KnowledgePuzzle: a browsing tool to adapt the web navigation process to the learner's mental model

This article presents KnowledgePuzzle, a browsing tool for knowledge construction from the web. It aims to adapt the structure of web content to the learner’s information needs regardless of how the web content is originally delivered. Learners are provided with a meta-cognitive space (eg, a concept mapping tool) that enables them to plan navigation paths and visualize the semantic processing of knowledge in their minds. Once the learner’s viewpoint becomes visually represented, it will be transformed to a layer of informative hyperlinks and annotations over previously visited pages. The attached layer causes the web content to be explicitly structured to accommodate the learner’s interests by interlinking and annotating chunks of information that make up the learner’s knowledge. Finally, a hypertext version of the whole knowledge is generated to enable fast and easy reviewing. A discussion about the

Technologies to enhance self-directed learning from hypertext

With the growing popularity of the World Wide Web, materials presented to learners in the form of hypertext have become a major instructional resource. Despite the potential of hypertext to facilitate access to learning materials, self-directed learning from hypertext is often associated with many concerns. Self-directed learners, due to their different viewpoints, may follow different navigation paths, and thus they will have different interactions with knowledge. Therefore, learners can end up being disoriented or cognitively-overloaded due to the potential gap between what they need and what actually exists on the Web. In addition, while a lot of research has gone into supporting the task of finding web resources, less attention has been paid to the task of supporting the interpretation of Web pages. The inability to interpret the content of pages leads learners to interrupt their current browsing activities to seek help from other human resources or explanatory learning materials. Such activity can weaken learner engagement and lower their motivation to learn. This thesis aims to promote self-directed learning from hypertext resources by proposing solutions to the above problems. It first presents Knowledge Puzzle, a tool that proposes a constructivist approach to learn from the Web. Its main contribution to Web-based learning is that self-directed learners will be able to adapt the path of instruction and the structure of hypertext to their way of thinking, regardless of how the Web content is delivered. This can effectively reduce the gap between what they need and what exists on the Web. SWLinker is another system proposed in this thesis with the aim of supporting the interpretation of Web pages using ontology based semantic annotation. It is an extension to the Internet Explorer Web browser that automatically creates a semantic layer of explanatory information and instructional guidance over Web pages. It also aims to break the conventional view of Web browsing as an individual activity by leveraging the notion of ontology-based collaborative browsing. Both of the tools presented in this thesis were evaluated by students within the context of particular learning tasks. The results show that they effectively fulfilled the intended goals by facilitating learning from hypertext without introducing high overheads in terms of usability or browsing efforts

Spotlight browsing of resource archives

Many organizations, particularly in the heritage sector, have large archives of digital content that they could make available to the general public or special interest groups if they had the appropriate mechanisms. Currently, these organizations can develop pre-crafted web sites, simple database-driven web sites or search facilities for accessing the content. However, none of these can be expected to appropriately present this content or scaffold its effective use. Our proposed solution is an approach to navigation that we term spotlight browsing. It has the following key features: (i) Users can select a collection of resources from the archive, shining a spotlight on this area of the archive; (ii) The collection is structured in a number of ways to support its exploration and convey interesting properties of the collection; (iii) Users can see what is on the periphery of their current collection in order to encourage further exploration; (iv) Users can redefine the collection in order to move their spotlight to another area of the archive; (v) Any item viewed while browsing can be bookmarked into a personal collection that can be built up using resources from many different spotlights. The approach has been implemented and tested using an archive of content from a heritage institution

The use of scaffolding to improve student learning with interactive multimedia programs in chemistry

