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The purpose of this study was to develop a suitable module for digital conservation of traditional knowledge of medicinal plants (MPs) used by tribal communities living in the Anuppur district of Madhya Pradesh, Central India.

The research used a qualitative approach to gather the data of MPs through the use of literature review and field survey. Based on the acquired data, a prototype digital learning system was constructed and assessed. This study used digital learning technologies to assess the requirements for transmitting traditional knowledge of important MPs used by tribal communities so that people can absorb and conserve them.

Over time, the focus on the digital conservation of traditional MP’s knowledge has progressively increased globally. Despite the rise in this field of study, information technology methods to preserve and distribute traditional knowledge of MPs have remained a few. When adopting digital learning to maintain traditional knowledge of MPs, it was discovered that it would be necessary to engage with relevant knowledge keepers, use multimedia, and provide content in local languages.

This study helps in conservation of important MP species that are having biologically important therapeutic compounds meant for treating various ailments. Older generations of various tribal communities mainly hold traditional knowledge of important MPs, and unless it is preserved, it will perish along with its caretakers.

It is worth looking at a digital platform that can help future generations to maintain traditional knowledge of MPs, as it is a dynamic and ever-changing, it must involve a digital tool for its future conservation. Current methods for maintaining traditional knowledge of MPs were ineffective and constrained by space and time.

This paper seeks to develop a conceptual model that enables understanding of consumer purchase decisions in relation to the first customized products, including steps of the decision process, determinants, and consequences of each step.

The classic grounded theory approach was used.

The study found that the process consists of six steps called knowledge learning and preliminary information searching, problem recognition, budget setting, detailed information searching and solution creating, purchase involvement, and use and post‐purchase. The process is distinct from the process of traditional models of consumer decision mainly from three aspects: the process starting from “knowledge learning and information searching”, not from “problem recognition”, while “problem recognition” is the second step; information searched in the process mainly on components of products, with little on products; and the process includes a step “solution creating”, but without steps “alternative evaluation” and “choice”. The consequences of the first step consist of knowledge mastered, market information acquired, pre‐decisions, perceived value of customized PC, positive attitude towards customized PC, and self‐confidence, which are the main determinants of the following steps. Besides these determinants, others included are interest, curiosity, work with computers as tools, sources of knowledge and information on PC, and income.

The study provides a foundation for future quantitative research on determinants of consumers' purchasing the first customized products and provides insights into marketing: for example, target consumers of customized PC are characterized at least by having great self‐confidence in their capability to make an effective decision in purchasing customized PC, and having mastered enough PC knowledge.

Across a variety of domains, consumers are demanding increased customized products. While consumer decision making has become a prominent research topic in various fields of marketing and consumer science over the past decades, surprisingly little research has examined consumer purchase decisions in relation to the first customized personal computer (PC) and factors influencing such a process. The study may fill this gap.

This paper deals with the organizing of interactive product development. Developing products in interaction between firms may provide benefits in terms of specialization, increased innovation, and possibilities to perform development activities in parallel. However, the differentiation of product development among a number of firms also implies that various dependencies need to be dealt with across firm boundaries. How dependencies may be dealt with across firms is related to how product development is organized. The purpose of the paper is to explore dependencies and how interactive product development may be organized with regard to these dependencies.

The analytical framework is based on the industrial network approach, and deals with the development of products in terms of adaptation and combination of heterogeneous resources. There are dependencies between resources, that is, they are embedded, implying that no resource can be developed in isolation. The characteristics of and dependencies related to four main categories of resources (products, production facilities, business units and business relationships) provide a basis for analyzing the organizing of interactive product development.

Three in-depth case studies are used to explore the organizing of interactive product development with regard to dependencies. The first two cases are based on the development of the electrical system and the seats for Volvo’s large car platform (P2), performed in interaction with Delphi and Lear respectively. The third case is based on the interaction between Scania and Dayco/DFC Tech for the development of various pipes and hoses for a new truck model.

