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This case study explores how universal design for learning (UDL)-informed online instruction modules developed during COVID-19 can better support student information literacy outcomes. This study will also examine how hybrid learning lends itself to UDL and may resolve some of the issues within library instruction.

This case study explores how a team of librarians at Utah State University developed three UDL-informed modules to support library instruction and hybrid learning during the height of the COVID-19 pandemic. A survey was sent to composition instructors to understand how they utilized the three new UDL-informed modules and if the modules helped their students reach information literacy outcomes.

Findings from this case study describe how academic libraries should adopt the UDL framework to support best practices for online learning as well as inclusive pedagogies. The findings indicate that the UDL-informed modules developed for hybrid instruction help students meet information literacy outcomes and goals.

The authors present a case study examining the current climate of information literacy instruction and UDL while providing actionable instructional practices that can be of use to librarians implementing hybrid instruction.

This study aims to investigate the effectiveness of hybrid learning, blended learning and face-to-face learning in remediating misconceptions among primary school teacher education students.

This research uses a quasi-experimental design, using a quantitative approach. Data were collected from 99 students using a pretest and posttest four-tier test.

Hybrid learning proved to be the most effective, achieving a remarkable 90.32% success rate in remediating students’ misconceptions, surpassing blended learning and face-to-face learning methods.

The data come from a single Indonesian university and focuses only on a science concept; therefore, the scope of findings may be limited.

The research suggests that applying the conceptual change (CC) model in all learning types, particularly hybrid learning, effectively remediates misconceptions. Educators can use this insight to design impactful teaching strategies that combine online and traditional components, accommodating diverse learning styles and needs.

This research suggests that applying CC model in all learning types is actually able to remediate misconceptions, though hybrid learning is found to be the most effective one.

This study addresses a research gap by investigating the effectiveness of different learning modes in rectifying misconceptions. Although prior studies have explored learning modes, few have directly compared hybrid, blended and face-to-face learning in correcting misconceptions. The findings offer insights for effective teaching strategies to address STEM-related misconceptions, benefiting educators in optimizing their approaches. Furthermore, the study’s implications extend to the broader academic community, contributing to evidence-based teaching practices in science education and the development of effective strategies for addressing misconceptions in STEM courses.

Using sentiment analysis (SA), this study aims to examine the impact of COVID-19 on mental health and virtual learning experiences among 1,125 students at a public Argentinean faculty.

A study was conducted during the COVID-19 pandemic, surveying 1,125 students to gather their opinions. The survey data was analysed using text mining tools and SA. SA was used to extract the students’ emotions, views and feelings computationally and identify co-occurrences and patterns in related words. The study also examines educational policies implemented after the pandemic.

The prevalent emotions expressed in the comments were trust, sadness, anticipation and fear. A combination of trust and fear resulted in submission. Negative comments often included the words “virtual”, “virtual classroom”, “virtual classes” and “professor”. Two significant issues were identified: teachers’ inexperience with virtual classes and inadequate server infrastructure, leading to frequent crashes. The most effective educational policies addressed vital issues related to the “virtual classroom”.

Text mining and SA are valuable tools for decision-making during uncertain times, such as the COVID-19 pandemic. They can also provide insights to recover quality assurance processes at universities impacted by health concerns or external shocks.

The paper makes two main contributions: it conducts a SA to gain insights from comments and analyses the relationship between emotions and sentiments to identify optimal educational policies. The study pioneers exploring the link between emotions, policies and the pandemic at a public university in Argentina. This area of research still needs to be explored.

This paper aims to investigate the effect of learning styles on HyFlex learning towards equity of learning in higher education.

A quantitative approach was used, with data collection through a structured online questionnaire. The study participants were undergraduate students (n = 451) studying at various public and private universities in Indonesia. Measurement analysis is used to test the validity of the instrument used. Analysis of structural equations is used to test the relationships between the constructs under study.