The process of balancing and interpreting chemical equations involves the consideration of an abstract, non-observable phenomenon coupled with multi-level representation. Students find it conceptually demanding to visualise the particulate level of matter and hence experience difficulty in balancing chemical equations with understanding. Interactive multimedia with dynamic computer graphics can provide students with accurate, concrete representations of the particulate nature of matter. Such tools, when coupled with appropriate implementation strategies, have the potential to improve learning about chemical reactions. The study investigated the use of scaffolding techniques to enhance and direct student learning when using an interactive multimedia software (IMM) program, Balancing and Interpreting Chemical Equations (Garnett, Hackling & Oliver, 1997a) designed to develop skills and understanding of balancing and interpreting chemical equations. This research was conducted as an interpretive, collective case study which was supplemented with data from pre and posttests. In this design, a total of 12 Year 10 students were selected by purposeful sampling, arranged in pairs and then randomly assigned to either using the specified IMM software with or without scaffolding. Students were observed by the researcher whilst using the IMM software and various student interactions were recorded by a variety of media, including screen-capture of their interactions with the IMM software, audio recordings of the interactions and collaborations between students in pairs, and videotape recordings of both the interactions and collaborations between students in pairs and between students and the IMM software. The data from these sources, in addition to data from the pre and posttests, was used to generate a case history file which was analysed to elucidate information about how scaffolding affects the way in which students interact with the IMM software; how scaffolding affects the way in which students interact and collaborate with each other whilst working on the IMM software; and whether there was any evidence of enhanced understanding of the particulate nature of reactions and success in writing and balancing chemical equations following the use of this IMM software with scaffolding. The research indicated that scaffolding affects the manner in which students interact with the IMM software by encouraging and directing more efficient and deliberate access to the salient features of the program at specific times in the learning sequence. The research also indicated that the level of collaboration between students working in dyads on the IMM software was influenced by the use of the scaffolds and that once applied, the fading of support in scaffolded worksheets did not result in a deterioration of the nature or extent of the interactions within the dyad. Finally, while the scaffolds did not always result in higher levels of cognitive achievement (compared to non-scaffolded instruction), they did enhance the IMM learning environment and the opportunity for conceptual change. The implications that arise from this research extend to the use of this IMM software in the classroom, teaching practices within an IMM environment, software designers, and for further research

Ubiquitous learning architecture to enable learning path design across the cumulative learning continuum

The past twelve years have seen ubiquitous learning (u-learning) emerging as a new learning paradigm based on ubiquitous technology. By integrating a high level of mobility into the learning environment, u-learning enables learning not only through formal but also through informal and social learning modalities. This makes it suitable for lifelong learners that want to explore, identify and seize such learning opportunities, and to fully build upon these experiences. This paper presents a theoretical framework for designing personalized learning paths for lifelong learners, which supports contemporary pedagogical approaches that can promote the idea of a cumulative learning continuum from pedagogy through andragogy to heutagogy where lifelong learners progress in maturity and autonomy. The framework design builds on existing conceptual and process models for pedagogy-driven design of learning ecosystems. Based on this framework, we propose a system architecture that aims to provide personalized learning pathways using selected pedagogical strategies, and to integrate formal, informal and social training offerings using two well-known learning and development reference models; the 70:20:10 framework and the 3–33 model

Knowledge Integration in the Digital Age: Trajectories, Opportunities and Future Directions

Researchers from around the world have shaped knowledge integration (KI), a framework that captures the processes learners use to build on their multiple ideas and refine their understanding. KI emerged 25 years ago from syntheses of experimental, longitudinal, and meta-analytic studies of learning and instruction. Advances in KI have resulted from partnerships that combine expertise in learning, instruction, classroom teaching, assessment, technology, and the disciplines. This structured poster session includes partnerships that have advanced design of instruction, assessment, professional development, learning technologies, and research methodologies. Participants report on new technologies, including games, to strengthen KI; instructional designs that take advantage of collaboration to support KI; and extensions of KI to integrate science with other disciplines. They summarize exciting results and identify promising opportunities for advancing STEM instruction to promote intentional, life-long learners in the digital age

Doctor of Philosophy

dissertationSelf-regulated learning with online resources is a prevalent experience for today's learners, but these online learning opportunities frequently yield disappointing results when considering students' learning outcomes. The current research examined the impact of different forms of navigational scaffolds to help learners self-regulate their learning behaviors as they attempted to form well-organized, conceptual knowledge from varied online resources. Experiment 1 examined scaffolds for two potentially useful learning paths: conceptual coherence (depicted in a graphical overview of the domain) and foundational knowledge (depicted via visual cues about the importance of a concept to the domain). Results revealed no effects of a conceptual coherence scaffold on participants' self-regulated learning behaviors or learning outcomes. When foundational knowledge scaffolds were present, participants used more effective self-regulated learning strategies on higher priority concepts, but learning did not improve. Participants utilized prescribed learning paths only 63% of the time and thus may not have benefited from them. Experiment 2 investigated the impact of using a dynamic, automatic scaffold to structure learning paths through the online resources; both learning path (coherence vs. foundational) and amount of learner navigational control (low vs. high) were varied. Results revealed that when a foundational knowledge path was enforced, learners executed more effective self-regulated learning strategies and gained a deeper understanding of conceptual relationships. Overall findings suggest that learners working with digital resources benefit from navigational guidance that helps them focus on foundational ideas in an online, self-regulated environment

