Cognitive Styles and Adaptive Web-based Learning

Adaptive hypermedia techniques have been widely used in web-based learning programs. Traditionally these programs have focused on adapting to the user’s prior knowledge, but recent research has begun to consider adapting to cognitive style. This study aims to determine whether offering adapted interfaces tailored to the user’s cognitive style would improve their learning performance and perceptions. The findings indicate that adapting interfaces based on cognitive styles cannot facilitate learning, but mismatching interfaces may cause problems for learners. The results also suggest that creating an interface that caters for different cognitive styles and gives a selection of navigational tools might be more beneficial for learners. The implications of these findings for the design of web-based learning programs are discussed

Navigation in hypermedia learning systems: Experts vs. novices

With the advancement of Web technology, hypermedia learning systems are becoming more widespread in educational settings. Hypermedia learning systems present course content with non-sequential formats, so students are required to develop learning paths by themselves. Yet, empirical evidence indicates that not all students can benefit from hypermedia learning. Research into individual differences suggests that prior knowledge has significant effects on student learning in hypermedia systems, with experts and novices showing different preferences to the use of hypermedia learning systems and requiring different levels of navigation support. It is therefore essential to develop a mechanism to help designers understand the needs of experts and novices. To address this issue, this paper presents a framework to illustrate the needs of students with different levels of prior knowledge by analyzing the findings of previous research. The overall aim of this framework is to integrate students’ prior knowledge into the design of hypermedia learning systems. Finally, implications for the design of hypermedia learning systems are discussed

Footprints of information foragers: Behaviour semantics of visual exploration

Social navigation exploits the knowledge and experience of peer users of information resources. A wide variety of visual–spatial approaches become increasingly popular as a means to optimize information access as well as to foster and sustain a virtual community among geographically distributed users. An information landscape is among the most appealing design options of representing and communicating the essence of distributed information resources to users. A fundamental and challenging issue is how an information landscape can be designed such that it will not only preserve the essence of the underlying information structure, but also accommodate the diversity of individual users. The majority of research in social navigation has been focusing on how to extract useful information from what is in common between users' profiles, their interests and preferences. In this article, we explore the role of modelling sequential behaviour patterns of users in augmenting social navigation in thematic landscapes. In particular, we compare and analyse the trails of individual users in thematic spaces along with their cognitive ability measures. We are interested in whether such trails can provide useful guidance for social navigation if they are embedded in a visual–spatial environment. Furthermore, we are interested in whether such information can help users to learn from each other, for example, from the ones who have been successful in retrieving documents. In this article, we first describe how users' trails in sessions of an experimental study of visual information retrieval can be characterized by Hidden Markov Models. Trails of users with the most successful retrieval performance are used to estimate parameters of such models. Optimal virtual trails generated from the models are visualized and animated as if they were actual trails of individual users in order to highlight behavioural patterns that may foster social navigation. The findings of the research will provide direct input to the design of social navigation systems as well as to enrich theories of social navigation in a wider context. These findings will lead to the further development and consolidation of a tightly coupled paradigm of spatial, semantic and social navigation

The role of human factors in stereotyping behavior and perception of digital library users: A robust clustering approach

To deliver effective personalization for digital library users, it is necessary to identify which human factors are most relevant in determining the behavior and perception of these users. This paper examines three key human factors: cognitive styles, levels of expertise and gender differences, and utilizes three individual clustering techniques: k-means, hierarchical clustering and fuzzy clustering to understand user behavior and perception. Moreover, robust clustering, capable of correcting the bias of individual clustering techniques, is used to obtain a deeper understanding. The robust clustering approach produced results that highlighted the relevance of cognitive style for user behavior, i.e., cognitive style dominates and justifies each of the robust clusters created. We also found that perception was mainly determined by the level of expertise of a user. We conclude that robust clustering is an effective technique to analyze user behavior and perception

Consistency Problems for Jump-Diffusion Models

In this paper consistency problems for multi-factor jump-diffusion models, where the jump parts follow multivariate point processes are examined. First the gap between jump-diffusion models and generalized Heath-Jarrow-Morton (HJM) models is bridged. By applying the drift condition for a generalized arbitrage-free HJM model, the consistency condition for jump-diffusion models is derived. Then we consider a case in which the forward rate curve has a separable structure, and obtain a specific version of the general consistency condition. In particular, a necessary and sufficient condition for a jump-diffusion model to be affine is provided. Finally the Nelson-Siegel type of forward curve structures is discussed. It is demonstrated that under regularity condition, there exists no jump-diffusion model consistent with the Nelson-Siegel curves.Comment: To appear in Applied Mathematical Financ

