While smart maintenance is gaining popularity in professional engineering and construction management practice, little is known about the dimensions of its maturity. It is assumed that the complex networked environment of maintenance and the rise of data-driven methodologies require a different perspective on maintenance. This paper identifies maturity dimensions for smart maintenance of constructed assets that can be measured. A research design based on two opposite cases is used and data from multiple sources is collected in four embedded case studies in corporate facility management organizations. Through coding data in several cross-case analyses, a maturity framework is designed that is validated through expert consultation. The proposed smart maintenance maturity framework includes technological dimensions (e.g., tracking and tracing) as well as behavioral dimensions (e.g., culture). It presents a new and encompassing theoretical perspective on client leadership in digital construction, integrating innovation in both construction and maintenance supply networks.
While smart maintenance is gaining popularity in professional engineering and construction management practice, little is known about the dimensions of its maturity. It is assumed that the complex networked environment of maintenance and the rise of data-driven methodologies require a different perspective on maintenance. This paper identifies maturity dimensions for smart maintenance of constructed assets that can be measured. A research design based on two opposite cases is used and data from multiple sources is collected in four embedded case studies in corporate facility management organizations. Through coding data in several cross-case analyses, a maturity framework is designed that is validated through expert consultation. The proposed smart maintenance maturity framework includes technological dimensions (e.g., tracking and tracing) as well as behavioral dimensions (e.g., culture). It presents a new and encompassing theoretical perspective on client leadership in digital construction, integrating innovation in both construction and maintenance supply networks.
Individuals with mild intellectual disabilities or borderline intellectual functioning are at increased risk to develop a substance use disorder—however, effective treatment programs adapted to this target group are scarce. This study evaluated the effectiveness of Take it Personal!+ in individuals with mild intellectual disabilities or borderline intellectual functioning and substance use disorder. Take it Personal!+ is a personalized treatment based on motivational interviewing and cognitive-behavioral therapy supported by an mHealth application. Data were collected in a nonconcurrent multiple baseline single-case experimental design across individuals with four phases (i.e., baseline, treatment, posttreatment, and follow-up). Twelve participants were randomly allocated to baseline lengths varying between 7 and 11 days. Substance use quantity was assessed during baseline, treatment, and posttreatment with a daily survey using a mobile application. Visual analysis was supported with statistical analysis of the daily surveys by calculating three effect size measures in 10 participants (two participants were excluded from this analysis due to a compliance rate below 50%). Secondary, substance use severity was assessed with standardized questionnaires at baseline, posttreatment, and follow-up and analyzed by calculating the Reliable Change Index. Based on visual analysis of the daily surveys, 10 out of 12 participants showed a decrease in mean substance use quantity from baseline to treatment and, if posttreatment data were available, to posttreatment. Statistical analysis showed an effect of Take it Personal!+ in terms of a decrease in daily substance use in 8 of 10 participants from baseline to treatment and if posttreatment data were available, also to posttreatment. In addition, data of the standardized questionnaires showed a decrease in substance use severity in 8 of 12 participants. These results support the effectiveness of Take it Personal!+ in decreasing substance use in individuals with mild intellectual disabilities or borderline intellectual functioning.
Het project ‘Design Thinking bij Nationale Militaire Inzet Koninklijke Landmacht’- Fase1 (NMIKL fasse1) is gericht op nieuwe creatieve methoden om complexe vraagstukken van de Landmacht Nationale Inzet (LNI) op te lossen. Binnen het convenant tussen de Hogeschool Utrecht (HU) en LNI heeft LNI haar hulpvraag voorgelegd om de vele complexe vraagstukken van diverse aard te helpen oplossen. Het ontbreekt LNI aan een methode om de Inmiddels 75 benoemde complexe vraagstukken met ingewikkelde onderlinge relaties op te pakken. Dergelijke complexe vraagstukken worden ‘wicked problems’ genoemd. Ze bevatten gestapelde problematiek, zoals technologische uitdagingen, de factoren van duurzaamheid, klimaat en vergrijzing van de beroepsbevolking. Daar bovenop komt de toegenomen bedreiging van vrede in Europa. Om een gedegen vraagarticulatie voor de meest belangrijke LNI vraagstukken op te stellen, is een aanpak gewenst, die bij deze ‘wicked problems’ past. Suit-case (een HU-MKB-partner) is opgericht door TU Delft studenten, die gespecialiseerd zijn in het aanpakken van complexe vraagstukken met creatieve methoden, zoals ‘design thinking’ en ‘transition theory management’. Suit-case wil graag haar aanpak geschikt maken voor hiërarchisch gestructureerde organisaties zoals Defensie, zodat de techniek beschikbaar komt voor dergelijke bedrijven( zoals Shell, NS, enzovoorts). Ook deze bedrijven hebben te maken met de maatschappelijke uitdagingen en ‘wicked problems’ en hebben gezien de klimaat-doelstellingen versnelling in hun transitie-proces en daarmee vraagoplossendvermogen nodig. Co-Design van de HU heeft veel ervaring met DT binnen de zorg. Samen gaan we DT beter beschikbaar maken voor grote bedrijven met een hiërarchische structuur zodat ook zij complexe vraagstukken innovatief kunnen oppakken. Door minimaal drie LNI-vraagstukken te doorlopen wordt de ontwikkelde aanpak getest en leert LNI de methoden in de praktijk toe te passen. Het resultaat is een nieuwe, methodologisch onderbouwde vraagarticulatie-aanpak voor complexe vraagstukken voor hiërarchisch georganiseerde organisaties zoals LNI en drie goede vraagarticulaties met aanpak.
Intelligent technology in automotive has a disrupting impact on the way modern automobiles are being developed. New technology not only has brought complexity to already existing information in the car (digitization of driver instruments) but also brings new external information to the driver on how to optimize the driving style amongst others from the perspective of communicating with infrastructures (Vehicle to Infrastructure communication (V2I)). The amount of information that a driver has to process in modern vehicles is increasing rapidly due to the introduction of multiple displays and new external information sources. An information overload lies awaiting, yet current Human Machine Interface (HMI) designs and the corresponding legal frameworks lag behind. Currently, many initiatives (Pratijkproef Amsterdam, Concorda) are being developed with respect to V2I, amongst others with Rijkswaterstaat, North Holland and Brabant. In these initiatives, SME’s, like V-Tron, focus on the development of specific V2I hardware. Yet in the field of HMI’s these SME’s need universities (HAN University of Applied Science, Rhine Waal University of Applied Science) and industrial designers (Yellow Chess) to help them with design guidelines and concept HMI’s. We propose to develop first guidelines on possible new human-machine interfaces. Additionally, we will show the advantages of HMI’s that go further than current legal requirements. Therefore, this research will focus on design guidelines averting the information overload. We show two HMI’s that combine regular driver information with V2I information of a Green Light Optimized Speed Advise (GLOSA) use case. The HMI’s will be evaluated on a high level (focus groups and a small simulator study). The KIEM results in two publications. In a plenary meeting with experts, the guidelines and the limitations of current legal requirements will be discussed. The KIEM will lead to a new consortium to extend the research.
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.
