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The widespread use of mobile devices and laptops has replaced traditional paper-based learning and the question of how the brain efficiency of digital tablet-based learning differs from that of paper-based learning remains unclear. The purpose of this study was to investigate the difference in brain efficiency for learning between paper-based and digital tablet-based learning by measuring activity in the prefrontal cortex (PFC) using functional near-infrared spectroscopy. Thirty-two subjects were randomly assigned to the paper-based learning or the digital tablet-based learning group. Subjects in each group performed a memory task that required memorizing a three-minute novel (encoding phase) on a paper or digital tablet, followed by a test in which they answered four multiple-choice questions based on the novel's content. To compare both groups, behavioral performance on the test (retrieval phase) and activity in the PFC were measured. As a result, no significant difference in behavioral performance between both groups was observed (p > 0.05). However, the paper-based learning group showed significantly lower activity in the PFC in the encoding phase than the digital tablet-based learning group (p < 0.05) but not in the retrieval phase. The current study demonstrated that brain efficiency in encoding is higher in subjects with paper-based learning than those with digital tablet-based learning. This finding has important implications for education, particularly in terms of the pros and cons of electronic document-based learning. [ABSTRACT FROM AUTHOR]

Theories of embodied cognition postulate that perceptual, sensorimotor, and affective properties of concepts support language learning and processing. In this paper, we argue that language acquisition, as well as processing, is situated in addition to being embodied. In particular, first, it is the situated nature of initial language development that affords for the developing system to become embodied. Second, the situated nature of language use changes across development and adulthood. We provide evidence from empirical studies for embodied effects of perception, action, and valence as they apply to both embodied cognition and situated cognition across developmental stages. Although the evidence is limited, we urge researchers to consider differentiating embodied cognition within situated context, in order to better understand how these separate mechanisms interact for learning to occur. This delineation also provides further clarity to the study of classroom-based applications and the role of embodied and situated cognition in the study of developmental disorders. We argue that theories of language acquisition need to address for the complex situated context of real-world learning by completing a "circular notion": observing experimental paradigms in realworld settings and taking these observations to later refine lab-based experiments. [ABSTRACT FROM AUTHOR]

Concept formation requires animals to learn and use abstract rules that transcend the characteristics of specific stimuli. Abstract concepts are often associated with high levels of cognitive sophistication, so there has been much interest in which species can form and use concepts. A key abstract concept is that of sameness and difference, where stimuli are classified as either the same as or different than an original stimulus. Here, we used a simultaneous two-item same-different task to test whether paper wasps (Polistes fuscatus) can learn and apply a same-different concept. We trained wasps by simultaneously presenting pairs of same or different stimuli (e.g. colours). Then, we tested whether wasps could apply the concept to new stimuli of the same type (e.g. new colours) and to new stimulus types (e.g. odours). We show that wasps learned a general concept of sameness or difference and applied it to new samples and types of stimuli. Notably, wasps were able to transfer the learned rules to new stimuli in a different sensory modality. Therefore, P. fuscatus can classify stimuli based on their relationships and apply abstract concepts to novel stimulus types. These results indicate that abstract concept learning may be more widespread than previously thought. [ABSTRACT FROM AUTHOR]

This research provides an overview of the historical advances of the maze tests that are widely used to assess the cognitive impairments in rodents. Particularly, this study focuses on the issue of learning and memory behavioral tests, including dry and water mazes. Several types of mazes have been used in this setting, but their real advantages and applications depend on the type selected by the researcher. We answered some of the basic questions that any interested researcher in such studies may be faced with. The reviewed topics are as follows: the definition of maze learning, the role of the memory in the maze learning, the differences between several types of mazes, and foremost the rationale behind the maze constructions and designs. [ABSTRACT FROM AUTHOR]

A repeated crossover experiment comparing learning among students handing in pen-and-paper homework (PPH) with students handing in web-based homework (WBH) has been conducted. The system used in the experiments, the tutor-web, has been used to deliver homework problems to thousands of students in mathematics and statistics over several years. Since 2011, experimental changes have been made regarding how the system allocates items to students, how grading is done, and the type of feedback provided. The experiment described here was conducted annually from 2011 to 2014. Approximately, 100 students in an introductory statistics course participated each year. The main goals were to determine whether the above-mentioned changes had an impact on learning as measured by test scores in addition to comparing learning among students doing PPH with students handing in WBH. The difference in learning between students doing WBH compared to PPH, measured by test scores, increased significantly from 2011 to 2014 with an effect size of 0.634. This is a strong indication that the changes made in the tutor web have a positive impact on learning. Using the data from 2014, a significant difference in learning between WBH and PPH for 2014 was detected with an effect size of 0.416 supporting the use of WBH as a learning tool. [ABSTRACT FROM AUTHOR]

Background: Extensive application of radioactive materials to medical and military purposes justifies the necessity of training military nurse students regarding the management of radiation injury. The current study aimed at comparing the effect of two methods (lecture and webbased) of training on the management of radiation-injured patients among military nurse students from 2013 to 2014. Materials and Methods: The current semi-experimental study was conducted on 60 military nursing students in two military nursing schools in Tehran, Iran selected purposively. Subjects of the study were divided into two groups of 30 as lecture and web-based teaching. The effect of education was measured on three levels of knowledge, comprehension, and application; before, immediately after, and four weeks after completion of teaching. The data were analyzed with SPSS software version 21, using Repeated Measures (RM)-ANOVA and t-test. Results: Mean and standard deviation of scores in all learning levels (knowledge, comprehension, and application) in both groups had a significant difference between before and after the intervention (P<0.001). No significant difference was observed in the total mean scores of the two groups before intervention. In the post-test, immediately after training, mean scores of the web-based group had a greater increase, but no significant difference was observed (P=0.12). In the retention stage (four weeks after training), it was observed that the lecture-based method was more effective (P=0.01). Conclusion: According to the obtained results, learning increased in both methods . Therefore, it is recommended to use the combined teaching method to educate nursing students. [ABSTRACT FROM AUTHOR]

Generative Artificial Intelligence (AI), especially machine learning models that autonomously generate human-like content, has recently attracted significant attention in the education sector. This paper explores the potential of generative AI, including tools like ChatGPT, to shift from traditional outcome-oriented educational practices to a more balanced approach that values both the learning process and its outcomes. Traditionally, education has emphasized achieving predefined results, but the advent of generative AI tools, which enable students to easily produce tangible results, calls for a reevaluation of these practices. This shift suggests a need for a broader focus that encompasses the entire learning process leading to the final product, thereby promoting an educational practice that equally emphasizes both the journey and the destination of learning. Recognizing that the implementation of such practices, facilitated by generative AI, still requires exploration, this paper proposes a solution that integrates the experiential learning cycle and learning portfolio. This approach is designed to demonstrate the realization of process-outcome-balanced educational practices through the use of a pedagogical AI agent. [ABSTRACT FROM AUTHOR]

