Possible approaches to personalisation at Cass Business School

This report discusses the result of an investigation into the personalisation of learning and how it could be applied in a university with primarily face-to-face instruction, and, a diverse student body

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

Teacher Perceptions of Personalized Teaching & Learning in an Instructional Technology Graduate Course: A Phenomenographical Case Study

With the growing focus and popularity of personalized learning in K-12 education, the need to support educators in their ability to implement personalized learning pedagogy grows. The paradigm shift towards personalized learning includes necessary iteration to the types of professional development offered to practicing teachers. This study explored the perceptions of teachers experiencing the meta-learning phenomenon of both teaching and learning about Personalized Learning (PL) in a six-week, online graduate-level course. Inquiry was focused on uncovering how in-service K-12 teachers\u27 experience, understanding of PL, and ability to design PL evolve during a six-week graduate-level education course on personalized learning, ITEC 7600. Additionally, the study explored how ITEC 7600 help in-service teachers taking it to leverage personalized learning pedagogy while learning about personalized learning. Finally, a composite allowed the voice of the instructors to describe the experiences of their students’ understanding of PL, and ability to design PL as it evolves during a six-week graduate-level education course on personalized learning. Results illuminate that while a personalized path towards acquisition of PL pedagogy should be expected due to the qualitatively unique ways participants experience this course, a modeled meta-learning phenomenon is found to support educators’ growth in their ability to understand and design personalized learning environments. Results show ways in which the overall design of this course have an impact on current and future practice and research of personalized learning

Digital user's decision journey

The landscape of the Internet is continually evolving. This creates huge opportunities for different industries to optimize vital channels online, resulting in various-forms of new Internet services. As a result, digital users are interacting with many digital systems and they are exhibiting dynamic behaviors. Their shopping behaviors are drastically different today than it used to be, with offline and online shopping interacting with each other. They have many channels to access online media but their consumption patterns on different channels are quite different. They do philanthropy online to help others but their heterogeneous motivations and different fundraising campaigns leads to distinct path-to-contribution. Understanding the digital user’s decision making process behind their dynamic behaviors is critical as they interact with various digital systems for the firms to improve user experience and improve their bottom line. In this thesis, I study digital users’ decision journeys and the corresponding digital technology firms’ strategies using inter-disciplinary approaches that combine econometrics, economic structural modeling and machine learning. The uncovered decision journey not only offer empirical managerial insights but also provide guideline for introducing intervention to better serve digital users

Principles for Designing Context-Aware Applications for Physical Activity Promotion

Mobile devices with embedded sensors have become commonplace, carried by billions of people worldwide. Their potential to influence positive health behaviors such as physical activity in people is just starting to be realized. Two critical ingredients, an accurate understanding of human behavior and use of that knowledge for building computational models, underpin all emerging behavior change applications. Early research prototypes suggest that such applications would facilitate people to make difficult decisions to manage their complex behaviors. However, the progress towards building real-world systems that support behavior change has been much slower than expected. The extreme diversity in real-world contextual conditions and user characteristics has prevented the conception of systems that scale and support end-users’ goals. We believe that solutions to the many challenges of designing context-aware systems for behavior change exist in three areas: building behavior models amenable to computational reasoning, designing better tools to improve our understanding of human behavior, and developing new applications that scale existing ways of achieving behavior change. With physical activity as its focus, this thesis addresses some crucial challenges that can move the field forward. Specifically, this thesis provides the notion of sweet spots, a phenomenological account of how people make and execute their physical activity plans. The key contribution of this concept is in its potential to improve the predictability of computational models supporting physical activity planning. To further improve our understanding of the dynamic nature of human behavior, we designed and built Heed, a low-cost, distributed and situated self-reporting device. Heed’s single-purpose and situated nature proved its use as the preferred device for self-reporting in many contexts. We finally present a crowdsourcing system that leverages expert knowledge to write personalized behavior change messages for large-scale context-aware applications.PHDInformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144089/1/gparuthi_1.pd

Toward the future of global corporate travel management

This study aims to develop the global corporate travel management. In details, it reflected the current challenges in travel programme of buyers, discovered future scenarios of business travel and recommended strategic short and long-term actions. The study used qualitative approach to recognize challenges in corporate travel management. Interviews with sourcing and travel managers/assistants from three same size corporate buyers were conducted in October, 2017. Additionally, scenarios were built based on conventional intuitive logics method. Therein, 88 macro-economic and industrial trends were identified through secondary research. Discussions were organized with experts to rank the trends. Main findings from empirical research are a list of challenges in corporate travel management. Additionally, four scenarios “Demand More”, “Brand New”, “More Opportunities” and “No Surprise” were created based on two driven factors: The distribution of airlines standard network in the market share and intensity of tailored made travel services. In each scenario, proposed main travel solutions providers are travel agencies, direct booking aggregators and travel agencies, the internet, and GDS operators respectively. At the end, short and long-term strategic actions such as rewarding travellers when savings and driving toward traveller-centricity were recommended. The study contributed new aspects to the academic world. It built four future scenarios of business travel from corporate buyer’s perspective. After that, it presented scenarios implications and strategic actions for stakeholders. Such approach was not commonly used in previous studies. Besides, the study identified new participant - NDC aggregators – and new roles of GDS operators and metasearch engine in business travel distribution channels. In practice, the study tackled real business issue. It recognized the challenges and gave solutions to improve corporate travel management through short-term actions. Four scenarios and their implications mitigate the consequences of changes and clarify the managers concern. Lastly, long-term strategy navigates the global corporate travel management, at the same time, gradually changes the mindset of manager in suppliers’ negotiation and travel management

On Graphical Modeling of Preference and Importance

In recent years, CP-nets have emerged as a useful tool for supporting preference elicitation, reasoning, and representation. CP-nets capture and support reasoning with qualitative conditional preference statements, statements that are relatively natural for users to express. In this paper, we extend the CP-nets formalism to handle another class of very natural qualitative statements one often uses in expressing preferences in daily life - statements of relative importance of attributes. The resulting formalism, TCP-nets, maintains the spirit of CP-nets, in that it remains focused on using only simple and natural preference statements, uses the ceteris paribus semantics, and utilizes a graphical representation of this information to reason about its consistency and to perform, possibly constrained, optimization using it. The extra expressiveness it provides allows us to better model tradeoffs users would like to make, more faithfully representing their preferences

Considering temporal aspects in recommender systems: a survey

Under embargo until: 2023-07-04The widespread use of temporal aspects in user modeling indicates their importance, and their consideration showed to be highly effective in various domains related to user modeling, especially in recommender systems. Still, past and ongoing research, spread over several decades, provided multiple ad-hoc solutions, but no common understanding of the issue. There is no standardization and there is often little commonality in considering temporal aspects in different applications. This may ultimately lead to the problem that application developers define ad-hoc solutions for their problems at hand, sometimes missing or neglecting aspects that proved to be effective in similar cases. Therefore, a comprehensive survey of the consideration of temporal aspects in recommender systems is required. In this work, we provide an overview of various time-related aspects, categorize existing research, present a temporal abstraction and point to gaps that require future research. We anticipate this survey will become a reference point for researchers and practitioners alike when considering the potential application of temporal aspects in their personalized applications.acceptedVersio