Designing for engagement : building IT systems

Context The School of Information Technology at QUT has recently undertaken a major restructuring of their Bachelor of Information Technology (BIT) course. Some of the aims of this restructuring include a reduction in first year attrition and to provide an attractive degree course that meets both student and industry expectations. Emphasis has been placed on the first semester in the context of retaining students by introducing a set of four units that complement one another and provide introductory material on technology, programming and related skills, and generic skills that will aid the students throughout their undergraduate course and in their careers. This discussion relates to one of these four fist semester units, namely Building IT Systems. The aim of this unit is to create small Information Technology (IT) systems that use programming or scripting, databases as either standalone applications or web applications. In the prior history of teaching introductory computer programming at QUT, programming has been taught as a stand alone subject and integration of computer applications with other systems such as databases and networks was not undertaken until students had been given a thorough grounding in those topics as well. Feedback has indicated that students do not believe that working with a database requires programming skills. In fact, the teaching of the building blocks of computer applications have been compartmentalized and taught in isolation from each other. The teaching of introductory computer programming has been an industry requirement of IT degree courses as many jobs require at least some knowledge of the topic. Yet, computer programming is not a skill that all students have equal capabilities of learning (Bruce et al., 2004) and this is clearly shown by the volume of publications dedicated to this topic in the literature over a broad period of time (Eckerdal & Berglund, 2005; Mayer, 1981; Winslow, 1996). The teaching of this introductory material has been done pretty much the same way over the past thirty years. During this period of time that introductory computer programming courses have been taught at QUT, a number of different programming languages and programming paradigms have been used and different approaches to teaching and learning have been attempted in an effort to find the golden thread that would allow students to learn this complex topic. Unfortunately, computer programming is not a skill that can be learnt in one semester. Some basics can be learnt but it can take many years to master (Norvig, 2001). Faculty data typically has shown a bimodal distribution of results for students undertaking introductory programming courses with a high proportion of students receiving a high mark and a high proportion of students receiving a low or failing mark. This indicates that there are students who understand and excel with the introductory material while there is another group who struggle to understand the concepts and practices required to be able to translate a specification or problem statement into a computer program that achieves what is being requested. The consequence of a large group of students failing the introductory programming course has been a high level of attrition amongst first year students. This attrition level does not provide good continuity in student numbers in later years of the degree program and the current approach is not seen as sustainable.

Information enrichment for quality recommender systems

The explosive growth of the World-Wide-Web and the emergence of ecommerce are the major two factors that have led to the development of recommender systems (Resnick and Varian, 1997). The main task of recommender systems is to learn from users and recommend items (e.g. information, products or books) that match the users’ personal preferences. Recommender systems have been an active research area for more than a decade. Many different techniques and systems with distinct strengths have been developed to generate better quality recommendations. One of the main factors that affect recommenders’ recommendation quality is the amount of information resources that are available to the recommenders. The main feature of the recommender systems is their ability to make personalised recommendations for different individuals. However, for many ecommerce sites, it is difficult for them to obtain sufficient knowledge about their users. Hence, the recommendations they provided to their users are often poor and not personalised. This information insufficiency problem is commonly referred to as the cold-start problem. Most existing research on recommender systems focus on developing techniques to better utilise the available information resources to achieve better recommendation quality. However, while the amount of available data and information remains insufficient, these techniques can only provide limited improvements to the overall recommendation quality. In this thesis, a novel and intuitive approach towards improving recommendation quality and alleviating the cold-start problem is attempted. This approach is enriching the information resources. It can be easily observed that when there is sufficient information and knowledge base to support recommendation making, even the simplest recommender systems can outperform the sophisticated ones with limited information resources. Two possible strategies are suggested in this thesis to achieve the proposed information enrichment for recommenders: • The first strategy suggests that information resources can be enriched by considering other information or data facets. Specifically, a taxonomy-based recommender, Hybrid Taxonomy Recommender (HTR), is presented in this thesis. HTR exploits the relationship between users’ taxonomic preferences and item preferences from the combination of the widely available product taxonomic information and the existing user rating data, and it then utilises this taxonomic preference to item preference relation to generate high quality recommendations. • The second strategy suggests that information resources can be enriched simply by obtaining information resources from other parties. In this thesis, a distributed recommender framework, Ecommerce-oriented Distributed Recommender System (EDRS), is proposed. The proposed EDRS allows multiple recommenders from different parties (i.e. organisations or ecommerce sites) to share recommendations and information resources with each other in order to improve their recommendation quality. Based on the results obtained from the experiments conducted in this thesis, the proposed systems and techniques have achieved great improvement in both making quality recommendations and alleviating the cold-start problem.

Planning for smart urban ecosystems : information technology applications for capacity building in environmental decision making

Since the industrial revolution, our world has experienced rapid and unplanned industrialization and urbanization. As a result, we have had to cope with serious environmental challenges. In this context, an explanation of how smart urban ecosystems can emerge, gains a crucial importance. Capacity building and community involvement have always been key issues in achieving sustainable development and enhancing urban ecosystems. By considering these, this paper looks at new approaches to increase public awareness of environmental decision making. This paper will discuss the role of Information and Communication Technologies (ICT), particularly Webbased Geographic Information Systems (Web-based GIS) as spatial decision support systems to aid public participatory environmental decision making. The paper also explores the potential and constraints of these webbased tools for collaborative decision making.

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.