Profiling of Glycan Receptors for Minute Virus of Mice in Permissive Cell Lines Towards Understanding the Mechanism of Cell Recognition

The recognition of sialic acids by two strains of minute virus of mice (MVM), MVMp (prototype) and MVMi (immunosuppressive), is an essential requirement for successful infection. To understand the potential for recognition of different modifications of sialic acid by MVM, three types of capsids, virus-like particles, wild type empty (no DNA) capsids, and DNA packaged virions, were screened on a sialylated glycan microarray (SGM). Both viruses demonstrated a preference for binding to 9-O-methylated sialic acid derivatives, while MVMp showed additional binding to 9-O-acetylated and 9-O-lactoylated sialic acid derivatives, indicating recognition differences. The glycans recognized contained a type-2 Galβ1-4GlcNAc motif (Neu5Acα2-3Galβ1-4GlcNAc or 3′SIA-LN) and were biantennary complex-type N-glycans with the exception of one. To correlate the recognition of the 3′SIA-LN glycan motif as well as the biantennary structures to their natural expression in cell lines permissive for MVMp, MVMi, or both strains, the N- and O-glycans, and polar glycolipids present in three cell lines used for in vitro studies, A9 fibroblasts, EL4 T lymphocytes, and the SV40 transformed NB324K cells, were analyzed by MALDI-TOF/TOF mass spectrometry. The cells showed an abundance of the sialylated glycan motifs recognized by the viruses in the SGM and previous glycan microarrays supporting their role in cellular recognition by MVM. Significantly, the NB324K showed fucosylation at the non-reducing end of their biantennary glycans, suggesting that recognition of these cells is possibly mediated by the Lewis X motif as in 3′SIA-LeX identified in a previous glycan microarray screen

Deciphering interplay between Salmonella invasion effectors

Bacterial pathogens have evolved a specialized type III secretion system (T3SS) to translocate virulence effector proteins directly into eukaryotic target cells. Salmonellae deploy effectors that trigger localized actin reorganization to force their own entry into non-phagocytic host cells. Six effectors (SipC, SipA, SopE/2, SopB, SptP) can individually manipulate actin dynamics at the plasma membrane, which acts as a ‘signaling hub’ during Salmonella invasion. The extent of crosstalk between these spatially coincident effectors remains unknown. Here we describe trans and cis binary entry effector interplay (BENEFIT) screens that systematically examine functional associations between effectors following their delivery into the host cell. The results reveal extensive ordered synergistic and antagonistic relationships and their relative potency, and illuminate an unexpectedly sophisticated signaling network evolved through longstanding pathogen–host interaction

How can we use the endocytosis pathways to design nanoparticle drug-delivery vehicles to target cancer cells over healthy cells?

Targeted drug delivery in cancer typically focuses on maximising the endocytosis of drugs into the diseased cells. However, there has been less focus on exploiting the differences in the endocytosis pathways of cancer cells versus non-cancer cells. An understanding of the endocytosis pathways in both cancer and non-cancer cells allows for the design of nanoparticles to deliver drugs to cancer cells whilst restricting healthy cells from taking up anticancer drugs, thus efficiently killing the cancer cells. Herein we compare the differences in the endocytosis pathways of cancer and healthy cells. Second, we highlight the importance of the physicochemical properties of nanoparticles (size, shape, stiffness, and surface chemistry) on cellular uptake and how they can be adjusted to selectively target the dominated endocytosis pathway of cancer cells over healthy cells and to deliver anticancer drug to the target cells. The review generates new thought in the design of cancer-selective nanoparticles based on the endocytosis pathways

Key Parameters That Determine the Magnitude of the Decrease in Current in Nanopore Blockade Sensors

Nanopore blockade sensors were developed to address the challenges of sensitivity and selectivity for conventional nanopore sensors. To date, the parameters affecting the current of the sensor have not been elucidated. Herein, the impacts of nanopore size and charge and the shape, size, surface charge, and aggregation state of magnetic nanoparticles were assessed. The sensor was tolerant to all parameters contrary to predictions from electronic or geometric arguments on the current change. Theoretical models showed the greater importance of the polymers around nanoparticles and the access resistance of nanopores to the current, when compared with translocation-based nanopore sensors. The signal magnitude was dominated by the change in access resistance of ∼4.25 Mω for all parameters, resulting in a robust system. The findings provide understandings of changes in current when nanopores are blocked, like in RNA trapping or nanopore blockade sensors, and are important for designing sensors based on nanopore blockades