Survey instruments have satisfactory internal validity and consistency. The learning style of students in higher education positively influences the use of HyFlex’s three learning modalities. All three modalities of HyFlex learning positively affect learning equity, especially the asynchronous online modality. However, the synchronous online effect is insignificant. Active/reflective learning styles only affect face-to-face mode but do not significantly affect the two online modalities, synchronous and asynchronous. Some of the learning style dimensions have an indirect effect on equity through three HyFlex learning modalities. Face-to-face and online asynchronous mediate well the indirect relationship between learning style and equity. The impact of gender and higher education status was not shown to strengthen the relationship between learning styles, HyFlex learning modalities and equity.

This study will provide valuable understanding for lecturers, educators and developers to adapt and develop HyFlex learning strategies based on the positive dimensions of the Felder–Silverman learning style that can support equitable and inclusive learning. The study forms a foundation for researchers to investigate more constructs that could improve HyFlex learning in future studies.

This research is a pioneer in using learning styles to investigate trends in using three HyFlex learning modalities, particularly emphasising modalities that can provide equitable learning.

This chapter shares the challenges that scholars experienced during the pandemic and their responses to them. We find that participants responded to complex work and home challenges through ethics of grit and perseverance. Offering a caution against grit mindsets, we argue that academics would benefit from opportunities to develop fuller forms of resilience. To do so, we recommend that higher education institutions co-construct locally and culturally relevant conceptualisations of resilience and enact trauma-informed practice to better support academic resilience in their faculties.

This exploratory study aims to discover the different forms of challenges encountered by school stakeholders, including students, teachers, parents and management due to the coronavirus disease 2019 (COVID-19) pandemic.

Qualitative methodology was deployed for the study. A purposive sampling technique was used to select the respondents for a semi-structured interview. Data were examined using interpretative phenomenological analysis (IPA).

It was found that each stakeholder faced four different challenges: mental distress, physical immobility, financial crunches and technological concerns. Findings suggest that teachers are experiencing higher financial, technological and physical challenges as compared to other stakeholders followed by parents.

This paper discusses the major challenges faced by each stakeholder along with the opportunities. These findings will be useful for educationists, regulatory authorities, policymakers and management of educational institutions in developing countries to revisit their policy frameworks to develop new strategies and processes for the smooth implementation of remote learning during a period of uncertainty.

This study aims to analyse the systemic risk emitted by all publicly listed commercial banks in a key emerging economy, India.

The study makes use of the Tobias and Brunnermeier (2016) estimator to quantify the systemic risk (ΔCoVaR) that banks contribute to the system. The methodology addresses a classification problem based on the probability that a particular bank will emit high systemic risk or moderate systemic risk. The study applies machine learning models such as logistic regression, random forest (RF), neural networks and gradient boosting machine (GBM) and addresses the issue of imbalanced data sets to investigate bank’s balance sheet features and bank’s stock features which may potentially determine the factors of systemic risk emission.

The study reports that across various performance matrices, the authors find that two specifications are preferred: RF and GBM. The study identifies lag of the estimator of systemic risk, stock beta, stock volatility and return on equity as important features to explain emission of systemic risk.

The findings will help banks and regulators with the key features that can be used to formulate the policy decisions.

This study contributes to the existing literature by suggesting classification algorithms that can be used to model the probability of systemic risk emission in a classification problem setting. Further, the study identifies the features responsible for the likelihood of systemic risk.

In 2022, the new normal era began to experience an increase in the number of tourists visiting Bali. Even though spiritual tourism was optimistic in attracting foreign visitors, most tourists come from nearby nations like Australia, indicating that the visits had a brief duration in this new era. To sustain the income of spiritual tourism advocates, it is possible to overcome the brief visit. Therefore, this study aims to analyze the collaboration of digitalized spiritual tourism activities in 2022. Data were collected through literature study, observation and in-depth interviews to determine the spiritual tourism hybrid business. The result showed that the digitalization of spiritual tourism builds an on-off hybrid method in marketing and products, thus developing a theory of the characteristics. This on-off hybrid provides a touch of experience for tourists to visit directly. Therefore, digitalization builds the resilience of spiritual tourism in the new normal era through marketing and service of hybrid products.