Introduction: In medical and clinical education, creating critical thinking and promoting clinical reasoning abilities are the highest aims and results of education. The main aim of this study was to assess the efficacy of digital case scenarios versus print/paper case scenarios on clinical reasoning in problem-based learning (PBL). If a study used the multimedia scenario case interventions, video case scenarios and online-guided scenarios as digital case PBL, we would consider it eligible. Methods: The study was a systematic review and meta-analysis. A comprehensive search for all randomized controlled trials, systematic reviews and meta-analyses for digital case scenarios versus paper case scenarios in PBL were conducted using Medline (Ovid), Scopus, ISI Web of Science and CINAHL. Google Scholar was used to follow the bibliographies of the related papers to create an exhaustive data set. Search results were limited to the years 2003-2013. Results: Our searches yielded 65 hits. After initial screenings of the titles and abstracts, we assessed the full texts of studies. Five eligible studies with 222 students were included in the meta-analysis. The meta-analysis showed that both of the digital and paper-based scenarios have similar impacts on clinical reasoning. But the review of papers showed that 73% of students are more satisfied with digital scenarios in comparison with paper-based scenarios and found that digital scenarios are 90% more time saving than paper-based scenarios. Conclusion: According to the results of meta-analysis, efficacy of digital-based scenarios is similar to the efficacy of paper-based scenarios while simultaneously creating more satisfaction and saving the time of students and teachers; therefore, it is suggested that electronic PBL be used rather than paper-based in all levels of medical education. [ABSTRACT FROM AUTHOR]

Many studies have emphasized the incorporation of active learning into classrooms to reinforce didactic lectures for physiology courses. This work aimed to determine if presenting classic papers during didactic lectures improves the learning of physiology among undergraduate students. Twenty-two students of health information technology were randomly divided into the following two groups: 1) didactic lecture only (control group) and 2) didactic lecture plus paper presentation breaks (DLPP group). In the control group, main topics of gastrointestinal and endocrine physiology were taught using only the didactic lecture technique. In the DLPP group, some topics were presented by the didactic lecture method (similar to the control group) and some topics were taught by the DLPP technique (first, concepts were covered briefly in a didactic format and then reinforced with presentation of a related classic paper). The combination of didactic lecture and paper breaks significantly improved learning so that students in the DLPP group showed higher scores on related topics compared with those in the control group (P < 0.001). Comparison of the scores of topics taught by only the didactic lecture and those using both the didactic lecture and paper breaks showed significant improvement only in the DLPP group (P < 0.001). Data obtained from the final exam showed that in the DLPP group, the mean score of the topics taught by the combination of didactic lecture and paper breaks was significantly higher than those taught by only didactic lecture (P < 0.05). In conclusion, the combination of paper presentation breaks and didactic lectures improves the learning of physiology. [ABSTRACT FROM AUTHOR]

The present study focused on how self-control over pace might help learners successfully extract information from digital learning aids. Past research has indicated that too much control over pace can be overwhelming, but too little control over pace can be ineffective. Within the popular self-testing domain of flashcards, we sought to elucidate the optimal level of user control for digital learning and compare learning outcomes between paper and digital flashcards. College students learned vocabulary from paper flashcards or one of several digital flashcard versions and were scored on their memory recall and asked about their perceptions of the learning process. With digital flashcards, students were randomly assigned to an automatic slideshow of cards with no user control, automatic slideshow with pre-set pauses, automatic slideshow where users could press the spacebar to pause at any time, or a self-paced slideshow with complete user control. Users reported feeling more in control when indeed having some control, but ultimately memory recall, cognitive load, and satisfaction were similar across the five versions. However, memory recall was positively related to user satisfaction with their specific flashcard set, and negatively related to users' perceived mental effort and difficulty. Notably, whether paper or digital, students showed individual variability in how they advanced through the words. This research adds to the educational literature by suggesting that paper and digital flashcards are equally viable options for students. Given differences between individual users and the connection between satisfaction and recall, individualistic options that offer, but do not force, some control over pace seem ideal. Paper flashcards may already include such options, and e-flashcards should offer similar adaptive features to appeal to a wide variety of users. [ABSTRACT FROM AUTHOR]

Abstract: Autism affects children׳s learning and social development. Commonly used rehabilitative treatments are aimed at stimulating the social skills of children with autism. In this article, we present a prototype and a pilot study on an audio-augmented paper to support the therapy of children with autism spectrum disorder (ASD). The prototype supports audio recording with standard sheets of paper by using tangible tools that can be shared between the therapist and the child. The prototype is a tool for the therapist to engage the child in a storytelling activity. We use a progressive design method based on a dynamic process that merges concept generation, technology benchmarking and activity design into continuously enriching actions. The paper highlights the qualities and benefits of using tangible audio-augmented artefacts for therapy and educational intervention for children with ASD. The work describes three main qualities of our prototype: from building cooperation to attention control, flow control, and using the children׳s own voices to foster attention. [Copyright &y& Elsevier]

Financial education represents a powerful tool for improving economic literacy of citizens. This paper presents results from an experiment providing a group of 136 workers in an Italian university (administrative staff) an online, synchronous course. Classes were organized in 5 sessions of 2h each and covered basic topics about personal finance. The effectiveness of the course is assessed through a rigorous randomized controlled trial (RCT). In addition to the analysis of improvements in financial knowledge, financial self‐efficacy and the role of prior attitudes and behaviors were explored. Participants obtained post‐test scores statistically higher than individuals in the control group, with an average effect size of 0.55 SD. The effect is particularly relevant for participants starting with low levels of financial knowledge. Moreover, two novel findings emerge: financial self‐efficacy increases (0.51 SD) after the course, and pre‐treatment individuals' financial attitudes and behaviors shed further light on the financial learning process. [ABSTRACT FROM AUTHOR]

Algorithmic trading is playing an increasingly important role in the financial market, achieving more efficient trading strategies by replacing human decision-making. Among numerous trading algorithms, deep reinforcement learning is gradually replacing traditional high-frequency trading strategies and has become a mainstream research direction in the field of algorithmic trading. This paper introduces a novel approach that leverages reinforcement learning with human feedback (RLHF) within the double DQN algorithm. Traditional reward functions in algorithmic trading heavily rely on expert knowledge, posing challenges in their design and implementation. To tackle this, the reward-driven double DQN (R-DDQN) algorithm is proposed, integrating human feedback via a reward function network trained on expert demonstrations. Additionally, a classification-based training method is employed for optimizing the reward function network. The experiments, conducted on datasets including HSI, IXIC, SP500, GOOGL, MSFT, and INTC, show that the proposed method outperforms all baselines across six datasets and achieves a maximum cumulative return of 1502% within 24 months. [ABSTRACT FROM AUTHOR]

