Traditional mechanisms used to rank learning objects are not longer viable thanks to the current abundance of resources. This work proposes the construction of an improved relevance ranking function based on contextualized attention data extracted from the interaction between the users and the objects. A multidimensional approach to relevance is followed. Beside the Algorithmic relevance, curre...

We present here an original work that uses machine learning techniques to combine time series forecasts. In this proposal, a machine learning technique uses features of the series at hand to define adequate weights for the individual forecasting methods being combined. The combined forecasts are the weighted average of the forecasts provided by the individual methods. In order to evaluate this ...

the production, distribution, and consumption of information are the most important development indices of any nation. plenty of opportunities were created by e-learning which have overall paved the grounds for and enriched the presentation of learning materials through advanced audiovisual educational facilities. such learning environments are by and large flexible and provide more appropriate...

This paper shows that two uncertaintybased active learning methods, combined with a maximum entropy model, work well on learning English verb senses. Data analysis on the learning process, based on both instance and feature levels, suggests that a careful treatment of feature extraction is important for the active learning to be useful for WSD. The overfitting phenomena that occurred during the...

Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process...

This paper provides insights into teaching and learning based on the analysis of an accredited professional development program, entitled the Postgraduate Certificate in Third Level Learning and Teaching, aimed at lecturing staff/faculty in Irish higher education. The program has its theoretical basis in the Kolb Experiential Learning Cycle (Kolb, 1983), combined with principles of collaborativ...

Recent research has shown that learning technology combining adaptive and perceptual learning (PL) methods can improve pattern recognition, transfer, and fluency in complex learning domains (e.g., Mettler & Kellman, 2014). Both classic research and recent work suggest the benefit of paired comparisons in PL, but no previous work has used adaptive techniques to trigger comparisons. We asked whet...

Breast cancer is one of the most common types of cancer and leading cancer-related death causes for women. In the context of ICIAR 2018 Grand Challenge on Breast Cancer Histology Images, we compare one handcrafted feature extractor and five transfer learning feature extractors based on deep learning. We find out that the deep learning networks pretrained on ImageNet have better performance than...

We present a study on using storytelling for teaching skills to low-income workers in the developing world. Taking a cue from work on using dramatized stories and video to promote technology use and agricultural and HIV/AIDS education, we investigated storytelling’s ability for teaching lowliteracy populations. We created a series of videos to teach domestic workers in urban India bed-making an...