Enhancing learners' confidence through customized learning

Abstract

In the modern era, chronic diseases such as heart disease, cancer, diabetes, and asthma continue to increase among the general public. Through careful observation of symptoms, however, potential diseases may be detected early and managed accordingly. For that to happen, patients need to be aware of and informed about these diseases. To acquire such knowledge, patients may also need to gather essential health information from a variety of sources such as Internet articles, online scholarly papers, and other types of e-learning systems. However, the amount of available information—which is often overwhelming—discourages patient learning. To motivate patient learning, we propose an approach that delivers only relevant information that is specifc to each patient’s condition. In our approach, we utilize observed symptoms and vital signs to identify potential diseases of a patient. We use a constructed patient profle to deliver patient-specifc learning materials called a study plan. To monitor and promote their study, we developed a mobile application that allows patients to view their study plan(s) and study the customized learning materials. Such customized learning allows patients to take control of their symptoms and potential diseases, which ultimately helps them to improve their overall health outcomes. As another application area, we chose employee training. Competent employees are an important asset for any organization to be competitive. Employees can become more competent in their jobs when they enhance their skills in the feld to which they belong. Providing the necessary skill sets to each employee can be cumbersome since backgrounds and existing skillsets are different and any uniform training attempt may be ineffcient and costly. In order to effectively provide the necessary skills to each employee, the training must be customized. In our approach, we analyze employees’ existing skill sets using their learner profle and determine necessary training by comparing organizations’ required skill sets. We utilize European Skills, Competences and Occupations classifcation (ESCO) and Dublin Core (DC) metadata to streamline the customization process that is used to store available Massive Open Online Course (MOOC) course descriptions, applying the concept of learning object and learning object repository to our local database. When creating a customized study plan for each employee, learner profles and required skill sets are compared to produce required courses that are specifc to each employee. In this dissertation, we proposed the idea of customized learning by leveraging user profles, codifed learning materials, up-to-date MOOCs, and customized study plans to enhance learners’ level of understanding and improve their competency.