Year: 2025
Type: article
Abstract: Learner eXperience (LX) is a concept derived from User eXperience (UX) and it can be defined as the perceptions, answers, and performances of learners interacting with Digital Communication and Information Technologies (DICTs). Evaluating the LX to obtain experiences that support and facilitate learning and knowledge mastery is important. Thus, we developed the LEEM to assess and improve the learner's experience using DICTs during learning. The LEEM is a generic evaluation model and can be used for any level of education; it can be used independently of the discipline and used with any educational technology. Therefore, this article presents a feasibility study to evaluate the LEEM steps and sentences from the perspective of potential users. Nineteen teachers from different levels of education participated in this study. The study results were analyzed and generated in a new version of LEEM. The results showed positive points of LEEM, such as a practical, objective, easy-to-use, and useful model. In addition, opportunities for improving some items and sentences of LEEM were obtained. The teachers also suggested adding a description at the ends of the scales to facilitate the response to the items. This study contributes to creating a body of knowledge about LEEM and analyzing its use, feasibility, and evolution. Moreover, realizing the lack of content and synthesized characteristics about the technology that evaluates the LX, we carried out a benchmark on the LX evaluation technologies identified from a Systematic Mapping Study (SMS) to compare them with LEEM, in addition to presenting important characteristics to be analyzed in these types of technology, such as the elements and types of LX assessment and whether there is tool support for this assessment.
Institution: Universidade Federal do Paraná
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
Estimated APC paid: $1,390
OpenAlex ID: W4407835023