Time management skills are an essential component of college student success, especially in online classes. Through a randomized control trial of students in a for-credit online course at a public 4-year university, we test the efficacy of a scheduling intervention aimed at improving students' time management. Results indicate the intervention had positive effects on initial achievement scores; students who were given the opportunity to schedule their lecture watching in advance scored about a third of a standard deviation better on the first quiz than students who were not given that opportunity. These effects are concentrated in students with the lowest self-reported time management skills. However, these effects diminish over time such that we see a marginally significant negative effect of treatment on the last week's quiz grade and no difference in overall course scores. We examine the effect of the intervention on plausible mechanisms to explain the observed achievement effects. We find no evidence that the intervention affected cramming, procrastination, or the time at which students did work.

Student clickstream data-time-stamped records of click events in online courses-can provide fine-grained information about student learning. Such data enable researchers and instructors to collect information at scale about how each student navigates through and interacts with online education resources, potentially enabling objective and rich insight into the learning experience beyond self-reports and intermittent assessments. Yet, analyses of these data often require advanced analytic techniques, as they only provide a partial and noisy record of students' actions. Consequently, these data are not always accessible or useful for course instructors and administrators. In this paper, we provide an overview of the use of clickstream data to define and identify behavioral patterns that are related to student learning outcomes. Through discussions of four studies, we provide examples of the complexities and particular considerations of using these data to examine student self-regulated learning.

A strand of task‐based interaction research has emerged to better understand the effects of heritage language (HL) and second language (L2) learners’ peer collaboration on interactional moves (e.g., language‐related episodes [LREs], self‐repairs) and linguistic focus. To extend this line of research, this study compared 14 HL–L2 and 16 HL–HL advanced learners’ peer interactions across face‐to‐face (FTF) and written synchronous computer‐mediated communication (SCMC) modes. Each dyad completed 2 decision‐making/collaborative writing tasks in Spanish across both interaction modes. Results revealed that interaction mode had a large effect on the extent to which HL–L2 and HL–HL pairs produced self‐repairs and initiated LREs. That is, both pair types initiated more LREs in FTF mode, and self‐repaired non‐target‐like utterances more extensively in SCMC mode. As for pair types, HL–L2 pairs significantly resolved more lexis‐focused episodes in FTF mode, and HL–HL pairs only produced self‐repair episodes in SCMC mode. HL–L2 and HL–HL dyads addressed linguistic items (e.g., morphosyntax) rather equally across interaction modes. Our findings are discussed in light of the differences in prior language‐learning experiences of HL and L2 learners.

Distance learning is expanding rapidly in universities. While theoretical and qualitative literature stress the critical role of effective interpersonal interactions in motivating students and facilitating learning in online environments, quantitative evidence on the benefits of increased interpersonal interactions on student learning outcomes is limited. This study examines the effect of providing a voluntary meeting time and increasing instructor e-mail activity on student grades in a fully online Pre-Calculus course at a public university. Student selection into courses was minimal since students only had access to one condition at a time. We further use a propensity score matching strategy to address demographic variations in student characteristics across cohorts. Our results indicate that the increased interpersonal interaction opportunities increased final exam scores by 0.22 standard deviations and improved passing rates by 19 percentage points. The Rosenbaum’s sensitivity analysis indicates that it is unlikely that these results are due to omitted variable bias.

Despite steady investment in English language education made by developing countries over the past few decades, results continue to be constrained by lack of high-quality instructors and language learning resources. Thus, using technology in language instruction has increasingly been recognized as a potential approach for addressing these constraints. This study uses administrative data from a large public university in Mexico to examine the impact of a technology-enhanced blended program on students' English course grades and course completion rates. Specifically, we focus on a campuswide policy change in all compulsory English language courses that replaces half of the traditional face-to-face class time with an interactive online learning environment developed by a leading technology-mediated English language learning and assessment provider. Our results suggest that, compared to traditional face-to-face instruction, blended learning had a significant, positive impact on students' course grades and course completion rates. In addition, the enrollment-teacher ratio increased after replacing half of the face-to-face instructional time with online learning, suggesting that blended learning environments hold promise for providing high-quality and costeffective language instruction.