Taking intermittent quizzes reduces achievement gaps and enhances online learning, even in highly distracting environments

Inserting brief quiz questions into an online lecture can boost learning and may reduce racial achievement gaps, even when students are tuning in remotely in a distracting environment. That’s a main finding of our recent research published in Communications Psychology. With co-authors Dahwi Ahn, Hymnjyot Gill and Karl Szpunar, we present evidence that adding mini-quizzes into an online lecture in science, technology, engineering or mathematics – collectively known as STEM – can boost learning, especially for Black students.This article is published as Chan, J. C. K., & *Assadipour, Z., Taking intermittent quizzes reduces achievement gaps and enhances online learning even in highly distracting environments. The Conversation.; May 14, 2025; https://doi.org/10.64628/AAI.gqeapp5y9

Interpolated Retrieval of Relevant Material, Not Irrelevant Material, Enhances New Learning of a Video Lecture In-Person and Online

Interpolated retrieval enhances the learning of new information—a finding known as the forward testing effect. The context change account suggests that learning benefits are due to a shift in internal context, which can be triggered through the retrieval of either content-relevant or content-irrelevant information. In two experiments, we examined whether interpolated episodic, autobiographical, and semantic retrieval would enhance new learning of a video lecture, compared to interpolated review. Participants watched a STEM topic lecture divided into three ~5 min segments and completed their assigned interpolated activity after the first two segments. Across both a laboratory (Experiment 1, N = 249) and online setting (Experiment 2, N = 246), only episodic retrieval enhanced the learning of new material; autobiographical and semantic retrieval (content-irrelevant) did not improve new learning. Critically, we introduced a measure of context change to determine whether the level of engagement in these interpolated activities predicted recall. Engagement correlated with criterial test performance when controlling for effort (seriousness). Our results support a multi-factor explanation for the forward testing effect, providing evidence for both the context change and strategy change accounts, although we emphasize that support for context change should be interpreted with caution.This article is published as Assadipour, Z.; Ahn, D.; Chan, J.C.K. Interpolated Retrieval of Relevant Material, Not Irrelevant Material, Enhances New Learning of a Video Lecture In-Person and Online. Behav. Sci. 2025, 15, 668. https://doi.org/10.3390/bs15050668.Funding - This research was funded by the United States National Science Foundation, grant number 2017333. Institutional Review Board Statement - The study was conducted in accordance with the Declaration of Helsinki, and approved by the Iowa State University, protocol 15-609. Approval date: 15 July 2020

The Challenge of Online Learning: Can Small Quizzes Make a Big Difference?

Online education is now a major part of college and university learning. These digital courses offer great convenience and flexibility. But many students struggle to stay focused during online lectures. They often let their minds wander and typically do not perform as well as students in traditional classrooms. Our research offers a simple but powerful solution: insert short quizzes throughout the lecture. We call this approach interpolated retrieval practice. Here's how it works: instead of watching a 20-minute lecture straight through, students watch it in four shorter segments and take a brief quiz containing just four brief questions after each segment. Research has shown that these quick quizzes not only help students remember what they have learned, but also to better learn new information that follows each quiz. This approach is easy to implement, cost-effective, and can tackle concentration problems often seen in online education.This article is published as 2. Chan, J. C. K., Ahn, D.; *Assadipour, Z.; Szpunar, K.K., The challenge of online learning: can small quizzes make a big difference? Behavioural Sciences & Psychology: Behind the Paper. April 2025 https://go.nature.com/4iQ01T

In-lecture quizzes improve online learning for university and community college students

Online classes are now integral to higher education, particularly for students at two-year community colleges, who are profoundly underrepresented in experimental research. Here, we provided a rigorous test of using interpolated retrieval practice to enhance learning from an online lecture for both university and community college students (N = 703). We manipulated interpolated activity (participants saw review slides or answered short quiz questions) and onscreen distractions (control, memes, TikTok). Our results showed that interpolated retrieval enhanced online learning for both student groups, but this benefit was moderated by onscreen distractions. Surprisingly, the presence of TikTok videos produced an ironic effect of distraction—it enhanced learning for students in the interpolated review condition, allowing them to perform similarly to students who took the interpolated quizzes. Moreover, we showed in an exploratory analysis that the intervention-induced learning improvements were mediated by a composite measure of engaged learning, thus providing a mechanistic account of our findings. Finally, our data provided preliminary evidence that interpolated retrieval practice might reduce the achievement gap for Black students.This article is published as Chan, J.C.K., Ahn, D., Szpunar, K.K. et al. In-lecture quizzes improve online learning for university and community college students. Commun Psychol 3, 54 (2025). https://doi.org/10.1038/s44271-025-00234-5This work is supported by the United States National Science Foundation (NSF) Science of Learning and Augmented Intelligence Grant 2017333 to Chan and Szpunar. The funders had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript

Analytical approaches to planning intermodal transportation systems for regular and hazmat freight

