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The study directs attention to the psychological conditions experienced and knowledge management practices leveraged by faculty in higher education institutes (HEIs) to cope with the shift to emergency remote teaching caused by the COVID-19 pandemic. By focusing attention on faculty experiences during this transition, this study aims to examine an under-investigated effect of the pandemic in the Indian context.

Interpretative phenomenological analysis is used to analyze the data gathered in two waves through 40 in-depth interviews with 20 faculty members based in India over a year. The data were analyzed deductively using Kahn’s framework of engagement and robust coding protocols.

Eight subthemes across three psychological conditions (meaningfulness, availability and safety) were developed to discourse faculty experiences and challenges with emergency remote teaching related to their learning, identity, leveraged resources and support received from their employing educational institutes. The findings also present the coping strategies and knowledge management-related practices that the faculty used to adjust to each discussed challenge.

The study uses a longitudinal design and phenomenology as the analytical method, which offers a significant methodological contribution to the extant literature. Further, the study’s use of Kahn’s model to examine the faculty members’ transitions to emergency remote teaching in India offers novel insights into the COVID-19 pandemic’s effect on educational institutes in an under-investigated context.

This study aims at understanding how higher education institutions (HEIs) can contribute to sustainable development, by designing their programmes for bringing about a transformative impact on communities and students, and also to examine what alternative pedagogical approaches could be used for that. In the past decades, HEIs have increasingly created social innovation (SI) programmes, as a way to achieve United Nations Sustainable Development Goals. These community-oriented and field-based programmes are difficult to ally with conventional classroom education. This study explores how these programmes could integrate the participatory approach and what would be the benefits. It also investigates the effectiveness of the experiential learning approach for teaching sustainability.

A case study method is used to document SI projects initiated by an HEI programme in rural India.

It was found that the participatory approach contributes to empowering communities and also benefits the students in terms of academic, professional and personal growth. Empirical findings show that experiential learning is an efficient method to teach sustainability. Ultimately, both pedagogical approaches are found to be mutually beneficial.

This study fills a gap in the literature, by providing empirical evidence on how HEI can implement innovative educational strategies such as participatory approach and experiential learning in their programmes towards teaching sustainability. A conceptual model for HEI interested in developing similar programmes is also proposed. To the best of the authors’ knowledge, this study is one of the first studies focusing on the context of Indian HEI.

This study aims to explore how university language students evaluate different sustainability themes and examine the overall relevance of ecological, social, cultural and economic sustainability dimensions in language education.

A questionnaire was designed to study Finnish university language students’ (n = 55) order of priority for sustainability dimensions and their sub-themes and the justifications for the priority orders using a mixed methods design. Qualitative content analysis was conducted using NVivo software, and weighted rankings were used to analyse the quantitative data.

The findings of the study showed that language students evaluated the social and cultural dimensions as the most relevant in language teaching. In all dimensions, students approached sustainability mainly by prioritising larger issues and advancing towards smaller ones. Most non-directional responses appeared in the economic dimension. In addition, individual prioritising and justification approaches varied between different sustainability dimensions.

To the best of the authors’ knowledge, no previous studies have examined language students’ evaluations of and justifications for all four sustainability dimensions. The results highlight the need to use multiple, holistic approaches and systems thinking to incorporate education for sustainable development.

This article aims to identify and describe the research outcomes of studies that have employed the theoretical framework of lesson study (LS) in initial science teacher preparation programs. The focus is on the impact of LS on preservice teachers’ (PST) pedagogical and content knowledge, beliefs, routines and norms for professional learning and instructional practices.

A systematic approach was employed to compile pertinent literature by initially searching scholarly databases using specific keywords and phrases related to prospective science teacher preparation. Seventeen studies, encompassing both qualitative research and mixed-methods research, met the inclusion criteria and significantly contributed to the study’s findings. The authors independently conducted a coding process, applying a predefined code scheme based on Lewis et al.'s (2019) theoretical framework. The outcomes of the coding process were compared, and reliability tests were conducted to ensure the consistency of the coding.

In preservice science teacher (PSST) education, LS proves transformative, enriching pedagogical and content knowledge, shaping beliefs, fostering collaboration and influencing instructional practices. Its collaborative, reflective and iterative nature significantly contributes to the professional growth of preservice science teachers, preparing them for effective, student-centered teaching practices. Further investigation is warranted in the realm of LS, particularly concerning preservice science teachers and their beliefs.

This literature review on science PSTs is one of the pioneering efforts to employ the professional development framework crafted by Lewis et al. (2019).

This paper investigates the change talk (CT) strategies of the motivational interviewing (MI) technique and their relevance in achieving change goals within communities of practice (CoP), focusing on addressing real-world problems in today's complex world.

We employ a literature review and conceptual analysis to study the interactions and potential areas of complement between CT, MI and CoP theories.

This paper combines CT, MI and CoP theories to develop an integrated model called Facilitative Change Talk Leadership (FCTL).

This paper provides an innovative model (FCTL) to inform leadership educators about facilitating communities of practice. We provide a hypothetical case study to suggest how FCTL might foster collaborative inquiry and resilience amidst complex challenges. This case study illustrates a practical pathway for leadership educators and community practitioners to use this model in their own contexts.

This study explores consumers' perceptions of purchasing fast food items through online platforms. The central idea of this research is to practically assess the various elements impacting the consumers’ perceptions of online purchasing of fast food items and find out the factors with high importance and performance value.

