Goal-setting in a blended learning environment

Last registered on April 25, 2018

Pre-Trial

Trial Information

General Information

Title
Goal-setting in a blended learning environment
RCT ID
AEARCTR-0002928
Initial registration date
April 23, 2018

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
April 25, 2018, 2:03 PM EDT

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

Locations

Region

Primary Investigator

Affiliation
Potsdam University

Other Primary Investigator(s)

PI Affiliation
University of Duisburg-Essen

Additional Trial Information

Status
On going
Start date
2018-04-23
End date
2018-10-31
Secondary IDs
Abstract
In a randomized experiment in an introductory microeconomics course at the University of Duisburg-Essen, we will test how incorporating goal setting into the technology-assisted tutoring website affects engagement and course outcomes.
External Link(s)

Registration Citation

Citation
Amann, Erwin and Sylvi Rzepka. 2018. "Goal-setting in a blended learning environment." AEA RCT Registry. April 25. https://doi.org/10.1257/rct.2928-1.0
Former Citation
Amann, Erwin and Sylvi Rzepka. 2018. "Goal-setting in a blended learning environment." AEA RCT Registry. April 25. https://www.socialscienceregistry.org/trials/2928/history/28790
Experimental Details

Interventions

Intervention(s)
Cramming at the end of the semester to pass the exam is common practice among college students. While these learning strategies may be effective for exam performance (Kerdijk et al. 2015), they have proven ineffective for long-term retention of study material (Carpenter et al. 2012). Social psychology has shown that setting goals may help students focus and put more effort into their studying and therefore, lead to more success in university (Locke & Latham 2002). The literature on educational technological identifies goal setting interventions as promising (Escueta et al 2017), also because technology provides the opportunity to scale interventions which aim at equipping students with tools to engage in learning throughout the entire semester. The results of a randomized experiment by Clark et al. (2017) suggest that goal setting is effective in improving student’s performance. However, the empirical evidence on how to leverage the potential of goal setting in other contexts – such as at European universities – is still scarce.

In a randomized experiment in an introductory microeconomics course at the University of Duisburg-Essen, we will test how incorporating goal setting into the technology-assisted tutoring website affects engagement and course outcomes. We intend to answer the following research questions:
• How does setting learning goals affect the participation in the online tutoring platform?
• How do treated students perform in the exam?
• In what way does the goal setting intervention shape students study intentions for the next semester?
Intervention Start Date
2018-04-23
Intervention End Date
2018-10-31

Primary Outcomes

Primary Outcomes (end points)
• Usage of e-learning platform (called JACK)
• Timing of learning
• Exam participation
• Exam performance
• Other learning activities
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
- Students in the course who enroll in Moodle, the online learning management platform used by the University of Duisburg-Essen, participate in the experiment and are randomly assigned to control and treatment group.
- In the treatment group, students will be asked to set goals for their preparation for online quizzes and will be reminded via e-mail of the goal they set to prepare for each of the online quizzes.
- As part of weekly recap questions, all students will be asked to complete the cognitive reflection test suggested by Frederick (2005).
- A questionnaire at the end of the course elicits self-control, collects socio-economic characteristics, proxies for ability and asks about learning activities students undertook during the semester.
Experimental Design Details
Randomization Method
Computer-based randomization through Moodle (among all students enrolled in Moodle).
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
NA
Sample size: planned number of observations
900
Sample size (or number of clusters) by treatment arms
450
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Based on descriptive statistics from previous semesters: With a sample size of about 900 students we would have statistical power to identify an effect of .17 SD, this corresponds to a 12% increase in JACK visits, a 17% increase in JACK questions answered and a 6% increase in points in the exam.
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials