Web-Based Learning Object Search Engine Solution Together with Data Visualization: The Case of MERLOT II

Open Educational Resources deliver a strategic opportunity to improve the quality of education. Currently, OER users, students, instructors, and scholars can find OERs from general search engines through metadata enrichment and logic extrapolation. Yet, most users of Web search engines today face difficulties when searching for decent and appropriate learning materials. One of the explanations may be that users are unable to get a clear overview of the list of results produced by current learning object repositories (LORs) for a given single keyword search. The purpose of this study is to propose an enhanced learning object (LO) search engine solution together with a data visualization feature in order to navigate a hitlist of LOs using a hierarchical knowledge graph based on a single keyword search in LORs. In order to conduct experiments and validate our approach, in this study we selected MERLOT II, a well-known learning resource repository. We implemented a Web-based solution where users can execute a single keyword search, then visualize results on a hierarchical knowledge graph. In order to accomplish our objectives, the back-end of the system was involved in the functions of data extraction, data transformation, data clustering and data visualization. The outcome of the search and data visualization results indicate that the proposed approach can help users to get a clear overview of the LOs based on a single keyword search.