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This research paper aims to provide information about certified learning apps for biological education and gave an ordered list of all learning apps currently used by Austrian biology teachers in the classroom, which should serve as an overview for all biology teachers. In addition, the (currently little known) certification process of learning apps (seal of quality for educational applications) is described.

Online questionnaire for all biology teachers throughout Austria, on the one hand to find out the apps, and on the other hand to research how Austrian teachers find suitable apps. The data were evaluated using descriptive statistics.

A total of84 different learning apps are currently used by biology teachers in Austria. There are two certified lernapps in Austria, both are used. The most common app in biology lessons is “Anton”. The teachers find the information about apps throughout their own research or through colleagues. There are regional and school-specific differences in regards of usage and knowledge about seal of quality. It needs its own teacher training (TT) via suitable learning apps, because problems (data protection, advertising) are sometimes not taken into account during use.

Limitations of this paper are that some of the teachers indicated the apps from other subjects (mathematics) to use this learning app, although this is not possible for biology lessons. Data protection was stated to the best of the authors’ knowledge by the authors, if the authors were not sure it says “unsure”. The participants are mainly women, but this corresponds to the gender ratio, which is typical of the Austrian teaching profession.

The overview of the apps, compiled by this Austria-wide research, can be taken over into the biology lessons of all teachers. In addition, on the basis of this study, a TT at the University of Education 2023 in Linz was created. In addition, the (currently little known) certification process of learning apps is described.

The TT and the overview of the learning apps used serve as guidelines for teachers as to which apps they can use in biology lessons without hesitation. Above all, the aspect of the follow-up of digital media/apps will be emphasized. Data backup, inappropriate advertising must be processed in class or completely omitted. Biology teachers need the right training (TT) and appropriate materials and tools (apps) to reduce problems (cybercrimes).

Currently, there is no prepared list of suitable (certified and uncertified) learning apps for biology lessons. There are isolated recommendations and individual apps, but the selection criteria and backgrounds of the authors are not clear. This list shows which apps (how often) are used by which teachers. In addition, the (currently little known) certification process of learning apps is described.

Feedback is crucial in a learning process, particularly in an online interaction where both learners and instructors are distantly located. Thus, this paper aims to investigate the association between feedback strategies, embedded course syllabus and learning improvement in the Sakai Learning Management System.

This paper uses a survey design to collect cross-sectional data from adult distance learning students. The data were analysed using descriptive statistics and a standard multiple regression model in Stata.

The results show that feedback strategies (timing, mode, quality and quantity) and embedded course syllabus have a significant relationship with learning improvement. However, the feedback strategy – target – is not significantly related to learning improvement though it is the highest feedback strategy.

This paper has contributed to the extant literature by providing empirical evidence to support the constructivism theory of learning from a distance learning perspective in a developing country. The study has shown that if the feedback strategies are well managed and applied, they would make a considerable impact on distance education students' academic pursuits. Hence, the paper provides a pedagogical foundation for short and long-term distance learning policy.

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 uses quantitative and qualitative methods in assessing performance and process outcomes in a team lecture hybrid (TLH) instructional design applied in a public affairs course.

Within a non-experimental prospective design, individual and team outcomes were assessed as follows: survey of student perceptions of learning outcomes; comparison of individual and group scores on in-class case analyses using paired t-tests; external reviewers' observations of traditional lecture versus TLH activities; and analysis of students' reflections on team dynamics using a team process reflection tool adapted from four team development stages.

The following student learning outcomes results were observed: increased use of critical thinking; higher student interaction with other students and the instructor; higher student engagement in initiating or contributing to content or other learning activities; higher student enthusiasm; increased use of problem-solving skills; improved performance evidenced by quality of individual versus group products; evidence suggesting improvements in student learning outcomes when active learners and an active instructor interact in a learning environment.

Instructor practice tips were provided in the following areas: use of assessment methods; student engagement as an active instructor; motivational tips for classes with students from a variety of disciplines; and individual team member accountability.

This paper contributes to the scholarship of teaching and learning (SOTL) by addressing limitations in both traditional and collaborative learning models and expanding holistic evaluations in SOTL.

