No abstract

Cognitive outcomes for children born prematurely are well characterized, including increased risk for deficits in memory, attention, processing speed, and executive function. However, little is known about deficits that appear within the first 12 months, and how these early deficits contribute to later outcomes. To probe for functional deficits in visual attention, preterm and full-term infants were tested at 5 and 10 months with the Infant Orienting With Attention task (IOWA; Ross-Sheehy, Schneegans and Spencer, 2015). 5-month-old preterm infants showed significant deficits in orienting speed and task related error. However, 10-month-old preterm infants showed only selective deficits in spatial attention, particularly reflexive orienting responses, and responses that required some inhibition. These emergent deficits in spatial attention suggest preterm differences may be related to altered postnatal developmental trajectories. Moreover, we found no evidence of a dose-response relation between increased gestational risk and spatial attention. These results highlight the critical role of postnatal visual experience, and suggest that visual orienting may be a sensitive measure of attentional delay. Results reported here both inform current theoretical models of early perceptual/cognitive development, and future intervention efforts.

Open educational resources (OER) are increasingly attractive options for reducing educational costs, yet controlled studies of their efficacy are lacking. The current study addressed many criticisms of past research by accounting for course and instructor characteristics in comparing objective student learning outcomes across multiple sections of General Psychology taught by trained graduate student instructors at a large research-intensive university. We found no evidence that use of the OER text impeded students' critical thinking compared to use of a traditional textbook, even after accounting for instructor characteristics. To the contrary, we found evidence of a slight increase in content knowledge when using an OER text. Importantly, this effect was driven by improvements from both our lowestperforming students and our highest-performing students. Moreover, student learning outcomes were not influenced by instructor experience, suggesting even novice instructors fared well with OER materials. Finally, students from traditionally underserved populations reported the lower cost of the book had a significantly higher impact on their decision to enroll in and remain enrolled in the course.

The events of the COVID-19 Pandemic forced many psychologists to abandon lab-based approaches and embrace online experimental techniques. Although lab-based testing will always be the gold standard of experimental precision, several protocols have evolved to enable supervised online testing for paradigms that require direct observation and/or interaction with participants. However, many tasks can be completed online in an unsupervised way, reducing reliance on lab-based resources (e.g., personnel and equipment), increasing flexibility for families, and reducing participant anxiety and/or demand characteristics. The current project demonstrates the feasibility and utility of unsupervised online testing by incorporating a classic change-detection task that has been well-validated in previous lab-based research. In addition to serving as proof-of-concept, our results demonstrate that large online samples are quick and easy to acquire, facilitating novel research questions and speeding the dissemination of results. To accomplish this, we assessed visual working memory (VWM) in 4- to 10-year-old children in an unsupervised online change-detection task using arrays of 1–4 colored circles. Maximum capacity (max K) was calculated across the four array sizes for each child, and estimates were found to be on-par with previously published lab-based findings. Importantly, capacity estimates varied markedly across array size, with estimates derived from larger arrays systematically underestimating VWM capacity for our youngest participants. A linear mixed effect analysis (LME) confirmed this observation, revealing significant quadratic trends for 4- through 7-year-old children, with capacity estimates that initially increased with increasing array size and subsequently decreased, often resulting in estimates that were lower than those obtained from smaller arrays. Follow-up analyses demonstrated that these regressions may have been based on explicit guessing strategies for array sizes perceived too difficult to attempt for our youngest children. This suggests important interactions between VWM performance, age, and array size, and further suggests estimates such as optimal array size might capture both quantitative aspects of VWM performance and qualitative effects of attentional engagement/disengagement. Overall, findings suggest that unsupervised online testing of VWM produces reasonably good estimates and may afford many benefits over traditional lab-based testing, though efforts must be made to ensure task comprehension and compliance.

In early 2020, in-person data collection dramatically slowed or was completely halted across the world as many labs were forced to close due to the COVID-19 pandemic. Developmental researchers who assess looking time (especially those who rely heavily on in-lab eye-tracking or live coding techniques) were forced to re-think their methods of data collection. While a variety of remote or online platforms are available for gathering behavioral data outside of the typical lab setting, few are specifically designed for collecting and processing looking time data in infants and young children. To address these challenges, our lab developed several novel approaches for continuing data collection and coding for a remotely administered audiovisual looking time protocol. First, we detail a comprehensive approach for successfully administering the Multisensory Attention Assessment Protocol (MAAP), developed by our lab to assess multisensory attention skills (MASks; duration of looking, speed of shifting/disengaging, accuracy of audiovisual matching). The MAAP is administered from a distance (remotely) by using Zoom, Gorilla Experiment Builder, an internet connection, and a home computer. This new data collection approach has the advantage that participants can be tested in their homes. We discuss challenges and successes in implementing our approach for remote testing and data collection during an ongoing longitudinal project. Second, we detail an approach for estimating gaze direction and duration collected remotely from webcam recordings using a post processing toolkit (OpenFace) and demonstrate its effectiveness and precision. However, because OpenFace derives gaze estimates without translating them to an external frame of reference (i.e., the participant's screen), we developed a machine learning (ML) approach to overcome this limitation. Thus, third, we trained a ML algorithm [(artificial neural network (ANN)] to classify gaze estimates from OpenFace with respect to areas of interest (AOI) on the participant's screen (i.e., left, right, and center). We then demonstrate reliability between this approach and traditional coding approaches (e.g., coding gaze live). The combination of OpenFace and ML will provide a method to automate the coding of looking time for data collected remotely. Finally, we outline a series of best practices for developmental researchers conducting remote data collection for looking time studies.