Join us to discuss what goes on in the mind of Teaching Assistants on Monday 10th May at 2pm BST

Thinking icon via flaticon.com

Both graduate and undergraduate teaching assistants (TAs) are crucial to facilitating students learning. What goes on inside the mind of a teaching assistant? How can understanding this help us train TA’s better for the roles they play in education? Join us to discuss via a paper by Julia M. Markel and Philip Guo. [1] From the abstract:

As CS enrolments continue to grow, introductory courses are employing more undergraduate TAs. One of their main roles is performing one-on-one tutoring in the computer lab to help students understand and debug their programming assignments. What goes on in the mind of an undergraduate TA when they are helping students with programming? In this experience report, we present firsthand accounts from an undergraduate TA documenting her 36 hours of in-lab tutoring for a CS2 course, where she engaged in 69 one-on-one help sessions. This report provides a unique perspective from an undergraduate’s point-of-view rather than a faculty member’s. We summarise her experiences by constructing a four-part model of tutoring interactions: a) The tutor begins the session with an initial state of mind (e.g., their energy/focus level, perceived time pressure). b) They observe the student’s outward state upon arrival (e.g., how much they seem to care about learning). c) Using that observation, the tutor infers what might be going on inside the student’s mind. d) The combination of what goes on inside the tutor’s and student’s minds affects tutoring interactions, which progress from diagnosis to planning to an explain-code-react loop to post-resolution activities. We conclude by discussing ways that this model can be used to design scaffolding for training novice TAs and software tools to help TAs scale their efforts to larger classes.

This paper was one of nine best papers at SIGCSE 2021, there’s a video of the paper presentation on pathable.sigcse2021.org. All welcome. As usual, we’ll be meeting on zoom, see sigcse.cs.manchester.ac.uk/join-us for details.

References

  1. Markel, Julia M. and Guo, Philip (2021) Inside the Mind of a CS Undergraduate TA: A Firsthand Account of Undergraduate Peer Tutoring in Computer Labs SIGCSE ’21: Proceedings of the 52nd ACM Technical Symposium on Computer Science EducationMarch 2021 Pages 502–508 DOI: 10.1145/3408877.3432533 (open access)

Join us to discuss how video production affects student engagement Monday 3rd August at 11am

As Universities transition to online teaching during the global coronavirus pandemic, there’s increasing interest in the use of pre-recorded videos to replace traditional lectures in higher education. Join us to discuss how video production affects student engagement, based on a paper published by Philip Guo at the University of California, San Deigo (UCSD) from the Learning at Scale conference on How video production affects student engagement: an empirical study of MOOC videos. (MOOC stands for Massive Open Online Course). [1] Here is the abstract:

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.

Details of the zoom meeting will be posted on our slack workspace at uk-acm-sigsce.slack.com. If you don’t have access to the workspace, send me (Duncan Hull) an email to request an invite to join the workspace. The paper refers to several styles of video production, some examples below.

Khan style tablet drawings

The paper refers to Khan style videos, this is an example, taken from Khan Academy course on algorithms, khanacademy.org/computing/computer-science/algorithms

What is an algorithm? Video introduction to Khan Academy algorithms course by Thomas Cormen and Devin Balkcom

Talking Heads

Some examples of talking head videos:

How to frame a talking head with Tomás De Matteis

There’s more than one way to do talking head videos, see Moving to Blended Learning, Part 3: Types of Video at www.elearning.fse.manchester.ac.uk/fseta/moving-to-blended-learning-part-3-types-of-video/

Making video-friendly slides

Steve Pettifer explains how to make video-friendly slides


Lose the words! Your PowerPoint / Keynote presentation should not be a script or a handout

References

  1. Guo, Philip J.; Kim, Juho; Rubin, Rob (2014). “How video production affects student engagement: An Empirical Study of MOOC Videos “. Proceedings of the first ACM conference on Learning @ scale conference: 41–50. doi:10.1145/2556325.2566239. see also altmetric.com/details/2188041 for online attention score