We aimed to analyze the impact of the transition to the hybrid model of teamwork and team dynamics from the perspective of the five key challenges, i.e. communication, coordination, connection, creativity and culture.

To achieve the stated aim, we conducted a literature review and then an exploratory qualitative study. We split the research into phases: December 2021 to January 2022 and July to August 2022. In the first phase, we conducted computer-assisted online interviews (CAWIs) with all members of the remote team and an in-depth interview with the manager. After the transition from remote to hybrid work in February 2022, we returned to the team to conduct in-depth interviews with team leaders and the manager.

We identified key findings, i.e. managerial implications of differences across the 5 Cs (communication, coordination, connection, creativity and culture) noted in the functioning of the analyzed team as the team shifted from fully remote work to the hybrid work model.

We concluded that if people do not spend time together and are not impregnated with the unique culture and values of a given organization, they will not feel a connection to its distinctive ethos and may choose to leave. In the longer-term, the last challenge may be the biggest single opportunity for employees post-pandemic and concurrently the single biggest challenge that organizational leadership will need to address, given that sustainable market success depends on talent.

The results showed that team communication, teamwork coordination, social and emotional connections among team members, nurturing of creativity, as well as of the organizational culture were of high importance to the team in the hybrid work model. Thus, we confirmed the findings of other authors. The study contributes to our understanding of the impact of the hybrid work model on teamwork and team dynamics and provides some guidance on how organizations can mitigate these, in particular through the team manager.

The amount of features in handwritten digit data is often very large due to the different aspects in personal handwriting, leading to high-dimensional data. Therefore, the employment of a feature selection algorithm becomes crucial for successful classification modeling, because the inclusion of irrelevant or redundant features can mislead the modeling algorithms, resulting in overfitting and decrease in efficiency.

The minimum redundancy and maximum relevance (mRMR) and the recursive feature elimination (RFE) are two frequently used feature selection algorithms. While mRMR is capable of identifying a subset of features that are highly relevant to the targeted classification variable, mRMR still carries the weakness of capturing redundant features along with the algorithm. On the other hand, RFE is flawed by the fact that those features selected by RFE are not ranked by importance, albeit RFE can effectively eliminate the less important features and exclude redundant features.

The hybrid method was exemplified in a binary classification between digits “4” and “9” and between digits “6” and “8” from a multiple features dataset. The result showed that the hybrid mRMR +  support vector machine recursive feature elimination (SVMRFE) is better than both the sole support vector machine (SVM) and mRMR.

In view of the respective strength and deficiency mRMR and RFE, this study combined both these methods and used an SVM as the underlying classifier anticipating the mRMR to make an excellent complement to the SVMRFE.

Image segmentation is one of the most essential tasks in image processing applications. It is a valuable tool in many oriented applications such as health-care systems, pattern recognition, traffic control, surveillance systems, etc. However, an accurate segmentation is a critical task since finding a correct model that fits a different type of image processing application is a persistent problem. This paper develops a novel segmentation model that aims to be a unified model using any kind of image processing application. The proposed precise and parallel segmentation model (PPSM) combines the three benchmark distribution thresholding techniques to estimate an optimum threshold value that leads to optimum extraction of the segmented region: Gaussian, lognormal and gamma distributions. Moreover, a parallel boosting algorithm is proposed to improve the performance of the developed segmentation algorithm and minimize its computational cost. To evaluate the effectiveness of the proposed PPSM, different benchmark data sets for image segmentation are used such as Planet Hunters 2 (PH2), the International Skin Imaging Collaboration (ISIC), Microsoft Research in Cambridge (MSRC), the Berkley Segmentation Benchmark Data set (BSDS) and Common Objects in COntext (COCO). The obtained results indicate the efficacy of the proposed model in achieving high accuracy with significant processing time reduction compared to other segmentation models and using different types and fields of benchmarking data sets.

The proposed PPSM combines the three benchmark distribution thresholding techniques to estimate an optimum threshold value that leads to optimum extraction of the segmented region: Gaussian, lognormal and gamma distributions.

On the basis of the achieved results, it can be observed that the proposed PPSM–minimum cross-entropy thresholding (PPSM–MCET)-based segmentation model is a robust, accurate and highly consistent method with high-performance ability.

