Designing learning experiences for online teaching and learning
- URL: http://arxiv.org/abs/2010.15602v1
- Date: Mon, 26 Oct 2020 07:03:49 GMT
- Title: Designing learning experiences for online teaching and learning
- Authors: Nachamma Sockalingam and Junhua Liu
- Abstract summary: SUTD adopts various student-centric teaching and learning teaching methods and approaches.
This means that our graduate/under instructors have to be ready to teach using these student student-centric teaching and learning pedagogies.
I share my experiences of redesigning this teaching course that is typically conducted face-to-face to a synchronous online course.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Teaching is about constantly innovating strategies, ways and means to engage
diverse students in active and meaningful learning. In line with this, SUTD
adopts various student-centric teaching and learning teaching methods and
approaches. This means that our graduate/undergraduate instructors have to be
ready to teach using these student student-centric teaching and learning
pedagogies. In this article, I share my experiences of redesigning this
teaching course that is typically conducted face-to-face to a synchronous
online course and also invite one of the participant in this course to reflect
on his experience as a student.
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) - Multimodal Classification of Teaching Activities from University Lecture
Recordings [0.9790236766474201]
We present a multimodal classification algorithm that identifies the type of activity that is being carried out at any time of the lesson.
Some academic activities are more easily identifiable with the audio signal while resorting to the text transcription is needed to identify others.
arXiv Detail & Related papers (2023-12-24T08:33:30Z) - Iterative Teacher-Aware Learning [136.05341445369265]
In human pedagogy, teachers and students can interact adaptively to maximize communication efficiency.
We propose a gradient optimization based teacher-aware learner who can incorporate teacher's cooperative intention into the likelihood function.
arXiv Detail & Related papers (2021-10-01T00:27:47Z) - 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) - Distribution Matching for Machine Teaching [64.39292542263286]
Machine teaching is an inverse problem of machine learning that aims at steering the student learner towards its target hypothesis.
Previous studies on machine teaching focused on balancing the teaching risk and cost to find those best teaching examples.
This paper presents a distribution matching-based machine teaching strategy.
arXiv Detail & Related papers (2021-05-06T09:32:57Z) - The Online Pivot: Lessons Learned from Teaching a Text and Data Mining
Course in Lockdown, Enhancing online Teaching with Pair Programming and
Digital Badges [1.477454374243818]
We describe the course, how we adapted it over the two pilot runs and what teaching techniques we used to improve students' learning and community building online.
We discuss the lessons learned and promote the use of innovative teaching techniques applied to the digital such as digital badges and pair programming in break-out rooms for teaching Natural Language Processing courses to beginners and students with different backgrounds.
arXiv Detail & Related papers (2021-05-03T09:38:26Z) - 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) - Interaction-limited Inverse Reinforcement Learning [50.201765937436654]
We present two different training strategies: Curriculum Inverse Reinforcement Learning (CIRL) covering the teacher's perspective, and Self-Paced Inverse Reinforcement Learning (SPIRL) focusing on the learner's perspective.
Using experiments in simulations and experiments with a real robot learning a task from a human demonstrator, we show that our training strategies can allow a faster training than a random teacher for CIRL and than a batch learner for SPIRL.
arXiv Detail & Related papers (2020-07-01T12:31:52Z) - 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) - ClassCode: An Interactive Teaching and Learning Environment for
Programming Education in Classrooms [7.156054045963555]
We present ClassCode, a web-based environment tailored to programming education in classrooms.
Students can take online tutorials prepared by instructors at their own pace. They can then deepen their understandings by performing interactive coding exercises interleaved within tutorials.
ClassCode tracks all interactions by each student, and summarizes them to instructors. This serves as a progress report, facilitating instructors to provide additional explanations in-situ or revise course materials.
arXiv Detail & Related papers (2020-01-22T18:28:16Z)
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.