This study furthers game-based learning for circular business model innovation (CBMI), the complex, dynamic process of designing business models according to the circular economy principles. The study explores how game-play in an educational setting affects learning progress on the level of business model elements and from the perspective of six learning categories. We experimented with two student groups using our game education package Re-Organise. All students first studied a reader and a game role description and then filled out a circular business model canvas and a learning reflection. The first group, i.e., the game group, updated the canvas and the reflection in an interactive tutorial after gameplay. The control group submitted their updated canvas and reflection directly after the interactive tutorial without playing the game. The results were analyzed using text-mining and qualitative methods such as word co-occurrence and sentiment polarity. The game group created richer business models (using more waste processing technologies) and reflections with stronger sentiments toward the learning experience. Our detailed study results (i.e., per business model element and learning category) enhance understanding of game-based learning for circular business model innovation while providing directions for improving serious games and accompanying educational packages.
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The principal aim of this study is to explore the relations between work domains and the work-related learning of workers. The article is intended to provide insight into the learning experiences of Dutch police officers during the course of their daily work. Interviews regarding actual learning events and subsequent changes in knowledge, skills or attitudes were conducted with police officers from different parts of the country and in different stages of their careers. Interpretative analyses grounded in the notion of intentionality and developmental relatedness revealed how and in what kinds of work domains police officers appear to learn. HOMALS analysis showed work-related learning activities to vary with different kinds of work domains. The implications for training and development involve the role of colleagues in different hierarchical positions for learning and they also concern the utility of the conceptualisation of work-related learning presented here.
Educational programs teaching entrepreneurial behaviour and knowledge are crucial to a vital and healthy economy. The concept of building a Communities of Practice (CoP) could be very promising. CoP’s are formed by people who engage in a process of collective learning in a shared domain of human endeavour (Wenger, McDermott and Snyder, 2002). They consist of a group of people who share a concern or a passion for something they do and learn how to do it better as they interact regularly. Normally CoP’s are rather homogeneous. Saxion institute Small Business & Retail Management (SB&RM) started a CoP with entrepreneurs September 2007. Typical in the this community, are the differences between the partners. The Community consists of students, entrepreneurs and members of an institution for higher education. They have different characteristics and they don’t share the same knowledge. Thus, building long-lasting relations can be complicated. Solid relations for longer periods are nevertheless inevitable in using CoP as a mean in an educational concept that takes approximately 4 years. After one year an evaluation took place on the main aspects of a lasting partnership. The central problem SB&RM in Deventer faces is to design the CoP in a way possible members will join and stay for a longer period and in a way it ensures entrepreneurial learning. This means important design characteristics have to be identified, and the CoP in Deventer has to be evaluated to assess whether it meets those design characteristics in an effective and efficient way. The main target of the evaluation is to determine which key factors are important to make sure continuity in partnership is assured and entrepreneurial learning is best supported. To solve the problem, an investigation on how a CoP works, what group dynamics take place, and how this can be measured has to be conducted. Furthermoreusing the CoP as a tool for entrepreneurship means key aspects of entrepreneurial learning have to be identified. After that the CoP in Deventer has to be examined on both aspects. According to literature CoP’s define themselves along three dimensions: domain (indicating what is it about), community (defining how it functions), and practice (indicating what capabilities it has produced) (Wenger, 1998). This leads to meaningful, shared and coordinated activities (Akkerman et al, 2007): Key aspects of a successful CoP lie in both hard and soft sides of creating a partnership. It means on one hand a CoP has to deal with defining their own overall vision, formulating long term goals and targets on the short term. They have to formulate how to achieve those targets and create meaningful activities (reification). On the other hand a CoP has to deal with relations, trust, norms and values (participation). Reification and participation as design characteristic can provide indicators on which the CoP in Deventer can be evaluated. A lasting partnership means joining the CoP and staying. Weick provides us with a suitable model that enables us to do research and evaluate whether the CoP in Deventer is successful or not, Weick’s model of means convergence. To effectively ensure entrepreneurial learning the process in the CoP has to provide or enable actionoriented forms through Project-based activity, accompanied by reflection, with high emotional exposure (or cognitive affection) preferably caused by discontinuities to be suitable as a tool in entrepreneurial learning. Furthermore it should be accompanied by the right preconditions to work effectively and efficiently. The evaluation of the present CoP in Deventer is done by interviewing all participants at the end of the first year of the partnership. In a structured interview, based on literature studies, all participants were separately questioned
