Abstract

Abstract
Human-Computer Interaction (HCI) research has illuminated how technology can influence users’ awareness of their environmental impact and the potential for mitigating these impacts. From hot water saving to food waste reduction, researchers have systematically and widely tried to find pathways to speed up achieving sustainable development goals through persuasive technology interventions. However, motivating users to adopt sustainable behaviors through interactive technologies presents significant psychological, cultural, and technical challenges in creating engaging and long-lasting experiences. Aligned with this perspective, there is a dearth of research and design solutions addressing the use of persuasive technology to promote sustainable recycling behavior. Guided by a participatory design approach, this investigation focuses on the design opportunities for leveraging persuasive and human-centered Internet of Things (IoT) applications to enhance user engagement in recycling activities. The assumption is that one pathway to achieve this goal is to adopt persuasive strategies that may be incorporated into the design of sustainable applications. The insights gained from this process can then be applied to various sustainable HCI scenarios and therefore contribute to HCI’s limited understanding in this area by providing a series of design-oriented research recommendations for informing the development of persuasive and socially engaged recycling platforms. In particular, we advocate for the inclusion of educational content, real-time interactive feedback, and intuitive interfaces to actively engage users in recycling activities. Moreover, recognizing the cultural context in which the technology is socially situated becomes imperative for the effective implementation of smart devices to foster sustainable recycling practices. To this end, we present a case study that seeks to involve children and adolescents in pro-recycling activities within the school environment.

Abstract

Abstract

Abstract
The learning environment is an essential part of teaching and learning. Its personalization has several advantages (e.g., guaranteeing learning quality or effective learning). In vocational education, a personalized learning environment might provide training most suitable to each professional according to individual characteristics, skills, or career path. Artificial intelligence’s ability to process big data can be harnessed to personalize a learning environment. This work intends to investigate the personalization of a learning environment using artificial intelligence (AI) in vocational training that can provide relevant training based on the trainees’ skills required. A framework will be proposed to personalize a learning environment in this scope. Its development will follow the design science research (DSR) methodology. During the process, the survey methodology (expert interviews and focus groups) will be conducted to validate the artifact requirements and evaluate our future framework. © 2025 Elsevier B.V., All rights reserved.

Abstract
A Learning management system (LMS) is considered appropriate for company training. It is increasingly used in companies or organizations as a tool to manage their online training. The company or organization should consider the implementation of an LMS that provides ease in training content selection to achieve the best use and satisfaction of its employees in the learning process. From this perspective, the present study aims to investigate the implementation of a personalized LMS to facilitate the formative content selection tailored to employees’ roles. A Survey research methodology was used to achieve this objective. Based on the literature and survey results, we propose an approach to reach the personalization of content selection.