This paper presents a novel variant of the teaching–learning-based optimization algorithm, termed BLTLBO, which draws inspiration from the blended learning model, specifically designed to tackle high-dimensional multimodal complex optimization problems. Firstly, the perturbation conditions in the "teaching" and "learning" stages of the original TLBO algorithm are interpreted geometrically, based on which the search capability of the TLBO is enhanced by adjusting the range of values of random numbers. Second, a strategic restructuring has been ingeniously implemented, dividing the algorithm into three distinct phases: pre-course self-study, classroom blended learning, and post-course consolidation; this structural reorganization and the random crossover strategy in the self-learning phase effectively enhance the global optimization capability of TLBO. To evaluate its performance, the BLTLBO algorithm was tested alongside seven distinguished variants of the TLBO algorithm on thirteen multimodal functions from the CEC2014 suite. Furthermore, two excellent high-dimensional optimization algorithms were added to the comparison algorithm and tested in high-dimensional mode on five scalable multimodal functions from the CEC2008 suite. The empirical results illustrate the BLTLBO algorithm's superior efficacy in handling high-dimensional multimodal challenges. Finally, a high-dimensional portfolio optimization problem was successfully addressed using the BLTLBO algorithm, thereby validating the practicality and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Machine learning-based controllers of prostheses using electromyographic signals have become very popular in the last decade. The regression approach allows a simultaneous and proportional control of the intended movement in a more natural way than the classification approach, where the number of movements is discrete by definition. However, it is not common to find regression-based controllers working for more than two degrees of freedom at the same time. In this paper, we present the application of the adaptive linear regressor in a relatively low-dimensional feature space with only eight sensors to the problem of a simultaneous and proportional control of three degrees of freedom (left–right, up–down and open–close hand movements). We show that a key element usually overlooked in the learning process of the regressor is the training paradigm. We propose a closed-loop procedure, where the human learns how to improve the quality of the generated EMG signals, helping also to obtain a better controller. We apply it to 10 healthy and 3 limb-deficient subjects. Results show that the combination of the multidimensional targets and the open-loop training protocol significantly improve the performance, increasing the average completion rate from 53% to 65% for the most complicated case of simultaneously controlling the three degrees of freedom. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has accelerated acceptance of learning from other countries, especially for high-income countries to learn from low- and middle-income countries, a practice known as global learning. COVID-19’s rapid disease transmission underscored how connected the globe is as well as revealed stark health inequities which facilitated looking outside of one’s borders for solutions. The Global Learning for Health Equity (GL4HE) Network, supported by Robert Wood Johnson Foundation, held a 3-part webinar series in December 2021 to understand the current state of global learning and explore how global learning can advance health equity in the post-COVID-19 era. This paper reflects on these cutting-edge discussions about the current state of global learning, drawing upon the highlights, perspectives, and conclusions that emerged from these webinars. The paper also comments on best practices for global learning, including adapting for context, addressing biases, funding considerations, ensuring bidirectional partnerships, community engagement, and adopting a multidisciplinary approach. [ABSTRACT FROM AUTHOR]

Background: Despite the increased availability of safe abortion methods in sub-Saharan Africa, women and girls continue to use unsafe abortion methods and procedures to terminate their unwanted pregnancies, resulting in severe complications, lifelong disabilities, and death. Barriers to safe abortion methods include restrictive laws, low awareness of safe abortion methods, poverty, and sociocultural and health system barriers. Nonetheless, there is a paucity of data on the decision-making around and use of abortion methods. This paper aims to provide answers to the following questions: Which abortion methods do women and girls use and why? Who and what influences their decisions? What can we learn from their decision-making process to enhance the uptake of safe abortion methods? We focus our in-depth analysis on the rationale behind the choice of abortion methods used by women and girls in Kilifi County in Kenya and Atlantique Department in Benin. Methods: We draw on data collected as part of an ethnographic study conducted between January and August 2021 on lived experiences, social determinants, and pathways to abortion. Data were collected using repeated in-depth interviews with 95 girls and women who had a recent abortion experience. Data from the interviews were supplemented using information from key informant interviews, focus group discussions, and participant observation. Data analysis was conducted through an inductive process. Results: Our findings reveal that women and girls use various methods to procure abortions, including herbs, high doses of pharmaceutical drugs, homemade concoctions, medical abortion drugs, and surgical abortion methods. Procedures may involve singular or multiple attempts, and sometimes, mixing several methods to achieve the goal of pregnancy termination. The use of various abortion methods is mainly driven by the pursuit of social safety (preservation of secrecy and social relationships, avoidance of shame and stigmatization) instead of medical safety (which implies technical safety and quality). Conclusion: Our findings reaffirm the need for comprehensive access to, and availability of, abortion-related information and services, especially safe abortion and post-abortion care services that emphasize both medical and social safety. Plain Language Summary: Despite the availability of safe abortion methods in sub-Saharan Africa, women and girls in the region continue to resort to unsafe methods, leading to severe complications, disabilities, and maternal death. This can be attributed to restrictive abortion laws, lack of awareness on safe abortion methods, poverty, and sociocultural and health system barriers. This paper uses data from a larger ethnographic study in Kilifi County, Kenya, and Atlantique Department, Benin, to understand which methods women and girls use, and why, to help improve the use of safe abortion methods. Data were collected through in-depth interviews with 95 girls and women who had recently undergone an abortion, as well as key informant interviews, focus group discussions, and participant observation. The findings reveal that women and girls use various methods to terminate their pregnancies, including herbs, high doses of pharmaceutical drugs, homemade concoctions, medical abortion drugs, and surgical methods. They often use these methods once, multiple times, or in combination to achieve their goal. The main reason for their choice of methods is not medical safety but social safety, including preserving social relationships and avoiding shame and stigma. We conclude that there is a pressing need for greater access to accurate, well-framed information about safe abortion methods. Abortion services should consider not only medical safety but also discretion to mitigate the social implications of having an abortion in a medical facility. By addressing these factors, it is possible to enhance the use of safe abortion methods and reduce the reliance on unsafe practices. [ABSTRACT FROM AUTHOR]

