Applying science of learning in education: Infusing psychological science into the curriculum

The field of specialization known as the science of learning is not, in fact, one field. Science of learning is a term that serves as an umbrella for many lines of research, theory, and application. A term with an even wider reach is Learning Sciences (Sawyer, 2006). The present book represents a sliver, albeit a substantial one, of the scholarship on the science of learning and its application in educational settings (Science of Instruction, Mayer 2011). Although much, but not all, of what is presented in this book is focused on learning in college and university settings, teachers of all academic levels may find the recommendations made by chapter authors of service. The overarching theme of this book is on the interplay between the science of learning, the science of instruction, and the science of assessment (Mayer, 2011). The science of learning is a systematic and empirical approach to understanding how people learn. More formally, Mayer (2011) defined the science of learning as the “scientific study of how people learn” (p. 3). The science of instruction (Mayer 2011), informed in part by the science of learning, is also on display throughout the book. Mayer defined the science of instruction as the “scientific study of how to help people learn” (p. 3). Finally, the assessment of student learning (e.g., learning, remembering, transferring knowledge) during and after instruction helps us determine the effectiveness of our instructional methods. Mayer defined the science of assessment as the “scientific study of how to determine what people know” (p.3). Most of the research and applications presented in this book are completed within a science of learning framework. Researchers first conducted research to understand how people learn in certain controlled contexts (i.e., in the laboratory) and then they, or others, began to consider how these understandings could be applied in educational settings. Work on the cognitive load theory of learning, which is discussed in depth in several chapters of this book (e.g., Chew; Lee and Kalyuga; Mayer; Renkl), provides an excellent example that documents how science of learning has led to valuable work on the science of instruction. Most of the work described in this book is based on theory and research in cognitive psychology. We might have selected other topics (and, thus, other authors) that have their research base in behavior analysis, computational modeling and computer science, neuroscience, etc. We made the selections we did because the work of our authors ties together nicely and seemed to us to have direct applicability in academic settings

Integrating memory context into personal information re-finding

Personal information archives are emerging as a new challenge for information retrieval (IR) techniques. The user’s memory plays a greater role in retrieval from person archives than from other more traditional types of information collection (e.g. the Web), due to the large overlap of its content and individual human memory of the captured material. This paper presents a new analysis on IR of personal archives from a cognitive perspective. Some existing work on personal information management (PIM) has begun to employ human memory features into their IR systems. In our work we seek to go further, we assume that for IR in PIM system terms can be weighted not only by traditional IR methods, but also taking the user’s recall reliability into account. We aim to develop algorithms that combine factors from both the system side and the user side to achieve more effective searching. In this paper, we discuss possible applications of human memory theories for this algorithm, and present results from a pilot study and a proposed model of data structure for the HDMs achieves

Interaction Issues in Computer Aided Semantic\ud Annotation of Multimedia

The CASAM project aims to provide a tool for more efficient and effective annotation of multimedia documents through collaboration between a user and a system performing an automated analysis of the media content. A critical part of the project is to develop a user interface which best supports both the user and the system through optimal human-computer interaction. In this paper we discuss the work undertaken, the proposed user interface and underlying interaction issues which drove its development

Adaptive Information Cluster at Dublin City University

The Adaptive Information Cluster (AIC) is a collaboration between Dublin City University and University College Dublin, and in the AIC at DCU, we investigate and develop as one stream of our research activities, various content analysis tools that can automatically index and structure video information. This includes movies or CCTV footage and the motivation is to support useful searching and browsing features for the envisaged end-users of such systems. We bring in the HCI perspective to this highly-technically-oriented research by brainstorming, generating scenarios, sketching and prototyping the user-interfaces to the resulting video retrieval systems we develop, and we conduct usability studies to better understand the usage and opinions of such systems so as to guide the future direction of our technological research

Generating collaborative systems for digital libraries: A model-driven approach

This is an open access article shared under a Creative Commons Attribution 3.0 Licence (http://creativecommons.org/licenses/by/3.0/). Copyright @ 2010 The Authors.The design and development of a digital library involves different stakeholders, such as: information architects, librarians, and domain experts, who need to agree on a common language to describe, discuss, and negotiate the services the library has to offer. To this end, high-level, language-neutral models have to be devised. Metamodeling techniques favor the definition of domainspecific visual languages through which stakeholders can share their views and directly manipulate representations of the domain entities. This paper describes CRADLE (Cooperative-Relational Approach to Digital Library Environments), a metamodel-based framework and visual language for the definition of notions and services related to the development of digital libraries. A collection of tools allows the automatic generation of several services, defined with the CRADLE visual language, and of the graphical user interfaces providing access to them for the final user. The effectiveness of the approach is illustrated by presenting digital libraries generated with CRADLE, while the CRADLE environment has been evaluated by using the cognitive dimensions framework

Can a workspace help to overcome the query formulation problem in image retrieval?

We have proposed a novel image retrieval system that incorporates a workspace where users can organise their search results. A task-oriented and user-centred experiment has been devised involving design professionals and several types of realistic search tasks. We study the workspace’s effect on two aspects: task conceptualisation and query formulation. A traditional relevance feedback system serves as baseline. The results of this study show that the workspace is more useful with respect to both of the above aspects. The proposed approach leads to a more effective and enjoyable search experience

Formal models, usability and related work in IR (editorial for special edition)

The Glasgow IR group has carried out both theoretical and empirical work, aimed at giving end users efficient and effective access to large collections of multimedia data

Evaluating a workspace's usefulness for image retrieval

Image searching is a creative process. We have proposed a novel image retrieval system that supports creative search sessions by allowing the user to organise their search results on a workspace. The workspace’s usefulness is evaluated in a task-oriented and user-centred comparative experiment, involving design professionals and several types of realistic search tasks. In particular, we focus on its effect on task conceptualisation and query formulation. A traditional relevance feedback system serves as a baseline. The results of this study show that the workspace is more useful in terms of both of the above aspects and that the proposed approach leads to a more effective and enjoyable search experience. This paper also highlights the influence of tasks on the users’ search and organisation strategy