Hard-to-Manage Preschool Boys: Symptomatic Behavior across Contexts and Time

Preschool boys identified by their parents and/or teachers as active, inattentive, and impulsive ( N = 69) at age 4 were compared with boys without problem ( N = 43) on observational measures of symptm-related behaviors, obtained across context (home, laboratory, and preschool). Problem boys differed from comparison boys on measures of activity/inattention, noncompliance, and impulsivity obtained in the 3 settings. At a 2-year follow-up, when they were 6 years old, problem boys continued to differ from comparison boys on laboratory measures of activity and impulsivity; there also was some stability in these symptomatic behaviors. Implications of these findings for the emergence and persistence of externalizing problems in preschool boys are addressed.     

Modeling Student Cognition in Digital and Nondigital Assessment Environments

Inferences about student knowledge, skills, and attributes based on digital activity still largely come from whether students ultimately get a correct result or not. However, the ability to collect activity stream data as individuals interact with digital environments provides information about students’ processes as they progress through learning activities. These data have the potential to yield information about student cognition if methods can be developed to identify and aggregate evidence from diverse data sources. This work demonstrates how data from multiple carefully designed activities aligned to a learning progression can be used to support inferences about students’ levels of understanding of the geometric measurement of area. The article demonstrates evidence identification and aggregation of activity stream data from two different digital activities, responses to traditional assessment items, and ratings based on observation of in-person non-digital activity aligned to a common learning progression using a Bayesian Network approach.     

At the heart of child care: Predictors of teacher sensitivity in center-based child care

This study examined the extent to which characteristics of early childhood teachers and settings predicted observed teacher sensitivity. Participants included 41 head teachers at child care centers located in Northern California. Accreditation status, center size, and program quality were uniquely associated with teacher sensitivity. Accreditation was also associated with a number of other teacher (training, ethnic minority status, and depression) and setting characteristics (program quality, subsidies, and child ethnic minority enrollment). Other unique predictors included more teacher training, smaller center size, and perceived organizational health. Having a greater number of depressive symptoms or working in a larger center were identified as risks to teacher sensitivity, and were moderated by higher levels of teacher training and observed program quality The current study provides preliminary support for the importance of examining the ways that teacher and setting characteristics are related to teacher interactions with young children.     

Age Differences in Imagery Abilities

Age differences were examined in 4 aspects of visual mental imagery, namely, image generation, maintenance, scanning, and rotation. The results suggested that one or more distinct processes are used to carry out each aspect of imagery, and that this is true for 5-year-olds, 8-year-olds, 14-year-olds, and adults. There was no evidence that younger children have fewer processing components, which become differentiated into more specialized subsystems over age. In addition, the results suggested that younger children are relatively poor at scanning, rotating, and generating objects in images, but are relatively good at maintaining images.     

Perception of global climate change as a mediator of the effects of major and religious affiliation on college students’ environmentally responsible behavior

Previous research has shown a reliable association between environmental education and environmentally responsible behavior (ERB). Research has also shown that aspects of religion were associated with ERB. However, the mechanisms of associations are unclear. This study builds on previous research addressing the relationship between student major, religious affiliation, and ERB in two important ways. First, we tested the role of global climate change (GCC) perceptions as a mediating variable in the relationship between major and ERB, and between religious affiliation and ERB. Second, we developed a new measure of ERB focusing on impacts to natural resources. Student major was found to be a significant predictor of participation in ERB, as was religious affiliation. Student major and religious affiliation were also found to be significant predictors of GCC perceptions. The effect of major and religious affiliation on ERB was both mediated by GCC perceptions.     

Reframing Service-Learning as Learning and Participation With Urban Youth

This article describes a critical service-learning project that resulted from an educational partnership among a national teachers' union, a local teachers' union, and a major research university. The partnership—funded by a grant from the Corporation for National and Community Service, Learn and Serve program—focused on professional development opportunities for K–12 educators across subject areas throughout an urban school district. Teachers enrolled in a university-level graduate course where they learned about critical service-learning, engaged in community-based activities, developed partnerships with local organizations, and facilitated critical service-learning projects in local schools and communities. Here, we highlight one of the many projects that emerged from this partnership as we attempt to connect theory with practice by reframing service-learning as learning and participation. We ask: How can a reframing of service-learning as learning and participation impact how we understand the educative and social engagements of four urban youth?     

