Using Student Data to Advance the University's Teaching Mission - - PowerPoint PPT Presentation

Using Student Data to Advance the University's Teaching Mission

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KEVIN GUSKIEWICZ

Dean of the College of Arts and Sciences

KELLY HOGAN

Associate Dean of Instructional Innovation Teaching Associate Professor of Biology

Using data t to track ck s student o

• utcomes: a

a case s study in transitioning t to h high s struct cture a act ctive learning STEM cl classes

4 DEPARTMENTS

(BIOLOGY, CHEMISTRY, PHYSICS and MATH)

12 GATEWAY COURSES TRANSFORMED

25FACULTY APPRENTICES IN SIX SEMESTERS

>6,000 STUDENTS PER YEAR Improved Learning…

45FACULTY IN LEARNING COMMUNITIES

New tools needed PRACTICE AND FEEDBACK LISTENING TO CONTENT

Use a new innovation

“WHAT BARRIERS EXIST?” TIME TO DEVELOP THE COURSE. KNOWLEDGE ABOUT PEDAGOGY SUPPORT FROM A GROUP OF COLLEAGUES

Learn about innovation Convinced of value of innovation Decide to try the innovation

Stages of Innovation Process:

• 1. MENTOR-APPRENTICE

RELATIONSHIPS

• 2. FACULTY LEARNING

COMMUNITIES TIME (COURSE RELEASE) KNOWLEDGE/PRACTICE WITH PEDAGOGY SUPPORT FROM COLLEAGUES DURING CULTURAL SHIFT

INTERVENTION:

Before class During class After class

Readings, videos,

• nline homework,
• nline discussions

problem solving, individual work, peer instruction, polling/clickers, designing experiments, etc problem sets,

• nline quizzes

DESIRED OUTCOME FOR PEDAGOGY:

High Structure Active Learning

Organic Chemistry I. Nearly identical final exams given.

CHEMISTRY: EVIDENCE THAT INCREASING STRUCTURE IMPROVES PERFORMANCE FOR ALL

M.T. Crimmins and B. Mdkiff J. Chem. Educ., 2017, 94 (4), pp 429–438 Additionally, D/F rates dropped from 18% to 9.5% for all students

PHYSICS: Increasing structure improves learning of specific concepts

Traditional structure Traditional structure + Some Active Learning Lecture/Studio with Life Science Focus D.P. Smith et al. American Journal of Physics 86, 862 (2018)

Preliminary f findings acr cross p project ct:

13 13% increase in normalized learning

gains with high structure, active learning compared to instructor centered design

(data from over 14,000 student measurements)

PHOTO CREDIT: KRISTEN CHAVEZ

Have the pedagogical/curricular changes impacted different student groups?

PHOTO CREDIT: KRISTEN CHAVEZ

Biology: Some student groups disproportionately benefit from increased structure

3.2 - 3.7 % increase 6.1 % increase 6.3 % increase

All students First generation students Black students

Eddy, S. L.; Hogan, K. A. CBE Life Sci. Ed. 2014, 13, 453-468 Failure rates dropped by 40%.

Those results required

• btaining data from

institutional data requests…

What if we all had a way to see data for our own classes routinely?

Change in Grade Distribution for First Generation, Pell-Eligible Students in One Redesigned Course (Biol 202)

10 20 30 40 50 60

Fall 2012 Fall 2016

A B C D F W 77% successful 82 % successful

n=22 n=27

percent of students

Data retrieved from MCAD

My Course Analytics Data (MCAD)

Data are available from Fall 2010 to the most recent semester during which the course was taught and completed. Example data from the dashboard show the percent of students in different demographic

• categories. Hovering over the bars will give the percentages and total number in each subgroup.

Learn more: https://cfe.unc.edu/mcad/

My Course Analytics Data (MCAD)

Example data. Dashboard users customize their queries to examine individual courses in specific semesters or to combine multiple semesters.

A A B B C C D D

Pell recipient Non-Pell recipient

A PROFESSOR’S PERSPECTIVE

MARC COHEN

ASSISTANT PROFESSOR ENGLISH AND COMPARATIVE LITERATURE

Underrepresented minority Non- Underrepresented minority

A B C A B

Female Male

A B C B

First generation Non-First generation

A B A B C

MCAD IN THE CLASSROOM – AND IN THE CHAIR’S OFFICE

PATRICK CONWAY CFE WORKSHOP 2 NOVEMBER 2018

PEDAGOGICAL PRINCIPLE

Students come to the classroom with preconceptions about how the world works. If their initial understanding is not engaged, they may fail to grasp the new concepts and information that are taught.

National Research Council: How People Learn. Washington, DC: National Academy Press, 2000, pp 14-15

MCAD’S ROLE

• In large classes, difficult to identify those individual

preconceptions.

• One partial solution:
• Look to the success of various groups in previous years, and
• Adjust the class content to reach those with less success in those

years.

EXAMPLE: WOMEN IN ECONOMICS

• A national trend: fewer women majoring in Economics
• 2013: look “by hand” at grades I gave in Econ 101. Women

seemed to have somewhat lower grades on average.

• Response:
• Changing examples and applications – more music/design/advertising.
• Identifying/highlighting successful women in economics.
• Greater emphasis on engaging women in the classroom.
• By 2015: closer to parity.
• Today: with MCAD, such queries are done in seconds.

PROBLEMS

• Loose link between pedagogical goal and available

categories.

• Only available for completed courses. “Formative

assessment” would be very helpful.

FROM THE CHAIR’S PERSPECTIVE

• NB: Chairs don’t have access to other faculty’s data at present.
• In courses where we have challenges – differing success rates –

we can quantify these differences.

• Over time, we can experiment with teaching techniques as a

department to bring success rates in line with our high expectations for our students.

• Example: Eddy, Sarah L., and Kelly A. Hogan. 2014. “Getting Under

the Hood: How and for Whom Does Increasing Course Structure Work?” CBE-Life Sciences Education 13 (3): 453–68.

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