Suitable Resources Research Articles

Incorporation of Nanocatalysts for the Production of Bio-Oil from Staphylea holocarpa Wood

Biomass has been recognized as the most common source of renewable energy. In recent years, researchers have paved the way for a search for suitable biomass resources to replace traditional fossil fuel energy and provide high energy output. Although there are plenty of studies of biomass as good biomaterials, there is little detailed information about Staphylea holocarpa wood (S. holocarpa) as a potential bio-oil material. The purpose of this study is to explore the potential of S. holocarpa wood as a bio-oil. Nanocatalyst cobalt (II) oxide (Co3O4) and Nickel (II) oxide (NiO) were used to improve the production of bio-oil from S. holocarpa wood. The preparation of biofuels and the extraction of bioactive drugs were performed by the rapid gasification of nanocatalysts. The result indicated that the abundant chemical components detected in the S. holocarpa wood extract could be used in biomedicine, cosmetics, and biofuels, and have a broad industrial application prospect. In addition, nanocatalyst cobalt tetraoxide (Co3O4) could improve the catalytic cracking of S. holocarpa wood and generate more bioactive molecules at high temperature, which is conducive to the utilization and development of S. holocarpa wood as biomass. This is the first time that S. holocarpa wood was used in combination with nanocatalysts. In the future, nanocatalysts can be used to solve the problem of sustainable development of biological resources.

Causes of Subpar Academic Achievement of Public Basic Schools with Emphasis on Basic Education Certificate Examination (BECE): A Case Study of Sagnarigu Municipality in Northern Region, Ghana

The study was set up to determine the causes of poor academic achievement in the Basic Education Certificate Examination (BECE) in the Sagnarigu Municipality in Tamale, Northern Region, Ghana. The study sought to identify the contributing causes of such subpar learning outcomes and to provide some policy interventions to address them. For the study, two research questions were established. Data collection and analysis were done using a qualitative approach. In relation to the basic schools in the Sagnarigu Municipality, the study's accessible population included students, head teachers, teachers, parents, and municipal examination officers. As data sources, interviews and historical records were used. The researcher used the case study technique because he wanted to clearly understand why Sagnarigu Municipality students perform poorly on the BECE examination. Twenty (20) Junior High Schools were chosen purposively from the Municipality. The sample size was also chosen using a random sampling technique and included (10) head teachers, (20) teachers, (20) parents, (20) students, and (2) municipal education examination officers, making a total of (72) participants. The study discovered that the low academic accomplishment in the BECE was mostly caused by all inputs and processes, including teachers, the school environment, parents, and the students themselves. The highlighted school environmental problems included a dearth of teachers with advanced degrees, a lack of suitable physical and material resources to support teaching and learning, and teachers abusing their time spent in direct contact with students. Instances of routine tardiness and absenteeism to school, inability to complete the curriculum and inadequate exercises, assignments, and projects given to students, as well as low/inadequate motivation and pay from the employer, were found to be teacher factors that contributed to the low academic achievement. The student traits that I considered relevant included instances of tardiness and absenteeism, lack of parental or guardian support for homework at home, involvement in vices like internet fraud also known as "yahoo" or "game guys", going to movie theaters and dance clubs, and drug usage. Parents' inability to offer reading materials like textbooks and supplemental readers, their lack of engagement with their children's instructors, and their lack of participation in PTA activities were all factors in the home that affected students' academic performance. Given the foregoing, the study came to the conclusion that all stakeholders—including the government, nongovernmental organizations, teachers, parents, and students—must play their respective parts in addressing the causes of low achievement in the basic schools under consideration in the Sagnarigu Municipality.

Development of Interactive English Teaching Online Platform Based on Collaborative Filtering Algorithm

In order to better promote the development of Interactive English teaching, we develop the existing online teaching platform on the basis of an improved collaborative filtering recommendation algorithm and construct an online English teaching platform that can meet the needs of teaching interaction. With the help of the “hierarchical learning” mode, an interactive teaching model in the form of self-study is constructed to provide users with the most suitable English learning resources. A new method is used to search the nearest neighbor set intelligently for the target user as a supplement to its similarity. This algorithm can be used well in interactive English teaching mode. On this basis, the system module of this study mainly includes a communication page, course evaluation, collaborative editing, and resource sharing. This study also investigates the actual use of students. The results show that the interactive English online teaching platform can meet most of the students’ needs. In this study, the interactive English online teaching platform developed based on a collaborative filtering algorithm has a significant effect, which enhances the interactivity of teaching, improves the quality of English teaching, and increases the breadth of teaching.