Integration Scaffolding in Hypermedia Learning

This dissertation project used 80 undergraduate students to examine the effectiveness of three forms of facilitation in hypermedia learning with text and diagrams about the human circulatory system: 1) signaling key terms, 2) prompted referencing of diagrammatic representations, and 3) integration scaffolding which provided facilitation in locating corresponding components within diagrams. These three experimental manipulations were compared to a control condition in which learners used the same hypermedia learning environment, without any facilitative feature in coordinating between text and diagrams. Two measures captured differences in learning: 1) a multiple choice pretest and posttest of declarative and conceptual knowledge and 2) a diagram interpretation task requiring learners to use diagrams to explain their understanding of the circulatory system. Eye-tracking measures and concurrent think-aloud protocols were collected during the 20-minute learning sessions to provide process measures of students\u27 learning and a self-report cognitive load measure was administered immediately after the learning session. Results indicated that the integration scaffolding condition led to higher posttest scores on the multiple choice measure, but no significant differences were detected for the diagram interpretation task. Eye-tracking results demonstrated that the integration scaffolding condition had a higher number of and a higher total duration of fixations on relevant areas within the diagrams. The relevant areas represent diagrammatic representations corresponding to the textual referents within the accompanying text. Additionally, these learners spent a significantly larger proportion of their time inspecting diagrams looking at the relevant areas of the diagrams and a significantly larger proportion of these learners\u27 fixations were on relevant areas. Analyses of learners\u27 self-regulated learning processes, based on concurrent think-aloud protocols, indicated that the integration scaffolding condition also generated more correct summarizations than the remaining groups. The self-report cognitive load measure failed to reveal any differences among the learning conditions. Taken together, these results provide support for models of text-picture integration (Mayer, 2005; Schnotz, 2005) and, to some extent, Cognitive Load Theory. Further, the experiment suggests that directing learners\u27 attention to corresponding elements within text and diagrams can be an effective technique for facilitating the process of text-picture integration

A data-assisted approach to supporting instructional interventions in technology enhanced learning environments

The design of intelligent learning environments requires significant up-front resources and expertise. These environments generally maintain complex and comprehensive knowledge bases describing pedagogical approaches, learner traits, and content models. This has limited the influence of these technologies in higher education, which instead largely uses learning content management systems in order to deliver non-classroom instruction to learners. This dissertation puts forth a data-assisted approach to embedding intelligence within learning environments. In this approach, instructional experts are provided with summaries of the activities of learners who interact with technology enhanced learning tools. These experts, which may include instructors, instructional designers, educational technologists, and others, use this data to gain insight into the activities of their learners. These insights lead experts to form instructional interventions which can be used to enhance the learning experience. The novel aspect of this approach is that the actions of the intelligent learning environment are now not just those of the learners and software constructs, but also those of the educational experts who may be supporting the learning process. The kinds of insights and interventions that come from application of the data-assisted approach vary with the domain being taught, the epistemology and pedagogical techniques being employed, and the particulars of the cohort being instructed. In this dissertation, three investigations using the data-assisted approach are described. The first of these demonstrates the effects of making available to instructors novel sociogram-based visualizations of online asynchronous discourse. By making instructors aware of the discussion habits of both themselves and learners, the instructors are better able to measure the effect of their teaching practice. This enables them to change their activities in response to the social networks that form between their learners, allowing them to react to deficiencies in the learning environment. Through these visualizations it is demonstrated that instructors can effectively change their pedagogy based on seeing data of their students’ interactions. The second investigation described in this dissertation is the application of unsupervised machine learning to the viewing habits of learners using lecture capture facilities. By clustering learners into groups based on behaviour and correlating groups with academic outcome, a model of positive learning activity can be described. This is particularly useful for instructional designers who are evaluating the role of learning technologies in programs as it contextualizes how technologies enable success in learners. Through this investigation it is demonstrated that the viewership data of learners can be used to assist designers in building higher level models of learning that can be used for evaluating the use of specific tools in blended learning situations. Finally, the results of applying supervised machine learning to the indexing of lecture video is described. Usage data collected from software is increasingly being used by software engineers to make technologies that are more customizable and adaptable. In this dissertation, it is demonstrated that supervised machine learning can provide human-like indexing of lecture videos that is more accurate than current techniques. Further, these indices can be customized for groups of learners, increasing the level of personalization in the learning environment. This investigation demonstrates that the data-assisted approach can also be used by application developers who are building software features for personalization into intelligent learning environments. Through this work, it is shown that a data-assisted approach to supporting instructional interventions in technology enhanced learning environments is both possible and can positively impact the teaching and learning process. By making available to instructional experts the online activities of learners, experts can better understand and react to patterns of use that develop, making for a more effective and personalized learning environment. This approach differs from traditional methods of building intelligent learning environments, which apply learning theories a priori to instructional design, and do not leverage the in situ data collected about learners