Course Relevance and Student Success

Last registered on October 05, 2022

View Trial History

Pre-Trial

Trial Information

General Information

Title

Course Relevance and Student Success

RCT ID

AEARCTR-0010094

Initial registration date

September 28, 2022

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published

October 05, 2022, 11:39 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Country

United States of America

Region

Primary Investigator

Name

Olga Stoddard

Affiliation

Brigham Young University

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Katelyn Cranney

PI Affiliation

BYU

Contact Investigator

PI Name

Emily Leslie

PI Affiliation

BYU

Contact Investigator

Additional Trial Information

Status

In development

Start date

2022-09-20

End date

2023-04-12

Keywords

Behavior, Education

Additional Keywords

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

In this study we experimentally investigate a link between students’ interests and learning. We test whether students’ performance on exam questions is causally related to whether learning is assessed through questions that align with their interests. Using the setting of a large introductory economics class at a private university in Western U.S., we elicit students' interests in the beginning of the semester using an online survey. We will then experimentally vary test questions in their relevance to these interests. Examining student performance on these test questions will allow us to assess whether student performance is affected by the degree to which test questions align with their interests.

External Link(s)

Registration Citation

Citation

Cranney, Katelyn, Emily Leslie and Olga Stoddard. 2022. "Course Relevance and Student Success." AEA RCT Registry. October 05. https://doi.org/10.1257/rct.10094-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Students will be randomly assigned to one of two test forms. Test forms will contain the same number of questions of equal difficulty levels and equal length. They will assess students’ knowledge of exactly the same concepts but some questions will vary the context in which they are asked.

Intervention Start Date

2022-09-26

Intervention End Date

2022-12-15

Primary Outcomes

Primary Outcomes (end points)

Students’ exam scores for each question and their overall exam score will be used as our main outcome measures.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

We will also collect students' basic demographic information (including gender, ethnicity/race, first-generation student status) as part of the initial survey to investigate which kinds of students benefit most from different exam questions.

Secondary Outcomes (explanation)

Experimental Design

We will elicit students' interests through a questionnaire at the beginning of the semester. Then, when students take regular class midterm and final exams, they will be randomly assigned to one of two test forms. Test forms will contain the same number of questions of equal difficulty levels and equal length. They will assess students’ knowledge of exactly the same concepts but some questions will vary the context in which they are asked. Randomization will be at the student level.

Experimental Design Details

Randomization Method

Computerized randomization

Randomization Unit

Student level

Was the treatment clustered?

Yes

Experiment Characteristics

Sample size: planned number of clusters

550 students

Sample size: planned number of observations

550 students

Sample size (or number of clusters) by treatment arms

Approximately 250 students in the treatment (questions that highly align with students' interest) and 250 students in the control (questions don't align with students' interests).

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Supporting Documents and Materials

IRB