Dispersal and distribution of a generalist predator in habitats with multiple food resources

The ability to locate suitable food resources affects fitness in animals. Therefore, movements are necessary to optimize foraging in habitats where food is distributed in patches of different qualities. The aim of this work was to investigate the dispersal and distribution of females and males of the omnivorous mirid D. hesperus in mesocosms composed by food patches of different values in terms of fitness. In agreement with the Marginal Value Theorem (MVT) and the Ideal Free Distribution (IFD), individuals were expected to aggregate in the highest quality patches. Besides, the proportion of individuals in patches was predicted to be proportional to fitness, and interference among individuals was expected to rise as the density of individuals increased. Emigration rates were predicted to be higher for low- than for high-quality patches, while the opposite was predicted for immigration. Three types of habitats each with different combinations of food resources were tested: (1) habitat including patches of tomato plants with no-prey, and patches infested with either mite or whitefly; (2) with no-prey and whitefly; (3) with no-prey and mites. Each type of habitat was set up in a tomato greenhouse compartment and replicated four times. Individuals were tracked by mark-recapture methods using luminous paintings. The number of females and males in whitefly patches was significantly higher than in mite and no-prey patches, but a significant interaction sex*habitat and sex*patch was found. In habitats with only one type of prey, D. hesperus adults fitted the IFD, while in mixed prey habitats their distribution diverged from IFD. Interference was found to be significant, with female fitness decreasing as their density increased. Emigration rates were significantly lower for whitefly patches with a significant interaction patch*sex; the opposite was found for immigration. This research shows that it is unlikely that D. hesperus forage according to the omniscient principle of IFD and MVT; in contrast, it strongly suggests that it uses some simple rules to make decisions about inter-patch movement, and emigration from habitats and patches.

The Sentiment is in the Details

Determining the sentiment in the individual sentences of a newspaper article in an automated fashion is a major challenge. Manually created sentiment dictionaries often fail to meet the required standards. And while computer-generated dictionaries show promise, they are often limited by the availability of suitable linguistic resources. I propose and test a novel, language-agnostic and resource-efficient way of constructing sentiment dictionaries, based on word embedding models. The dictionaries are constructed and evaluated based on four corpora containing two decades of Danish, Dutch (Flanders and the Netherlands), English, and Norwegian newspaper articles, which are cleaned and parsed using Natural Language Processing. Concurrent validity is evaluated using a dataset of human-coded newspaper sentences, and compared to the performance of the Polyglot sentiment dictionaries. Predictive validity is tested through two long-standing hypotheses on the negativity bias in political news. Results show that both the concurrent validity and predictive validity is good. The dictionaries outperform their Polyglot counterparts, and are able to correctly detect a negativity bias, which is stronger for tabloids. The method is resource-efficient in terms of manual labor when compared to manually constructed dictionaries, and requires a limited amount of computational power.

Infusing educational technologies in the heart of the university—A systematic literature review from an organisational perspective

AbstractEducational technologies have experienced unprecedented prominence on university agendas with many institutions motivated to keep the lessons learned from the COVID‐19 sparked transition with regard to online teaching. In response to this renewed interest in ensuring the longevity of educational technologies in higher education, this systematic review analysed the various organisational factors—for example, leadership, infrastructure, strategy—considered essential in the literature for the successful implementation of educational technologies. Specifically, we reviewed 1614 papers published in five prominent educational technology journals in the last decade. From this sample, we identified 47 papers that discussed organisational factors. Drawing on these studies, we constructed an organisational framework, which outlines the different organisational factors, actors and processes involved in implementing educational technologies. The identified organisational factors are structured into three main categories: (1) Leadership and Strategy, (2) Infrastructure and Resources and (3) Recognition and Motivation. Our aim was to further the scholarly understanding of the organisational layer involved in digital change as well as provide concrete recommendations for practitioners. Practitioner notesWhat is already known about this topic Previous research has stressed the importance of taking organisational factors such as infrastructure, leadership, strategy and staff commitment into account when implementing educational technologies. However, review papers have failed to systematically organise these studies to create a comprehensive understanding of the organisational factors involved in implementing educational technologies and ensuring their longevity at an institution. There is currently a high level of interest in how educational technologies can be implemented in the higher education landscape, as many institutions are facing the question of what lessons they can learn from the crisis and how they can continue on their path of digitalisation. What this paper adds This review paper addresses a gap in our scholarly understanding of the organisational layers involved in the implementation of educational technologies in higher education institutions (HEIs). This paper provides a framework on organisational factors, which influence the implementation of educational technologies in HEIs. This review paper demonstrates that bottom‐up and opinion leadership, support structures tailored to the need and time of faculty as well as recognition and incentives have the largest impact on a sustainable implementation of educational technologies in HEIs. Implications for practice and/or policy Universities should create structures that enable innovation and creativity by promoting bottom‐up and opinion leadership as well as shared decision‐making processes as they are important for the successful implementation of educational technologies in HEIs. Besides providing a reliable and suitable infrastructure, institutional support and resources in terms of technical advice and training tailored to specific needs, should be in place when planning the implementation of educational technologies in HEIs. The additional workload instructors face when implementing digital teaching should be recognised and incentivised as it strengthens instructor engagement which is crucial for the implementation of educational technologies in HEIs.

