Informed learning in the undergraduate classroom: The role of information experiences in shaping outcomes

This research aimed to inform the design of effective information literacy lessons in higher education. Phenomenography, a research approach designed to study human experience, was used to explore the experiences of a teacher and undergraduate students using information to learn about language and gender issues. The findings show that the way learners use information influences content-focused learning outcomes, and reveal an instructional pattern for enabling students to use information while becoming aware of the topic they are investigating. Based on the findings, a design model is offered in which learning outcomes are realized through targeted information literacy activities.

The BEE Undergraduate Model for Knowledge Development applied to the QUT Spatial Science Course : Diversity in Surveying Curriculum

This paper provides an overview of the current QUT Spatial Science undergraduate program based in Brisbane, Queensland, Australia. It discusses the development and implementation of a broad-based educational model for the faculty of built environment and engineering courses and specifically to the course structure of the new Bachelor of Urban Development (Spatial Science) study major. A brief historical background of surveying courses is discussed prior to the detailing of the three distinct and complementary learning themes of the new course structure with a graphical course matrix. Curriculum mapping of the spatial science major has been undertaken as the course approaches formal review in late 2010. Work-integrated learning opportunities have been embedded into the curriculum and a brief outline is presented. Some issues relevant to the tertiary surveying/ spatial sector are highlighted in the context of changing higher education environments in Australia.

Collaborative filtering recommender systems using tag information

Recommender Systems is one of the effective tools to deal with information overload issue. Similar with the explicit rating and other implicit rating behaviours such as purchase behaviour, click streams, and browsing history etc., the tagging information implies user’s important personal interests and preferences information, which can be used to recommend personalized items to users. This paper is to explore how to utilize tagging information to do personalized recommendations. Based on the distinctive three dimensional relationships among users, tags and items, a new user profiling and similarity measure method is proposed. The experiments suggest that the proposed approach is better than the traditional collaborative filtering recommender systems using only rating data.

A new undergraduate model for broadly based spatial science curriculum at Queensland University of Technology : diversity in surveying curriculum

This paper provides an overview of the current QUT Spatial Science undergraduate program based in Brisbane, Queensland, Australia. It discusses the development and implementation of a broad-based educational model for the faculty of built environment and engineering courses and specifically to the course structure of the new Bachelor of Urban Development (Spatial Science) study major. A brief historical background of surveying courses is discussed prior to the detailing of the three distinct and complementary learning themes of the new course structure with a graphical course matrix. Curriculum mapping of the spatial science major has been undertaken as the course approaches formal review in late 2010. Work-integrated learning opportunities have been embedded into the curriculum and a brief outline is presented. Some issues relevant to the tertiary surveying/ spatial sector are highlighted in the context of changing higher education environments in Australia.

Integrating information literacy into higher education curricula : an IL curricular integration model

This study investigates a way to systematically integrate information literacy (IL) into an undergraduate academic programme and develops a model for integrating information literacy across higher education curricula. Curricular integration of information literacy in this study means weaving information literacy into an academic curriculum. In the associated literature, it is also referred to as the information literacy embedding approach or the intra-curricular approach. The key findings identified from this study are presented in 4 categories: the characteristics of IL integration; the key stakeholders in IL integration; IL curricular design strategies; and the process of IL curricular integration. Three key characteristics of the curricular integration of IL are identified: collaboration and negotiation, contextualisation and ongoing interaction with information. The key stakeholders in the curricular integration of IL are recognised as the librarians, the course coordinators and lecturers, the heads of faculties or departments, and the students. Some strategies for IL curricular design include: the use of IL policies and standards in IL curricular design; the combination of face to face and online teaching as an emerging trend; the use of IL assessment tools which play an important role in IL integration. IL can be integrated into the intended curriculum (what an institution expects its students to learn), the offered curriculum (what the teachers teach) and the received curriculum (what students actually learn). IL integration is a process of negotiation, collaboration and the implementation of the intended curriculum. IL can be integrated at different levels of curricula such as: institutional, faculty, departmental, course and class curriculum levels. Based on these key findings, an IL curricular integration model is developed. The model integrates curriculum, pedagogy and learning theories, IL theories, IL guidelines and the collaboration of multiple partners. The model provides a practical approach to integrating IL into multiple courses across an academic degree. The development of the model was based on the IL integration experiences of various disciplines in three universities and the implementation experience of an engineering programme at another university; thus it may be of interest to other disciplines. The model has the potential to enhance IL teaching and learning, curricular development and to implement graduate attributes in higher education. Sociocultural theories are applied to the research process and IL curricular design of this study. Sociocultural theories describe learning as being embedded within social events and occurring as learners interact with other people, objects, and events in a collaborative environment. Sociocultural theories are applied to explore how academic staff and librarians experience the curricular integration of IL; they also support collaboration in the curricular integration of IL and the development of an IL integration model. This study consists of two phases. Phase I (2007) was the interview phase where both academic staff and librarians at three IL active universities were interviewed. During this phase, attention was paid specifically to the practical process of curricular integration of IL and IL activity design. Phase II, the development phase (2007-2008), was conducted at a fourth university. This phase explores the systematic integration of IL into an engineering degree from Year 1 to Year 4. Learning theories such as sociocultural theories, Bloom’s Taxonomy and IL theories are used in IL curricular development. Based on the findings from both phases, an IL integration model was developed. The findings and the model contribute to IL education, research and curricular development in higher education. The sociocultural approach adopted in this study also extends the application of sociocultural theories to the IL integration process and curricular design in higher education.