Assessing information systems success models : empirical comparison (Research in Progress)

Information System (IS) success may be the most arguable and important dependent variable in the IS field. The purpose of the present study is to address IS success by empirically assess and compare DeLone and McLean’s (1992) and Gable’s et al. (2008) models of IS success in Australian Universities context. The two models have some commonalities and several important distinctions. Both models integrate and interrelate multiple dimensions of IS success. Hence, it would be useful to compare the models to see which is superior; as it is not clear how IS researchers should respond to this controversy.

Evaluating information systems

The book within which this chapter appears is published as a research reference book (not a coursework textbook) on Management Information Systems (MIS) for seniors or graduate students in Chinese universities. It is hoped that this chapter, along with the others, will be helpful to MIS scholars and PhD/Masters research students in China who seek understanding of several central Information Systems (IS) research topics and related issues. The subject of this chapter - ‘Evaluating Information Systems’ - is broad, and cannot be addressed in its entirety in any depth within a single book chapter. The chapter proceeds from the truism that organizations have limited resources and those resources need to be invested in a way that provides greatest benefit to the organization. IT expenditure represents a substantial portion of any organization’s investment budget and IT related innovations have broad organizational impacts. Evaluation of the impact of this major investment is essential to justify this expenditure both pre- and post-investment. Evaluation is also important to prioritize possible improvements. The chapter (and most of the literature reviewed herein) admittedly assumes a blackbox view of IS/IT1, emphasizing measures of its consequences (e.g. for organizational performance or the economy) or perceptions of its quality from a user perspective. This reflects the MIS emphasis – a ‘management’ emphasis rather than a software engineering emphasis2, where a software engineering emphasis might be on the technical characteristics and technical performance. Though a black-box approach limits diagnostic specificity of findings from a technical perspective, it offers many benefits. In addition to superior management information, these benefits may include economy of measurement and comparability of findings (e.g. see Part 4 on Benchmarking IS). The chapter does not purport to be a comprehensive treatment of the relevant literature. It does, however, reflect many of the more influential works, and a representative range of important writings in the area. The author has been somewhat opportunistic in Part 2, employing a single journal – The Journal of Strategic Information Systems – to derive a classification of literature in the broader domain. Nonetheless, the arguments for this approach are believed to be sound, and the value from this exercise real. The chapter drills down from the general to the specific. It commences with a highlevel overview of the general topic area. This is achieved in 2 parts: - Part 1 addressing existing research in the more comprehensive IS research outlets (e.g. MISQ, JAIS, ISR, JMIS, ICIS), and Part 2 addressing existing research in a key specialist outlet (i.e. Journal of Strategic Information Systems). Subsequently, in Part 3, the chapter narrows to focus on the sub-topic ‘Information Systems Success Measurement’; then drilling deeper to become even more focused in Part 4 on ‘Benchmarking Information Systems’. In other words, the chapter drills down from Parts 1&2 Value of IS, to Part 3 Measuring Information Systems Success, to Part 4 Benchmarking IS. While the commencing Parts (1&2) are by definition broadly relevant to the chapter topic, the subsequent, more focused Parts (3 and 4) admittedly reflect the author’s more specific interests. Thus, the three chapter foci – value of IS, measuring IS success, and benchmarking IS - are not mutually exclusive, but, rather, each subsequent focus is in most respects a sub-set of the former. Parts 1&2, ‘the Value of IS’, take a broad view, with much emphasis on ‘the business Value of IS’, or the relationship between information technology and organizational performance. Part 3, ‘Information System Success Measurement’, focuses more specifically on measures and constructs employed in empirical research into the drivers of IS success (ISS). (DeLone and McLean 1992) inventoried and rationalized disparate prior measures of ISS into 6 constructs – System Quality, Information Quality, Individual Impact, Organizational Impact, Satisfaction and Use (later suggesting a 7th construct – Service Quality (DeLone and McLean 2003)). These 6 constructs have been used extensively, individually or in some combination, as the dependent variable in research seeking to better understand the important antecedents or drivers of IS Success. Part 3 reviews this body of work. Part 4, ‘Benchmarking Information Systems’, drills deeper again, focusing more specifically on a measure of the IS that can be used as a ‘benchmark’3. This section consolidates and extends the work of the author and his colleagues4 to derive a robust, validated IS-Impact measurement model for benchmarking contemporary Information Systems (IS). Though IS-Impact, like ISS, has potential value in empirical, causal research, its design and validation has emphasized its role and value as a comparator; a measure that is simple, robust and generalizable and which yields results that are as far as possible comparable across time, across stakeholders, and across differing systems and systems contexts.

Dynamic Performance Measures for Object Tracking Systems

Performance evaluation of object tracking systems is typically performed after the data has been processed, by comparing tracking results to ground truth. Whilst this approach is fine when performing offline testing, it does not allow for real-time analysis of the systems performance, which may be of use for live systems to either automatically tune the system or report reliability. In this paper, we propose three metrics that can be used to dynamically asses the performance of an object tracking system. Outputs and results from various stages in the tracking system are used to obtain measures that indicate the performance of motion segmentation, object detection and object matching. The proposed dynamic metrics are shown to accurately indicate tracking errors when visually comparing metric results to tracking output, and are shown to display similar trends to the ETISEO metrics when comparing different tracking configurations.

Strategic information systems research : an archival analysis

The Journal of Strategic Information Systems (JSIS) has been an international outlet for Information Systems research that focuses on strategic issues since 1991. This paper reports on an analysis of the research published in JSIS to date. The paper presents a preliminary classification system for research topics related to Strategic Information Systems into which all 316 JSIS research papers as at end 2009 are classified. Discussion on changing emphases in topics over time is provided, in the context of the editorial philosophy of the journal. The paper seeks to stimulate discussion on future directions for research in Strategic Information Systems.