Putting ICAP to the test: how technology-enhanced learning activities are related to cognitive and affective-motivational learning outcomes in higher education.

Digital technology is considered to have great potential to promote learning in higher education. In line with the Interactive, Constructive, Active, Passive (ICAP) framework, this seems to be particularly true when instructors stimulate high-quality learning activities such as constructive and interactive learning activities instead of active and passive learning activities. Against the background of a lack of empirical studies in authentic, technology-enhanced instructional settings, we investigated the cognitive and affective-motivational effects of these learning activity modes in technology-enhanced higher education courses. To this end, we used 3.820 student assessments regarding 170 course sessions for which the teachers stated the learning activities students were engaged in. Results of multilevel structural equation modelling highlight the importance of technology-enhanced interactive learning activities for students' perception of learning and the potential negative consequences of passive learning activities for affective-motivational outcomes. However, the superiority of constructive and interactive learning activities compared to passive and active learning activities for cognitive and affective-motivational outcomes was not supported by the findings. Instead, the findings point to potential differential effects of the individual learning activities within one activity mode. Future research should follow up on these effects to gain a more fine-grained understanding of how technology-enhanced learning activities can be optimized to enhance students' learning outcomes.

Restoring cerebellar-dependent learning.

Behavioral and pharmaceutical interventions reverse defects associated with increased cerebellar long-term depression in a mouse model of Fragile X syndrome.

How adverse childhood experiences get under the skin: A systematic review, integration and methodological discussion on threat and reward learning mechanisms.

Adverse childhood experiences (ACEs) are a major risk factor for the development of multiple psychopathological conditions, but the mechanisms underlying this link are poorly understood. Associative learning encompasses key mechanisms through which individuals learn to link important environmental inputs to emotional and behavioral responses. ACEs may impact the normative maturation of associative learning processes, resulting in their enduring maladaptive expression manifesting in psychopathology. In this review, we lay out a systematic and methodological overview and integration of the available evidence of the proposed association between ACEs and threat and reward learning processes. We summarize results from a systematic literature search (following PRISMA guidelines) which yielded a total of 81 articles (threat: n=38, reward: n=43). Across the threat and reward learning fields, behaviorally, we observed a converging pattern of aberrant learning in individuals with a history of ACEs, independent of other sample characteristics, specific ACE types, and outcome measures. Specifically, blunted threat learning was reflected in reduced discrimination between threat and safety cues, primarily driven by diminished responding to conditioned threat cues. Furthermore, attenuated reward learning manifested in reduced accuracy and learning rate in tasks involving acquisition of reward contingencies. Importantly, this pattern emerged despite substantial heterogeneity in ACE assessment and operationalization across both fields. We conclude that blunted threat and reward learning may represent a mechanistic route by which ACEs may become physiologically and neurobiologically embedded and ultimately confer greater risk for psychopathology. In closing, we discuss potentially fruitful future directions for the research field, including methodological and ACE assessment considerations.

Learning interventions and training methods in health emergencies: A scoping review.

BACKGROUND: Keeping the health workforce and the public informed about the latest evolving health information during a health emergency is critical to preventing, detecting and responding to infectious disease outbreaks or other health emergencies. Having a well-informed, ready, willing, and skilled workforce and an informed public can help save lives, reduce diseases and suffering, and minimize socio-economic loss in affected communities and countries. Providing "just in time" support and opportunities for learning in health emergencies is much needed for capacity building. In this paper, 'learning intervention' refers to the provision of ad-hoc, focused, or personalized training sessions with the goal of preparing the health workers for emergencies or filling specific knowledge or skill gaps. We refer to 'training methods' as instructional design strategies used to teach someone the necessary knowledge and skills to perform a task. METHODS: We conducted a scoping review to map and better understand what learning interventions and training methods have been used in different types of health emergencies and by whom. Studies were identified using six databases (Pubmed/Medline, Embase, Hinari, WorldCat, CABI and Web of Science) and by consulting with experts. Characteristics of studies were mapped and displayed and major topic areas were identified. RESULTS: Of the 319 records that were included, contexts most frequently covered were COVID-19, disasters in general, Ebola and wars. Four prominent topic areas were identified: 1) Knowledge acquisition, 2) Emergency plans, 3) Impact of the learning intervention, and 4) Training methods. Much of the evidence was based on observational methods with few trials, which likely reflects the unique context of each health emergency. Evolution of methods was apparent, particularly in virtual learning. Learning during health emergencies appeared to improve knowledge, general management of the situation, quality of life of both trainers and affected population, satisfaction and clinical outcomes. CONCLUSION: This is the first scoping review to map the evidence, which serves as a first step in developing urgently needed global guidance to further improve the quality and reach of learning interventions and training methods in this context.