Background: There has been a steady increase in the number of students with disabilities (SWD) in Higher Education Institutions (HEIs) in South Africa, with a significant number of students having visual disabilities. Equal access remains a key challenge in the classroom setting, thus emphasising a significant gap. Objectives: This paper capitalised on the significance of this gap and examined the potential of Universal Design of Instruction (UDI) to promote equal access for students with visual disabilities (SWVDs) in the classroom within a university setting in order to maximise learning outcomes. Method: The study was conducted at the University of KwaZulu-Natal (UKZN), which had approximately 204 SWVDs. This paper draws primarily on the quantitative component of the study. Data collection entailed distributing a questionnaire to all SWVDs. Analysis was conducted using SPSS 21, which produced descriptive and inferential statistics. The theoretical framework of Sen's Capability Approach in line with the Social Model of Disability was applied. Results: Findings indicated a lack of UDI in the classroom with very little compliance to all principles, resulting in increased challenges in teaching and learning for SWVDs. The incorporation of UDI in the classroom does have a positive correlation with learning outcomes. Conclusion: The incorporation of UDI principles can offer a potential design for easier access to teaching and learning to enhance and maximise learning outcomes; alleviate access challenges in the classroom; and address the negative experiences thereof for SWVDs. Contribution: The study adds value to the scarce body of knowledge on UDI in the classroom for university SWVDs from a learning enhancement perspective. [ABSTRACT FROM AUTHOR]

Ethnic minority resources are very rich and contain rich historical resources and culture. Under the impact of modern information technology, the development of minority resources and the inheritance of ethnic culture are facing many challenges, and the current school education is lagging behind in exploring the ecological resources of minority groups, which makes the integration of creative education and minority groups encounter a bottleneck. In response to this situation, we make full use of the platform of creative education to actively explore the traditional skills contained in the lives of ethnic minorities. In the evaluation of creative education, we should not only focus on the evaluation of students' works, but also on the improvement of students' knowledge of various creative tools, their ability to use comprehensive subject knowledge, hands-on ability, solution ability and creativity ability during the whole learning process. Based on this, this paper proposes a back propagation neural network (BPNN)-based quality evaluation method for creative education to evaluate the quality of creative education from multiple dimensions. Experiments and comparisons show that the BPNN-based evaluation method proposed in this paper can better evaluate the whole process of creative education and help the further development of creative education in minority regions. [ABSTRACT FROM AUTHOR]

A prominent application area in the domain of computer vision is human activity recognition, which involves automatically detecting people's actions from video footage. In this paper, a generic decision support tool capable of performing human activity recognition by employing computer vision is developed. The objective of the decision support tool is to facilitate the analysis of video footage by learning to identify human activities from video footage. The decision support tool facilitates the processing of raw data, the training of a computer vision model in respect of the processed data, and the deployment of the trained computer vision model in respect of unseen video footage. This paper details a computerised implementation of the decision support tool in respect of a benchmark data set and real-world data set involving the cash replenishment process of a South African bank. [ABSTRACT FROM AUTHOR]

This paper charts the journey from classroom-based training delivery to hybrid and virtual learning opportunities used to overcome the challenges imposed by public health restrictions introduced in response to the COVID-19 pandemic. The public health measures introduced in March 2020 had a significant effect on the ability of the Children First Information and Advice Service (CFIAS), in Tusla, Ireland's Child and Family Agency, to deliver services. One of the key tools used by the CFIAS to support understanding of responsibilities, and best practice, in child safeguarding by professionals, and within organisations, has been the provision of direct training and information sessions. The introduction of public health restrictions necessitated a complete rethink by the CFIAS on how child safeguarding training and information are delivered. The paper presents an outline of the background and context of child safeguarding in Ireland, followed by a description of some of the challenges experienced by the CFIAS in response to the pandemic public health restrictions. It includes discussion on strategies and solutions considered to overcome these challenges. There is further discussion on the tools and methods eventually used, followed by a reflection on lessons learned by the CFIAS in areas including training delivery and methodology, eLearning, and information provision. The paper provides an analysis of limited qualitative and quantitative data, as well as a reflection on the lived experience of the CFIAS team members responding to the challenges posed during this time period, rather than a preplanned research study on pedagogical approaches in adult learning. [ABSTRACT FROM AUTHOR]

We have all seen the newspaper headlines: screens make us read slower, learn less deeply, remember less and sleep worse. Is this why students prefer to print out their electronic textbooks? We suspected it was habit and attitude rather than measurable cognitive effort during reading that made people prefer print texts, but we needed evidence. We decided to find out what recent research had to say on the subject and read scholarly articles addressing the issues of the actual reading and/or learning processes involved in reading on screen compared to on paper. We then considered these results in relation to our own experience of using tablets and teaching scholars and students how to use their tablets/smartphones in their work. Habit and attitude appeared to be important, and a digitally born textbook is by far the best alternative to a print textbook when it comes to studying. But even those who prefer to read on screens are originally native paper readers, and as long as the existing application interfaces cannot address the shortcomings of screens regarding spatial landmarks, we will keep returning to paper under certain circumstances. We would like to see developers make more user-friendly e-readers, and authors and publishers learn to fully utilize of the potential of the e-book. [ABSTRACT FROM AUTHOR]

Smart environments integrated with digital technologies have emerged as a powerful tool to support personalized, interactive, and adaptive learning experiences. The central objective of developing smart environment is to foster learner agency enabling learners to develop the ability to take ownership and manage their own learning process. However, developing learner agency presents a significant challenge. It requires researchers, practitioners, and system developers to understand the roles of teachers and students, the instructional design, and the affordances of technologies to transfer learners from passive recipients to active participants in their learning process. To address the need, this special issue collected twenty-nine articles which underwent a rigorous peer review process. The acceptance rate for this special issue was less than fifteen percent and only four papers were accepted and included. The four papers discuss the application of instructional approaches and various digital tools such as artificial intelligence, virtual reality, and mobile technologies to design smart learning environments which foster and evaluate learner agency. [ABSTRACT FROM AUTHOR]

In this paper we discuss the pedagogical features necessary to make appropriate recommendations of papers to students in an e-learning domain. Analyzing data collected in a human subject study several characteristics of learners and of papers are found that are important to making good recommendations. These pedagogical features distinguish e-learning domains from many commercial domains where the only key factor is a user's likes and dislikes. [ABSTRACT FROM AUTHOR]