Distribution of Irrigated and Rainfed Agricultural Land in a Semi-Arid Sandy Area

Under water resource and terrain constraints, a certain scale threshold of irrigated and rainfed agricultural areas exists in semi-arid sandy areas. If this threshold is exceeded, water and soil resources will be unbalanced, and the ecological environment will deteriorate. Accurate assessment of the suitable scale of cultivated land in semi-arid sandy areas is of great significance for sustainable utilization of cultivated land resources and regional ecological security. Most existing research methods are based on water resource constraints and rarely consider terrain factors. Therefore, based on the principle of water balance and with the Horqin Left Wing Rear Banner as the research area, this study adopted a multi-objective fuzzy optimization model and relative terrain index analysis method to explore the appropriate spatial ratio of irrigation and rainfed agriculture. The results show that the area of irrigated agriculture in the study area is 77,700 hm2, and the appropriate scale is 91,700 hm2. The current area of dry farming is 184,600 hm2, and the suitable scale is 117,100 hm2. The results also show that the utilization efficiency of water and soil resources in irrigated agriculture was not optimal, rainfed agriculture exceeded its suitable scale, and water and soil resources were seriously unbalanced. However, the region of cultivated land that exceeds the appropriate scale is mostly located in an area with poor terrain, less precipitation, and other unsuitable conditions for cultivation, which is prone to abandonment, resulting in deterioration of the ecological environment. Therefore, the spatial layout of agricultural land use in the study area should be adapted to local conditions, and the water-saving structure of irrigated agriculture should be optimized to achieve the maximum comprehensive benefits. Dry farming should be controlled on a reasonable scale, and the part exceeding the appropriate scale should be returned to grassland to ensure sustainable development.

A Multi-Objective Approach for Optimizing Edge-Based Resource Allocation Using TOPSIS

Existing approaches for allocating resources on edge environments are inefficient and lack the support of heterogeneous edge devices, which in turn fail to optimize the dependency on cloud infrastructures or datacenters. To this extent, we propose in this paper OpERA, a multi-layered edge-based resource allocation optimization framework that supports heterogeneous and seamless execution of offloadable tasks across edge, fog, and cloud computing layers and architectures. By capturing offloadable task requirements, OpERA is capable of identifying suitable resources within nearby edge or fog layers, thus optimizing the execution process. Throughout the paper, we present results which show the effectiveness of our proposed optimization strategy in terms of reducing costs, minimizing energy consumption, and promoting other residual gains in terms of processing computations, network bandwidth, and task execution time. We also demonstrate that by optimizing resource allocation in computation offloading, it is then possible to increase the likelihood of successful task offloading, particularly for computationally intensive tasks that are becoming integral as part of many IoT applications such robotic surgery, autonomous driving, smart city monitoring device grids, and deep learning tasks. The evaluation of our OpERA optimization algorithm reveals that the TOPSIS MCDM technique effectively identifies optimal compute resources for processing offloadable tasks, with a 96% success rate. Moreover, the results from our experiments with a diverse range of use cases show that our OpERA optimization strategy can effectively reduce energy consumption by up to 88%, and operational costs by 76%, by identifying relevant compute resources.

