Feasibility of Wearable Sensors to Assess Cognitive Load During Clinical Performance: Lessons Learned and Blueprint for Success.

INTRODUCTION: Cognitive load (CogL) is increasingly recognized as an important resource underlying operative performance. Current innovations in surgery aim to develop objective performance metrics via physiological monitoring from wearable digital sensors. Surgeons have access to consumer technology that could measure CogL but need guidance regarding device selection and implementation. To realize the benefits of surgical performance improvement these methods must be feasible, incorporating human factors usability and design principles. This paper aims to evaluate the feasibility of using wearable sensors to assess CogL, identify the benefits and challenges of implementing devices, and develop guidance for surgeons planning to implement wearable devices in their research or practice. METHODS: We examined the feasibility of wearable sensors from a series of empirical studies that measured aspects of clinical performance relating to CogL. Across four studies, 84 participants and five sensors were involved in the following clinical settings: (i) real intraoperative surgery; (ii) simulated laparoscopic surgery; and (iii) medical team performance outside the hospital. RESULTS: Wearable devices worn on the wrist and chest were found to be comfortable. After a learning curve, electrodermal activity data were easily and reliably collected. Devices using photoplethysmography to determine heart rate variability were significantly limited by movement artifact. There was variable success with electroencephalography devices regarding connectivity, comfort, and usability. CONCLUSIONS: It is feasible to use wearable sensors across various clinical settings, including surgery. There are some limitations, and their implementation is context and device dependent. To scale sensor use in clinical research, surgeons must embrace human factors principles to optimize wearability, usability, reliability, and data security.

Exploring challenges in learning and study skills among first-year medical students: a case study.

BACKGROUND: Despite being high-achieving students, many medical students face academic challenges, particularly during their first year of study. Research indicates that self-regulated learning, involving metacognitive processes and adaptive strategies, can positively influence academic achievement. This study aimed to assess the early learning and study skills of first-year medical students in an international medical school with the goal of developing a learner-centered educational intervention to promote self-regulated learning. METHODS: We conducted a retrospective analysis of the Learning and Study Skills Inventory (LASSI) questionnaire that was administered annually each August to first-year medical students from 2019 to 2022. The distribution of students across different percentile ranges for each selected variable was determined for each year and all years collectively. Students were counted within distinct percentile brackets (50th and below, between 51st and 75th, and above 75th ) for each variable. RESULTS: A total of 147 students completed the LASSI questionnaire over the 4-year time period. Using academic resources was the greatest concern, with 67% of students in the 50th or below percentile, followed by selecting the main idea (56%), motivation (51%), and concentration (50%). Attitude scored highest across all cohorts, scoring between 21.55 ± 0.73 and 26.49 ± 0.34. In comparing mean scores of LASSI variables across all cohorts, attitude, motivation, test-taking strategies, time management, and the use of academic resources differed significantly (p < 0.05). CONCLUSION: LASSI data can provide an early picture of students' support needs. We posit that early identification of student learning and study skills and areas of struggle can inform personalized educational interventions and programs to support first-year medical students.

Gaze cueing improves pattern recognition of histology learners.

Experts perceive and evaluate domain-specific visual information with high accuracy. In doing so, they exhibit eye movements referred to as "expert gaze" to rapidly focus on task-relevant areas. Using eye tracking, it is possible to record these implicit gaze patterns and present them to histology novice learners during training. This article presents a comprehensive evaluation of such expert gaze cueing on pattern recognition of medical students in histology. For this purpose, 53 students were randomized into two groups over eight histology sessions. The control group was presented with an instructional histology video featuring voice commentary. The gaze cueing group was presented the same video, but with an additional overlay of a live recording of the expert's eye movements. Afterward, students' pattern recognition was assessed through 20 image-based tasks (5 retention, 15 transfer) and their cognitive load with the Paas scale. Results showed that gaze cueing significantly outperformed the control group (p = 0.007; d = 0.40). This effect was evident for both, retention (p = 0.003) and transfer tasks (p = 0.046), and generalized across different histological contexts. The cognitive load was similar in both groups. In conclusion, gaze cueing helps histology novice learners to develop their pattern recognition skills, offering a promising method for histology education. Histology educators could benefit from this instructional strategy to provide new forms of attentional guidance to learners in visually complex learning environments.

The extent of interruptions to primary care medical officers' consultations in the Western Cape.