Muscle activation characteristics in cross-country skiers with a history of anterior compartment pain

A large proportion of elite cross-country skiers suffer from chronic anterior compartment syndrome (CACS). This study used surface electromyograms (EMGs) to investigate whether differences existed in the activation characteristics of the tibialis anterior muscle between elite cross-country skiers with a history of anterior compartment pain (symptomatic group) and a pain-free control group. Based on self-reported pain symptoms, twelve young, national-level cross-country ski athletes were assigned to a symptomatic group (N = 5), a control group (N = 4), or analyzed individually if their diagnosis was not certain (N = 3). During skating, EMGs were recorded on five lower leg muscles. The relative increase in EMG power per step when increasing the effort level of skating was larger in the symptomatic group than in the control group for tibialis anterior (143 ± 12% vs. 125 ± 23%; Cohen's d = 1.17), peroneus longus (123 ± 24% vs. 107 ± 6%; d = 0.91), and gastrocnemius lateralis (167 ± 51% vs. 117 ± 12%; d = 1.64). The symptomatic group showed more power in the lower frequency bands of the tibialis anterior's EMG spectra (p < 0.001), whereas no group differences were found in other muscles (all p>0.2). Within the step cycle, these differences appeared in the swing phase and in the gliding phase during single leg support. The observed differences in the EMG spectra may serve as an early identification of athletes who are at risk of developing CACS.     

Learning theories for artificial intelligence promoting learning processes

This paper discusses a three-level model that synthesizes and unifies existing learning theories to model the roles of artificial intelligence (AI) in promoting learning processes. The model, drawn from developmental psychology, computational biology, instructional design, cognitive science, complexity and sociocultural theory, includes a causal learning mechanism that explains how learning occurs and works across micro, meso and macro levels. The model also explains how information gained through learning is aggregated, or brought together, as well as dissipated, or released and used within and across the levels. Fourteen roles for AI in education are proposed, aligned with the model's features: four roles at the individual or micro level, four roles at the meso level of teams and knowledge communities and six roles at the macro level of cultural historical activity. Implications for research and practice, evaluation criteria and a discussion of limitations are included. Armed with the proposed model, AI developers can focus their work with learning designers, researchers and practitioners to leverage the proposed roles to improve individual learning, team performance and building knowledge communities.

Practitioner notes

What is already known about this topic

• Numerous learning theories exist with significant cross-over of concepts, duplication and redundancy in terms and structure that offer partial explanations of learning.
• Frameworks concerning learning have been offered from several disciplines such as psychology, biology and computer science but have rarely been integrated or unified.
• Rethinking learning theory for the age of artificial intelligence (AI) is needed to incorporate computational resources and capabilities into both theory and educational practices.

What this paper adds

• A three-level theory (ie, micro, meso and macro) of learning that synthesizes and unifies existing theories is proposed to enhance computational modelling and further develop the roles of AI in education.
• A causal model of learning is defined, drawing from developmental psychology, computational biology, instructional design, cognitive science and sociocultural theory, which explains how learning occurs and works across the levels.
• The model explains how information gained through learning is aggregated, or brought together, as well as dissipated, or released and used within and across the levels.
• Fourteen roles for AI in education are aligned with the model's features: four roles at the individual or micro level, four roles at the meso level of teams and knowledge communities and six roles at the macro level of cultural historical activity.

Implications for practice and policy

• Researchers may benefit from referring to the new theory to situate their work as part of a larger context of the evolution and complexity of individual and organizational learning and learning systems.
• Mechanisms newly discovered and explained by future researchers may be better understood as contributions to a common framework unifying the scientific understanding of learning theory.