There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

The power of feedback.

Videos are a widely-used kind of resource for online learning. This paper presents an empirical study of how video production decisions affect student engagement in online educational videos. To our knowledge, ours is the largest-scale study of video engagement to date, using data from 6.9 million video watching sessions across four courses on the edX MOOC platform. We measure engagement by how long students are watching each video, and whether they attempt to answer post-video assessment problems.Our main findings are that shorter videos are much more engaging, that informal talking-head videos are more engaging, that Khan-style tablet drawings are more engaging, that even high-quality pre-recorded classroom lectures might not make for engaging online videos, and that students engage differently with lecture and tutorial videos.Based upon these quantitative findings and qualitative insights from interviews with edX staff, we developed a set of recommendations to help instructors and video producers take better advantage of the online video format. Finally, to enable researchers to reproduce and build upon our findings, we have made our anonymized video watching data set and analysis scripts public. To our knowledge, ours is one of the first public data sets on MOOC resource usage.

http://up.csail.mit.edu/other-pubs/las2014-pguo-engagement.pdf

How video production affects student engagement: an empirical study of MOOC videos

The last 20 years have seen ever-increasing research activity in the field of human activity recognition. With activity recognition having considerably matured, so has the number of challenges in designing, implementing, and evaluating activity recognition systems. This tutorial aims to provide a comprehensive hands-on introduction for newcomers to the field of human activity recognition. It specifically focuses on activity recognition using on-body inertial sensors. We first discuss the key research challenges that human activity recognition shares with general pattern recognition and identify those challenges that are specific to human activity recognition. We then describe the concept of an Activity Recognition Chain (ARC) as a general-purpose framework for designing and evaluating activity recognition systems. We detail each component of the framework, provide references to related research, and introduce the best practice methods developed by the activity recognition research community. We conclude with the educational example problem of recognizing different hand gestures from inertial sensors attached to the upper and lower arm. We illustrate how each component of this framework can be implemented for this specific activity recognition problem and demonstrate how different implementations compare and how they impact overall recognition performance.

A tutorial on human activity recognition using body-worn inertial sensors

A Tutorial on Human Activity Recognition Using Body-Worn

Computational design tools can automatically generate large quantities of viable designs for a given design problem. This raises the challenge of how to enable designers to efficiently and effectively evaluate and select preferred designs from a large set of alternatives. In GeneratiVR, we present two novel interaction techniques to address this challenge, by leveraging Virtual Reality for rich, spatial user input. With these interaction methods, users can directly manipulate designs or demonstrate desired design functionality. The interactions allow users to rapidly filter through an expansive design space to specify or find their preferred designs.

GeneratiVR: Spatial Interactions in Virtual Reality to Explore Generative Design Spaces

Expert feedback is valuable but hard to obtain for many designers. Online crowds can provide a source of fast and affordable feedback, but workers may lack relevant domain knowledge and experience. Can expert rubrics address this issue and help novices provide expert-level feedback? To evaluate this, we conducted a 2x2 experiment in which student designers received feedback on a visual design artifact from both experts and novices, who produced feedback using either an expert rubric or no rubric. We find that rubrics help novice workers provide feedback that is rated just as valuable as expert feedback. A follow-up analysis on writing style showed that student designers find feedback most helpful when it is emotional, positive, and specific, and that providing a rubric improves the application of these characteristics in feedback. The analysis also finds that expertise only affects style by increasing critique length, but an informal evaluation suggests that experts may instead produce value through providing clearer justifications. ACM Classification

Worker Expertise and Expert Rubrics in Crowdsourced Design Critique

In co-located collaborative design meetings, product designers share and exchange independently gathered or generated information with their team in order to reach a shared understanding of the design space. This allows the team to make well-informed, coordinated decisions throughout the design process. The Prodigy Project seeks to develop better tools for product designers to exchange information during shared problem and solution framing tasks. We developed two prototypes to explore the collaborative behavior of designers in collocated collaborative meetings. These prototypes allow team members to synchronously share information from a variety of sources with each other and a shared display while maintaining the natural flow of team meetings. The major contributions we make are exploring further how designers in the same physical space negotiate for attention to their devices, and how software collaboration tools can enhance existing work processes.

Designing Software to Facilitate Shared Understanding in Collaborative Design Teams

A revolution is occurring in terms of how pervasive computing hardware is designed, prototyped, and manufactured. A broad set of researchers and users now have access to a host of digital fabrication tools and techniques that empower them to create new devices and realize new concepts more quickly, cheaply, and easily. This special issue brings together four articles that describe recent research in this space of printing and fabrication for pervasive computing.

A revolution in the making [Guest editors' introduction]

OROBORO is a novel collaborative controller which focuses on musical performance as social experience by exploring synchronized actions of two musicians operating a single instrument. Each performer uses two paddle mechanisms – one for hand orientation sensing and one for servo-motor directed feedback. We introduce a haptic mirror in which the movement of one performer’s active hand is used to induce movement of the partner’s passive hand and vice versa. Theoretical motivation and system implementation are described.

/pdf/oroboro-a-collaborative-bi-manual-controller-with-26wm3qq8fj.pdf

Björn Hartmann

Papers

GeneratiVR: Spatial Interactions in Virtual Reality to Explore Generative Design Spaces

Worker Expertise and Expert Rubrics in Crowdsourced Design Critique

Designing Software to Facilitate Shared Understanding in Collaborative Design Teams

A revolution in the making [Guest editors' introduction]

OROBORO: A Collaborative Bi-Manual Controller with Interpersonal Haptic Feedback.