Financial incentives or app-based support: improving academic progress through a communication intervention

Last registered on June 10, 2026

Pre-Trial

Trial Information

General Information

Title
Financial incentives or app-based support: improving academic progress through a communication intervention
RCT ID
AEARCTR-0017674
Initial registration date
January 17, 2026

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
January 22, 2026, 7:02 AM EST

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

Last updated
June 10, 2026, 3:30 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

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Primary Investigator

Affiliation
NIFU

Other Primary Investigator(s)

PI Affiliation

Additional Trial Information

Status
In development
Start date
2026-01-19
End date
2026-06-19
Secondary IDs
This trial builds on the pilot intervention: Financial incentives, commitment and study planning: improving academic progress through a communication intervention. AEARCTR-0015515
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Many students struggle to achieve their intended academic progress, often opting to
withdraw from courses, miss exams or fail to pass them. Research highlights that young and inexperienced decision-makers face numerous psychological and behavioral barriers that hinder goal attainment. In this project, we test three interventions, developed in collaboration with the Norwegian State Educational Loan Fund (SELF), to examine whether targeted communication can support students in adhering to their academic plans. The first two interventions test the effect of information about financial consequences of credit completion / lack of credit completion. The third intervention tests the effect of offering a study success program targeting psychological and behavioral barriers to credit completion. We estimate effects on grades, credits and the tendency to fail/miss an exam. Outcomes will be captured both using administrative records and through an online survey at the end of the spring semester.
External Link(s)

Registration Citation

Citation
Fidjeland, Andreas, Simone Häckl-Schermer and Siv-Elisabeth Skjelbred. 2026. "Financial incentives or app-based support: improving academic progress through a communication intervention." AEA RCT Registry. June 10. https://doi.org/10.1257/rct.17674-2.0
Experimental Details

Interventions

Intervention(s)
Second semester students from Norwegian higher education institutions receive an email from SELF with either
1) a gain-framed message highlighting the incentives in the student financing system for credit completion,
2) a loss-framed version of the same information or
3) an invitation to participate in a study success program delivered through a web application.
The control group is not contacted. While treatments 1) and 2) are delivered in April, treatment 3 starts in January.

Revision June 2026:
Due to low take up of the Study Success program, we decided to revise the treatment protocol for treatment 3 and add a fourth treatment arm.
Revised 3) In addition to the invitation to participate in the Study Sucess program sent in January, students also received the loss email (T2) together with a link information video from the Study Sucess program in April.

4) A loss-framed message highlighting the incentives in the student financing system combined with two information video from the Study Success program.

The e-mails of the revised treatment 3 and the new treatment 4 are delivered in April parallell to treatment 1 and 2.
Intervention Start Date
2026-01-19
Intervention End Date
2026-06-19

Primary Outcomes

Primary Outcomes (end points)
We consider the following set of outcomes at the end of the second semester:
(1) Three separate measures of academic performance:
- Administrative records on completed credits,
- Missed exams and
- grade average

(2) Two survey measures on academic stress.
- Perceived stress scale (Cohen & Williamson (1988)
- Academic stress scale (Murberg, T. A., & Bru, E. 2004, Rege et al. 2025)
Primary Outcomes (explanation)
Completed credits are based on the institutions reporting to the Norwegian State Educational Loan Fund. All Norwegian higher education institutions are obliged to report this and there is a uniform system for the reporting across institutions. The Norwegian State Educational Loan fund convert student loans to grants based on the number of credits completed and thus this is considered a reliable source of information. Students who do not have any credits registered are assumed to not have completed any courses that semester and will be coded as zero.

Information about exam participation and performance is obtained from the exam records of the Norwegian Directorate of Higher Education. Observations are at the exam level, but we aggregate them to individual-semester level.

Missed exams are measured by the number of exams the student was registered for, but for which the student did not meet. Students can sign off the course two to three weeks before the exam, and if they do so they will not be registered as not met.

The performance on the exam is captured by the student’s grade. Norwegian higher education use one of two grading schemes. (1)Letter grades between A and F, where A is the highest grade, E is the lowest passing grade, and F is failed. These grades are transformed to the numbers 5 (A) to 0 (F) before computing the grade average. (2) Pass/fail. This latter grade scale applied to about 19 percent of the exam observations in the pilot study. Grade average is computed as the average grade of exams with a letter grade, and exams with Pass/fail are set to missing. Passed courses are captured by completed credits.

Academic stress:
The measures for academic stress is based on Murberg and Bru (2004) and Rege et al. (2025) and the perceived stress scale (Cohen & Williamson (1988)).

Exact question wording in the survey will be uploaded as an attachment to this pre-analysis plan prior to data collection. The items within each survey measure will be aggregated by taking their unweighted averages.

Secondary Outcomes

Secondary Outcomes (end points)
Based on survey measures:
Study behaviour:
(1) Self-reported hours spent on study activities (self-study and lectures) per week
(2) Self-reported planning, commitment and preparedness (Delavande, 2022)
(3) Use of study strategies and division of self-study time across strategies (Delavande, 2022)

Mindset
(4) Stress mindset (Yeager et al, 2022)
(5) Growth mindset (Belief that ability grows with effort from Gaumer, Erickson & Nooan, 2016)

Financial incentives awareness
(6) Financial incentives as motivational factor during the semester and knowledge about the role of credits for grant acquisition) (researcher developed)

Revision:
Outcomes for study behaviour 2 and 3 were altered to fit with the new video treatments. The outcomes are now:
(2) Self-reported preparedness (single item question)
(3) Use of study strategies (self-developed)
Secondary Outcomes (explanation)
The exact survey items will be uploaded as an attachment to this pre-analysis plan prior to data collection.