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-Chatbots are being used at an increasing rate, for instance, for simple Q&A conversations, flight reservations, online shopping and news aggregation. However, users expect to be served as effective and reliable as they were with human-based systems and are unforgiving once the system fails to understand them, engage them or show them human empathy. This problem is more prominent when the technology is used in domains such as health care, where empathy and the ability to give emotional support are most essential during interaction with the person. Empathy, however, is a unique human skill, and conversational agents such as chatbots cannot yet express empathy in nuanced ways to account for its complex nature and quality. This project focuses on designing emotionally supportive conversational agents within the mental health domain. We take a user-centered co-creation approach to focus on the mental health problems of sexual assault victims. This group is chosen specifically, because of the high rate of the sexual assault incidents and its lifetime destructive effects on the victim and the fact that although early intervention and treatment is necessary to prevent future mental health problems, these incidents largely go unreported due to the stigma attached to sexual assault. On the other hand, research shows that people feel more comfortable talking to chatbots about intimate topics since they feel no fear of judgment. We think an emotionally supportive and empathic chatbot specifically designed to encourage self-disclosure among sexual assault victims could help those who remain silent in fear of negative evaluation and empower them to process their experience better and take the necessary steps towards treatment early on.
Examining in-class activities to facilitate academic achievement in higher educationThere is an increasing interest in how to create an effective and comfortable indoor environment for lecturers and students in higher education. To achieve evidence-based improvements in the indoor environmental quality (IEQ) of higher education learning environments, this research aimed to gain new knowledge for creating optimal indoor environmental conditions that best facilitate in-class activities, i.e. teaching and learning, and foster academic achievement. The academic performance of lecturers and students is subdivided into short-term academic performance, for example, during a lecture and long-term academic performance, during an academic course or year, for example. First, a systematic literature review was conducted to reveal the effect of indoor environmental quality in classrooms in higher education on the quality of teaching, the quality of learning, and students’ academic achievement. With the information gathered on the applied methods during the literature review, a systematic approach was developed and validated to capture the effect of the IEQ on the main outcomes. This approach enables research that aims to examine the effect of all four IEQ parameters, indoor air quality, thermal conditions, lighting conditions, and acoustic conditions on students’ perceptions, responses, and short-term academic performance in the context of higher education classrooms. Next, a field experiment was conducted, applying the validated systematic approach, to explore the effect of multiple indoor environmental parameters on students and their short-term academic performance in higher education. Finally, a qualitative case study gathered lecturers’ and students’ perceptions related to the IEQ. Furthermore, how these users interact with the environment to maintain an acceptable IEQ was studied.During the systematic literature review, multiple scientific databases were searched to identify relevant scientific evidence. After the screening process, 21 publications were included. The collected evidence showed that IEQ can contribute positively to students’ academic achievement. However, it can also affect the performance of students negatively, even if the IEQ meets current standards for classrooms’ IEQ conditions. Not one optimal IEQ was identified after studying the evidence. Indoor environmental conditions in which students perform at their best differ and are task depended, indicating that classrooms should facilitate multiple indoor environmental conditions. Furthermore, the evidence provides practical information for improving the design of experimental studies, helps researchers in identifying relevant parameters, and lists methods to examine the influence of the IEQ on users.The measurement methods deduced from the included studies of the literature review, were used for the development of a systematic approach measuring classroom IEQ and students’ perceived IEQ, internal responses, and short-term academic performance. This approach allowed studying the effect of multiple IEQ parameters simultaneously and was tested in a pilot study during a regular academic course. The perceptions, internal responses, and short-term academic performance of participating students were measured. The results show associations between natural variations of the IEQ and students’ perceptions. These perceptions were associated with their physiological and cognitive responses. Furthermore, students’ perceived cognitive responses were associated with their short-term academic performance. These observed associations confirm the construct validity of the composed systematic approach. This systematic approach was then applied in a field experiment, to explore the effect of multiple indoor environmental parameters on students and their short-term academic performance in higher