The brain often switches freely between focused attention and divergent thinking, and the Default Mode Network (DMN) is activated during brain rest. Since its discovery, the DMN, together with its function and characteristics, indicates that learning does not stop when the brain "rests". Therefore, DMN plays an important role in learning. Neural activities such as beta wave rhythm regulation, "subconscious" divergence thinking mode initiation, hippocampal function, and neural replay occur during default mode, all of which explains that "rest" promotes learning. This paper summarized the function and neural mechanism of DMN in learning and proposed that the DMN plays an essential role in learning, which is that it enables rest to promote learning. [ABSTRACT FROM AUTHOR]

In recent years, the need for systems capable of achieving the dynamic learning and information storage efficiency of the biological brain has led to the emergence of neuromorphic research. In particular, neuromorphic optics was born with the idea of reproducing the functional and structural properties of the biological brain. In this context, solitonic neuromorphic research has demonstrated the ability to reproduce dynamic and plastic structures capable of learning and storing through conformational changes in the network. In this paper, we demonstrate that solitonic neural networks are capable of mimicking the functional behaviour of biological neural tissue, in terms of synaptic formation procedures and dynamic reinforcement. [ABSTRACT FROM AUTHOR]

The liturgical professional development project for pastoral workers and clergy in the Diocese of Rottenburg-Stuttgart has been developed in collaboration with the Department of Liturgical Studies at the University of Tübingen. The concept of biographical learning is the innovative element that explores a new type of liturgical formation (Bildung) where the learning content explores the participant's unique biography of learning, faith development, and theological education and the impact of these on their understanding of the liturgy and their liturgical practice. The learning process aims to equip professional pastoral theologians to reflect on and be responsive to the liturgical–pastoral contexts in which they work. The Department of Liturgical Studies provides the learning structure and context, while the diocese provides the teaching space and enables the participants to attend. The learning outcomes are unrelated to a specific professional or employment structure or associated with a points system, management, or career progression process. The project provides a learning process rather than a program of learning, distinguishing itself from many traditional approaches to liturgical formation. The challenge for the teaching team is to provide the participants with conceptual or theoretical material to reflect on their biographical narrative of theology and then apply this concept of biographical learning in their specific and diverse pastoral contexts. As part of the biographical learning process, participants contribute to "feedback loops" to the diocese and the teaching team. This paper does not address the competency framework for career development, employment assessment, or learning comprehension. All evaluations of professionalism, role attainment, career development, and competency are employment matters and are the purview of the Diocese of Rottenburg-Stuttgart. However, the learning process provides participants with frameworks for self-assessment and feedback loops to evaluate the teaching team, the process, and the content. [ABSTRACT FROM AUTHOR]

With mobile phones now in the hands of virtually all of our learners, it is becoming increasingly more difficult to imagine environments that do not include learning through mobile devices in even some small capacity. The interest in mobile learning is reflected in the enormous number of publications which have appeared over the past 10 to 15 years, but there are still questions about when, how, and why learners will choose to use or not use mobile devices as a regular part of their learning (Stockwell, 2022). Furthermore, the "disruptive" nature of mobile devices (see Hampel, 2019) has caused mixed reactions from teachers, some of whom feel that they are a distraction in the classroom, while others see a shifting of responsibility to the learners as a positive that can lead to autonomous behaviours that facilitate learning. Making the most of learning through mobile learning is dependent upon understanding the expectations of teachers, learners, and administrators, and to capitalise upon the affordances of the device, the learning ecology, and the short-term and long-term goals of the learners. This paper explores how mobile learning can play a role both inside and outside of the classroom, and the impact that it may have on both formal and informal learning opportunities. It includes a discussion of the shifting roles of teachers and learners, and then going on to explore the myths associated with technology in the development and sustainment of motivation and autonomy. [ABSTRACT FROM AUTHOR]

Wearable sensors are widely used in medical applications and human–computer interaction because of their portability and powerful privacy. Human activity identification based on sensor data plays a vital role in these fields. Therefore, it is important to improve the recognition performance of different types of actions. Aiming at the problems of insufficient time-varying feature extraction and gradient explosion caused by too many network layers, a time convolution network recognition model with attention mechanism (TCN-Attention-HAR) was proposed. The model effectively recognizes and emphasizes the key feature information. The ability of extracting temporal features from TCN (temporal convolution network) is improved by using the appropriate size of the receiver domain. In addition, attention mechanisms are used to assign higher weights to important information, enabling models to learn and identify human activities more effectively. The performance of the Open Data Set (WISDM, PAMAP2 and USC-HAD) is improved by 1.13%, 1.83% and 0.51%, respectively, compared with other advanced models, these results clearly show that the network model presented in this paper has excellent recognition performance. In the knowledge distillation experiment, the parameters of student model are only about 0.1% of those of teacher model, and the accuracy of the model has been greatly improved, and in the WISDM data set, compared with the teacher's model, the accuracy is 0.14% higher. [ABSTRACT FROM AUTHOR]

Effective means for transportation form a critical city infrastructure, particularly for resource-constrained smart cities. Rapid advancements in information and communication technologies have paved the path for intelligent transportation system (ITS), specifically designed for optimal effectiveness and safety with existing transportation infrastructure. A key function of ITS is its ability to aggregate large volumes of data across various sources for event detection. However, prediction accuracy remains a challenge since ITS event detection is characterized by very stringent latency requirements necessitating the use of lightweight detection schemes, thus seriously compromising the efficiency of ITS. This paper attempts to tackle this problem by introducing an IoT-integrated distributed context-aware fog-cloud ensemble that intelligently manages context instances at fog nodes ensuring availability of context instances for ITS. This system enhances prediction accuracy by utilizing a hybrid convolutional neural network (CNN) where each vehicle within the system retains only local information, while adjacent fog nodes gain access to global events via continual federated learning, updating regularly between fog and cloud models. Experiments presented herein illustrate the superiority of the CNN model, yielding an accuracy of more than 95%, which is an improvement of around 3% compared to the LeNet with same RGB input images. [ABSTRACT FROM AUTHOR]

The attitudes and behaviors towards people living with neurological conditions, such as epilepsy, have major implications for the quality of life of affected individuals and for human progress more broadly. Epilepsy is a common neurological disorder often associated with misconceptions leading to discrimination, stigma, and burden for people living with epilepsy (PLWE) and their families. Addressing these negative factors and improving the quality of life has become a crucial area of research. This conceptual framework paper explores the potential of attitude and behavior change to enhance the quality of life for PLWE and their families. The study was conducted in rural Limpopo and Mpumalanga provinces (South Africa), employing an explanatory sequential mixed method approach. Participants included were PLWE (n = 163), their family members and caregivers (n = 519), healthcare practitioners (n = 102), and community members (n = 4290). The findings revealed significant knowledge, awareness, and behavior disparities among participants, with PLWE showing better consistency. Furthermore, the study highlighted the impact of consistency and balance in knowledge, awareness, and behavior on the overall quality of life for PLWE and their families. It is important to have intentional epilepsy education and accurate information sharing to influence attitudes, positive behavior, and improved quality of life for PLWE and their families. While the primary emphasis of this study lies in epilepsy, its implications may extend to other stigmatized and discrimination-prone illnesses, especially those affecting the brain. This highlights the significance of addressing societal attitudes toward such conditions as a measure of social progress. [ABSTRACT FROM AUTHOR]