Experimental Design

Experimental Design
We conduct a person randomized RCT with around 25 000 first year students at Norwegian higher education institutions in the spring semester 2026. These students receive an email from the Norwegian Student Loan Fund. Depending on the treatment students receive information about the incentive structure they are facing when having a student loan or receive an invitation to participate in an online study success program, providing them with information on how to study more effectively and handle stress better. Students in the control group are not contacted. We observe administrative outcomes at the end of the semester and also collect survey outcomes on stress.
Experimental Design Details
Not available
Randomization Method
Conducted by the National Student educational Loan fund
Randomization Unit
student
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Approx. 25000 students
Sample size: planned number of observations
Approx. 25000 students
Sample size (or number of clusters) by treatment arms
Original:
T1: 4000
T2: 4000
T3: 6000+1000 in test launch
T3b: 6000

Revision:
T3-stress: 4000
T3-learning: 4000
T4: 5000 (test launch group included)

Control group (T0): 5797 (remainder of population)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We conduct power analysis using optimal design software aiming for a power of 80% and a false discovery rate (alpha) of 5%. For H1, we compare the pooled T1 & T2 (N = 8000) to the control group (N=4000). This sample gives us a MDES of 0.06 standard deviations after correcting for the imbalanced group size. For H2, we compare the pooled T3 (N = 13 000) to the control group (N=4000). This sample gives us a MDES of 0.05 standard deviations after correcting for the imbalanced group size. For H3, we compare the T1 (N = 4 000) to the control T2 (N=4000). This sample gives us a MDES of 0.064 standard deviations. For H4, we compare the T3a (N = 7 000) to the control T3b (N=6000). This sample gives us a MDES of 0.05 standard deviations. For H5, we compare the pooled T1 & T2 (N = 8000) to the pooled T3 (N=13 000). This sample gives us a MDES of 0.04 standard deviations after correcting for the imbalanced group size. For the survey outcomes, we, conservatively, expect a response rate of 10%. Adjusting the sample size accordingly, assuming equal participation accross treatments leads to the following MDES using the comparisons outlined above. For H1, we compare the pooled T1 & T2 (N = 800) to the control group (N=400). This sample gives us a MDES of 0.19 standard deviations after correcting for the imbalanced group size. For H2, we compare the pooled T3 (N = 1 300) to the control group (N=400). This sample gives us a MDES of 0.16 standard deviations after correcting for the imbalanced group size. For H3, we compare the T1 (N = 400) to the control T2 (N=400). This sample gives us a MDES of 0.20 standard deviations. For H4, we compare the T3a (N = 700) to the control T3b (N=600). This sample gives us a MDES of 0.16 standard deviations. For H5, we compare the pooled T1 & T2 (N = 800) to the pooled T3 (N=1300). This sample gives us a MDES of 0.13 standard deviations after correcting for the imbalanced group size. We expect to improve power with the addition of control variables Revision June 2026: Outcomes registry data: H4 is removed. Sample size numbers and MDE in H2 and H5 are updated to account for the lower sample size in T3. And power calculations for H6 and H7 are added. For H2, we compare T3 (N = 8 000) to the control group (N = 5797). This sample gives us a MDES of 0.05 standard deviations after correcting for the imbalanced group size. For H5, we compare the pooled T1 & T2 (N = 8000) to T3 (N = 8 000). This sample gives us a MDES of 0.05 standard deviations after correcting for the imbalanced group size. For H6, we compare T4 (N = 5 000) to the control (N = 5797). This sample gives us a MDES of 0.06 standard deviations. For H7, we compare T4 (N = 5 000) to T2 (N = 4 000). This sample gives us a MDES of 0.06 standard deviations. Survey outcomes: For H2, we compare T3 (N = 800) to the control group (N = 579). This sample gives us a MDES of 0.15 standard deviations after correcting for the imbalanced group size. For H5, we compare the pooled T1 & T2 (N = 800) to T3 (N = 900). This sample gives us a MDES of 0.14 standard deviations after correcting for the imbalanced group size. For H6, we compare T4 (N = 500) to the control (N = 579). This sample gives us a MDES of 0.17 standard deviations. For H7, we compare T4 (N = 500) to T2 (N = 400). This sample gives us a MDES of 0.19 standard deviations.
Supporting Documents and Materials

Documents

Document Name
Codebook
Document Type
survey_instrument
Document Description
The document contains the codebook with survey items in the original language (norwegian).
File
Codebook

MD5: aa50f87cb69689f1e96f1f7ed426eb7b

SHA1: bdfa06f5b27e42c016a5723a76d0ad3c3d4863d9

Uploaded At: June 10, 2026

IRB

Institutional Review Boards (IRBs)

IRB Name
HHUiS-IRB
IRB Approval Date
2025-12-08
IRB Approval Number
HHUiS-IRB-2025-005