education. A field study, with a between-groups experimental design, was conducted during a regular academic course in 2020-2021 to analyze the effect of different acoustic, lighting, and indoor air quality (IAQ) conditions. First, the reverberation time was manipulated to 0.4 s in the intervention condition (control condition 0.6 s). Second, the horizontal illuminance level was raised from 500 to 750 lx in the intervention condition (control condition 500 lx). These conditions correspond with quality class A (intervention condition) and B (control condition), specified in Dutch IEQ guidelines for school buildings (2015). Third, the IAQ, which was ~1100 ppm carbon dioxide (CO2), as a proxy for IAQ, was improved to CO2 concentrations under 800 ppm, meeting quality class A in both conditions. Students’ perceptions were measured during seven campaigns with a questionnaire; their actual cognitive and short-term academic performances were evaluated with validated tests and an academic test, composed by the lecturer, as a subject-matter-expert on the taught topic, covered subjects discussed during the lecture. From 201 students 527 responses were collected and analyzed. A reduced RT in combination with raised HI improved students’ perceptions of the lighting environment, internal responses, and quality of learning. However, this experimental condition negatively influenced students’ ability to solve problems, while students' content-related test scores were not influenced. This shows that although quality class A conditions for RT and HI improved students’ perceptions, it did not influence their short-term academic performance. Furthermore, the benefits of reduced RT in combination with raised HI were not observed in improved IAQ conditions. Whether the sequential order of the experimental conditions is relevant in inducing these effects and/or whether improving two parameters is already beneficial, is unknownFinally, a qualitative case study explored lecturers’ and students’ perceptions of the IEQ of classrooms, which are suitable to give tutorials with a maximum capacity of about 30 students. Furthermore, how lecturers and students interact with this indoor environment to maintain an acceptable IEQ was examined. Eleven lecturers of the Hanze University of Applied Sciences (UAS), located in the northern part of the Netherlands, and twenty-four of its students participated in three focus group discussions. The findings show that lecturers and students experience poor thermal, lighting, acoustic, and IAQ conditions which may influence teaching and learning performance. Furthermore, maintaining acceptable thermal and IAQ conditions was difficult for lecturers as opening windows or doors caused noise disturbances. In uncomfortable conditions, lecturers may decide to pause earlier or shorten a lecture. When students experienced discomfort, it may affect their ability to concentrate, their emotional status, and their quality of learning. Acceptable air and thermal conditions in classrooms will mitigate the need to open windows and doors. This allows lecturers to keep doors and windows closed, combining better classroom conditions with neither noise disturbances nor related distractions. Designers and engineers should take these end users’ perceptions into account, often monitored by facility management (FM), during the renovation or construction of university buildings to achieve optimal IEQ conditions in higher education classrooms.The results of these four studies indicate that there is not a one-size fits all indoor environmental quality to facilitate optimal in-class activities. Classrooms’ thermal environment should be effectively controlled with the option of a local (manual) intervention. Classrooms’ lighting conditions should also be adjustable, both in light color and light intensity. This enables lecturers to adjust the indoor environment to facilitate in-class activities optimally. Lecturers must be informed by the building operator, for example, professionals of the Facility Department, how to change classrooms’ IEQ settings. And this may differ per classroom because each building, in which the classroom is located, is operated differently apart from the classroom location in the building, exposure to the environment, and its use. The knowledge that has come available from this study, shows that optimal indoor environmental conditions can positively influence lecturers’ and students’ comfort, health, emotional balance, and performance. These outcomes have the capacity to contribute to an improved school climate and thus academic achievement.
About half of the e-waste generated in The Netherlands is properly documented and collected (184kT in 2018). The amount of PCBs in this waste is projected to be about 7kT in 2018 with a growth rate of 3-4%. Studies indicate that a third of the weight of a PCB is made or recoverable and critical metals which we need as resources for the various societal challenges facing us in the future. Recycling a waste PCB today means first shredding it and then processing it for material recovery mostly via non-selective pyrometallurgical methods. Sorting the PCBs in quality grades (wastebins) before shredding would however lead to more flexibility in selecting when and which recovery metallurgy is to be used. The yield and diversity of the recovered metals increases as a result, especially when high-grade recycling techniques are used. Unfortunately, the sorting of waste PCBs is not easily automated as an experienced operator eye is needed to classify the very inhomogeneous waste-PCB stream in wastebins. In this project, a knowledge institution partners with an e-waste processor, a high-grade recycling technology startup and a developer of waste sorting systems to investigate the efficiency of methods for sensory sorting of waste PCBs. The knowledge gained in this project will lead towards a waste PCB sorting demonstrator as a follow-up project.