In this paper, we propose a learning state evaluation method based on face detection and head pose estimation. This method is suitable for mobile devices with weak computing power, so it is necessary to control the parameter quantity of the face detection and head pose estimation network. Firstly, we propose a ghost and attention module (GA) base face detection network (GA-Face). GA-Face reduces the number of parameters and computation in the feature extraction network through the ghost module, and focuses the network on important features through a parameter-free attention mechanism. We also propose a lightweight dual-branch (DB) head pose estimation network: DB-Net. Finally, we propose a student learning state evaluation algorithm. This algorithm can evaluate the learning status of students based on the distance between their faces and the screen, as well as their head posture. We validate the effectiveness of the proposed GA-Face and DB-Net on several standard face detection datasets and standard head pose estimation datasets. Finally, we validate, through practical cases, that the proposed online learning state assessment method can effectively assess the level of student attention and concentration, and, due to its low computational complexity, will not interfere with the student's learning process. [ABSTRACT FROM AUTHOR]

A scheduling problem for parallel batch processing machines (BPMs) with jobs having unequal ready times in semiconductor wafer fabrication facilities (wafer fabs) is studied in this paper. A blended objective function combining the total weighted tardiness (TWT) and the total electricity cost (TEC) under a time-of-use (TOU) tariff is considered. A genetic programming (GP) procedure is designed to automatically discover priority indices for a heuristic scheduling framework. Results of computational experiments are reported that demonstrate that the learned priority indices lead to high-quality schedules in a short amount of computing time. [ABSTRACT FROM AUTHOR]

The introduction of ICT into education in educational settings has become increasingly common. Among these, the research and development of educational support robots have attracted attention. Conventional robots provide academic support through button operation by the learner. However, it has been reported that excessive requests for academic support can be problematic in environments in which learners can freely request academic support. To solve this problem, we developed a perplexion estimation method that estimates the state of perplexion from the learner's facial expression. When educational support is provided using the proposed method, the robot can autonomously provide academic support. Simulation experiments demonstrated that the perplexion estimation method has the potential to accurately estimate the learner's state. However, there is still no dedicated model for educational support robots that utilizes the perplexion estimation method. Therefore, this paper proposes an apprenticeship promotion model that integrates a learning support method based on cognitive apprenticeship theory and our perplexion estimation method. We then verified the learning effects of the robot equipped with the proposed model on the learner through participant experiments. The experimental results suggest that the robot equipped with the proposed model not only provides the same learning effect to university students as a conventional robot, but also can autonomously provide academic support at the optimal timing. [ABSTRACT FROM AUTHOR]

This paper aims at investigating the problem of fast convergence to the Nash equilibrium (NE) for N-Player noncooperative differential games. The proposed method is such that the players attain their NE point without steady-state oscillation (SSO) by measuring only their payoff values with no information about payoff functions, the model and also the actions of other players are not required for the players. The proposed method is based on an extremum seeking (ES) method, and moreover, compared to the traditional ES approaches, in the presented algorithm, the players can accomplish their NE faster. In fact, in our method, the amplitude of the sinusoidal excitation signal in classical ES is adaptively updated and exponentially converges to zero. In addition, the analysis of convergence to NE is provided in this paper. Finally, a simulation example confirms the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Despite lacking a generally accepted definition, Artificial General Intelligence (AGI) is commonly understood to refer to artificial agents possessing the capacity to build up a context-independent understanding of itself and the world and to generalize this knowledge across a multitude of contexts. In human agents, this capacity is, to a large degree, facilitated by processes of self-directed learning , during which agents voluntarily control the conditions under which episodes of learning and problem solving occur. Since self-directed learning depends on the degree of knowledge the agent has about various aspects of themselves (their bodily skills, their learning goal, etc.), an AGI implementation of this type of learning must build on a theory of how this self-knowledge is actualized and modified during the learning process. In this paper, we employ the pattern theory of self in order to characterize different aspects of an agent's self that are relevant for self-directed learning. Such aspects include agent-internal cognitive states such as thoughts, emotions, and intentions, but also relational states such as action possibilities in the environment. Combinations of these aspects form a characteristic pattern, which is unique to each individual agent, with no one aspect being necessary or sufficient for the individuation of that agent's self. Here, we focus on the interdependence of narrative and embodied aspects of the self-pattern, since they involve particularly salient challenges consisting in conceptualizing the interaction between propositional and motor representations. In our paper, we model the reciprocal interaction of these aspects of the self-pattern within an individual cognitive agent. We do so by extending an approach by Ryan, Agrawal, & Franklin (2020), who laid the groundwork for the implementation of the pattern theory of self in the LIDA (Learning Intelligent Decision Agent) model. We describe how embodied and narrative aspects of an agent's self-pattern are realized by patterns of interaction between different LIDA modules over time, and how interactions at multiple temporal scales allow the agent's self-pattern to be both dynamically variable and relatively stable. Finally, we investigate the implications this view has for the creation of artificial agents that can benefit from self-directed learning, both in the context of deliberate planning and adaptive motor execution. [ABSTRACT FROM AUTHOR]

As the demand for Internet access increases, malicious traffic on the Internet has soared also. In view of the fact that the existing malicious-traffic-identification methods suffer from low accuracy, this paper proposes a malicious-traffic-identification method based on contrastive learning. The proposed method is able to overcome the shortcomings of traditional methods that rely on labeled samples and is able to learn data feature representations carrying semantic information from unlabeled data, thus improving the model accuracy. In this paper, a new malicious traffic feature extraction model based on a Transformer is proposed. Employing a self-attention mechanism, the proposed feature extraction model can extract the bytes features of malicious traffic by performing calculations on the malicious traffic, thereby realizing the efficient identification of malicious traffic. In addition, a bidirectional GLSTM is introduced to extract the timing features of malicious traffic. The experimental results show that the proposed method is superior to the latest published methods in terms of accuracy and F1 score. [ABSTRACT FROM AUTHOR]

