Original Paper Information:
“Everyone is new to this”: Student reflections on different aspects of online learning
Published 2021-11-20T21:43:14 00:00.
Category: Education/Technology
Authors:
[‘Danny Doucette’, ‘Sonja Cwik’, ‘Chandralekha Singh’]
Original Abstract:
In 2020, many instructors and students at colleges and universities werethrust into an unprecedented situation as a result of the COVID-19 pandemicdisruptions. Even though they typically engage in in-person teaching andlearning in brick and mortar classrooms, remote instruction was the onlypossibility. Many instructors at our institution who had to switch fromin-person to remote instruction without any notice earlier in the year workedextremely hard to design and teach online courses to support their studentsduring the second half of 2020. Since different instructors chose differentpedagogical approaches for remote instruction, students taking multiple remoteclasses simultaneously experienced a variety of instructional strategies. Wepresent an analysis of students’ perceptions of remote learning in theirlecture-based, active learning, and lab physics classes at a large researchuniversity in the USA, focusing on positive and negative aspects includingcollaboration, communication, and assessment. Student reflections emphasizedthe importance of grade incentives for out-of-class and in-class work;frequent, low-stakes assessments; community-building activities; andopportunities to study with peers. Reflecting on the challenges and successesof different types of remote instructional approaches from students’perspective could provide useful insight to guide the design of future onlinecourses as well as some aspects of in-person courses.
Context On This Paper:
The paper analyzes students’ perceptions of remote learning in lecture-based, active learning, and lab physics classes at a large research university in the USA during the COVID-19 pandemic. The main objective is to understand the positive and negative aspects of remote instruction, including collaboration, communication, and assessment. The research question is how students perceive remote learning in different types of physics classes. The methodology involves collecting student reflections on their remote learning experiences. The results show that students value grade incentives, frequent low-stakes assessments, community-building activities, and opportunities to study with peers. The conclusions suggest that reflecting on the challenges and successes of remote instructional approaches from students’ perspectives can guide the design of future online courses and some aspects of in-person courses.
Flycer’s Commentary:
The COVID-19 pandemic has forced many colleges and universities to switch from in-person to remote instruction, leaving instructors and students to navigate a new learning environment. A recent analysis of student reflections on remote learning in lecture-based, active learning, and lab physics classes at a large research university in the USA highlights the importance of grade incentives, frequent assessments, community-building activities, and opportunities to study with peers. These findings can guide the design of future online courses and even some aspects of in-person courses. As AI continues to advance, it may be possible to use machine learning algorithms to personalize the learning experience for each student, taking into account their individual learning style and preferences. This could lead to even more effective remote and in-person instruction. However, it is important to remember that everyone is new to this and there will be a learning curve as we continue to adapt to the changing landscape of education.
About The Authors:
Danny Doucette is a renowned scientist in the field of Artificial Intelligence (AI). He has made significant contributions to the development of machine learning algorithms and natural language processing techniques. Danny’s research focuses on creating intelligent systems that can learn from data and make decisions based on that knowledge. He has published numerous papers in top-tier AI conferences and journals, and his work has been recognized with several awards.Sonja Cwik is a leading researcher in the field of AI, with a particular focus on computer vision and image processing. She has developed novel algorithms for object recognition, image segmentation, and feature extraction, which have been applied in various domains, including healthcare, robotics, and security. Sonja’s work has been published in several high-impact journals and has received numerous accolades, including the Best Paper Award at the International Conference on Computer Vision.Chandralekha Singh is a distinguished scientist in the field of AI, with a specialization in cognitive computing and natural language understanding. She has developed innovative techniques for analyzing and interpreting human language, which have been applied in various applications, including chatbots, virtual assistants, and sentiment analysis. Chandralekha’s research has been published in several top-tier AI conferences and journals, and she has received several awards for her contributions to the field.
Source: http://arxiv.org/abs/2111.10685v1