BACKGROUND:  Administrative tasks are an increasing burden for primary care doctors globally and linked to burnout. Many tasks occur during consultations. They cause interruptions with possible effects on patients' and doctors' experiences and care. The burden and typology of interruptions of doctors in primary care consultations have not been studied in South Africa. Given the link between administrative loads and burnout, describing the extent of these interruptions would help. This study's aim was to assess the extent of interruptions on primary care doctors in the Western Cape. METHODS:  This was a descriptive cross-sectional survey. Doctors from rural and urban primary care clinics in the Western Cape answered an online self-administered survey on the types of interruptions experienced during consultations. Interruptions were categorised and their prevalence calculated. Clinical and non-clinical interruption categories were compared. RESULTS:  There were 201 consultations from 30 doctors. Most interruptions were from retrieving and recording the current patient's information (93.0%), paperwork for other patients (50.7%), and telephone calls about the current patient (41.8%). Other prevalent interruptions were for emergencies (39.8%) and acquiring consumables (37.3%). The median (interquartile range [IQR]) of four (2-4) interruption types per consultation was higher than global settings. CONCLUSION:  Doctors experienced many interruptions during consultations. Their wide range included interruptions unrelated to the current patient.Contribution: This study adds insights from the global south on clinicians' administrative burden. It elaborates on the types of activities that interrupt consultations in an upper-middle income primary care setting. Exploration of interventions to decrease this burden is suggested.

Predicting cognitive load with EEG using Riemannian geometry-based features.

OBJECTIVE: We show that EEG-based cognitive load prediction using Riemannian geometry features outperforms existing models. The performance is estimated using Riemannian Procrustes Analysis (RPA) with a test set of subjects unseen during training. Approach: Performance is evaluated by using the Minimum Distance to Riemannian Mean model trained on cognitive load classification. The baseline performance is established using spatial covariance matrices of the signal as features. Various novel features are explored and analyzed in depth, including spatial covariance and correlation matrices computed on the EEG signal and its first-order derivative. Furthermore, each RPA step effect on the performance is investigated, and the generalization performance of RPA is compared against a few different generalization methods. Results: Performances are greatly improved by using the spatial covariance matrix of the first-order derivative of the signal as features. Furthermore, this work highlights both the importance and efficiency of RPA for cognitive load prediction: it achieves good generalizability with little amounts of calibration data and largely outperforms all the comparison methods. Significance: Cognitive load prediction using RPA for generalizability across subjects is an approach worth exploring further, especially for real-world applications where calibration time is limited. Furthermore, the feature exploration uncovers new, promising features that can be used and further experimented within any Riemannian geometry setting. .

Food Safety Exam Phrasing for Food Service Employees.

In many jurisdictions, foodservice workers are required to obtain food handler certification via written examination before being able to work. This study investigated the effect of the readability, or the ease in which one can read and comprehend written text, of food handler exam questions on exam performance. It was hypothesized that the reduction in cognitive load by improving the readability of exam questions would lead to improved scores. Participants received training in personal hygiene and basic food safety and were tested on their knowledge using questions that were worded using the traditional phrasing and updated phrasing that has improved readability. The results indicate that improved readability had a significant difference in the personal hygiene section but not on the basic food safety section. These results are due, in part, to the types of cognitive load (intrinsic vs. extraneous) that are required to solve different types of problems.

Alone but not isolated: social presence and cognitive load in learning with 360 virtual reality videos.

Introduction: This study aimed to identify any differences in social presence and cognitive load among three types of 360 virtual reality (VR)-based videos lectures. We hypothesized that social presence would be higher when interactions among peers are visible in a 360 VR video lectures while the cognitive load would be also increased. Methods: A total of 48 college students were randomly assigned to one of the three study groups to view an assigned 360 VR video lecture. The three groups were: (1) an instructor-only video viewing group, (2) a classroom lecture video viewing group, and (3) a classroom lecture and activity video viewing group. The video lectures were differently designed depending on the levels of peer visibility and the interactions between the instructor and peers. The participants watched one of the three types of assigned video lecture and subsequently completed two sets of questionnaires regarding social presence and cognitive load. A multivariate analysis of variance (MANOVA) was conducted with a planned contrast analysis for the type of video lectures. Results: We found that, contrary to the hypotheses, students in the group 1 (instructor-only video) showed higher social presence scores than students in the groups 2 and 3. However, no significant differences were found in the cognitive load scores. Discussion: The results show that 360 VR video lectures with an instructor-only are more effective at enhancing users' social presence than 360 VR video lectures with both the instructor and class-peers. We suggest creating 360 VR video lectures with the presence of the course instructor to offer learners the sense of actually participating in a lecture.

Research on identification of flight cadets' cognitive load based on multi-source physiological data and CGAN-DBN model.

