Web‐based learning object selection software using analytical hierarchy process

Abstract

The concepts of sustainability and reusability have great importance in engineering education. In this context, metadata provides reusability and the effective use of Learning Objects (LOs). In addition, searching the huge LO Repository with metadata requires too much time. If the selection criteria do not exactly match the metadata values, it is not possible to find the most appropriate LO. When this situation arises, the multi-criteria decision making (MCDM) method can meet the requirements. In this study, the SDUNESA software was developed and this software allows for the selection of a suitable LO from the repository by using an analytical hierarchy process MCDM method. This web-based SDUNESA software is also used to store, share and select a suitable LO in the repository. To meet these features, the SDUNESA software contains Web 2.0 technologies such as AJAX, XML and SOA Web Services. The SDUNESA software was especially developed for computer engineering education. Instructors can use this software to select LOs with defined criteria. The parameters of the web-based SDUNESA learning object selection software that use the AHP method are defined under the computer education priorities. The obtained results show that the AHP method selects the most reliable learning object that meets the criteria.

A social network-based teacher model to support course construction

“…In particular, they need a specific driver to translate the own standard of a LOR into the standard used in their network. After that, different systems have been developed to retrieve LOs from these wide networks and local LORs (see Simon et al, 2005;Ternier et al, 2008;Limongelli, Miola, Sciarrone, & Temperini, 2012a;Yigit, Isik, & Ince, 2014). They focus on how to enhance the users query and to filter the resulting LOs.…”

AHP-TOPSIS Method for Learning Object Metadata Evaluation

“…LORs store LOs to provide e-content for such systems. Having a lot of LOs and metadata, selection and evaluation of LOs in LORs is difficult issue considering complexity of metadata and time waste issues [4]. Some methods are developed for evaluation and selection of LO with search parameters and criteria.…”

“…Moreover, frequent pattern tree [8], term frequency [9] are used for evaluation and selection of LOs. Yigit et al [4] and Ince et al [5] used AHP method for LO selection based on IEEE LOM metadata. The Analytical Hierarch Process (AHP) is the most popular MCDM model to solve complex problems [10].…”

“…For these reasons, evaluation and selection process can be regarded as multi criteria decision making problem. We used AHP [4] and Fuzzy AHP [5] methods for LO selection in previous studies. In order to solve the drawbacks and critics of the AHP, AHP is combined with the TOPSIS for LO selection and evaluation.…”

“…Metadata has many tag elements to identify LOs in LORs [3]. If there are a lot of LO in the LOR, evaluation and the selection of LOs are difficult process [4]. Moreover, this process may consume huge amount of time and cause unwanted selections [5].…”