CHEER UP - Cambridge Handbook of Engineering Education Research - Updated Perspectives - Jim Pellegrino & Sean Brophy - Shared screen with speaker view
Hi All, Welcome to today's session!
Please feel free to introduce yourself here
Please post any questions in Q&A
Claudia Torres Garibay
Hello, this is Claudia Torres Garibay from Oregon Tech.
Hi Everyone - I am Nicole Ramo; an Instructional Post-doc from University of Michigan's Biomedical Engineering Department
Adrian Nat Gentry
Hi this is Nat from Purdue ENE
Joana Marques Melo
Hello! This is Joana Marques Melo from Purdue
Hi. I'm John Tingerthal from Northern Arizona University
Hi, Chris McGrail from UMass Amherst
Hello from Arkansas. Taylor Williams from Harding University. I'm also a PhD candidate at Purdue in engineering education, advised by Kerrie Douglas.
Cindy Rottmann from the University of Toronto
For anybody introducing yourselves in the chat—select “all panelists and attendees” not “all panelists"
Thanks Cindy, I was just going to mention that.
Thanks for hosting Aditya.
Great discussions so far this summer.
Hi! Marnie Jamieson University of Alberta, Hi Cindy!
Hi, Betul Bilgin from University of Illinois of Chicago (UIC)
Hi Cindy again! Hello all, I am Qin Liu, from the University of Toronto
haha…hi Marnie and Qin…the Canadians are turning out in decent numbers.
Jeff Paul here. PhD candidate from UofM.Will these slides be made available?
Hi - Lisa Romkey from the University of Toronto (Hi Qin, Marnie and Cindy!)
(University of Manitoba = UofM)
@Jeff - I'll ask Jim and Sean.
Sorry, I think I missed the why on the IRT curve; which is "more desired"?
Hi Lisa and Jeff
@Jeff My understanding is that the probability of a student getting the answer correct should be indicative of their developing knowledge. So a student who has mastered the item has a very high probability of getting the right answer and the student who just heard about it has a low probability.
@Marnie. Thanks. So the "step function" assessments are better at dividing those who have mastered it from those that are still learning.
@Jeff yes. So the intent is not to trick students - it is to better understand where they are at to help them address what they still need to learn so they can be more likely to master (and thus get the right answer). In my opinion a good exam will use questions at a variety of learning levels in different questions.
@Marnie. Interesting. So, the exam, as a whole, should have a shallow curve with good distribution. But each question should have a sharp curve.Hmm...
@Stephanie - I don't think this is from CHEER
@Jeff or you have a multiple choice question - one could give part marks for answers that are derived from different levels of understanding or competence and I think it depends on whether you are writing a formative quiz or a summative quiz.
If anyone has questions for the panelists, please try to submit them to the Q&A feature.
I love the comment that "assessments drive what students know."This is so true, and, as discussed in the paper, assessments assist learning. Even if that is not their core goal.
Kai Jun (KJ) Chew
@Jeff, I agree. because of the nature of higher ed (students have to strategize their time, and assessments are part of their deliverables), students tend to learn to assessment. I think we as instructors should consider that while designing assessments, even if they are not meant to be so originally.
Maimuna Begum Kali
Missed the beginning!! is there any way to watch the webinar later??
http://bit.do/cheerupvideos for the recordings
Recordings available at: http://bit.do/cheerupvideos
@ Nicole - Thanks
Maimuna Begum Kali
Jim's email: email@example.com
Thank you for a very interesting and relevant talk as we re-evaluate what a valid assessment looks like in a remote and online learning environments.
Thank you, Sean, Jim and Aditya!
Sean's email: firstname.lastname@example.org
This was incredibly useful. Thank you, Jim, Sean, and Aditya!
R Mishael Sedas
Thank you all!