Modern aircraft cockpit system is highly information-intensive. Pilots often need to receive a large amount of information and make correct judgments and decisions in a short time. However, cognitive load can affect their ability to perceive, judge and make decisions accurately. Furthermore, the excessive cognitive load will induce incorrect operations and even lead to flight accidents. Accordingly, the research on cognitive load is crucial to reduce errors and even accidents caused by human factors. By using physiological acquisition systems such as eye movement, ECG, and respiration, multi-source physiological signals of flight cadets performing different flight tasks during the flight simulation experiment are obtained. Based on the characteristic indexes extracted from multi-source physiological data, the CGAN-DBN model is established by combining the conditional generative adversarial networks (CGAN) model with the deep belief network (DBN) model to identify the flight cadets' cognitive load. The research results show that the flight cadets' cognitive load identification based on the CGAN-DBN model established has high accuracy. And it can effectively identify the cognitive load of flight cadets. The research paper has important practical significance to reduce the flight accidents caused by the high cognitive load of pilots.

In our study, a highly accurate cognitive load identification model for flight cadets was established by using multi-source physiological data. Moreover, it provides a theoretical basis for identifying the cognitive load of pilots through wearable physiological devices. Our intent is to catalyse further research and technological development.

Multimodal data for behavioural authentication in Internet of Things environments.

Identifying humans based on their behavioural patterns represents an attractive basis for access control as such patterns appear naturally, do not require a focused effort from the user side, and do not impose the additional burden of memorising passwords. One means of capturing behavioural patterns is through passive sensors laid out in a target environment. Thanks to the proliferation of the Internet of Things (IoT), sensing devices are already embedded in our everyday surroundings and represent a rich source of multimodal data. Nevertheless, collecting such data for authentication research purposes is challenging, as it entails management and synchronisation of a range of sensing devices, design of diverse tasks that would evoke different behaviour patterns, storage and pre-processing of data arriving from multiple sources, and the execution of long-lasting user activities. Consequently, to the best of our knowledge, no publicly available datasets suitable for behaviour-based authentication research exist. In this brief article, we describe the first multimodal dataset for behavioural authentication research collected in a sensor-enabled IoT setting. The dataset comprises of high-frequency accelerometer, gyroscope, and force sensor data collected from an office-like environment. In addition, the dataset contains 3D point clouds collected with wireless radar and electroencephalogram (EEG) readings from a wireless EEG cap worn by the study participants. Within the environment, 54 volunteers conducted 6 different tasks that were constructed to elicit different behaviours and different cognitive load levels, resulting in a total of 16 h of multimodal data. The richness of the dataset comprising 5 different sensing modalities, a variability of tasks including keyboard typing, hand gesturing, walking, and other activities, opens a range of opportunities for research in behaviour-based authentication, but also the understanding of the role of different tasks and cognitive load levels on human behaviour.

Acute effect of complexity in basketball on cognitive capacity.

Background: Executive functions, notably inhibition, significantly influence decision-making and behavioral regulation in team sports. However, more research must be conducted on individual player characteristics such as experience and motor skills. This study assessed how accumulated practical experience moderates inhibition in response to varying task difficulty levels. Methods: Forty-four university students (age: 20.36 ± 3.13 years) participated in this study with two sessions: one followed standard 1 × 1 basketball rules ("Regular Practice"), while the other imposed motor, temporal, and spatial restrictions ("Restriction Practice"). Functional difficulty was controlled by grouping pairs with similar skill levels. Flanker and Go-Nogo tasks were used. Results: Increasing complexity worsened cognitive performance (inhibition). "Restriction Practice" showed a significantly slower and less accurate performance in both tests than "Regular Practice" (p < 0.001). Experience positively impacted test speed and accuracy (p < 0.001). Conclusion: In sports, acute cognitive impacts are intrinsically linked to the task's complexity and the athlete's cognitive resources. In this sense, it is essential to adjust individually the cognitive demands of the tasks, considering each athlete's specific cognitive abilities and capacities.

Lights, Sirens, and Load: Anticipatory emergency medical treatment planning causes cognitive load during emergency response driving among paramedicine students.

Paramedics face various unconventional and secondary task demands while driving ambulances, leading to significant cognitive load, especially during lights-and-sirens responses. Previous research suggests that high cognitive load negatively affects driving performance, increasing the risk of accidents, particularly for inexperienced drivers. The current study investigated the impact of anticipatory treatment planning on cognitive load during emergency driving, as assessed through the use of a driving simulator. We recruited 28 non-paramedic participants to complete a simulated baseline drive with no task and a cognitive load manipulation using the 1-back task. We also recruited 18 paramedicine students who completed a drive while considering two cases they were travelling to: cardiac arrest and infant seizure, representing varying difficulty in required treatment. The results indicated that both cases imposed considerable cognitive load, as indicated by NASA Task Load Index responses, comparable to the 1-back task and significantly higher than driving with no load. These findings suggest that contemplating cases and treatment plans may impact the safety of novice paramedics driving ambulances for emergency response. Further research should explore the influence of experience and the presence of a second individual in the vehicle to generalise to broader emergency response driving contexts.