In recent decades, Islamic education and the religiosity of young Muslims have received considerable attention in academic research in German-speaking countries. However, an analysis of the different learning environments of religious education and their respective significance has yet to be carried out so far. Using Austria as an example, this paper explores these different processes of religious education among Muslim adolescents. Based on qualitative guided interviews, the experiences and learning processes in the family, in the mosque, in the school, and online are depicted from the learners' perspective. In this way, this paper assigns Muslim adolescents a constitutive role in the analysis. In this context, we discuss how the understanding of education, pedagogical approaches, and person-centredness differs in the learning environments of Muslim religious education. [ABSTRACT FROM AUTHOR]

Informed consent is the cornerstone of human research subject protection. Many subjects sign consent documents without understanding the study purpose, procedures, risks, benefits, and their rights. Proof of comprehension is not required and rarely obtained. Understanding might improve by using an interactive system with multiple options for hearing, viewing and reading about the study and the consent form at the subject’s own pace with testing and immediate feedback. This prospective randomized study compared the IRB-approved paper ICF for an actual clinical research study with an interactive presentation of the same study and its associated consent form using an iPad device in two populations: clinical research professionals, and patients drawn from a variety of outpatient practice settings. Of the 90 participants, 69 completed the online test and survey questions the day after the session (maximum 36 hours post-session). Among research professionals (n = 14), there was a trend (p  = .07) in the direction of iPad subjects testing better on the online test (mean correct  =  77%) compared with paper subjects (mean correct  =  57%). Among patients (n = 55), iPad subjects had significantly higher test scores than standard paper consent subjects (mean correct  =  75% vs 58%, p < .001). For all subjects, the total time spent reviewing the paper consent was 13.2 minutes, significantly less than the average of 22.7 minutes total on the three components to be reviewed using the iPad (introductory video, consent form, interactive quiz). Overall satisfaction and overall enjoyment slightly favored the interactive iPad presentation. This study demonstrates that combining an introductory video, standard consent language, and an interactive quiz on a tablet-based system improves comprehension of research study procedures and risks. [ABSTRACT FROM AUTHOR]

Most undergraduates lack the scientific background to read and appreciate much of the primary literature in physiology. Even when the underlying concepts are elegantly simple, the inherent complexity of contemporary papers often makes the work inaccessible to them. However, with a little help, they can be guided to an understanding of the creative thought processes that underlie the research and to appreciate its significance. This is especially true of many classic papers in physiology that often rely on easily comprehensible techniques. Moreover, the American Physiological Society (APS) has invited prominent scientists to select important papers in their fields and to write essays that both put the work into historical context and explain why it is scientifically important. The APS Legacy Project makes these classic papers freely available online. One such paper by Gottschalk and Mylle presents data from a series of micropuncture studies that confirm all of the predictions of the countercurrent exchange model of concentrated urine production (2). The included handout of questions for discovery learning and teaching points suggest ways to use the paper as an instructional resource. [ABSTRACT FROM AUTHOR]

This case study investigated how 23 students adapted to using a completely online textbook in lieu of a traditional paper text. All were enrolled in a single advanced MSW practice course. A variety of adaptation styles evolved. The students' primary strategy was to revert to making paper copies when permitted to do so instead of reading the assigned materials online. While a few students adapted to the electronic textbook, most generally did not because of interface design, time constraints, and study strategies. Implications for further research on relying completely on electronically-distributed reading materials are discussed. [ABSTRACT FROM AUTHOR]

This position paper investigates the merits and potential benefits of creating a new, more comprehensive professional association for members of the learning assistance and developmental education profession. This task was assigned to the College Reading and Learning Association/National Association for Developmental Education (CRLA/NADE) Working Group by the CRLA and NADE national executive boards. This Working Group considered not only the issue of effectiveness of the current professional associations but also the merits of expanding the mission and vision of a new professional association. Building upon the success of CRLA and NADE, the Working Group identified many ways a new association could better serve members and have a greater influence on student success and in society (CRLA/NADE Taskforce, 2007). [ABSTRACT FROM AUTHOR]

This paper analyses farmers’ networking strategies for sustainable agricultural development. The focus is on internal barriers of farmers’ networks with respect to the management of the group and collective learning processes. These aspects determine to an extent the success or failure of collective strategies. Based upon case study material we will draw lessons and present ideas on how management and learning can be enhanced. We argue that in collective strategies the focus should not only be on the goal of the group, but that attention to the process of cooperation such as safeguarding coherence, monitoring and evaluation of goals and views, shared responsibility and balanced leadership is a prerequisite for effective collective action. [Copyright &y& Elsevier]

This paper presents research findings and design strategies that illustrate how digital technology can be applied as a tool for hybrid placemaking in ways that would not be possible in purely digital or physical spaces. Digital technology has revolutionised the way people learn and gather new information. This trend has challenged the role of the library as a physical place, as well as the interplay of digital and physical aspects of the library. The paper provides an overview of how the penetration of digital technology into everyday life has affected the library as a place, both as designed by placemakers and as perceived by library users. It then identifies a gap in current library research about the use of digital technology as a tool for placemaking, and reports results from a study of Gelatine -- a custom-built user check-in system that displays real-time user information on a set of public screens. Gelatine and its evaluation at The Edge, at the State Library of Queensland, illustrates how combining affordances of social, spatial and digital space can improve the connected learning experience among on-site visitors. Future design strategies involving gamifying the user experience in libraries are described based on Gelatine's infrastructure. The presented design ideas and concepts are relevant for managers and designers of libraries, as well as other informal, social learning environments. [ABSTRACT FROM AUTHOR]

The manufacturing sector plays a strategic role as a major contributor to economic growth and development. However, the harsh business environment in Nigeria has constrained learning and capability building in the Nigerian manufacturing sector. The present state of the manufacturing sector underscores the need for firm-level learning and strategic policy actions. This paper utilized data from the Enterprise Survey Panel covering the periods 2007, 2009, and 2014/2015 to investigate firm learning and productivity in the Nigerian manufacturing sector. Case study illustrations were also undertaken to further provide insights into the links between learning variables and the productivity of selected firms in the sector. Data were analyzed using descriptive statistics; dynamic panel model (DPM) via ordinary least squares (OLS) and General Method of Moments (GMM) techniques. The results of the estimation show there is a positive and significant relationship between export participation lagged by one period (t-1) and the current firm performance. A one-period lag of the learning variables, namely: skills and training increased the productivity of firms. The case study illustrations revealed that major learning capabilities include customer feedback; through employees, staff training/seminars/workshops, and supplier feedback. The paper provides evidence to conjecture that the STI mode of learning, which involves formal research and development (R&D) in firms is not deep enough, and that domestic firms have less productivity relative to firms with some proportion of foreign ownership. Also, some of the constraints to learning and productivity are an unstable regulatory environment, poor infrastructure and high cost of doing business. The paper recommends both formal and informal modes/mechanisms of learning are important to ensure improved productivity of manufacturing firms in Nigeria Also, learning opportunities may differ within and across manufacturing subsectors. Industry regulators or agencies should organize to provide a forum for firms and relevant stakeholders to regularly interact on learning experiences to learn from each other and collaborate to address obstacles to productivity. [ABSTRACT FROM AUTHOR]