If Engrams Are the Answer, What Is the Question?

Engram labelling and manipulation methodologies are now a staple of contemporary neuroscientific practice, giving the impression that the physical basis of engrams has been discovered. Despite enormous progress, engrams have not been clearly identified, and it is unclear what they should look like. There is an epistemic bias in engram neuroscience toward characterizing biological changes while neglecting the development of theory. However, the tools of engram biology are exciting precisely because they are not just an incremental step forward in understanding the mechanisms of plasticity and learning but because they can be leveraged to inform theory on one of the fundamental mysteries in neuroscience-how and in what format the brain stores information. We do not propose such a theory here, as we first require an appreciation for what is lacking. We outline a selection of issues in four sections from theoretical biology and philosophy that engram biology and systems neuroscience generally should engage with in order to construct useful future theoretical frameworks. Specifically, what is it that engrams are supposed to explain? How do the different building blocks of the brain-wide engram come together? What exactly are these component parts? And what information do they carry, if they carry anything at all? Asking these questions is not purely the privilege of philosophy but a key to informing scientific hypotheses that make the most of the experimental tools at our disposal. The risk for not engaging with these issues is high. Without a theory of what engrams are, what they do, and the wider computational processes they fit into, we may never know when they have been found.

Tutor auditory memory for guiding sensorimotor learning in birdsong.

Memory-guided motor shaping is necessary for sensorimotor learning. Vocal learning, such as speech development in human babies and song learning in bird juveniles, begins with the formation of an auditory template by hearing adult voices followed by vocally matching to the memorized template using auditory feedback. In zebra finches, the widely used songbird model system, only males develop individually unique stereotyped songs. The production of normal songs relies on auditory experience of tutor's songs (commonly their father's songs) during a critical period in development that consists of orchestrated auditory and sensorimotor phases. "Auditory templates" of tutor songs are thought to form in the brain to guide later vocal learning, while formation of "motor templates" of own song has been suggested to be necessary for the maintenance of stereotyped adult songs. Where these templates are formed in the brain and how they interact with other brain areas to guide song learning, presumably with template-matching error correction, remains to be clarified. Here, we review and discuss studies on auditory and motor templates in the avian brain. We suggest that distinct auditory and motor template systems exist that switch their functions during development.

Perirhinal cortex learns a predictive map of the task environment.

Goal-directed tasks involve acquiring an internal model, known as a predictive map, of relevant stimuli and associated outcomes to guide behavior. Here, we identified neural signatures of a predictive map of task behavior in perirhinal cortex (Prh). Mice learned to perform a tactile working memory task by classifying sequential whisker stimuli over multiple training stages. Chronic two-photon calcium imaging, population analysis, and computational modeling revealed that Prh encodes stimulus features as sensory prediction errors. Prh forms stable stimulus-outcome associations that can progressively be decoded earlier in the trial as training advances and that generalize as animals learn new contingencies. Stimulus-outcome associations are linked to prospective network activity encoding possible expected outcomes. This link is mediated by cholinergic signaling to guide task performance, demonstrated by acetylcholine imaging and systemic pharmacological perturbation. We propose that Prh combines error-driven and map-like properties to acquire a predictive map of learned task behavior.

Learning effects in speech-in-noise tasks: Effect of masker modulation and masking release.