A quantitative research approach was used to collect data from 402 participants in the form of a pen-and-paper-based method using a 5-point Likert scale. The collected data were analyzed using structural equation modeling (SEM) and importance-performance analysis. Theory of planned behavior and technology acceptance model form the basis for this research.

The findings indicate that constructs such as convenience, perceived quality and perceived healthiness positively influence consumers' perceptions of online purchasing of fast food items. On the other hand, competitive prices, discounts and promotions (CPDP) and online shopping experience have no significant impact on perceived value for money.

A constraint of this study is that it was done in a particular geographical location, which restricts the generalizations of the findings. The study only examined consumers' perceptions of online fast food purchasing, and future research could explore consumers' actual behaviors toward personalized fast food recommendations by online sellers.

The research supports and extends the existing literature by comprehensively understanding consumers' perceptions of purchasing fast food online. These findings can help online fast food sellers improve their services and develop targeted marketing strategies.

Coronavirus disease 2019 (COVID-19) pandemic has led to unprecedented mental health repercussions in the lives of every individual including university students. Therefore, study on students’ psychological state and its associated factors during the pandemic are of importance. This study aims to discuss the aforementioned issue.

An online survey was done on a total of 207 university students of Pakistan to collect information on socio-demographic characteristics, concerns or fears amidst COVID-19 and mental distress. Validated tools; Perceived Stress Scale (PSS), Generalized Anxiety Disorder Scale (GAD-7) and Patient Health Questionnaire (PHQ-9)-Depression were used to assess stress, anxiety and depression, respectively.

Around 14% of the university students were experiencing severe stress and anxiety, while 8.2% had severe depression. The authors found that stress among university students was related to psychiatric illness or symptoms (OR = 5.1: 1.1, 22.9) and unpredictability due to the pandemic (OR = 3.7: 1.2, 11.2). The significant determinants of anxiety were psychiatric illness/symptoms (OR = 6.6: 3.4, 12.9), implementation of public health measures (OR = 3.7: 1.1, 11.6), employed mothers (OR = 2.4: 1.1, 5.0) and lack of support from university administration (OR = 2.2: 1.0, 5.0). While the factors associated with depression included psychiatric illness or symptoms (OR = 8.4: 3.3, 21.5), unpredictability due to pandemic (OR = 6.8: 2.2, 20.7), impaired social support system (OR = 3.7: 1.3, 10.4) and studying without a scholarship (OR = 2.1: 1.0, 4.4).

These findings call for an urgent need to develop appropriate interventions and educational programs that could address the psychological needs of students.

The study directs the role of university and faculty in dealing the mental health needs of the student in COVID-19 pandemic time.

Educational programs are important that could address the psychological needs of students in COVID-19 pandemic.

University students reported mental distress during COVID-19 pandemic which shows that younger people are at risk of COVID-19 repercussions. Moreover, several stressors (i.e. impaired social support system and lack of support from universities) were revealed that could be mitigated by implementing appropriate strategies.

This study aims to explore motives behind teachers' and students' use of translanguaging and how they use it in Tanzanian public secondary school classrooms.

Data were collected using interviews and non-participant observations.

The findings indicate that translanguaging was used to facilitate content comprehension, promote classroom interaction and increase students' motivation to learn. Translanguaging was implemented using three strategies: paraphrasing an English text into Kiswahili, translating an English text into its Kiswahili equivalent and word-level translanguaging.

By highlighting the motivations for translanguaging and corresponding strategies associated with translanguaging pedagogy in the Tanzanian context, this study has significant practical implications for teachers and students to showcase their linguistic and multimodal knowledge, while fostering a safe learning space that relates to students' daily experiences.

The study offers new insights into previous research on the role of language-supportive pedagogy appropriate for teachers and students working within bi-/multilingual education settings.

Higher education plays an essential role in achieving the United Nations sustainable development goals (SDGs). However, there are only scattered studies on monitoring how universities promote SDGs through their curriculum. The purpose of this study is to investigate the connection of existing common core courses in a university to SDG education. In particular, this study wanted to know how common core courses can be classified by machine-learning approach according to SDGs.

In this report, the authors used machine learning techniques to tag the 166 common core courses in a university with SDGs and then analyzed the results based on visualizations. The training data set comes from the OSDG public community data set which the community had verified. Meanwhile, key descriptions of common core courses had been used for the classification. The study used the multinomial logistic regression algorithm for the classification. Descriptive analysis at course-level, theme-level and curriculum-level had been included to illustrate the proposed approach’s functions.

The results indicate that the machine-learning classification approach can significantly accelerate the SDG classification of courses. However, currently, it cannot replace human classification due to the complexity of the problem and the lack of relevant training data.

The study can achieve a more accurate model training through adopting advanced machine learning algorithms (e.g. deep learning, multioutput multiclass machine learning algorithms); developing a more effective test data set by extracting more relevant information from syllabus and learning materials; expanding the training data set of SDGs that currently have insufficient records (e.g. SDG 12); and replacing the existing training data set from OSDG by authentic education-related documents (such as course syllabus) with SDG classifications. The performance of the algorithm should also be compared to other computer-based and human-based SDG classification approaches for cross-checking the results, with a systematic evaluation framework. Furthermore, the study can be analyzed by circulating results to students and understanding how they would interpret and use the results for choosing courses for studying. Furthermore, the study mainly focused on the classification of topics that are taught in courses but cannot measure the effectiveness of adopted pedagogies, assessment strategies and competency development strategies in courses. The study can also conduct analysis based on assessment tasks and rubrics of courses to see whether the assessment tasks can help students understand and take action on SDGs.

The proposed approach explores the possibility of using machine learning for SDG classifications in scale.