Distance Teaching Experience of Campus-based Teachers at Times of Pandemic Confinement

• URL: http://arxiv.org/abs/2211.16280v1
• Date: Tue, 29 Nov 2022 15:09:52 GMT
• Title: Distance Teaching Experience of Campus-based Teachers at Times of Pandemic Confinement
• Authors: Abbas Cheddad and Christian Nordahl
• Abstract summary: Campus-based programs and courses have been redesigned in a timely manner. Students engagement and active participation become an issue. This study analyses these effects along with our teachers experience in the new learning environment.
• Score: 0.7056222499095848
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Amidst the outbreak of the coronavirus (COVID 19) pandemic, distance education, where the learning process is conducted online, has become the norm. Campus-based programs and courses have been redesigned in a timely manner which was a challenge for teachers not used to distance teaching. Students engagement and active participation become an issue; add to that new emerging effects associating with this set-up, such as the so called 'Zoom fatigue', which was coined recently by some authors. In realising this problem, solutions were suggested in the literature to help trigger students engagement and enhance teachers experience in online teaching. This study analyses these effects along with our teachers experience in the new learning environment and concludes by devising some recommendations. To attain the above objectives, we conducted online interviews with six of our teachers, transcribed the content of the videos and then applied the inductive research approach to assess the results.

Related papers

• Teaching Empirical Methods at Eindhoven University of Technology [55.17240664632298]
  We discuss the challenges of teaching a course on research methods. We share our lessons learned and the do's and don'ts we learned over several iterations of teaching the course.
  arXiv  Detail & Related papers  (2024-07-05T17:14:08Z)
• Pandemic Pedagogy: Evaluating Remote Education Strategies during COVID-19 [6.190511747986327]
  The COVID-19 pandemic precipitated an abrupt shift in the educational landscape, compelling universities to transition from in-person to online instruction. We present a retrospective study aimed at understanding and evaluating the remote teaching practices employed during that period. Our findings indicate that while remote teaching practices moderately influenced students' learning outcomes, they had a pronounced positive impact on student satisfaction.
  arXiv  Detail & Related papers  (2023-08-30T08:34:01Z)
• Distance Learning in Primary School During the COVID 19 Pandemic: Results of the "SMART KIDS" Experiment [0.0]
  The paper analyzes the results of the introduction of the distance learning form (DLF) using electronic educational resources (EER) and the teacher's virtual classroom in primary school. Despite the outlined problems, the quality of distance learning of primary school students during the pandemic using EER was positively and highly assessed by teachers.
  arXiv  Detail & Related papers  (2022-04-07T14:41:41Z)
• Disadvantaged students increase their academic performance through collective intelligence exposure in emergency remote learning due to COVID 19 [105.54048699217668]
  During the COVID-19 crisis, educational institutions worldwide shifted from face-to-face instruction to emergency remote teaching (ERT) modalities. We analyzed data on 7,528 undergraduate students and found that cooperative and consensus dynamics among students in discussion forums positively affect their final GPA. Using natural language processing, we show that first-year students with low academic performance during high school are exposed to more content-intensive posts in discussion forums.
  arXiv  Detail & Related papers  (2022-03-10T20:23:38Z)
• A literature survey on student feedback assessment tools and their usage in sentiment analysis [0.0]
  We evaluate the effectiveness of various in-class feedback assessment methods such as Kahoot!, Mentimeter, Padlet, and polling. We propose a sentiment analysis model for extracting the explicit suggestions from the students' qualitative feedback comments.
  arXiv  Detail & Related papers  (2021-09-09T06:56:30Z)
• The Challenges of Assessing and Evaluating the Students at Distance [77.34726150561087]
  The COVID-19 pandemic has caused a strong effect on higher education institutions with the closure of classroom teaching activities. This short essay aims to explore the challenges posed to Portuguese higher education institutions and to analyze the challenges posed to evaluation models.
  arXiv  Detail & Related papers  (2021-01-30T13:13:45Z)
• What Makes a Star Teacher? A Hierarchical BERT Model for Evaluating Teacher's Performance in Online Education [9.849385259376524]
  We conduct a systematic study to understand and effectively predict teachers' performance using the subtitles of 1,085 online courses. Based on these insights, we then propose a hierarchical course BERT model to predict teachers' performance in online education. Our proposed model can capture the hierarchical structure within each course as well as the deep semantic features extracted from the course content.
  arXiv  Detail & Related papers  (2020-12-03T01:51:20Z)
• Point Adversarial Self Mining: A Simple Method for Facial Expression Recognition [79.75964372862279]
  We propose Point Adversarial Self Mining (PASM) to improve the recognition accuracy in facial expression recognition. PASM uses a point adversarial attack method and a trained teacher network to locate the most informative position related to the target task. The adaptive learning materials generation and teacher/student update can be conducted more than one time, improving the network capability iteratively.
  arXiv  Detail & Related papers  (2020-08-26T06:39:24Z)
• Interactive Knowledge Distillation [79.12866404907506]
  We propose an InterActive Knowledge Distillation scheme to leverage the interactive teaching strategy for efficient knowledge distillation. In the distillation process, the interaction between teacher and student networks is implemented by a swapping-in operation. Experiments with typical settings of teacher-student networks demonstrate that the student networks trained by our IAKD achieve better performance than those trained by conventional knowledge distillation methods.
  arXiv  Detail & Related papers  (2020-07-03T03:22:04Z)
• Neural Multi-Task Learning for Teacher Question Detection in Online Classrooms [50.19997675066203]
  We build an end-to-end neural framework that automatically detects questions from teachers' audio recordings. By incorporating multi-task learning techniques, we are able to strengthen the understanding of semantic relations among different types of questions.
  arXiv  Detail & Related papers  (2020-05-16T02:17:04Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.