# The Interoperability of Learning Object Design, Search and Adaptation Processes in the Repositories
## 2 Overview on Existing Practices
Technologies can be used to foster different pedagogical approaches, which can be characterized as associative, constructivist, situative and connectivism [35]. The key limitation of handheld technology for the delivery of learning objects is the small screen that is available for effective display. The smallness of the screen does not only adversely affect the clarity but also negatively affects the acceptance and integration of this potentially useful technology in education. Study [36] investigated characteristics of effective design of learning objects on such devices, reporting user response to learning object design possibilities for mobile devices. Three sets of design recommendations can be distinguished [37]: design presentation of conceptual models, small screen design, and design in relation to specific learning use. The role of the teacher himself/herself has changed over time, as well as a significant increase in the availability of teaching and learning materials. When e-learning is used, teachers can act as course developers and facilitators, guiding learners through their learning experience. The variety of learning resources available on the web and the flexibility of modern learning management systems can allow teachers, who meet remotely, or find difficulties to meet, to share methodological approaches and learning content, giving them more opportunities through digital technologies [38]. Aspects such as the involvement of teachers and their activities in the e-course, the attitude of students towards the subject and the acceptance of technology have a positive impact on e-learning [39]. Most universities are using various elements of distance learning. The authors [40] explored the possibility of creating an internal repository of university teaching materials for university staff. The paper finds a significant gap between the needs of the technical team to describe learning objects using metadata for the smooth management of learning objects and the needs of academic teachers, for whom the didactic efficiency of the objects is paramount. The creation and management of learning objects using technical repositories must be straightforward. Research and teaching staff should only have a few essential metadata fields visible and filled. Professionals should complete the rest [40]. The authors [22] point out that one of the key issues in developing well-functioning practical personalized e-learning systems is related to the required complex ontological models. To solve the problem, the authors suggest using previously created ontologies collected in the ontological library for e-learning. In this case, researchers should preserve the ontologies created as part of research projects, describe them, and offer valuable mappings to other related ontologies in the library. The authors [41] discuss possible solutions to the problem of searching for objects of a single topic in learning repositories and suggest that the issue of searching for data in the learning repositories may be solved by applying text-mining algorithms. In addition, methods based on deep learning are being actively developed as they can improve the quality of data search by extracting new characteristics and metadata [42]. After instructional designers, instructors, and learners discover LOs from a digital repository, the next step is to integrate the retrieved LOs into their learning projects. However, the adaption process is not always smooth. Common challenges are system/software dependency, as well as language and culture-related content issues. For example, the lack of availability of an object in the desired language can cause adaptation issues [43]. The problem of recommending learning objects to a group of users or instructors is more difficult than the traditional problem of recommending to only one individual. To resolve this problem, a collaborative methodology was proposed for searching, selecting, rating and recommending learning objects [44]. [PERSON] et al.