User profiling based on folksonomy information in Web 2.0 for personalized recommender systems

Information overload has become a serious issue for web users. Personalisation can provide effective solutions to overcome this problem. Recommender systems are one popular personalisation tool to help users deal with this issue. As the base of personalisation, the accuracy and efficiency of web user profiling affects the performances of recommender systems and other personalisation systems greatly. In Web 2.0, the emerging user information provides new possible solutions to profile users. Folksonomy or tag information is a kind of typical Web 2.0 information. Folksonomy implies the users‘ topic interests and opinion information. It becomes another source of important user information to profile users and to make recommendations. However, since tags are arbitrary words given by users, folksonomy contains a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise makes it difficult to profile users accurately or to make quality recommendations. This thesis investigates the distinctive features and multiple relationships of folksonomy and explores novel approaches to solve the tag quality problem and profile users accurately. Harvesting the wisdom of crowds and experts, three new user profiling approaches are proposed: folksonomy based user profiling approach, taxonomy based user profiling approach, hybrid user profiling approach based on folksonomy and taxonomy. The proposed user profiling approaches are applied to recommender systems to improve their performances. Based on the generated user profiles, the user and item based collaborative filtering approaches, combined with the content filtering methods, are proposed to make recommendations. The proposed new user profiling and recommendation approaches have been evaluated through extensive experiments. The effectiveness evaluation experiments were conducted on two real world datasets collected from Amazon.com and CiteULike websites. The experimental results demonstrate that the proposed user profiling and recommendation approaches outperform those related state-of-the-art approaches. In addition, this thesis proposes a parallel, scalable user profiling implementation approach based on advanced cloud computing techniques such as Hadoop, MapReduce and Cascading. The scalability evaluation experiments were conducted on a large scaled dataset collected from Del.icio.us website. This thesis contributes to effectively use the wisdom of crowds and expert to help users solve information overload issues through providing more accurate, effective and efficient user profiling and recommendation approaches. It also contributes to better usages of taxonomy information given by experts and folksonomy information contributed by users in Web 2.0.

A pattern mining approach for information filtering systems

It is a big challenge to clearly identify the boundary between positive and negative streams for information filtering systems. Several attempts have used negative feedback to solve this challenge; however, there are two issues for using negative relevance feedback to improve the effectiveness of information filtering. The first one is how to select constructive negative samples in order to reduce the space of negative documents. The second issue is how to decide noisy extracted features that should be updated based on the selected negative samples. This paper proposes a pattern mining based approach to select some offenders from the negative documents, where an offender can be used to reduce the side effects of noisy features. It also classifies extracted features (i.e., terms) into three categories: positive specific terms, general terms, and negative specific terms. In this way, multiple revising strategies can be used to update extracted features. An iterative learning algorithm is also proposed to implement this approach on the RCV1 data collection, and substantial experiments show that the proposed approach achieves encouraging performance and the performance is also consistent for adaptive filtering as well.

Privacy by information accountability for e-health systems

Privacy has become one of the main impediments for e-health in its advancement to providing better services to its consumers. Even though many security protocols are being developed to protect information from being compromised, privacy is still a major issue in healthcare where privacy protection is very important. When consumers are confident that their sensitive information is safe from being compromised, their trust in these services will be higher and would lead to better adoption of these systems. In this paper we propose a solution to the problem of patient privacy in e-health through an information accountability framework could enhance consumer trust in e-health services and would lead to the success of e-health services.

