NEXTlearn - New strategies for digital learning and assessment

Last registered on November 10, 2025

Pre-Trial

Trial Information

General Information

Title
NEXTlearn - New strategies for digital learning and assessment
RCT ID
AEARCTR-0016760
Initial registration date
November 10, 2025

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
November 10, 2025, 10:25 AM EST

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

Locations

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Primary Investigator

Affiliation
University of Innsbruck

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2025-10-02
End date
2026-03-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The NEXTlearn project is a randomized controlled trial to improve learning outcomes in introductory courses for first-year undergraduate students. The intervention provides targeted learning support designed to enhance study habits, motivation, and self-control while fostering student engagement with course materials. The evaluation uses a baseline survey administered in the first lecture session and follow-up surveys throughout the semester. Survey measures include expected study time allocation across activities (lectures, problem sets, textbook learning, group study), learning strategies, interest in economics, subjective understanding of course material, and non-cognitive skills such as self-control. Baseline data are linked to administrative records on course participation and performance, conditional on student consent. The study aims to identify the causal impact of the intervention on academic effort, engagement, and achievement, contributing to the literature on economics of education and teaching innovation in higher education.
External Link(s)

Registration Citation

Citation
Steinmayr, Andreas. 2025. "NEXTlearn - New strategies for digital learning and assessment." AEA RCT Registry. November 10. https://doi.org/10.1257/rct.16760-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
All students attend the same lecture and take the same lecture exam. The content of the
discussion sections is identical. The difference lies solely in how the sections are organized.

• Treatment condition: NEXTlearn format: students receive access to digital take-
home quizzes that include both assignments to be discussed in class and additional
exercises, which are automatically graded. These take-home exercises can be repeated
multiple times during the week for practice. They are graded but contribute only
marginally to the overall grade. In the discussion sections, students discuss their solu-
tions in groups and with the instructor. At the end of each session, a short (15-minute),
paper-based exam on the previous week’s content is administered. The discussion sec-
tion grade is primarily based on these short tests, with minor contributions from the
take-home quizzes.

• Control condition: Traditional course structure: students receive PDFs with as-
signments to be solved before the respective session, but assignments are not graded.
The solutions are discussed in class. The assignments are not graded. The discussion
section grade is based on a midterm and end-of-term exam.
Intervention Start Date
2025-10-02
Intervention End Date
2026-01-31

Primary Outcomes

Primary Outcomes (end points)
• Exam participation at the first sitting
• Passing exam at the first sitting (unconditional)
• Exam score at the first sitting (conditional on participation)
• Interest in economic topics (anticipated probability of taking a voluntary economic
class in the future)
• Engagement score (survey-based)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Differentiation of exam scores by question type:
– Calculation tasks
– Factual knowledge
– Conceptual understanding
• Interest in economic topics in general (overall, components)
• Supportiveness of the course for a) exam preparation and b) general understanding of
economics
• Time use for all introductory modules (economics, mathematics, business)
• Enrollment in subsequent economics courses

Mechanisms:
Attendance in discussion sessions (number of sessions attended)
• Perceived usefulness of study materials
• Time use related to the economics course (weekly hours across main learning activities)
• Study behaviors and learning strategies
• Exam preparation and attitudes before the first sitting (intention to participate, time
investment, preparedness, confidence, stress)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Discussion sections - grouped by instructors - are randomly divided into a control and a treatment group. Students enroll in a discussion section using the regular enrollment process. The treatment condition is revealed only after enrollment is completed.
Experimental Design Details
Not available
Randomization Method
We randomized at the discussion section-instructor level using complete enumeration of all possible assignments. We applied pre-specified constraints on seminar types and instructor pairings, calculated a balance score for time slots, and retained only assignments meeting all constraints and achieving optimal balance. One final assignment was randomly drawn from this restricted set. All assignments, balance scores, and the final draw were archived for full replicability.
Randomization Unit
Instructors for discussion sections
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
12 instructors, 27 discussion sections
Sample size: planned number of observations
700 students
Sample size (or number of clusters) by treatment arms
About 50% in each treatment arm.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
For binary outcomes, we consider a baseline success rate of p1 = 0.65 and a treatment effect of 10 percentage points (p2 = 0.75). Under these assumptions, the estimated power equals 0.29 at the 5% significance level and 0.40 at the 10% level. For continuous outcomes, we assume standardized variables with a unit standard deviation (SD = 1) and an expected treatment effect of 0.2 standard deviations (δ = 0.2). Under the same assumptions, the estimated power equals 0.25 at the 5% significance level and 0.36 at the 10% level. We expect that the inclusion of highly predictive baseline measures will significantly improve precision and power. Thus, we consider the provided numbers as conservative.
IRB

Institutional Review Boards (IRBs)

IRB Name
Board for Ethical Questions in Science of the University of Innsbruck
IRB Approval Date
2025-11-05
IRB Approval Number
104/2025
Analysis Plan

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