Previous research has shown that learning effects are present for speech intelligibility in temporally modulated (TM) noise, but not in stationary noise. The present study aimed to gain more insight into the factors that might affect the time course (the number of trials required to reach stable performance) and size [the improvement in the speech reception threshold (SRT)] of the learning effect. Two hypotheses were addressed: (1) learning effects are present in both TM and spectrally modulated (SM) noise and (2) the time course and size of the learning effect depend on the amount of masking release caused by either TM or SM noise. Eighteen normal-hearing adults (23-62 years) participated in SRT measurements, in which they listened to sentences in six masker conditions, including stationary, TM, and SM noise conditions. The results showed learning effects in all TM and SM noise conditions, but not for the stationary noise condition. The learning effect was related to the size of masking release: a larger masking release was accompanied by an increased time course of the learning effect and a larger learning effect. The results also indicate that speech is processed differently in SM noise than in TM noise.

Flexible multitask computation in recurrent networks utilizes shared dynamical motifs.

Flexible computation is a hallmark of intelligent behavior. However, little is known about how neural networks contextually reconfigure for different computations. In the present work, we identified an algorithmic neural substrate for modular computation through the study of multitasking artificial recurrent neural networks. Dynamical systems analyses revealed learned computational strategies mirroring the modular subtask structure of the training task set. Dynamical motifs, which are recurring patterns of neural activity that implement specific computations through dynamics, such as attractors, decision boundaries and rotations, were reused across tasks. For example, tasks requiring memory of a continuous circular variable repurposed the same ring attractor. We showed that dynamical motifs were implemented by clusters of units when the unit activation function was restricted to be positive. Cluster lesions caused modular performance deficits. Motifs were reconfigured for fast transfer learning after an initial phase of learning. This work establishes dynamical motifs as a fundamental unit of compositional computation, intermediate between neuron and network. As whole-brain studies simultaneously record activity from multiple specialized systems, the dynamical motif framework will guide questions about specialization and generalization.

Does using artificial intelligence assistance accelerate skill decay and hinder skill development without performers' awareness?

Artificial intelligence in the workplace is becoming increasingly common. These tools are sometimes used to aid users in performing their task, for example, when an artificial intelligence tool assists a radiologist in their search for abnormalities in radiographic images. The use of artificial intelligence brings a wealth of benefits, such as increasing the efficiency and efficacy of performance. However, little research has been conducted to determine how the use of artificial intelligence assistants might affect the user's cognitive skills. In this theoretical perspective, we discuss how artificial intelligence assistants might accelerate skill decay among experts and hinder skill acquisition among learners. Further, we discuss how AI assistants might also prevent experts and learners from recognizing these deleterious effects. We then discuss the types of questions: use-inspired basic cognitive researchers, applied researchers, and computer science researchers should seek to answer. We conclude that multidisciplinary research from use-inspired basic cognitive research, domain-specific applied research, and technical research (e.g., human factors research, computer science research) is needed to (a) understand these potential consequences, (b) design artificial intelligence systems to mitigate these impacts, and (c) develop training and use protocols to prevent negative impacts on users' cognitive skills. Only by answering these questions from multidisciplinary perspectives can we harness the benefits of artificial intelligence in the workplace while preventing negative impacts on users' cognitive skills.

Learners' Spontaneous Gesture Before a Math Lesson Predicts the Efficacy of Seeing Versus Doing Gesture During the Lesson.

