Math in Higher Ed

Accounting Professor Ann Weiss joins for a special episodediscussing how Cressey and Albrecht’s Fraud Triangle applies to education and how we as professors can make use of it to reduce cheating the right way.

Further reading and sources:

• Donald R Cressey – 1953 -- Other People’s Money: A Study in the Social Psychology of Embezzlement
• https://www.whistleblowers.org/fraud-triangle/
• 2013 -- Students Cheating Behaviors: The Influence of Fraud Triangle - Luky PatriciaWidianingsih Accounting Study Program, Universitas Pelita Harapan [email protected]

AI can solve most math problems and is only getting better, leaving many students wondering why they should even bother. We need to have the answers to those questions. This episode steps back from homework, assessments, and videos to ask the bigger questions: what do we want students to leave with? Does it depend on area of study? Finally, has the purpose of math education qualitativelychanged or do we just have more powerful tools?

Have any ideas for future episodes or thoughts about this one? I'd love to know what you think. You can contact me here.

Here are two articles I referenced in the NYT:

• Tech Workers Maxed Out Their A.I. Use. Now They’re Trying to Minimize It.
• A.I. Spending Sets a Record, With No End in Sight

I realized my current setup was producing students who could pass my class but weren't ready for the next one. AI didn't create that problem, but it did make it impossible to ignore. This episode is about rethinking assessment in face-to-face and hybrid math courses. What needs to move in-person, AI hypocrisy (if it exists), and how to do all of this without burning out.

Have any ideas for future episodes or thoughts about thisone? I'd love to know what you think. Find my contact information ⁠⁠⁠⁠here⁠⁠⁠⁠.

Are you sick of telling students the same instructions multiple times or giving a nice introduction only to have them immediately raise their hand and ask what they’re supposed to do? If so, this episode is for you. I talk about why relying on spoken instruction fails almost everyone, how to design communication that reaches students through multiple modalities, and how to give students the same flexibility when they're showing what they know.

Have any ideas for future episodes or thoughts about this one? I'd love to know what you think. Find my contact information ⁠⁠⁠here⁠⁠⁠.

We all know a huge issue in student AI use is academic dishonesty. Another issue that’s just as important is when they think they understand something just because AI gave them an answer and “it makes sense”. This episode gets into this illusion of competence, learned helplessness, and practical ways to help students engage with AI actively rather than passively. I also talk about how we can build these habits without dedicating entire class sessions to it.

Have any ideas for future episodes or thoughts about this one? I'd love to know what you think. Find my contact information ⁠⁠here⁠⁠.

AI isn't going away, and our students are already using it. In this episode we talk about how math educators can engage with AI, what it's genuinely useful for, where it falls short, and how modeling good AI habits might be the most important thing we do for our students this year.

Have any ideas for future episodes or thoughts about this one? I'd love to know what you think. Find my contact information ⁠⁠here⁠⁠.

Most math video lectures are designed to be watched passively and, as a result, students treat them that way. In this episode I talk about how we can change that: the structuring and recording of our videos and how we can teach students to actually engage with them. Plus: writing math on screen, tools, and why perfection is overrated.

Sources and further reading:

• Video Improves Learning in Higher Education: A Systematic Review - Noetel et al
• Video-based lecture engagement in a flipped classroom environment - Gutiérrez-González, Zamarron, and Royuela
• Decoding Video Logs: Unveiling Student Engagement Patterns in Lecture Capture Videos - Akçapınar, Er, and Bayazit

Have any ideas for future episodes or thoughts about this one? I'd love to know what you think. Find my contact information ⁠here⁠.

Most math homework looks the same: either an online assignment or a list of problems to drill some skills with answers included to odd problems. In this episode I break down how to design assignments that build real understanding, including how to write better problems, how to scaffold review without it feeling remedial, and how to get students thinking critically about their own answers.

Have any ideas for future episodes or thoughts about this one? I'd love to know what you think. Find my contact information ⁠here⁠.

This is the first of two episodes talking about how to make math homework more useful and covers a few questions we need to ask ourselves (what do we think the point of homework should be, should it be required, and how should it be graded) and explores the difference between facilitating learning and the memorization of facts or algorithms.

The next episode will walk through the designing of homework that accomplishes these goals.

Have any ideas for future episodes or thoughts about this one? I'd love to know what you think. Find my contact information here.