Scholars at Work Conference

Friday, September 11, 2020
9:00 AM - 11:00 AM
Virtual

The Scholars At Work Conference allows faculty to share their passions, research, and innovations with peers and colleagues from around our institution.

The 2020 Scholar At Work Conference will be held virtually on:

September 11, 2020

9:00am-11:00am

Register today

REGISTER FOR ALL TRACK 1 SESSIONS

 

REGISTER FOR ALL TRACK 2 SESSIONS

 

9:00 am Opening Keynote

TRACK ONE

9:15am-9:45am

Presenter: Dr. Shaheen Ahmed, PhD

 

Title: Your Special Students Will Make You Special Someday

 

A special student (with learning disability) was unable to follow the MS Excel how-to’s for the Statistical Quality Control course. I started producing how-to videos to help the student. Currently, over 400 video demonstrations are watched all over the world ((http://www.theopeneducator.com/ & https://www.youtube.com/theopeneducator). In addition to the video demonstrations, a complete open-source textbook on the Design and Analysis of Experiments (DOE) has been developed, especially having the special learners in mind.

9:45am-10:15am

Presenter: Michael Hart

 

Title: Developing a low-cost big data research environment using horizontally scalable containerized virtualization infrastructure over wireless networks.


Big data presents several challenges to higher education researchers.  This presentation focuses on the benefits of containerization for researchers needing to analyze large amounts of data.  More specifically, it will model a clustered containerized environment that is customized to work between MNSU wireless access points.  This allows research environments on campus to scale horizontally.  In achieving this, the presentation will illustrate several strategies necessary for effective containerized research environments on campus. 

10:15am-10:45am

Presenter: Shane Bowyer

 

Title: Growing Agriculture without a tractor: One student at a time

 

Minnesota State Mankato is in the heart of agriculture; however, until very recently, agriculture programming has not really been seen during this campus’ 151-year history. The designation of becoming a non-grant institution in 2015 brought light to the many possibilities of creating programs around agriculture. Faculty with hidden passions started stepping forward. The agriculture community got excited. Alumni working in agriculture started saying it is about time! In this presentation, the audience will learn about how the College of Business quickly grew an agriculture program without a tractor, or even a barn!

10:45am-11:15am

Presenter: Mika Laidlaw

 

Title:  My Mentor’s Mentor: Legacy of Japanese and Japanese American Ceramics

I am a product of long chain of artists and mentors who deeply cared about what they did and what they left behind. My presentation will focus upon a group of spectacular Japanese and Japanese American artists in a field of contemporary ceramics.  I will also discuss their influence on my research and teaching. 

TRACK TWO

9:15am-9:45am

Presenter: Jeff Dennis

Title: Demi-Romantic Non-Binary Pansexual: Learning from Micro-Identities in the Classroom

About 36% of Minnesota college students identify as non-cisgender or non-heterosexual, and many are embracing gender and sexual identities other than the traditional LGBT (lesbian, gay, bisexual, transgender).  Some of these emergent identities are broadly defined (non-binary, pansexual), but most delineate precise patterns of desire, behavior, and belonging.  The proliferation of micro-identities requires professors to move far beyond the basics of inclusivity,  such as  "Don't assume that all students are heterosexual" and "Don't identify a  student's gender based on their appearance", to rethink classroom exercises, exam questions, and even subject matter (does it make sense to talk about a wage gap between men and women, when some people identify as neither?). However, micro-identities also allow professors and students a variety of learning opportunities, especially in the social sciences

9:45am-10:15am

Presenter: Dan Moen

 

Title: Generation Z and the Online Classroom

 

The next generation of students (Gen Z) enter a time of uncertainty, debt, unstable leadership.  They have lived through (as children) the great recession, terror on TV, and weather crises.  From an adaptive standpoint, social scientists believe these experiences to have shaped Gen Z students' values and perceptions as they enter our college classrooms. This interactive presentation equips educators with evidence-based practices to win at the online teaching game through employing experiential learning opportunities.  Salient research, a brief literature update, and applicable examples will be provided to spark your creative genius.  Participants are encouraged to reflect on their own online courses throughout the presentation.  Your presenter will also share their course adaptation journey from knowledge-based online courses to evidence-based learning.  Using Bloom's taxonomy of learning and other applicable theory as a guide, your presenter will outline the "step-up" and "spiderweb" learning models.  A "backward" design method is also discussed for syllabi creation.      

 

10:15-10:45 am: Break

10:45am-11:15am

Presenter: Chandu Valluri

Title: Predicting Customer Churn for Subprime Auto Loan Borrowers

This presentation specifically discusses the notion of churn. Customer churn (commonly referred to as churn) is the idea that customers can refrain from doing business with a provider by discontinuing purchases of the good or service provided by the firm (Gordini and Veglio, 2017; Tamaddoni et al., 2016; Knox and Van Oest, 2014; Sharma and Panigrahi, 2011).
The presentation will describe churn in the context of the banking world. More specifically, the author examines the determinants of used car customer auto loan churn. Using a combination of both traditional (logistic regression, linear discriminant analysis) as well as non-traditional machine learning (decision trees and random forests) supervised classification methods the study finds a clear difference between the full model and the restricted model. Furthermore, the random forest classification technique reports the strongest performance and details the most important character variables to be individual net worth. Both the explanatory and predictive power of each of the models is analyzed using multiple performance measures.

Contact

April Emanuel
Cetl@mnsu.edu