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Utilizing Learning Analytics: Exploring the Success of

Student Course Achievement on Graduation

– ALS Teaching Institute 2016

Greenville, NC

Jared Allsop, Lecturer

Rasul Mowatt, Associate Professor

Sarah Young, Associate Professor

Julie Knapp, Lecturer

Dohyun Lee, Doctoral Student

Department of Recreation, Park, and Tourism Studies

Indiana University

Bloomington, IN

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Download the PowerPoint Slides

Utilizing Learning Analytics:

Exploring the Success of

Student Course Achievement

on Graduation

http://tinyurl.com/mnfbop2

+Ice Breaker

Yellow

Orange

Blue

Purple

Pink

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1. The Learning Analytics Project

2. Interactive Demonstration on

Campus-Wide Learning Analytics

Project

Two Part Presentation

+The Learning Analytics

ProjectDefinition, Background, and the Study

+IU faculty use learning analytics to

further student achievement & success

+Student Learning Analytics

Fellows Program

+What is Learning Analytics?

Learning Analytics is the study of students as learners

through a process of systematic collection, exploration, and

analysis of data describing students, their objectives, and

outcomes.

Learning Analytics is a way to understand and optimize

learning in environments that learners learn.

Learning Analytics, when coupled with data mining grants

those involved in instruction and curriculum development an

opportunity to develop new tools and apply those tools to

patterns in learning.

+Background of Study

Leisure Studies and/or Parks and Recreation curricula across

the United States are focused on the production of a student

that can:

Demonstrate entry-level knowledge,

Design services that facilitate human experiences and embrace

cultural dimensions of diversity,

Day-to-day operations and strategic planning, and,

Show the potential to succeed as a professional at a supervisory

level.

With this in mind, we typically introductory or foundation

courses designed to prepare students for the major and field.

+Background of Study, Cont’d

Two courses vital to the education of all RPTS majors are SPH-R 110 (Foundations of Leisure and Public Health in Modern Society), and SPH-R 142 (Living Well). Both courses serve as pre-requisites for students choosing majors in RPTS as well as serving as Social and Historical Studies general education courses for students across the IUB campus.

In SPH-R 110, students learn leisure’s relational importance to the public health of individuals, groups and communities by studying its social, behavioral, psychological, historical, philosophical, economic, anthropological, and geographical foundations.

In SPH-R 142, students’ view of living well and public health by actively pursuing healthy lifestyles is studied and broadened in an effort to help students achieve balance in health, physical activity, and leisure pursuits.

+Research Objectives

With this in mind, the following are the research questions for

the proposed interdisciplinary study across five majors

within RPTS:

1. Does high student achievement in these courses lead

students to choose RPTS majors?

Majors within RPTS are Outdoor Recreation & Human Ecology (ORPHE),

Public, Nonprofit, & Community Recreation (PNC Rec.), Recreational

Sports (RSM), Recreational Therapy (RT), and Tourism, Hospitality and

Event Management (THEM).

2. Does students’ success in R110 and/or R142 predict

success in RPTS major coursework?

Specifically, we would identify key courses within the majors at the 100-,

200-, 300-, and 400-level.

+Research Objectives, Cont’d

With this in mind, the following are the research questions for

the proposed interdisciplinary study across five majors

within RPTS:

3. Do students enrolled in R110 and/or R142 as a general

education courses achieve successful and timely

graduation rates?

In relationship to Degree Mapping, credit hour degree requirements,

and in regards to interdisciplinary programs, the information that could

be gathered from enrollment management and advising notifications.

+Summary of Study

The study subjects were 3,032 students who took SPH-R 110 or SPH-R 142 between Fall 2010 and Spring 2014 semesters. The data collected over the eight-semester period was obtained from the Bloomington Assessment and Research office. The data set was analyzed utilizing descriptive statistics, chi-square independence test, and binary logistic regression analysis.

To address the question of whether course enrollment led students to pursue a RPTS major, a comparison was made of students’ majors at the time of course with their majors after one year of taking either course.

Whether high achievement in these courses contributed to successful and timely graduation rates was determined by conducting a binary logistic regression using course grades as the independent variable and award of degree (i.e., failure or success) as the dependent variable.

+Results

Among the students who were still enrolled at Indiana University one year after taking one or both courses, 116 students (11%) out of 1,061 students changed their non-RPTS major to an RPTS major while only 55 students (5%) out of 1,004 students changed their RPTS major at the time of the course to a non-RPTS major.

The significance of the numerical difference between the two kinds of major changers was supported by the results of chi-square independence test with large effect size (P<.001; contingency coefficient = .641, Cramer’s V = .836).

In the results of binary logistic regression analysis, the students’ academic achievements/course grades in the two courses could be used as a predictor of their successful graduation/degree award (P<.001); academic achievements could be used to explain 19% of variance of successful graduation.

Students who had 1.0 point higher grades in SPH-R110 or SPH-R142 had 1.256 times greater possibility of successfully earning their degrees {Exp(B) = 1.256}. For example, a student with a grade of A had 1.256 times greater possibility of earning his/her degree than another student with a grade of B (i.e., 1.0 point of grade difference).

+Conclusion of Study

There was enough evidence supporting claims that:

1) enrollment in SPH-R 110 and SPH-R 142 can lead students

to choose RPTS majors, and,

2) academic achievements in the two courses can be

perceived to contribute to achievement of successful

graduation rates.

+Interactive Demonstration on

Campus-Wide Learning

Analytics Project

+Campus-Wide Learning

Analytics Project

Brought together over 50 professors, lecturers,

and graduate students.

From 17 different departments across the IUB

campus

Engaged in Interdisciplinary discussions on the

importance and role of Learning Analytics.

Created a community of Learning Analytics

Scholars

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Roundtable discussion

- Learning Analytics,

10 minutes per

question

5 GroupsRemember your

sticky note color

+Roundtable Discussions

Do you personally see any value in learning analytics? Why or why not?

Follow-up questions:

What does that value look like in your department?

What does that value look like in your school?

What does that value look like in your university?

Discussion

If you kept a Blue or Purple sticky note, stay at your table.

If you kept a Yellow, Orange or Pink sticky note, please rotate clockwise to the next table.

+Roundtable Discussions

What questions would you potentially answer using Learning Analytics?

Follow-up questions:

Why are those questions of interest to you as an educator?

How would you go about answering those questions?

Discussion

If you kept a Blue or Purple sticky note, stay at your table.

If you kept a Yellow, Orange or Pink sticky note, please rotate clockwise to the next table.

+Roundtable Discussions

How would answering those questions affect your students engagement and/or learning?

Follow-up questions: Would your teaching be any different if you had answers

to those questions? How so?

Would you view your students differently if you had answers to those questions? How so?

Discussion

If you kept a Blue or Purple sticky note, stay at your table.

If you kept a Yellow, Orange or Pink sticky note, please rotate clockwise to the next table.

+Roundtable Discussions

How would you go about implementing a

Learning Analytics program?

Follow-up questions: Where would you get the data?

What statistical procedures would you use?

Discussion

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Additional Questions?

Thank you for your time and for attending our session.

Rasul & Jared

Conclusion