The Semantic Student: Using Knowledge Modeling Activities to Enhance Enquiry-Based Group Learning in Engineering Education

This paper argues that training engineering students in basic knowledge modeling techniques, using linked data principles, and semantic Web tools – within an enquiry-based group learning environment – enables them to enhance their domain knowledge, and their meta-cognitive skills. Knowledge modeling skills are in keeping with the principles of Universal Design for instruction. Learners are empowered with the regulation of cognition as they become more aware of their own development. This semantic student approach was trialed with a group of 3rd year Computer Engineering Students taking a module on computer architecture. An enquiry-based group learning activity was developed to help learners meet selected module learning outcomes. Learners were required to use semantic feature analysis and linked data principles to create a visual model of their knowledge structure. Results show that overall student attainment was increased when knowledge modeling activities were included as part of the learning process. A recommendation for practice to incorporate knowledge modeling as a learning strategy within an overall engineering curriculum framework is described. This can be achieved using semantic Web technologies such as semantic wikis and linked data tools

Detailed empirical studies of student information storing in the context of distributed design team-based project work

This paper presents the findings of six empirical case studies investigating the information stored by engineering design students in distributed team-based Global Design Projects. The aim is to understand better how students store distributed design information in order to prepare them for work in today‟s international and global context. This paper outlines the descriptive element of the work, the qualitative and quantitative research methods used and the results. It discusses the issues around the emergent themes of information storing; information storing systems; information storing patterns; and information strategy, making recommendations; establishing that there is a need for more prescriptive measures to supporting distributed design information management. This work will be of great value to industry also

Collaborative Authoring of Adaptive Educational Hypermedia by Enriching a Semantic Wiki’s Output

This research is concerned with harnessing collaborative approaches for the authoring of Adaptive Educational Hypermedia (AEH) systems. It involves the enhancement of Semantic Wikis with pedagogy aware features to this end. There are many challenges in understanding how communities of interest can efficiently collaborate for learning content authoring, in introducing pedagogy to the developed knowledge models and in specifying user models for efficient delivery of AEH systems. The contribution of this work will be the development of a model of collaborative authoring which includes domain specification, content elicitation, and definition of pedagogic approach. The proposed model will be implemented in a prototype AEH authoring system that will be tested and evaluated in a formal education context

Are digital natives a myth or reality?: Students’ use of technologies for learning

This paper outlines the findings of a study investigating the extent and nature of use of digital technologies by undergraduate students in Social Work and Engineering, in two British universities. The study involved a questionnaire survey of students (n=160) followed by in-depth interviews with students (n=8) and lecturers and support staff (n=8) in both institutions. Firstly, the findings suggest that students use a limited range of technologies for both learning and socialisation. For learning, mainly established ICTs are used- institutional VLE, Google and Wikipedia and mobile phones. Students make limited, recreational use of social technologies such as media sharing tools and social networking sites. Secondly, the findings point to a low level of use of and familiarity with collaborative knowledge creation tools, virtual worlds, personal web publishing, and other emergent social technologies. Thirdly, the study did not find evidence to support the claims regarding students adopting radically different patterns of knowledge creation and sharing suggested by some previous studies. The study shows that students’ attitudes to learning appear to be influenced by the approaches adopted by their lecturers. Far from demanding lecturers change their practice, students appear to conform to fairly traditional pedagogies, albeit with minor uses of technology tools that deliver content. Despite both groups clearly using a rather limited range of technologies for learning, the results point to some age differences, with younger, engineering students making somewhat more active, albeit limited, use of tools than the older ones. The outcomes suggest that although the calls for radical transformations in educational approaches may be legitimate it would be misleading to ground the arguments for such change solely in students’ shifting expectations and patterns of learning and technology use

Agile elicitation of semantic goals by wiki

Formal goal and service descriptions are the shibboleth of the semantic web services approach, yet the people responsible for creating them are neither machines nor logicians, and rarely even knowledge engineers: the people who need and specify functionality are not those who provide it, and both may be distinct from the semantic annotators. The gap between users' informal conceptualisations of problems and formal descriptions is one which must be effectively bridged for semantic web services to be widely adopted. We show how a simple technique–using a wiki to collect user requirements and mediate a progressive, iterative refinement and formalisation of user goals by domain experts and their knowledge engineer colleagues–can achieve this. Further, we suggest how the process could be extended, so as to itself benefit from semantic technologies

Collaborative knowledge management - A construction case study

Due to the new threats and challenges faced by the construction industry today, construction companies must seek new solutions in order to remain ahead of the competition. Knowledge has been identified to be a significant organisational resource, which if used effectively can provide competitive advantage. A lot of emphasis is being put on how to identify, capture and share knowledge in today's organisations. It has been argued over the years that due to the fragmented nature of the construction industry and ad-hoc nature of the construction projects, capture and reuse of valuable knowledge gathered during a construction project pose a challenge. As a result critical mistakes are repeated on projects and construction professionals have to kee

