Wang, Q., Quek, C., & Hu, H. (2017). Designing and Improving a Blended Synchronous Learning Environment : An Educational Design Research. International Review of Research in Open and Distributed Learning, 18(3), 99-118
Definition: blended synchronous learning has attracted much attention and it is often labelled with synchronous hybrid learning (Cain & Henriksen 2013); synchronous blended learning (Okita, 201 3 ); multi – access learning (Irvine, Code, & Richards, 2013); or simultaneous delivery of course s to on – campus and off – campus students (White et al ., 2010). Adapted from the definition given by Bower , Dalgarno, Kennedy, Lee, and Kenney (2015), blended synchronous learning in this paper is defined as a learning method that enables online students to participate in classroom learning activities simultaneously via comput er – mediated communication technologies such as video conferencing . By following this approach , on – campus students attend F2F le ssons in the physical classroom. M eanwhile, online students who are situated at multiple sites participate in the identical class room learning activities via two – way video conferencing in real time .
With regard to educational benefits , blended synchronous learning can help to establish rich teaching presence, social presence, and cognitive presence ( Garrison, Anderson, & Archer, 200 0 ; Szeto, 2015 ). A BSLE provides a mimic classroom environment (White et al. , 2010) , where teachers ’ direct instruction and facilitation can be easily carried out a nd the teaching presence is hence naturally established.
The Oregon State University Ecampus Research Unit conducted the national study in collaboration with 3Play Media. The researchers surveyed 2,124 students across 15 public and private universities throughout the United States. Of all respondents, 19 percent reported hearing difficulties, and 37 reported vision difficulties. However, only 13 percent had registered with an office of disability services, and less than 12 percent reported they require academic accommodations.
The study revealed that students find closed captions and video transcripts helpful, whether the student is deaf or hard of hearing or not.
Key findings from the study:
Almost 100 percent of survey respondents had at least one course — either face-to-face or online — that included some video content;
75 percent of students use captions as a learning aid in face-to-face and online classrooms;
98.6 percent of students who use captions say they are helpful;
71 percent of students without hearing difficulties use captions at least some of the time;
Students reference video transcripts as a learning aid 85 percent of the time;
66 percent of English-as-a-second-language (ESL) students find captions extremely or very helpful;
61 percent of students with learning disabilities find captions helpful;
More than one quarter of students were unsure about the availability of closed captions for video content in their course; and
Almost one-in-five students were unsure about the availability of video transcripts for their course.
Further details about the study and a link to the full report can be found on 3Play Media’s site.
A.D.A.M. Interactive Anatomy Online is a 3D visualization and curriculum-development tool all about the human body. Teachers can select and create assignments that allow students to manipulate 3D images of the human body.
Construct 2 Grades: 7–12 Pricing: Free, paid Concepts: Digital creation, programming and coding, game design
Construct 2 is a Web-based 2D game-creation tool for students and teachers who want to get into game design without the need to know programming languages.
the only path to developing really powerful AI would be to use this unstructured information. It’s also called unsupervised learning— you just give it data and it learns by itself what to do with it, what the structure is, what the insights are.
One of the people you work with at Google is Geoff Hinton, a pioneer of neural networks. Has his work been crucial to yours?
Sure. He had this big paper in 2006 that rejuvenated this whole area. And he introduced this idea of deep neural networks—Deep Learning. The other big thing that we have here is reinforcement learning, which we think is equally important. A lot of what Deep Mind has done so far is combining those two promising areas of research together in a really fundamental way. And that’s resulted in the Atari game player, which really is the first demonstration of an agent that goes from pixels to action, as we call it.