The analysis is focused on what different dependencies the firms considered and dealt with, and how product development was organized with regard to these dependencies. It is concluded that there is a complex and dynamic pattern of dependencies that reaches far beyond the developed product as well as beyond individual business units. To deal with these dependencies, development may be organized in teams where several business units are represented. This enables interaction between different business units’ resource collections, which is important for resource adaptation as well as for innovation. The delimiting and relating functions of the team boundary are elaborated upon and it is argued that also teams may be regarded as actors. It is also concluded that a modular product structure may entail a modular organization with regard to the teams, though, interaction between business units and teams is needed. A strong connection between the technical structure and the organizational structure is identified and it is concluded that policies regarding the technical structure (e.g. concerning “carry-over”) cannot be separated from the management of the organizational structure (e.g. the supplier structure). The organizing of product development is in itself a complex and dynamic task that needs to be subject to interaction between business units.

Prior learning and prior knowledge are among the most dependable and consistent factors in predicting students’ success (Richardson et al., 2012). Although for UK Higher Education, the traditional A-level (advanced level qualification) remains the principal qualification students use to gain entry to University, there has been a small but significant rise in alternative qualifications, such as the International Baccalaureate (IB) and vocational qualifications such as that from the Business and Technology Education Council (BTEC). The multidisciplinary nature of Psychology means students enter the degree program with a range of qualifications in differing topic areas. The current case study aimed to assess if science qualifications aided student success in the University of Liverpool’s Psychology course. Ordinal regression and correlations were used to examine the impact of prior qualifications on three first-year cohort module scores (Psychobiology, Social psychology, and Research Methods) and the overall degree mark across three cohorts of Psychology students (n = 1,072). University entry grades showed a significant overall and subject specific effect of scientific prior knowledge. However, the effects of previous qualifications were not cumulative and did not persist beyond the first year of study. These findings were strongest for Chemistry in the Psychobiology module suggesting that scientific literacy – the understanding of scientific concepts, phenomena, and processes, as well as an individual’s ability to apply such knowledge to new or non-scientific situations (Schleicher, 2019) – rather than domain-specific knowledge is driving such increase in grades. A negative relationship was seen for those holding BTEC qualifications, suggesting that vocational qualifications, specifically for this Psychology program, were of less use than academic ones, even if topic areas were similar – a finding which may also apply to other academic based courses, and warrants further study. Although the advantage of prior qualifications diminishes across the course of study, this small but distinct advantage suggests that making a science qualification a requirement for a place on a Psychology degree course would be a beneficial step for admissions tutors to consider.

The literature on non-traditional classroom environments claims that the changed emphasis in higher education teaching from the lecturer to students has intensified the global focus on student-centred learning, prompting colleges and universities globally to introspect, re-examine, and re-structure their pedagogical approaches in an attempt to align with national educational policies, and to position themselves favourably with potential students in an increasingly competitive higher education environment. This is an environment that now relies heavily on digital learning technologies, which has provoked scholars such as Heick (2012) to perceive the change to the virtual as one that makes higher education institutions accessible from anywhere – in the cloud, at home, in the workplace, or restaurant. The COVID-19 crisis has reinforced the need for this flexibility. These forces have put universities and colleges under pressure to implement new teaching approaches in non-traditional classroom settings that are appropriate for, and responsive to, the COVID-19 crisis and students in terms of learning and social support. This chapter identified and appraised key teaching approaches. It is evident that there are three key teaching approaches that higher education institutions have adopted for delivering learning in an emergency and in a student-centred fashion. The three approaches, which include the time and place dispersion, transactional distance, and collaborative learning approaches, embrace social support because they are grounded in social constructivism. Academics need to be fully committed to the role of social support giving – that is, emotional, instrumental, informational, and appraisal support – in order to foster student wellbeing and cognitive development as students learn together but apart in non-traditional classrooms. The hurried manner in which teaching and learning practices in many higher education institutions have been moved to the online format has led academics to violate many key principles of the approaches they have adopted. And this situation is borne out in the case study discussed in Chapter 8 of this volume. A review of current remote teaching and learning practices is required if academics are to embrace the full principles of the approaches that are appropriate for teaching and learning in non-traditional classroom contexts.