A novel hybrid segmentation model is constructed exploiting a combination of Gaussian, gamma and lognormal distributions using MCET. Moreover, and to provide an accurate and high-performance thresholding with minimum computational cost, the proposed PPSM uses a parallel processing method to minimize the computational effort in MCET computing. The proposed model might be used as a valuable tool in many oriented applications such as health-care systems, pattern recognition, traffic control, surveillance systems, etc.

This research aims to explore digital feedback needs/preferences in online education during lockdown and the implications for post-pandemic education.

An empirical study approach was used to explore feedback needs and experiences from educational institutions in the Netherlands and Germany (N = 247) using a survey method.

The results showed that instruments supporting features for effortless interactivity are among the highly preferred options for giving/receiving feedback in online/hybrid classrooms, which are in addition also opted for post-pandemic education. The analysis also showed that, when communicating feedback digitally, more inclusive formats are preferred, e.g. informing learners about how they perform compared to peers. The increased need for comparative performance-oriented feedback, however, may affect students' goal orientations. In general, the results of this study suggest that while interactivity features of online instruments are key to ensuring social presence when using digital forms of feedback, balancing online with offline approaches should be recommended.

This research contributes to the gap in the scientific literature on feedback digitalization. Most of the existing research are in the domain of automated feedback generated by various learning environments, while literature on digital feedback in online classrooms, e.g. empirical studies on preferences for typology, formats and communication channels for digital feedback, to the best of the authors’ knowledge is largely lacking. The findings and recommendations of this study extend their relevance to post-pandemic education for which hybrid classroom is opted among the highly preferred formats by survey respondents.

The study aims to investigate the effect of the dialogue embedded synectics model of teaching on the creative thinking of students.

The research design of the study was a nonequivalent control group design of quasi experimental research. This study collected data from 80 students in the seventh grade from two different government schools in Bathinda, Punjab, India, which were selected using a random method. The subjects of experimental group were taught by the investigator using the dialogue embedded synectics model of teaching and the subjects of control group were taught by their teacher using the traditional teaching method, i.e. the Herbartian method. The data collections were done using the creative thinking test developed by Baqer Mehdi (1995). The data analysis techniques used t-test.

Key finding indicates that the dialogue embedded synectics model of teaching is effective in enhancing the creative thinking of students as compared to the traditional method.

The present work is unique in terms of development of an innovative pedagogy, i.e. the dialogue embedded synectics model of teaching, which has the potential to encourage students' creative thinking, a key concern for society in the 21st century. Therefore, it is suggested to conduct similar type of studies on this innovative pedagogy and this model of teaching may be used by teachers for enhancing creative thinking of seventh class students.

This study investigates the impact of large-scale teaching in higher education on students’ preparedness for the workforce within the context of evolving labour market demands, the expansion of higher education and the application of high-impact teaching strategies. It synthesizes perspectives on employer work readiness, the challenges and opportunities of large-scale teaching and strategies for fostering a dynamic academia-industry feedback loop. This multifaceted approach ensures the relevance of curricula and graduates’ preparedness while addressing the skills gap through practical recommendations for aligning teaching methodologies with employer expectations.

The research methodically examines the multifaceted challenges and opportunities inherent in large-scale teaching. It focuses on sustaining student engagement, maintaining educational quality, personalizing learning experiences and cultivating essential soft skills in extensive student cohorts.

This study highlights the critical role of transversal skills in work readiness. It also uncovers that despite its challenges, large-scale teaching presents unique opportunities. The diversity of large student groups mirrors modern workplace complexities, and technological tools aid in personalizing learning experiences. Approaches like peer networking, innovative teaching methods, real-world simulations and collaborative resource utilization enrich education. The importance of experiential learning for augmenting large-scale teaching in honing soft skills is emphasized.

This manuscript contributes to the discourse on large-scale teaching, aligning it with employer expectations and the dynamic requirements of the job market. It offers a nuanced perspective on the challenges and opportunities this educational approach presents, providing insights for crafting engaging and effective learning experiences in large cohorts. The study uniquely integrates experiential learning, co-creation in education and industry-academia feedback loops, underscoring their importance in enhancing student work readiness in large-scale teaching.