A Personalized Recommendation System for English Teaching Resources Based on Learning Behavior Detection

When confronted with a plethora of resources, many students struggle to quickly filter out the content that is relevant to them. Because there are many English teaching resources and it is difficult to accurately recommend suitable teaching resources for students. Therefore, in this paper we suggest a personalized recommendation system for English teaching resources, which is founded on learning behavior detection. To begin with, a spatiotemporal convolutional network is introduced to effectively identify students’ online classroom behavior, and a global attention module is added to increase the model’s ability to learn global feature information. Furthermore, the identified characteristics of student behavior are incorporated into the recommendation module. Similarly, the differential evolution (DE) algorithm is implemented to the smoothing factor and kernel function center of a generalized regression neural network (CRNN) for resource recommendation mode, while taking into account the strong dependence of the GRNN training effect on the smoothing factor and the kernel function center. The smoothing factor and offset factor are optimized and solved, and the optimized smoothing factor and offset factor are used to recommend GRNN resources. Experiments show that the approach described in this work first has a high precision (i.e., 90.98%) in behavior recognition, and second, the recommendation performance is superior to both of the comparison algorithms (i.e., 85.23% and 78.33%), resulting in better resource recommendation accuracy. The fundamental goal of this work is to deliver several important guidelines for the informatization and intelligence of the English educational resources and services.

A Personalized Recommendation Method for Ethnic Music Teaching Resources Based on Video Tags

In order to improve the effect of ethnic music teaching and improve the recommendation accuracy of teaching resources, this paper proposes a personalized recommendation method for ethnic music teaching resources based on video tags. A national music teaching resource library is constructed as the resource source, and the K-nearest neighbor (KNN) algorithm is used to classify the teaching resources in the resource library. According to the results of resource classification, describe the characteristics of teaching resources, so as to recommend suitable teaching resources to corresponding students to meet individual needs. According to the main characteristics of tags, a tagging system is established, and at the same time, the decay of user interest over time is considered, and weights are assigned to user video interest tags in descending order of time, and the total user interest tag vector is calculated. In this paper, the obtained user total interest label vector is normalized. The vector space model is used to represent teaching resources and user interests, so as to realize personalized recommendation of teaching resources. The experimental results show that the accuracy rate of the proposed method is higher than 90%, the recall rate is more than 97%, and the F1 value is larger, and the convergence is better, reflecting the better recommendation effect of the method.

Network Optimization of Online Learning Resources from the Perspective of Knowledge Flow

To effectively share and recommend knowledge, the online learning platform needs to deliver the most suitable and valuable learning resources to the demanders through the best path at a low cost. The existing studies mostly focus on the evaluation of knowledge flow ability and the extraction of knowledge classification features, but rarely tackle the knowledge flow evolution and network optimization in the light of the management of online learning resources (OLRs). To solve the problem, this paper explores the network optimization of OLRs from the perspective of knowledge flow. Firstly, the evolutionary game of the implicit knowledge flow in the OLR network was analyzed. In addition, an optimization model of OLRs was constructed, according to the evolutionary game mechanism for the implicit knowledge flow in the OLR network based on knowledge sharing, and the self-organizing hierarchical reconstruction. Finally, the network optimization effect was rated, and the network optimization was proved effective, with the management of music OLRs as an example.

Supporting prospective mathematics teachers’ planning and teaching technology-based tasks in the context of a practicum course

The introduction of digital technologies into mathematics classrooms requires the creation of suitable technology-based mathematics resources, as well as educating and encouraging teachers to use these resources. This study examines four prospective secondary mathematics teachers' planning and teaching of technology-based mathematical tasks in the scope of a 14-week practicum course within a four-year mathematics education programme in Türkiye. Dynamic Geometry Task Analysis and Instrumental Orchestration frameworks have been chosen as the conceptual basis of the study. Action research towards a cyclical process is used to analyse how the incorporation of two frameworks in the process guide or support the development of the prospective teachers' classroom practices with the use of technology. The findings of the study indicate that using the technology specific frameworks in a practicum course was helpful to improve prospective teachers’ designing and teaching technology-based tasks. They showed different development, change and evaluation in their tasks based on their teaching experiences through the process.

Farming on Mars: Treatment of basaltic regolith soil and briny water simulants sustains plant growth.

A fundamental challenge in human missions to Mars is producing consumable foods efficiently with the in situ resources such as soil, water, nutrients and solar radiation available on Mars. The low nutrient content of martian soil and high salinity of water render them unfit for direct use for propagating food crops on Mars. It is therefore essential to develop strategies to enhance nutrient content in Mars soil and to desalinate briny water for long-term missions on Mars. We report simple and efficient strategies for treating basaltic regolith simulant soil and briny water simulant for suitable resources for growing plants. We show that alfalfa plants grow well in a nutrient-limited basaltic regolith simulant soil and that the alfalfa biomass can be used as a biofertilizer to sustain growth and production of turnip, radish and lettuce in the basaltic regolith simulant soil. Moreover, we show that marine cyanobacterium Synechococcus sp. PCC 7002 effectively desalinates the briny water simulant, and that desalination can be further enhanced by filtration through basalt-type volcanic rocks. Our findings indicate that it is possible to grow food crops with alfalfa treated basaltic regolith martian soil as a substratum watered with biodesalinated water.