The design and development of an undergraduate signal processing laboratory

The School of Electrical and Electronic Systems Engineering of Queensland University of Technology (like many other universities around the world) has recognised the importance of complementing the teaching of signal processing with computer based experiments. A laboratory has been developed to provide a "hands-on" approach to the teaching of signal processing techniques. The motivation for the development of this laboratory was the cliche "What I hear I remember but what I do I understand." The laboratory has been named as the "Signal Computing and Real-time DSP Laboratory" and provides practical training to approximately 150 final year undergraduate students each year. The paper describes the novel features of the laboratory, techniques used in the laboratory based teaching, interesting aspects of the experiments that have been developed and student evaluation of the teaching techniques

Developing national level informatics competencies for undergraduate nurses : methodological approaches from Australia and Canada

Health information systems are being implemented in countries by governments and regional health authorities in an effort to modernize healthcare. With these changes, there has emerged a demand by healthcare organizations for nurses graduating from college and university programs to have acquired nursing informatics competencies that would allow them to work in clinical practice settings (e.g. hospitals, clinics, home care etc). In this paper we examine the methods employed by two different countries in developing national level nursing informatics competencies expected of undergraduate nurses prior to graduation (i.e. Australia, Canada). This work contributes to the literature by describing the science and methods of nursing informatics competency development at a national level.

'Information in context' : co-designing workplace structures and systems for organizational learning

With the aim of advancing professional practice through better understanding how to create workplace contexts that cultivate individual and collective learning through situated 'information in context' experiences, this paper presents insights gained from three North American collaborative design (co-design) implementations. In the current project at the Auraria Library in Denver, Colorado, USA, participants use collaborative information practices to redesign face-to-face and technology-enabled communication, decision making, and planning systems. Design processes are described and results-to-date described, within an appreciative framework which values information sharing and enables knowledge creation through shared leadership.

Systems thinking : an approach for advancing workplace information literacy

As the importance of information literacy has gained increased recognition, so too have academic library professionals intensified their efforts to champion, activate, and advance these capabilities in others. To date, however, little attention has focused on advancing these essential competencies amongst practitioner advocates.This paper helps redress the paucity of professional literature on the topic of workplace information literacy among library professionals.

Methodological developments in phenomenography : investing using information to learn in the discipline classroom

This paper discusses methodological developments in phenomenography that make it apropos for the study of teaching and learning to use information in educational environments. Phenomenography is typically used to analyze interview data to determine different ways of experiencing a phenomenon. There is an established tradition of phenomenographic research in the study of information literacy (ex: Bruce, 1997; 2008; Lupton, 2008; Webber, Boon, & Johnston, 2005). Drawing from the large body of evidence complied in two decades of research, phenomenographers developed variation theory, which explains what a learner can feasibly learn from a classroom lesson based on how the phenomenon being studied is presented (Marton, Runesson, & Tsui, 2004). Variation theory’s ability to establish the critical conditions necessary for learning to occur has resulted in the use of phenomenographic methods to study classroom interactions by collecting and analyzing naturalistic data through observation, as well as interviews concerning teachers’ intentions and students’ different experiences of classroom lessons. Describing the methodological developments of phenomenography in relation to understanding the classroom experience, this paper discusses the potential benefits and challenges of utilizing such methods to research the experiences of teaching and learning to use information in discipline-focused classrooms. The application of phenomenographic methodology for this purpose is exemplified with an ongoing study that explores how students learned to use information in an undergraduate language and gender course (Maybee, Bruce, Lupton, & Rebmann, in press). This paper suggests that by providing a nuanced understanding of what is intended for students to learn about using information, and relating that to what transpires in the classroom and how students experience these lessons, phenomenography and variation theory offer a viable framework for further understanding and improving how students are taught, and learn to use information.

Crowdsourcing interactions : using crowdsourcing for evaluating interactive information retrieval systems

In the field of information retrieval (IR), researchers and practitioners are often faced with a demand for valid approaches to evaluate the performance of retrieval systems. The Cranfield experiment paradigm has been dominant for the in-vitro evaluation of IR systems. Alternative to this paradigm, laboratory-based user studies have been widely used to evaluate interactive information retrieval (IIR) systems, and at the same time investigate users’ information searching behaviours. Major drawbacks of laboratory-based user studies for evaluating IIR systems include the high monetary and temporal costs involved in setting up and running those experiments, the lack of heterogeneity amongst the user population and the limited scale of the experiments, which usually involve a relatively restricted set of users. In this paper, we propose an alternative experimental methodology to laboratory-based user studies. Our novel experimental methodology uses a crowdsourcing platform as a means of engaging study participants. Through crowdsourcing, our experimental methodology can capture user interactions and searching behaviours at a lower cost, with more data, and within a shorter period than traditional laboratory-based user studies, and therefore can be used to assess the performances of IIR systems. In this article, we show the characteristic differences of our approach with respect to traditional IIR experimental and evaluation procedures. We also perform a use case study comparing crowdsourcing-based evaluation with laboratory-based evaluation of IIR systems, which can serve as a tutorial for setting up crowdsourcing-based IIR evaluations.