The world container transportation industry has grown significantly over the past few decades. Large numbers of containers are transported everyday over long distances via a single or combinations of different modes of transportation (road, rail, water and air). Many of these containers contain hazardous materials (hazmat) whose transportation is regulated by governments due to the related risks. In contrast to other areas of transportation, operations-research-based models for intermodal transportation of containers, specifically hazmat ones, is still a young domain. The purpose of the thesis is to provide analytical approaches to planning intermodal transportation for regular and hazmat freights. Planning of intermodal transportation can be addressed at the strategic, tactical or operational level. In this regard, this thesis contributes to the current literature in the following three ways. First, at the operational level, we study crane scheduling at an intermodal terminal, such that the unloading of inbound vessels and the loading of outbound vehicles could be completed in minimum weighted time. The approach calls for a multi-processor multi-stage scheduling methodology, where each crane has availability time windows. Second, at the tactical level, we propose a routing framework for transportation of hazmat and regular containers in a congested network to minimize two objectives: total cost and total risk. The model considers congestion as a source of exposure and makes a trade-off between congestion exposures and capacity costs. Third, at the strategic level, we study the regulation of intermodal transportation for hazardous materials. A bi-level network design model and a bi-level bi-objective toll-setting policy model, which consider government and carrier at two levels of administration, are proposed to mitigate the transportation risk. The thesis concludes with comprehensive remarks. We summarize the contributions of this thesis, show the overall results obtained, and present the possible directions that this research may take in the future

Can students effectively self-test with self-generated questions? A yoked design approach

Engaging in retrieval practice (i.e., the testing effect and test-potentiated new learning) has continuously been shown to enhance memory and retention of studied information. College students face practical challenges in implementing retrieval practice, particularly when these opportunities are not integrated into the classroom and curriculum. In higher education, students are not universally provided with study guides or practice quiz questions to incorporate into studying. When students create their own test questions, concerns arise about the quality and difficulty of these questions compared to those created by instructors. There is limited research on the effectiveness of student’s self-testing with self-generated questions, and prior work investigating student-generated questions has often not provided students with the opportunity to engage in retrieval practice (see Myers et al., 2023). Perhaps students may reap dual benefits from both generative learning strategies and engaging in retrieval practice. Moreover, Foos and colleagues (1994) noted that there is a confound of question quality and difficulty when directly comparing participants who self-generate their own questions to participants who answer provided questions, which led them to employ a yoked-control design. The present study will investigate the effectiveness of college students self-testing with their self-generated questions compared to answering provided questions among STEM-based passages in a yoked design. All provided questions will be generated by the participant’s yoked counterpart. Additionally, the present study will also examine differences in performance between student-generated questions and questions generated with the assistance of ChatGPT

THE DISCRETE TIME, COST AND QUALITY TRADE-OFF PROBLEM IN PROJECT SCHEDULING: AN EFFICIENT SOLUTION METHOD BASED ON CELLDE ALGORITHM

<p>ENGLISH ABSTRACT:The trade-off between time, cost, and quality is one of the important problems of project management. This problem assumes that all project activities can be executed in different modes of cost, time, and quality. Thus a manager should select each activity’s mode such that the project can meet the deadline with the minimum possible cost and the maximum achievable quality. As the problem is NP-hard and the objectives are in conflict with each other, a multi-objective meta-heuristic called CellDE, which is a hybrid cellular genetic algorithm, is implemented as the optimisation method. The proposed algorithm provides project managers with a set of non-dominated or Pareto-optimal solutions, and enables them to choose the best one according to their preferences. A set of problems of different sizes is generated and solved using the proposed algorithm. Three metrics are employed for evaluating the performance of the algorithm, appraising the diversity and convergence of the achieved Pareto fronts. Finally a comparison is made between CellDE and another meta-heuristic available in the literature. The results show the superiority of CellDE.</p><p>AFRIKAANSE OPSOMMING: ‘n Balans tussen tyd, koste en gehalte is een van die belangrike probleme van projekbestuur. Die vraagstuk maak gewoonlik die aanname dat alle projekaktiwiteite uitgevoer kan word op uiteenlopende wyses wat verband hou met koste, tyd en gehalte. ‘n Projekbestuurder selekteer gewoonlik die uitvoeringsmetodes sodanig per aktiwiteit dat gehoor gegegee word aan minimum koste en maksimum gehalte teen die voorwaarde van voltooiingsdatum wat bereik moet word.<br /><br /> Aangesien die beskrewe problem NP-hard is, word dit behandel ten opsigte van konflikterende doelwitte met ‘n multidoelwit metaheuristiese metode (CellDE). Die metode is ‘n hibride-sellulêre genetiese algoritme. Die algoritme lewer aan die besluitvormer ‘n versameling van ongedomineerde of Pareto-optimale oplossings vir voorkeurgedrewe besluitvorming. Uiteenlopende probleme word opgelos deur die algoritme. Drie verskillende waardebepalings word toegepas op die gedrag van die algoritme. Die resultate bevestig die voortreflikheid van CellDE.</p&gt