Intelligent tutoring systems in higher education : towards enhanced dimensions

This paper describes how intelligent tutoring systems (ITSs) improve flexible learning in higher education. The benefits of ITSs over course management systems (CMSs) are discussed, and we demonstrate how the traditionally used dimensions of flexibility can be enhanced to tackle the challenges that higher education is facing from an abundance of online educational products and services. In addition, a new data-driven approach to analyzing questions about flexible learning is suggested, which could lead to better-optimized settings for flexible learning

Enhancing Free-text Interactions in a Communication Skills Learning Environment

Learning environments frequently use gamification to enhance user interactions.Virtual characters with whom players engage in simulated conversations often employ prescripted dialogues; however, free user inputs enable deeper immersion and higher-order cognition. In our learning environment, experts developed a scripted scenario as a sequence of potential actions, and we explore possibilities for enhancing interactions by enabling users to type free inputs that are matched to the pre-scripted statements using Natural Language Processing techniques. In this paper, we introduce a clustering mechanism that provides recommendations for fine-tuning the pre-scripted answers in order to better match user inputs

Mechatronic Systems

Mechatronics, the synergistic blend of mechanics, electronics, and computer science, has evolved over the past twenty five years, leading to a novel stage of engineering design. By integrating the best design practices with the most advanced technologies, mechatronics aims at realizing high-quality products, guaranteeing at the same time a substantial reduction of time and costs of manufacturing. Mechatronic systems are manifold and range from machine components, motion generators, and power producing machines to more complex devices, such as robotic systems and transportation vehicles. With its twenty chapters, which collect contributions from many researchers worldwide, this book provides an excellent survey of recent work in the field of mechatronics with applications in various fields, like robotics, medical and assistive technology, human-machine interaction, unmanned vehicles, manufacturing, and education. We would like to thank all the authors who have invested a great deal of time to write such interesting chapters, which we are sure will be valuable to the readers. Chapters 1 to 6 deal with applications of mechatronics for the development of robotic systems. Medical and assistive technologies and human-machine interaction systems are the topic of chapters 7 to 13.Chapters 14 and 15 concern mechatronic systems for autonomous vehicles. Chapters 16-19 deal with mechatronics in manufacturing contexts. Chapter 20 concludes the book, describing a method for the installation of mechatronics education in schools

Obstacles to wearable computing

In the year 2021, wearable technology could look beautiful and feel magical, but instead is exemplified by a plain wristband that looks suspiciously like a prison monitor. How can we make wearable technology that respects our privacy, enhances our daily lives, integrates with our other connected devices without leashing us to a smartphone, and visually expresses who we are? This study uses a novel method of participatory design fiction (PDFi) to understand potential users of everyday wearable technology through storytelling. I recruited participants from the general public and gave them a five-point prompt to create a design fiction (DF), which inspired the user-centred design of an everyday connected wearable device. The participants each received a technology probe to wear in the wild for a year. They then updated their DFs as a way to reflect on the implications of the technology. For the purposes of privacy, augmenting device functionality through interoperability, and integration into an Internet of Things (IoT) ecosystem, I used the Hub-of-All-Things personal data store to provide the software infrastructure. By listening to their stories, we can elicit design concepts directly from the users, to help us create wearable IoT devices that put the wearer at the centre of the design process, and are satisfying both functionally and emotionally.The Alan Turing Institute Doctoral Scheme, University of Cambridge Department of Computer Science and Technology, The Kenneth Hayter Memorial Fun

Using students’ digital footprints to identify peer influences on academic outcomes

The ability of researchers to identify the type of activities and levels of interaction among students on a campus is important to research in Learning Analytics and in particular, anthropological studies which explore interactions among students. Historically the collection of base data in such studies has in the main been through observation, questionnaires or a combination of both. This work utilises the unique digital footprints created by student interactions with online systems within a University environment to measure student behaviour and correlate it with exam performance. The specific digital footprint we use is a students connections to the Eduroam WiFi platform within a campus. The advantage of this data-set is that it captures the personal interactions each student has with the IT systems. Datasets of this type are usually structured, complete and traceable. We will present findings that illustrate that the behaviour of students can be contextualised within the academic environment by mining this dataset. We achieve this through identifying student location and those who share that location with them and cross-referencing this with the scheduled University timetable. Our work uses the digital footprint to identify student location and thus co-location of students. From this co-location analyses we infer peer groupings and levels of interaction. This can be used for identifying peers in a University community and for identifying popular locations for different students and their peer groups to meet. This thesis examines the data collection process we followed and our data-mining process. Using the spatio-temporal data derived from the WiFi system we mined the data to produce actionable knowledge for use in the learning process. This research contains min- imal Personal Data and no Sensitive Personal Data as defined by the DCU Data Protection Policy (Version 2.0). All data has been anonymised, stored and used in conformance with the Universitys Personal Data Security Schedule (PDSS)

Market Engineering

This open access book provides a broad range of insights on market engineering and information management. It covers topics like auctions, stock markets, electricity markets, the sharing economy, information and emotions in markets, smart decision-making in cities and other systems, and methodological approaches to conceptual modeling and taxonomy development. Overall, this book is a source of inspiration for everybody working on the vision of advancing the science of engineering markets and managing information for contributing to a bright, sustainable, digital world. Markets are powerful and extremely efficient mechanisms for coordinating individuals’ and organizations’ behavior in a complex, networked economy. Thus, designing, monitoring, and regulating markets is an essential task of today’s society. This task does not only derive from a purely economic point of view. Leveraging market forces can also help to tackle pressing social and environmental challenges. Moreover, markets process, generate, and reveal information. This information is a production factor and a valuable economic asset. In an increasingly digital world, it is more essential than ever to understand the life cycle of information from its creation and distribution to its use. Both markets and the flow of information should not arbitrarily emerge and develop based on individual, profit-driven actors. Instead, they should be engineered to serve best the whole society’s goals. This motivation drives the research fields of market engineering and information management. With this book, the editors and authors honor Professor Dr. Christof Weinhardt for his enormous and ongoing contribution to market engineering and information management research and practice. It was presented to him on the occasion of his sixtieth birthday in April 2021. Thank you very much, Christof, for so many years of cooperation, support, inspiration, and friendship