that paralleled the sacrifices of Karbala with contemporary struggles. The COVID-19 pandemic introduced new dimensions to turbat’s role, with its promotion as a medicinal remedy by religious figures, despite lacking historical precedent in traditional Shīʿī teachings. These developments illustrate how turbat al-ḥusayn continues to be dynamically recontextualized in response to modern challenges. The study concludes that turbat al-ḥusayn transcends its ritualistic and spiritual origins, serving as a flexible and enduring symbol of Shīʿī identity. Its evolving interpretations underscore the interplay between tradition and modernity, highlighting its ongoing relevance in both devotional life and socio-political discourse. Full article

In knowledge structure theory (KST), an individual’s knowledge state represents the items that the individual can completely solve. Based on the differences in individuals’ latent cognitive competence, polytomous knowledge states can be used to partially represent individuals to solve items. This paper explores the construction of polytomous knowledge states and polytomous knowledge structures on a polytomous knowledge domain $Q\times L$. A quasi-ordinal polytomous knowledge space and a polytomous knowledge space can be induced by two different entail relations, respectively. When the polytomous knowledge structure $(Q,L,\mathcal{K})$ on $Q\times L$ is determined, accurately evaluating an individual’s polytomous knowledge state is the key to providing learning guidance and taking teaching remedial measures for the individual. Therefore, we study the basic assessment procedure for a given polytomous knowledge structure, and a concrete example is designed to illustrate the method presented in this paper. Full article

The current talent training system for the environmental engineering major (EEM) at local colleges faces significant challenges, including undefined training objectives, an incomplete curriculum, inconsistent practical teaching platforms, and homogeneous teaching teams. To address these issues, this study introduces the ‘Four Styles’ cultivation system implemented at the EEM of Hubei Polytechnic University. This system integrates advanced environmental remediation technologies into environmental engineering education through the development of a ‘1 + multiple’ curriculum, the establishment of ‘cloud + field’ practical platforms, and the formation of a diverse ‘1 + 2’ teaching team. The effectiveness of this system was evaluated using self-assessment scores from graduates and employer satisfaction ratings. Results showed that graduates rated their application ability with an average score of 3.96 ± 0.11, with the highest scores in work ethics (4.14), lifelong self-learning (4.11), and teamwork (4.09). Employer satisfaction with graduates’ abilities averaged 81.6 ± 2.33%, with the highest ratings for work ethics (86.0%), teamwork (85.5%), and lifelong self-learning (84.7%) Despite these successes, areas for improvement were identified, including better training in analyzing engineering problems (3.79) and mastering modern tools (3.79). These findings suggest that the ‘Four Styles’ cultivation system effectively enhances the practical skills of EEM students while identifying areas for future curriculum development. Full article

Whilst the benefits of telehealth were identified during the COVID-19 pandemic, we noted barriers to its use at a vital time. Through a health service improvement approach, we sought to increase allied health professional capability in telehealth, but we also sought to understand if there were risks associated with its use. We designed and implemented tools to evaluate allied health professional competence and confidence in using telehealth with private and public patients in a metropolitan teaching hospital setting. With an emphasis on technology capability, we undertook audits over three consecutive years (2020 to 2022) of allied health professional telehealth occasions of service reporting on compliance with the audit criteria and investigating staff confidence in undertaking telehealth sessions using a co-designed survey. The audit tool and confidence survey results were used to identify risk factors to telehealth service delivery using a Modified Health Failure Modes, Effects Analysis. Although confidence levels were relatively high among staff, confidence in managing safety factors and technology risks associated with telehealth were not initially verified by the audit findings. Remedial efforts resulted in service improvements in many identified risk factors, yet technology performance and its troubleshooting remained a primary variable in the ability of staff to comply with the requirements of the real-time audits. Health workers using telehealth should have training to engage safely and effectively in telehealth care and the technology. Full article

In e-learning systems, even though the automatic detection of learning styles is considered the key element in the adaptation process, it does not represent the main goal of this process at all. Indeed, to accomplish the task of adaptation, it is also necessary to be able to automatically select the learning objects according to the detected styles. The classification techniques are the most used techniques to automatically select the learning objects by processing data derived from learning object metadata. By using these classification techniques, considerable results are obtained via several approaches and consist of mapping the learning objects into different teaching strategies and then mapping these strategies into the identified learning styles. However, these approaches have some limitations related to robustness. Indeed, a common feature of these approaches is that they do not directly map learning object metadata elements to learning style dimensions. Moreover, they do not consider the fuzzy nature of learning objects. Indeed, any learning object can be suitable for different learning styles at varying degrees of suitability. This highlights the need to find a way to remedy this shortcoming. Our work is part of the automatic selection of learning objects. So, we will propose an approach that uses the fuzzy classification technique to select learning objects based on learning styles. In this approach, the metadata of each learning object that complies with the Institute of Electrical and Electronics Engineers (IEEE) standard are stored in a database as an Extensible Markup Language (XML) file. The Fuzzy C Means algorithm is used, on one hand, to assign fuzzy suitability rates to the stored learning objects and, on the other hand, to cluster them into the Felder and Silverman learning styles model categories. The experiment results show the performance of our approach. Full article

It is commonly known that the present systems and techniques used in education are outdated. In 1983, UNESCO had already called attention to this, calling present techniques archaic and inefficient. Though a lot of new developments have been achieved and a lot of commendable work has been carried out to remedy particular shortfalls in present systems, no literature was found that develops a concise and complete model for an education approach that maps the use of emergent technologies and techniques to improve on shortfalls in present teaching and learning paradigms. This paper reviews emergent technologies and techniques and their impacts and successes, to propose a combined model for online education to improve the effectiveness, accessibility and impact of teaching and learning activities. This paper concludes by presenting the possible future scope of education and employment structures by examining the possible impacts of the proposed model. Full article