Hybrid teaching, which integrates traditional in-person learning based on students’ perspectives where online learning offers a flexible approach to education, combines the benefits of technology with face-to-face interactions. Moreover, teaching and learning in a hybrid way met several challenges for both teachers and learners, including technological problems, time management, communication difficulties, and assessment complexities. This systematic review investigates six main research questions: (1) What pedagogical frameworks are used in hybrid teaching and learning? (2) How can we enhance students’ engagement in hybrid teaching and learning? (3) What is the impact of technological integration on hybrid learning scenarios, both for students and teachers? (4) How do training and support measures influence the willingness and ability of university teachers to implement hybrid teaching formats? (5) How do formative assessment and feedback methods in hybrid learning environments enable teachers to effectively monitor student progress and provide tailored support? (6) How does the implementation of hybrid learning affect student learning outcomes? This study identifies the following key themes: technological integration, pedagogical innovation, faculty support, student engagement, assessment practices, and learning outcomes. Our contribution of this literature review is related to teaching and learning by showing teachers the most appropriate way to avoid the challenges encountered when teaching in a hybrid way. These include strong technology integration, innovative pedagogical strategies, strong academic development and support, active student engagement, effective assessment practices, and positive learning outcomes.

Question Answering (QA) has been an area of interest for researchers, in part motivated by the international QA evaluation forums, namely the Text REtrieval Conference (TREC), and more recently, the Cross Language Evaluation Forum (CLEF) through QA@CLEF, that since 2004 includes the Portuguese language. In these forums, a collection of written documents is provided, as well as a set of questions, which are to be answered by the participating systems. Each system is evaluated by its capacity to answer the questions, as a whole, and there are relatively few results published that focus on the performance of its different components and their influence on the overall system performance. That is the case of the Information Retrieval (IR) component, which is broadly used in QA systems. Our work concentrates on the different options of preprocessing Portuguese text before feeding it to the IR component, evaluating their impact on the IR performance in the specific context of QA, so that we can make a sustained choice of which options to choose. From this work we conclude the clear advantage of the basic preprocessing techniques: case folding and removal of punctuation marks. For the other techniques considered, stop word removal enhanced the performance of the IR system but that was not the case as far as Stemming and Lemmatization are concerned.info:eu-repo/semantics/publishedVersio

IMOOC on Climate Change: Evaluation of a Massive Open Online Learning Pilot Experience

Application execution required in cloud and fog architectures are generally heterogeneous in terms of device and application contexts. Scaling these requirements on these architectures is an optimization problem with multiple restrictions. Despite countless efforts, task scheduling in these architectures continue to present some enticing challenges that can lead us to the question how tasks are routed between different physical devices, fog nodes and cloud. In fog, due to its density and heterogeneity of devices, the scheduling is very complex and in the literature, there are still few studies that have been conducted. However, scheduling in the cloud has been widely studied. Nonetheless, many surveys address this issue from the perspective of service providers or optimize application quality of service (QoS) levels. Also, they ignore contextual information at the level of the device and end users and their user experiences. In this paper, we conducted a systematic review of the literature on the main task by: scheduling algorithms in the existing cloud and fog architecture; studying and discussing their limitations, and we explored and suggested some perspectives for improvement.