Automatic detection of accommodation steps as an indicator of knowledge maturing

Jointly working on shared digital artifacts – such as wikis – is a well-tried method of developing knowledge collectively within a group or organization. Our assumption is that such knowledge maturing is an accommodation process that can be measured by taking the writing process itself into account. This paper describes the development of a tool that detects accommodation automatically with the help of machine learning algorithms. We applied a software framework for task detection to the automatic identification of accommodation processes within a wiki. To set up the learning algorithms and test its performance, we conducted an empirical study, in which participants had to contribute to a wiki and, at the same time, identify their own tasks. Two domain experts evaluated the participants’ micro-tasks with regard to accommodation. We then applied an ontology-based task detection approach that identified accommodation with a rate of 79.12%. The potential use of our tool for measuring knowledge maturing online is discussed

A cloud-based tool for sentiment analysis in reviews about restaurants on TripAdvisor

The tourism industry has been promoting its products and services based on the reviews that people often write on travel websites like TripAdvisor.com, Booking.com and other platforms like these. These reviews have a profound effect on the decision making process when evaluating which places to visit, such as which restaurants to book, etc. In this contribution is presented a cloud based software tool for the massive analysis of this social media data (TripAdvisor.com). The main characteristics of the tool developed are: i) the ability to aggregate data obtained from social media; ii) the possibility of carrying out combined analyses of both people and comments; iii) the ability to detect the sense (positive, negative or neutral) in which the comments rotate, quantifying the degree to which they are positive or negative, as well as predicting behaviour patterns from this information; and iv) the ease of doing everything in the same application (data downloading, pre-processing, analysis and visualisation). As a test and validation case, more than 33.500 revisions written in English on restaurants in the Province of Granada (Spain) were analyse

How Controlled English can Improve Semantic Wikis

The motivation of semantic wikis is to make acquisition, maintenance, and mining of formal knowledge simpler, faster, and more flexible. However, most existing semantic wikis have a very technical interface and are restricted to a relatively low level of expressivity. In this paper, we explain how AceWiki uses controlled English - concretely Attempto Controlled English (ACE) - to provide a natural and intuitive interface while supporting a high degree of expressivity. We introduce recent improvements of the AceWiki system and user studies that indicate that AceWiki is usable and useful

Collaborative editing of knowledge resources for cross-lingual text mining

The need to smoothly deal with textual documents expressed in different languages is increasingly becoming a relevant issue in modern text mining environments. Recently the research on this field has been considerably fostered by the necessity for Web users to easily search and browse the growing amount of heterogeneous multilingual contents available on-line as well as by the related spread of the Semantic Web. A common approach to cross-lingual text mining relies on the exploitation of sets of properly structured multilingual knowledge resources. The involvement of huge communities of users spread over different locations represents a valuable aid to create, enrich, and refine these knowledge resources. Collaborative editing Web environments are usually exploited to this purpose. This thesis analyzes the features of several knowledge editing tools, both semantic wikis and ontology editors, and discusses the main challenges related to the design and development of this kind of tools. Subsequently, it presents the design, implementation, and evaluation of the Wikyoto Knowledge Editor, called also Wikyoto. Wikyoto is the collaborative editing Web environment that enables Web users lacking any knowledge engineering background to edit the multilingual network of knowledge resources exploited by KYOTO, a cross-lingual text mining system developed in the context of the KYOTO European Project. To experiment real benefits from social editing of knowledge resources, it is important to provide common Web users with simplified and intuitive interfaces and interaction patterns. Users need to be motivated and properly driven so as to supply information useful for cross-lingual text mining. In addition, the management and coordination of their concurrent editing actions involve relevant technical issues. In the design of Wikyoto, all these requirements have been considered together with the structure and the set of knowledge resources exploited by KYOTO. Wikyoto aims at enabling common Web users to formalize cross-lingual knowledge by exploiting simplified language-driven interactions. At the same time, Wikyoto generates the set of complex knowledge structures needed by computers to mine information from textual contents. The learning curve of Wikyoto has been kept as shallow as possible by hiding the complexity of the knowledge structures to the users. This goal has been pursued by both enhancing the simplicity and interactivity of knowledge editing patterns and by using natural language interviews to carry out the most complex knowledge editing tasks. In this context, TMEKO, a methodology useful to support users to easily formalize cross-lingual information by natural language interviews has been defined. The collaborative creation of knowledge resources has been evaluated in Wikyoto