Abstract
The emergence of accessible virtual reality headsets in the past decade multiplied educational uses of immersive virtual reality. Higher education, in particular, has seen many such reports emerge. However, there are scarce frameworks for higher education professionals to plan and deploy immersive virtual reality within their pedagogical practice. To attain a perspective on this field, we conducted a systematic literature review using SCOPUS search, focusing on Instructional Design Models for Immersive Virtual Reality in online Higher Education. This review aimed to provide a comprehensive overview of these models, their respective phases, and distinctive characteristics. The review identified two categories of Instructional Design Models for Immersive Virtual Reality in Higher Education: 1) Models specific to such contexts, with aspects such as managing immersion time or providing prior contact with the immersive environment; 2) Models developed for other contexts and adapted to immersive virtual reality, addressing aspects such as the importance of creating objectives, assessment elements, or defining resource purpose. We conclude that current instructional models used for immersive virtual reality in higher education lack the combination of the overall pedagogical concerns with the specific ones for immersive virtual reality. Thus, we recommend further research to develop instruction models that combine both aspects of learning design concerns.

Abstract
The proper integration of technology in teaching and learning processes must consider the role of teachers and students, as well as the design of tasks and the context in which they are implemented. Teachers' perceived self-efficacy significantly influences their willingness to integrate educational robotics (ER) into their practice, so initial teacher training should provide opportunities for teachers to participate in structured activities that integrate ER. In this study, a class of pre-service teachers from an initial teacher training programme were provided with their first contact with an ER platform through the use of a simulator. We present the design process of a student exploration guide and teacher guide, developed over three iterative cycles of implementation, assessment and redesign. The analysis of the data collected allowed for improvements in the design of the tasks, the graphic component of the student exploration guide, and more precise indications for the teacher's actions. The main contribution of this study is the chain orchestration between the simulator, student exploration guide and teacher guide, which allowed pre-service teachers to solve a set of challenges of increasing complexity, thereby progressively decreasing their difficulties and contributing to an adequate integration of ER in their future teaching practices.

Abstract
The Internet revolution in 1990, followed by the data-driven and information revolution, has transformed the world as we know it. Nowadays, what seam to be 10 to 20 years ago, a science fiction idea (i.e., machines dominating the world) is seen as possible. This revolution also brought a need for new regulatory practices where user trust and artificial Intelligence (AI) discourse has a central role. This work aims to clarify some misconceptions about user trust in AI discourse and fight the tendency to design vulnerable interactions that lead to further breaches of trust, both real and perceived. Findings illustrate the lack of clarity in understanding user trust and its effects on computer science, especially in measuring user trust characteristics. It argues for clarifying those notions to avoid possible trust gaps and misinterpretations in AI adoption and appropriation.

Abstract
There are several educational software (ES) used in the classroom environment for the teaching and learning of geometric contents that are part of the Portuguese basic education mathematics program. There are studies that show that the use of this type of artifact has a fundamental role in the behavior of students, raising, among other aspects, a greater motivation for learning mathematics. The aim of this work is to explore and describe implications for the behavior and learning of students in the 7th grade of Portuguese basic education, in face of a pedagogical practice that involves carrying out tasks using ES Plickers, in the theme similarities of the domain geometry and measurement, throughout intervention carried out. The adopted methodology presents characteristics of a quasi-experimental study. The participants were 61 students from three classes of a school in the north of Portugal, followed during eight consecutive classes. A set of tasks using Plickers, tests and a questionnaire survey were used as instruments for data collection. The results point to positive increments, at a behavioral level, as well as in the evolution of learning, in view of the use of this methodology in the classroom.

Abstract
Virtual reality (VR) technologies have been evolving in recent decades, allowing simulating real-life situations in controlled and safe virtual environments, where they reveal increasingly realistic details. There is an increase in the number of publications on virtual reality interventions in different areas, especially in Education, particularly in interventions with children diagnosed with Autism Spectrum Disorders (ASD). The lack of social skills prevents these children diagnosed with ASD to respond appropriately and adapt to the most diverse daily social situations. On this basis, VR has revealed a set of evidences that present promising results and show great acceptance among the diversified population with ASD. In order to understand how VR may contribute to the improvement of skills, allowing their inclusion, we conducted a systematic review of the literature. We present considerations on the selected studies, identifying the main gaps and pointing out possible directions for future research. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
To tackle wildfires and improve forest biomass management, cost effective and reliable mowing and pruning robots are required. However, the development of visual perception systems for forestry robotics needs to be researched and explored to achieve safe solutions. This paper presents two main contributions: an annotated dataset and a benchmark between edge-computing hardware and deep learning models. The dataset is composed by nearly 5,400 annotated images. This dataset enabled to train nine object detectors: four SSD MobileNets, one EfficientDet, three YOLO-based detectors and YOLOR. These detectors were deployed and tested on three edge-computing hardware (TPU, CPU and GPU), and evaluated in terms of detection precision and inference time. The results showed that YOLOR was the best trunk detector achieving nearly 90% F1 score and an inference average time of 13.7ms on GPU. This work will favour the development of advanced vision perception systems for robotics in forestry operations.