User sensitive research in e-learning: exploring the role of individual user characteristics

The increasing need for active and accessible learning in the inclusive knowledge society drives the demand for e-learning that engages users much more effectively than ever before. In this context, it is crucial to conduct research that embraces innovation in user sensitive design, or else influential individual user differences may be overlooked. The objective of this paper is to explore the creation of successful e-learning systems that are able to increase users’ learning performance and enhance their personal learning experiences. The paper reports two converging and complimentary approaches, namely case studies and experimentation. First, case studies are used to explore the extent to which effective e-learning systems comply with eight specific factors. Of the eight, accessibility, individual differences and student modeling turn out to be the weakest points in current practice. Second, an empirical study investigates the influences of user individual user differences on users’ learning outcomes in an e-learning environment. The experiment found that individual differences in motivation to learn and expectations about e-learning significantly impacted users’ learning achievements. Third, based on these studies, improvements in research methodology are identified towards greater consideration of user sensitive research issues, thus enabling us to outline improved experimental procedures. Further experiment results should provide us with better insights into the arguments needed to carefully assess benefits of developing and involving a user model in an e-learning application. Consequently, evaluation and justification could now encompass both system performance as well as user performance.     

Label-free Growth Receptor-2 Detection and Dissociation Constant Assessment in Diluted Human Serum Using a Longitudinal Extension Mode of a Piezoelectric Microcantilever Sensor

We have investigated real-time, label-free, in-situ detection of human epidermal growth factor receptor 2 (Her2) in diluted serum using the first longitudinal extension mode of a lead zirconate-lead titanate (PZT)/glass piezoelectric microcantilever sensor (PEMS) with H3 single-chain variable fragment (scFv) immobilized on the 3-mercaptopropyltrimethoxysilane (MPS) insulation layer of the PEMS surface. We showed that with the longitudinal extension mode, the PZT/glass PEMS consisting of a 1 mm long and 127 μm thick PZT layer bonded with a 75 μm thick glass layer with a 1.8 mm long glass tip could detect Her2 at a concentration of 6-60 ng/ml (or 0.06-0.6 nM) in diluted human serum, about 100 times lower than the concentration limit obtained using the lower-frequency flexural mode of a similar PZT/glass PEMS. We further showed that with the longitudinal mode, the PZT/glass PEMS determined the equilibrium H3-Her2 dissociation constant K(d) to be 3.3±0.3 × 10(-8) M consistent with the value, 3.2±0.28 ×10(-8) M deduced by the surface plasmon resonance method (BIAcore).     

Simulated environments with animated agents: effects on visual attention,emotion, performance,and perception

This research assessed how emotive animated agents in a simulation‐based training affect the performance outcomes and perceptions of the individuals interacting in real time with the training application. A total of 56 participants consented to complete the study. The material for this investigation included a nursing simulation in which participants interacted with three animated agents. The results of this investigation indicated that both experienced and novice participants focused more visual attention time on the body of the animated agent than the other defined areas of interest in the simulated environment. The results also indicated that novice participants conveyed more neutral facial expressions during the interaction with the animated agents than experience participants. The results of the simulation performance scores indicated that novice participants achieved higher simulation performance scores on the simulation task than experienced participants. Lastly, the results of the agent persona instrument showed that experienced and novice participants perceived the animated agents as facilitators of learning, credible, human‐like and engaging.     

State-Space Synthesis of Virtual Auditory Space

Binaural displays for immersive listening must model realistic acoustic environments, multiple sound sources, and accommodate source and head motion. Many displays accomplish this by convolving collections of spatially distributed point sources with head-related transfer functions (HRTFs). The computational load of such a system scales linearly with the number of HRTFs modeled by the display. Realistic scenes often require a large number of HRTFs, and this framework is computationally burdensome. We propose a method that significantly eases this load by formulating the HRTF filter array as a state-space system. Three state-space architectures are explored. The performance of the most general architecture is found to suffer due to the interaural time delay (ITD). This problem may be circumvented with two alternative architectures, although the ideal choice depends on the specific display application. For each architecture, two order-reduction techniques are explored. Both techniques are based on the Hankel operator; one is ad hoc and simple to implement whereas the other is optimal in the Hankel norm. The two methods yield similar auditory performance, although the optimal method may be desirable for HRTF approximation.     

Convergent Smoothing and Segmentation of Noisy Range Data in Multiscale Space

With few exceptions, most of the existing noise reduction and data segmentation algorithms are only suited to image data. Therefore, an adaptive smoothing algorithm, with model-based masks, within a scale space framework is proposed for range data in this paper. This algorithm smoothes range data that conform to predefined, geometric models, while leaving other data points unaffected. The convergence of the algorithm in yielding dominant features is shown based on its compliance with the anisotropic diffusion concept. The weights of the smoothing masks are adaptively calculated according to the Mahalanobis distances between range data and model-based predictions. These behave as the diffusion coefficient in the anisotropic diffusion equation, thus satisfying the requirements of the causality criterion that no new features are introduced from fine to coarse scales. The computational complexity of this algorithm is examined and compared to that of the well-known RANSAC feature extraction algorithm. Unlike RANSAC, it has the advantage that the computational complexity is less affected by increasing the order of the model, and is independent of the number of model outliers. The proposed algorithm can be used to smooth range data in multiscale space by increasing the number of smoothing iterations. Robust, robot-occlusion-invariant features are then easily extracted from the smoothed data by least squares fitting algorithms.     

Heroin related overdose problems

During the first ten months of 1992 the Oslo Ambulance Department registered 716 incidences of assumed drug-related intoxications. 80% happened in down town Oslo. 19 cases of asystoly were recorded, 13 of the patients recovered after treatment, without sequelae. Five of these patients left the location after emergency help and they refused hospitalization. 432 of the patients were unconscious when the ambulance personal arrived, 472 were treated with naloxone both by the intramuscular and the intravenous route. Most of the persons refused further observation. A team of specially trained out reach workers offers help after acute medical treatment by means of "streetwork". The intervention is directed at addicts who have experienced an overdose.     

Investigation of soybean oil as a diesel fuel extender: Endurance tests

Engine performance and crankcase lubricant viscosity were followed with 1∶2 and 1∶1 fuel mixtures of degummed soybean oil in No. 2 diesel fuel in tests with a John Deere 6-cylinder, 404 cubic in. displacement, direct-injection, turbocharged engine for a total of 600 running hours. A crankcase oil contamination problem resulting in an unacceptable thickening and a potential for gelling did exist with a 50/50 blend or a greater concentration of soybean oil, but it did not occur with the 1∶2 blend. The data accumulated during the initial 600 hr running time indicates that a fuel blend of one-third degummed soybean oil and two-thirds No. 2 diesel (1∶2 blend) may be a suitable fuel for agricultural equipment during periods of diesel fuel shortages or allocations. Additional data are being accumulated and will be analyzed in the future.