Assessing the Needs of Victimized Adolescents in Therapeutic Residential Care in Spain

Children and adolescents in residential care often present with emotional and/or behavioral problems associated to previous adverse experiences such as abuse and neglect. Consequently, child welfare systems have developed therapeutic residential care (TRC) programs to address the most complex needs of this population. The aim of this study is to explore the characteristics of youths in TRC comparing them with those of youth in general residential care (GRC), and to detect the factors predicting referral to TRC programs. The sample consisted of 900 adolescents aged 12–17 years old (M = 15.57; SD = 1.33; 66.2% boys), from General Residential Care (n = 554) and Therapeutic Residential Care (n = 346). Profile information was collected through official files and an ad hoc questionnaire. Mental health problems were evaluated using the youth self-report (YSR). Significant sociodemographic differences were found between groups. Also, a higher frequency of emotional abuse and neglect, worse mental health, more breakdowns in child welfare measures and risk behaviors were found among adolescents in TRC. Sociodemographic and familial characteristics, features of the protective process and risk behaviors were associated to referral to TRC programs. Youths in GRC and TRC present with mental and behavioral problems that make it necessary to implement prevention programs and early detection procedures. Screening and evaluation of youth’s mental health and establishment of concrete criteria are suggested to ensure appropriate referral to the most suitable resource according to the individual needs of adolescents.

Enhancing the primary care pediatrician's role in managing psychosocial issues: a cross sectional study of pediatricians and parents in Israel

BackgroundPsychosocial issues are an integral part of children's health and well-being, and it is widely acknowledged that pediatricians should be involved in their management. We examined the current perception of the pediatrician’s role in the management of psychosocial problems in Israel from the perspective of parents and pediatricians, and identified possible barriers.MethodsWe assessed parents' and pediatricians' perspectives through a cross sectional survey. 1000 parents with children under 10 were randomly selected from a large database representing the Israeli population and phone-surveyed by a polling company. Due to a low response-rate (5.4%), there was an overrepresentation of married parents and underrepresentation of parents with primary or secondary education. 173 Pediatricians were recruited both at a medical conference and by a web-based questionnaire.Results55% of the parents reported they were concerned with at least one psychosocial problem, yet less than 50% of them discussed these issues with the pediatrician. 59.9% of the parents did not perceive psychosocial problems as relevant to the pediatrician's role. Pediatricians with some previous training related to psychosocial issues were more likely to report on a lack of professional confidence (p = .037) and insufficient available resources (p = .022) as barriers to their involvement, while pediatricians who had no training were more likely to report on the parents' perception of their role as the barrier to involvement (p = .035).ConclusionsParents tend to avoid the discussion of psychosocial concerns in pediatric settings due to their perception that it's irrelevant to the pediatrician's role. Trained pediatricians feel unconfident in their ability to manage psychosocial issues and report on a lack of suitable resources. These findings suggest current pediatric mental-health training is insufficient to equip pediatricians with the knowledge and skills required to their involvement in psychosocial problems, and imply necessary changes to environment of community-based pediatrics. In order to change the practice of pediatricians in the community to enable them to address a variety of psychological issues, appropriate training is needed, through all stages of the pediatrician’s professional life, including medical school, pediatric residency and continuous medical education.

Intelligent Sports Auxiliary Training Method Based on Collaborative Filtering Recommendation Algorithm

In recent years, people’s living standards are rising, and the demand for health is also rising. National physical exercise has become the current trend. Using personalized recommendation technology to screen appropriate information and assist people in sports training can improve the efficiency of users to obtain relevant information and improve users’ physical quality. Therefore, the collaborative filtering recommendation algorithm is optimized by combining bisection, and the intelligent recommendation model of sports training resources is constructed based on the algorithm. This paper uses the improved algorithm to calculate the similarity between users. Compared with other traditional algorithms, the user algorithm in this paper has higher accuracy and certain reference value. To sum up, the intelligent recommendation model of sports training resources proposed in the research can more accurately recommend suitable sports training resources for users, so as to assist users in correct sports training and improve users’ physical quality, which plays an improvement of the physical quality of the whole people in China.