The gap between word-of-mouth marketing habits, direct product service and the tendency to digitize creates adaptation problems that take time. These problems make a practical contribution to building marketing and spiritual tourism products. The theoretical contribution is to build integrated marketing and spiritual tourism digital product concepts. A qualitative research method was adopted because the population of spiritual tourism is very limited. Therefore, it needs to be explored through experienced and knowledgeable informants. Literature study, observation and in-depth interviews were used to collect data. The literature study technique collects data from written sources, namely books, articles and internet sources. Observations were made by analyzing non-participants by recording various marketing activities and services for spiritual tourism products. Additionally, in-depth interviews were conducted with informants about digitalization in the new normal era.

The result showed that the digitalization of spiritual tourism builds an on-off hybrid method in marketing and products, thus developing a theory of the characteristics. This on-off hybrid provides a touch of experience for tourists to visit directly. Therefore, digitalization builds the resilience of spiritual tourism in the new normal era through marketing and service of hybrid products.

The method has successfully built digital and direct visit products. Digital products share knowledge, while direct visit products serve to gain hands-on experience. These products provide income for spiritual tourism actors. However, direct visit products are more emphasized to spread income, such as hotels, restaurants and souvenirs. This development provides a theoretical implication that the characteristics of tourism products can be enjoyed at the service provider’s premises and the area of origin of tourists with digital technology. Therefore, digitalization has changed the theory of the characteristics of tourism products from having to be enjoyed by service providers (Yoeti, 1991).

This study aims to explore the impact of hybrid learning on the satisfaction, effectiveness and academic performance of faculty and students in private universities in Kuwait. The study specifically addresses the challenges and experiences confronted by students and faculty members in utilising hybrid learning, assesses whether hybrid learning leads to improvements in academic performance and proposes measures for providing quality hybrid learning models in post-coronavirus disease 2019 (COVID-19) situations.

This study employed a quantitative method by collecting data via a questionnaire targeting private university students and faculty members in Kuwait. A total of 311 participants completed the survey.

The results show that students were in favour of the hybrid learning method and viewed this as being efficient when coming to satisfaction, academic performance and overall effectiveness; whilst faculty members have voiced the members' disfavour of the hybrid model of teaching as the members believe that the system is unjust, especially when coming to student's academic performance.

Although research related to hybrid learning in different parts of the world has existed for many years, the research only recently gained prominence in Kuwait due to the COVID-19 pandemic. This paper will likely be of interest to academics, policymakers, the government and universities as the pandemic continues to make hybrid learning more popular and, therefore, would increase awareness with regards to students' and faculty members' opinions about the system and proposed ways to resolve any issues.

With the rapid growth of the domestic lending industry, assessing whether the borrower of each loan is at risk of default is a pressing issue for financial institutions. Although there are some models that can handle such problems well, there are still some shortcomings in some aspects. The purpose of this paper is to improve the accuracy of credit assessment models.

In this paper, three different stages are used to improve the classification performance of LSTM, so that financial institutions can more accurately identify borrowers at risk of default. The first approach is to use the K-Means-SMOTE algorithm to eliminate the imbalance within the class. In the second step, ResNet is used for feature extraction, and then two-layer LSTM is used for learning to strengthen the ability of neural networks to mine and utilize deep information. Finally, the model performance is improved by using the IDWPSO algorithm for optimization when debugging the neural network.

On two unbalanced datasets (category ratios of 700:1 and 3:1 respectively), the multi-stage improved model was compared with ten other models using accuracy, precision, specificity, recall, G-measure, F-measure and the nonparametric Wilcoxon test. It was demonstrated that the multi-stage improved model showed a more significant advantage in evaluating the imbalanced credit dataset.

In this paper, the parameters of the ResNet-LSTM hybrid neural network, which can fully mine and utilize the deep information, are tuned by an innovative intelligent optimization algorithm to strengthen the classification performance of the model.