This paper aims to present a novel pedagogical approach to education for sustainability within the business curriculum that adopts a sustainability audit of a fictional company presented as a case study as the focus of learning, teaching and assessment. It evaluates the user’s ability to provide the active learning called for in education for sustainability literature and hands-on learning that business management students prefer.

This study explores students’ qualitative and quantitative responses to pre- and post-module surveys and module evaluations to establish the effectiveness of focussing learning, teaching and assessment on a sustainability audit. The study, undertaken over a two-year period, adopts four indicators of learning and teaching effectiveness to synthesise, evaluate and present the findings as follows: development of sustainability knowledge and skill, employment skills, career and life skills and engagement.

The study finds that a sustainability audit can develop students’ knowledge and skills in all four indicators of learning and teaching effectiveness. In addition, the findings suggest it can raise students’ learning awareness and recognition of their role in the learning process.

This paper reports the findings of a small scale, two-year study. As such, it presents indicative findings rather than generalised conclusions.

Designing a pedagogical approach to education for sustainability within the business curriculum around the completion of a sustainability audit can offer hands-on learning experiences that meet students’ preferences for interactive, experiential and collaborative learning within real-world environments, employers’ demands for employment-ready graduates and educators’ hopes for sustainability advocates.

This study builds on the existing pedagogic discourse of pedagogic means and methods for education for sustainability within the business curriculum. It provides insight into effective hands-on education for sustainability within the business curriculum and offers experience-based guidance to educators seeking to develop immersive, active and experiential, real-world pedagogical approaches.

This paper aims to examine the preferences of students towards different teaching methods and the perceived effectiveness of experiential teaching methods in different operations management (OM) modules.

Student perceptions of different teaching methods and various aspects of an experiential teaching method, in the form of a business simulation game, are examined using survey data from 274 respondents in four small post‐experience and two large pre‐experience OM modules.

The paper's analysis suggests that traditional and experiential teaching methods are both popular with OM students, whilst independent teaching methods are less well liked. Analysis also shows that students on both kinds of OM modules perceive most aspects of the experiential teaching method used in this study (The Operations Game) very positively.

This research study was confined to a particular type of experiential teaching method – a business simulation game. There is a need for further research to investigate the perceived effectiveness of other experiential teaching methods, such as role‐plays and live cases. Furthermore, the paper does not examine the use of experiential teaching methods that do not require the physical presence of students.

For OM educators, the paper clarifies how they might incorporate experiential teaching methods in different class settings. Whilst experiential teaching methods are typically used for small post‐experience modules, these data indicate that the method can also be used on larger pre‐experience modules with great success. The paper also notes a number of challenges involved in using experiential teaching methods on both kinds of module.

This is the first known study to directly examine the perceived effectiveness of an experiential teaching method in both small post‐experience and larger pre‐experience OM modules.

This study aims to assess “learning opportunities” provided to undergraduate students, from level three to six, in higher education (HE). A knowledge gap was identified within the current practice relating to learning opportunities for built environment (BE) students in HE. The study focussed on the themes under section two of the national student survey (NSS): how students explore ideas or concepts in-depth, bring information and ideas together from different topics and apply the learned content in a real-life context. The study aimed to provide recommendations for enhancing “learning opportunities” to the BE students within HE.

Data collection focussed on section two of NSS “learning opportunities” and documentary analysis, and a qualitative survey were adopted for this study. A documental analysis of 334 mid-module reviews was carried out. The qualitative data was collected from level three to level six students and academics from architecture, construction management, civil engineering and quantity surveying disciplines representing BE context. A sample of 40 students and 15 academics, including a Head of school, a Principal lecturer, Subject leads and lecturers, participated in interviews as part of a qualitative survey. In total, 12 drivers were developed using the data obtained through literature, documental analysis and interviews. These drivers were analysed using manual content analysis to identify their influence on the specified themes under NSS section two and circulated amongst academics to be ranked by identifying its influence to promote learning opportunities to BE students in HE.