Gestures-hand movements that accompany speech and express ideas-can help children learn how to solve problems, flexibly generalize learning to novel problem-solving contexts, and retain what they have learned. But does it matter who is doing the gesturing? We know that producing gesture leads to better comprehension of a message than watching someone else produce gesture. But we do not know how producing versus observing gesture impacts deeper learning outcomes such as generalization and retention across time. Moreover, not all children benefit equally from gesture instruction, suggesting that there are individual differences that may play a role in who learns from gesture. Here, we consider two factors that might impact whether gesture leads to learning, generalization, and retention after mathematical instruction: (1) whether children see gesture or do gesture and (2) whether a child spontaneously gestures before instruction when explaining their problem-solving reasoning. For children who spontaneously gestured before instruction, both doing and seeing gesture led to better generalization and retention of the knowledge gained than a comparison manipulative action. For children who did not spontaneously gesture before instruction, doing gesture was less effective than the comparison action for learning, generalization, and retention. Importantly, this learning deficit was specific to gesture, as these children did benefit from doing the comparison manipulative action. Our findings are the first evidence that a child's use of a particular representational format for communication (gesture) directly predicts that child's propensity to learn from using the same representational format.

A Hierarchical Bayesian Model of Adaptive Teaching.

How do teachers learn about what learners already know? How do learners aid teachers by providing them with information about their background knowledge and what they find confusing? We formalize this collaborative reasoning process using a hierarchical Bayesian model of pedagogy. We then evaluate this model in two online behavioral experiments (N = 312 adults). In Experiment 1, we show that teachers select examples that account for learners' background knowledge, and adjust their examples based on learners' feedback. In Experiment 2, we show that learners strategically provide more feedback when teachers' examples deviate from their background knowledge. These findings provide a foundation for extending computational accounts of pedagogy to richer interactive settings.

The Ungrading Learning Theory We Have Is Not the Ungrading Learning Theory We Need.

Ungrading is an emancipatory pedagogy that focuses on evaluative assessment of learning. Self-regulated learning (SRL) has consistently been referred to as the learning theory that undergirds ungrading, but SRL-with its deficit frame in the literature and in practice-fails to uphold ungrading's emancipatory aims. An asset-framed learning theory-one that combines the cultural orientation of funds of knowledge with the power dynamics of community cultural wealth-is proposed as an alternative to SRL. The proposed learning theory aligns ungrading to its emancipatory aims and may provide an opportunity to better understand the learning that occurs in ungraded classrooms. Scholarly and practical impacts for Science, Technology, Engineering, and Mathematics (STEM), and specifically biology, educational research and practice include investigating the plausibility of mixing learning theories, aligning learning theory to emancipatory aims and researching how faculty activate funds of knowledge and community cultural wealth, both individually and collectively, in ungraded STEM classrooms.

Simulation-based echocardiography learning contribution on training of medical residents.

INTRODUCTION: Echocardiography is a pivotal exam in critically ill patients, a specific training is crucial. Medical residents often lack echocardiography practice. AIM: This study aims to evaluate the impact of simulation-based training on medical residents' echocardiography mastery. METHODS: This interventional study was conducted among medical residents at the Simulation Center of the Faculty of Medicine in Monastir (CeSim) in January 2022. The intervention consisted of a theoretical training and a simulator-based practical training concerning echocardiography. Residents underwent evaluation before and after training through a "Pre-Test" and a "Post-Test," respectively, using a French-language questionnaire. Participation was entirely voluntary. RESULTS: A total of 28 medical residents participated in our study, with the majority being female (57.1%). The median age was 29 years (interquartile range: 28-31.75). Following training, the proportion of participants who reported having the necessary skills for echocardiography interpretation significantly increased (p<0.05). Respondents demonstrated significant improvements in their scores on theoretical tests and practical skills assessments. Concerning echocardiographic views, the percentage of participants who correctly identified the title of the parasternal small axis section increased from 53.6% before training to 100% after training (p <10-3). Significant enhancements were observed in all parameters evaluating the practice of echocardiographic sections by respondents on a mannequin after training, encompassing time to obtain the view, view quality, image quality, visualization of structures, interpretability, and image stability (p<10-3). There was a significant improvement in average response rates for echocardiographic clinical syndroms among medical residents before and after training. All participants emphasized the indispensability of ultrasound education in the training of physicians specializing in managing cardiopulmonary emergencies. CONCLUSIONS: This study reports the beneficial role of simulation-based training in enhancing the mastery of medical residents in echocardiography. Incorporating such training methods into their learning curricula is advisable.