No Arabic abstract
The COVID-19 pandemic significantly disrupted the educational sector. Faced with this life-threatening pandemic, educators had to swiftly pivot to an alternate form of course delivery without severely impacting the quality of the educational experience. Following the transition to online learning, educators had to grapple with a host of challenges. With interrupted face-to-face delivery, limited access to state-of-the-art labs, barriers with educational technologies, challenges of academic integrity, and obstacles with remote teamwork and student participation, creative solutions were urgently needed. In this chapter, we provide a rationale for a variety of course delivery models at different stages of the pandemic and highlight the approaches we took to overcome some of the pressing challenges of remote education. We also discuss how we ensured that hands-on learning remains an integral part of engineering curricula, and we argue that some of the applied changes during the pandemic will likely serve as a catalyst for modernizing education.
Due to the COVID-19 pandemic, there was an urgent need to move to online teaching and develop innovations to guarantee the Student Learning Outcomes (SLOs) are being fulfilled. The contributions of this paper are two-fold: the effects of an experimented teaching strategy, i.e. multi-course project-based learning (MPL) approach, are presented followed with online assessment techniques investigation for senior level electrical engineering (EE) courses at Qatar University. The course project of the senior course was designed in such a way that it helps in simultaneously attaining the objectives of the senior and capstone courses, that the students were taking at the same time. It is known that the MPL approach enhances the critical thinking capacity of students which is also a major outcome of Education for Sustainable Development (ESD). The developed project ensures the fulfillment of a series of SLOs, that are concentrated on soft engineering and project management skills. The difficulties of adopting the MPL method for the senior level courses are in aligning the project towards fulfilling the learning outcomes of every individual course. The study also provides the students feedback on online assessment techniques incorporated with the MPL, due to online teaching during COVID-19 pandemic. In order to provide a benchmark and to highlight the obtained results, the innovative teaching approaches were compared to conventional methods taught on the same senior course in a previous semester. Based on the feedback from teachers and students from previously conducted case study it was believed that the MPL approach would support the students. With the statistical analysis (Chi-square, two-tailed T statistics and hypothesis testing using z-test) it can be concluded that the MPL and online assessment actually help to achieve better attainment of the SLOs, even during a pandemic situation.
This short papers discusses the issues of teaching cloud computing from a software engineering rather than a business perspective. It discusses what topics might be covered in a senior course on cloud software engineering.
The COVID-19 pandemic has transformed mobile health applications and telemedicine from nice to have tools into essential healthcare infrastructure. This need is particularly great for the elderly who, due to their greater risk for infection, may avoid medical facilities or be required to self-isolate. These are also the very groups at highest risk for cognitive decline. For example, during the COVID-19 pandemic artificially intelligent conversational agents were employed by hospitals and government agencies (such as the CDC) to field queries from patients about symptoms and treatments. Digital health tools also proved invaluable to provide neuropsychiatric and psychological self-help to people isolated at home or in retirement centers and nursing homes.
Automatic analysis of teacher and student interactions could be very important to improve the quality of teaching and student engagement. However, despite some recent progress in utilizing multimodal data for teaching and learning analytics, a thorough analysis of a rich multimodal dataset coming for a complex real learning environment has yet to be done. To bridge this gap, we present a large-scale MUlti-modal Teaching and Learning Analytics (MUTLA) dataset. This dataset includes time-synchronized multimodal data records of students (learning logs, videos, EEG brainwaves) as they work in various subjects from Squirrel AI Learning System (SAIL) to solve problems of varying difficulty levels. The dataset resources include user records from the learner records store of SAIL, brainwave data collected by EEG headset devices, and video data captured by web cameras while students worked in the SAIL products. Our hope is that by analyzing real-world student learning activities, facial expressions, and brainwave patterns, researchers can better predict engagement, which can then be used to improve adaptive learning selection and student learning outcomes. An additional goal is to provide a dataset gathered from real-world educational activities versus those from controlled lab environments to benefit the educational learning community.
We present ReproducedPapers.org: an open online repository for teaching and structuring machine learning reproducibility. We evaluate doing a reproduction project among students and the added value of an online reproduction repository among AI researchers. We use anonymous self-assessment surveys and obtained 144 responses. Results suggest that students who do a reproduction project place more value on scientific reproductions and become more critical thinkers. Students and AI researchers agree that our online reproduction repository is valuable.