This study highlighted 12 drivers which promote learning opportunities in HE within BE curriculum. Findings established that topics should be explained with more real-life or industry-orientated concepts such as simplification integrated into module delivery. Contrary to the literature, the use of physical materials (i.e. handouts and whiteboard) in addition to a virtual learning environment for detailed explanations were considered effective in exploring concepts. During the current COVID-19 pandemic, context-based learning needs to be promoted by integrating videos of practical implementation for better understanding. The study recognised that lab, fieldwork and tutorials were essential to apply what students have learned in BE curricula to a real-life context.

This study identified current learning approaches and provided recommendations to improve the BE students learning experience in HE. They identified 12 drivers that would significantly help academics and academic institutions to understand how learning opportunities should be facilitated in the BE curriculum to enhance student performances in HE.

Limited by the types of sensors, the state information available for musculoskeletal robots with highly redundant, nonlinear muscles is often incomplete, which makes the control face a bottleneck problem. The aim of this paper is to design a method to improve the motion performance of musculoskeletal robots in partially observable scenarios, and to leverage the ontology knowledge to enhance the algorithm’s adaptability to musculoskeletal robots that have undergone changes.

A memory and attention-based reinforcement learning method is proposed for musculoskeletal robots with prior knowledge of muscle synergies. First, to deal with partially observed states available to musculoskeletal robots, a memory and attention-based network architecture is proposed for inferring more sufficient and intrinsic states. Second, inspired by muscle synergy hypothesis in neuroscience, prior knowledge of a musculoskeletal robot’s muscle synergies is embedded in network structure and reward shaping.

Based on systematic validation, it is found that the proposed method demonstrates superiority over the traditional twin delayed deep deterministic policy gradients (TD3) algorithm. A musculoskeletal robot with highly redundant, nonlinear muscles is adopted to implement goal-directed tasks. In the case of 21-dimensional states, the learning efficiency and accuracy are significantly improved compared with the traditional TD3 algorithm; in the case of 13-dimensional states without velocities and information from the end effector, the traditional TD3 is unable to complete the reaching tasks, while the proposed method breaks through this bottleneck problem.

In this paper, a novel memory and attention-based reinforcement learning method with prior knowledge of muscle synergies is proposed for musculoskeletal robots to deal with partially observable scenarios. Compared with the existing methods, the proposed method effectively improves the performance. Furthermore, this paper promotes the fusion of neuroscience and robotics.

In recent years, knowledge graph completion has gained increasing research focus and shown significant improvements. However, most existing models only use the structures of knowledge graph triples when obtaining the entity and relationship representations. In contrast, the integration of the entity description and the knowledge graph network structure has been ignored. This paper aims to investigate how to leverage both the entity description and the network structure to enhance the knowledge graph completion with a high generalization ability among different datasets.

The authors propose an entity-description augmented knowledge graph completion model (EDA-KGC), which incorporates the entity description and network structure. It consists of three modules, i.e. representation initialization, deep interaction and reasoning. The representation initialization module utilizes entity descriptions to obtain the pre-trained representation of entities. The deep interaction module acquires the features of the deep interaction between entities and relationships. The reasoning component performs matrix manipulations with the deep interaction feature vector and entity representation matrix, thus obtaining the probability distribution of target entities. The authors conduct intensive experiments on the FB15K, WN18, FB15K-237 and WN18RR data sets to validate the effect of the proposed model.

The experiments demonstrate that the proposed model outperforms the traditional structure-based knowledge graph completion model and the entity-description-enhanced knowledge graph completion model. The experiments also suggest that the model has greater feasibility in different scenarios such as sparse data, dynamic entities and limited training epochs. The study shows that the integration of entity description and network structure can significantly increase the effect of the knowledge graph completion task.

The research has a significant reference for completing the missing information in the knowledge graph and improving the application effect of the knowledge graph in information retrieval, question answering and other fields.