Open education resources’ benefits and challenges in the academic world: a systematic review

PurposeOpen educational resources (OERs) are internet-based digital content that is used for academic purposes by instructors, students and researchers in the era of the information economy. Hence, this study aims to systematically review the literature, focusing on OERs’ benefits and challenges in the academic world.Design/methodology/approachThe relevant literature systematically reviewed following the preferred reporting items for systematic literature reviews and meta-analyses (PRISMA) guidelines. The pertinent literature was obtained from four main scholarly databases, and finally, 21 papers that met the inclusion criteria were included in this study.FindingsThe findings revealed that the key benefits of OERs include expanded access to knowledge, supporting lifelong learning, pedagogical benefits and enhancing students’ learning outcomes. However, the key challenges include lack of time to find appropriate resources, lack of awareness about the usage and copyrights, quality assurance and technological limitations and lack of organizational support.Practical implicationsThe practical and policy implications highlight the joint venture of academia and library professionals to help the students evaluating OERs, quality assurance, copyright issues and lifelong learning.Originality/valueEarlier studies missed few significant insights of OERs, such as they did not address the quality assurance of OERs; the issue of understanding of copy right (creative common license) challenges related with OERs; and lack of time for finding suitable resources. Hence, this study identified significance insights related with OERs.

Optimization strategy of national park resource utilization system—Take Bawangling Zone of Hainan Tropical Rain Forest National Park as an example

The national park with Chinese characteristics is the highest level of protection of a kind of natural protection, its establishment marks the park will implement the strictest ecological protection means. It is of great value to construct the utilization system of national park resources under the new natural protected area system in the new era to avoid the misunderstanding of “ecological protection only” and explore how to carry out the sustainable utilization of resources in the reform of national park system and mechanism. According to the analytic hierarchy process (AHP) and Delphi method, the evaluation framework, indicators, reference standards and weights of resource utilization under the national park system were determined in combination with the requirements of constructing the protected natural area system and the total value of resource ecosystem services (including harvest value, existence value and future value). Based on the application research of Bawangling zone of Hainan Tropical Rainforest National Park, the optimal resource utilization system in the future was proposed, and two optimization strategies of ecological adjustment of resource utilization system and construction of suitable resource utilization system were put forward.

Design thinking-based Data Analytic Lifecycle for improving management control in banks

ABSTRACT In developing countries, banks have been looking out for new ways to improve their performance using digital transformation. This research bases itself on critical methodology, in which, a Data Analytics Lifecycle based on the Design Thinking concept (DAL-DT) has been used to support management control systems, and propose ways to optimise employee incentives, capital budgeting, workforce planning systems, in the context of a commercial bank in Vietnam. In addition, our study also examines the organisational actors engaged in the application of DT initiatives through the social practice theoretical lens of Bourdieu, regarding habitus, capitals, and fields. The results reveal that although DAL-DT, in principle, provides effective strategic plans along with a cohesive corporate culture that supports the implementation of DT initiatives, there are some constraints to this innovative reform. For instance, the top management of commercial banks in developing nations seem to display a lack of willingness and misunderstanding of the concept of DT, add to that the lack of suitable resources coupled with over-expectations.

The Effect of Pandemic-Related Economic Disruption on Young Adolescents in Ireland.

The sudden health and economic crisis brought about by the COVID-19 pandemic affords an opportunity to examine the impact of economic disruption to children and families. Any negative effects on the well-being of children are important to consider in relation to both short- and long-term outcomes. Using pre-pandemic and mid-pandemic waves of the longitudinal Growing Up in Ireland study, we examined whether the impact of economic disruption was equivalent for families who were (or were not) financially vulnerable pre-pandemic. We then investigated whether economic disruption was associated with a negative effect on the emotional well-being of 12-year-olds, and if there was evidence for such a negative effect being mediated through a lack of material resources or strain on family dynamics. Our results indicated that middle-income rather than lowest-income families experienced the most economic disruption, likely reflecting the sector-specific nature of business closures in the pandemic. Families who were financially vulnerable pre-pandemic were less likely to have had suitable resources for homeschooling. Both falls in income and strain in family relationships, such as arguing more with their parents, were associated with poorer scores on a measure of the child’s emotional well-being. The emergency income support payment introduced at the start of the pandemic appeared to have a protective effect on the association between family income loss and child well-being, which has wider implications for policy on child poverty.