Background: Theories of learning are of clear importance to resilience in healthcare since the ability to successfully adapt and improve patient care is closely linked to the ability to understand what happens and why. Learning from both positive and negative events is crucial. While several tools and approaches for learning from adverse events have been developed, tools for learning from successful events are scarce. Theoretical anchoring, understanding of learning mechanisms, and establishing foundational principles for learning in resilience are pivotal strategies when designing interventions to develop or strengthen resilient performance. The resilient healthcare literature has called for resilience interventions, and new tools to translate resilience into practice have emerged but without necessarily stipulating foundational learning principles. Unless learning principles are anchored in the literature and based on research evidence, successful innovation in the field is unlikely to occur. The aim of this paper is to explore: What are key learning principles for developing learning tools to help translate resilience into practice? Methods: This paper reports on a two-phased mixed methods study which took place over a 3-year period. A range of data collection and development activities were conducted including a participatory approach which involved iterative workshops with multiple stakeholders in the Norwegian healthcare system. Results: In total, eight learning principles were generated which can be used to help develop learning tools to translate resilience into practice. The principles are grounded in stakeholder needs and experiences and in the literature. The principles are divided into three groups: collaborative, practical, and content elements. Conclusions: The establishment of eight learning principles that aim to help develop tools to translate resilience into practice. In turn, this may support the adoption of collaborative learning approaches and the establishment of reflexive spaces which acknowledge system complexity across contexts. They demonstrate easy usability and relevance to practice. [ABSTRACT FROM AUTHOR]

The theoretical and practical acquisition of skills to carry out the necessary steps consciously and safely in an emergency is essential for training specialized personnel. Due to the lack of trained experts on site, such as firefighters or emergency doctors, learning the skills is a high priority in the maritime sector. Not least through adjustments in the certification of qualifications, through the refreshing of knowledge in specified time frames, the topic has been given greater importance. This paper will further describe the efforts of the FIP-S2@Novia cooperation to develop a virtual reality-based learning application for the maritime sector, in particular an application for learning how to use a Fast Rescue Boat in a person overboard operation. Furthermore, the paper describes the technical approach, the implementation of the VR application in Unity as well as the connection of the application to the European maritime simulation network (EMSN Connect), and its use in a connected simulation exercise. [ABSTRACT FROM AUTHOR]

With the development of smart classrooms, analyzing students' emotions for classroom learning is an effective means of accurately capturing their learning process. Although facial expression-based emotion analysis methods are effective in analyzing classroom learning emotions, current research focuses on facial expressions and does not consider the fact that expressions in different postures do not represent the same emotions. To provide a continuous and deeper understanding of students' learning emotions, this study proposes an algorithm to characterize learning emotions based on classroom time-series image data. First, face expression data for classroom scenarios are established to address the lack of expression databases in real teaching environments. Second, to improve the accuracy of facial expression recognition, a residual channel cross transformer masking net expression recognition model is proposed in this paper. Finally, to address the problem that the existing research dimension of learning emotion is too single, this paper uses the facial expression and head posture data obtained from deep learning models for fusion analysis and innovatively proposes a Dempster–Shafer evidence-theoretic fusion model to characterize the learning emotion within the lecture duration of knowledge points. The experiments show that both the proposed expression recognition model and the learning sentiment analysis algorithm have good performance, with the expression recognition model achieving an accuracy of 73.58% on the FER2013 dataset. The proposed learning emotion analysis method provides technical support for holistic analysis of student learning effects and evaluation of students' level of understanding of the knowledge points. [ABSTRACT FROM AUTHOR]

Understanding student interaction in learning spaces is an ongoing challenge. The move away from didactic lecture delivery towards more active and hybrid learning renders this challenge ever more difficult. Researching pedagogic use of informal learning space, which is not formally timetabled or controlled, is always challenging because it is interacted with only transiently by both students and teachers. This paper introduces a mixed methods, phenomenological approach used in recent research to investigate campus learning spaces in face-to-face learning contexts. The full mixed methods approach combined space occupancy monitoring data with naturalistic ethnographic observation, field interviews and, where appropriate, more formal in-depth interviews to provide an effective way of understanding student and teacher engagement with learning spaces. Convergent use of these qualitative and quantitative methods yielded data which informed the application of subsequent methods, and the investment of researcher, pedagogic and infrastructural resource. In this paper we argue that as learning outside of formal teaching spaces increases, these mixed methods enable better, more efficient monitoring of pedagogic use of informal learning spaces. The mixed method can be adapted depending on the question being addressed and has the potential to inform resource allocation and investment into pedagogic and infrastructural change. [ABSTRACT FROM AUTHOR]

Fundamentally, newborn items that are used commercially, such as chicken, fish, and small camel, grow day by day in size and also increase their weight. The seller offers a credit policy to the buyer to increase sales for a particular growing item (fish), and in this paper, it is assumed that the buyer accepts the policy of the trade credit. In this paper, the buyer acquires the newborn items (fish) from the seller and then sells them when the newborn items have increased their size and weight. From this point of view, the present paper reveals a fuzzy-based supply chain model that includes carbon emissions and a permissible delay in payment for defective growing items (fish) under the effect of learning where the demand rate is imprecise in nature and is treated as a triangular fuzzy number. Finally, the buyer's total profit is optimized with respect to the number of newborn items. A numerical example has been presented for the justification of the model. The findings clearly suggest that the presence of trade credit, learning, and a fuzzy environment have an affirmative effect on the ordering policy. The buyer should order more to avoid higher interest charges after the grace period, which eventually increases their profit, while at the same time, it is also beneficial for the buyer to order less to gain the benefit of the trade credit period. The fuzziness theory controls the uncertainty situation of inventory parameters with the help of a de-fuzzified method. The lower and upper deviation of demand affects the total fuzzy profit. The effect of learning gives a positive response concerning the size of the order and the buyer's total fuzzy profit. This means that the decision-maker should be aware of the size of the newborn items, rate of learning, and trade credit period during the supply chain because these directly affect the buyer's total fuzzy profit. The impact of the inventory parameter of this model is presented with the help of sensitivity analysis. [ABSTRACT FROM AUTHOR]