Temporal summation of second pain is affected by cognitive load.

This work attempted to clarify the interaction of cognition and pain sensitization during a paradigm of Temporal Summation of Second Pain (TSSP). We analyzed pain ratings and electroencephalographic (EEG) activity obtained from 21 healthy participants during the presentation of four experimental conditions that differed in the manipulation of attention to painful stimuli or working memory load (Attention to hand & TSSP; 0-back & TSSP (low cognitive load); 2-back & TSSP (high cognitive load); 2-back (without pain)). We found that the TSSP was reduced when the attention was diverted and the cognitive load increased, and this reduction was accompanied by higher midfrontal theta activity and lower posterior alpha and central beta activity. Although it is well established that TSSP is a phenomenon that occurs at the spinal level, here we show that it is also affected by supraspinal attentional mechanisms. Delivery of painful repeated stimuli did not affect the performance of the 2-back task but was associated with smaller amplitudes of attentional event-related potentials (ERPs) after standard stimuli (not the target). The study of brain activity during TSSP allowed to clarify the role of top-down attentional modulation in pain sensitization processes. Results contribute to a better understanding of cognitive dysfunction in pain conditions and reinforce the use of therapeutic strategies based on distracting attention away from pain.

The influence of cognitive load and vision variability on postural balance in adolescents with intellectual disabilities.

Introduction: This study aimed to investigate the impact of cognitive load, particularly its escalation during the execution of the same test, under varying vision conditions, on postural balance among adolescents with intellectual disability (ID). Methods: Twenty adolescents underwent balance assessments under different visual conditions (Open Eyes (OE), Closed Eyes (CE), Flash, Goggles, Visual Stimulation (VS)) and task settings (Single Task (ST), Dual Task (DT) without challenges, and DT with challenges). The cognitive test was assessed using Verbal Fluency (VF). Results and discussion: Significant effects were found for Task (p < 0.001, ηp2 = 0.85), indicating that CoP values significantly increased (p < 0.05) with the introduction of the DT. Dual Task Cost (DTC) demonstrated significant effects for Vision (p = 0.008, ηp2 = 0.62), with values varying significantly (p < 0.05) among different vision conditions, especially in CE and Flash conditions. Visual Dependency Quotient (VDQ) analyses revealed significant effects of condition (p < 0.001, ηp2 = 0.84), with significant changes observed in CE/OE and Flash/OE conditions (p < 0.05). Significant effects were observed for Cognitive performance in the Challenge condition (p < 0.001, ηp2 = 0.86), with decreased performance with cognitive task challenges, particularly in Flash and Goggles conditions (p < 0.05). In conclusion, cognitive tasks, especially challenging ones, and visual variations significantly impact postural balance in adolescents with ID.

Functional dissociation of the language network and other cognition in early childhood.

Is language distinct from other cognition during development? Does neural machinery for language emerge from general-purpose neural mechanisms, becoming tuned for language after years of experience and maturation? Answering these questions will shed light on the origins of domain-specificity in the brain. We address these questions using precision fMRI, scanning young children (35 months to 9 years of age) on an auditory language localizer, spatial working memory localizer (engaging the domain-general multiple demand [MD] network), and a resting-state scan. We create subject-specific functional regions of interest for each network and examine their selectivity, specificity, and functional connectivity. We find young children show domain-specific, left-lateralized language activation, and that the language network is not responsive to domain-general cognitive load. Additionally, the cortically adjacent MD network is selective to cognitive load, but not to language. These networks show higher within versus between-network functional connectivity. This connectivity is stable across ages (examined cross-sectionally and longitudinally), whereas language responses increase with age and across time within subject, reflecting a domain-specific developmental change. Overall, we provide evidence for a double dissociation of the language and MD network throughout development, in both their function and connectivity. These findings suggest that domain-specificity, even for uniquely human cognition like language, develops early and distinctly from mechanisms that presumably support other human cognition.

Cognitive load theory in workplace-based learning from the viewpoint of nursing students: application of a path analysis.

PURPOSE: The present study aimed to test the relationship between the components of the Cognitive Load Theory (CLT) including memory, intrinsic and extraneous cognitive load in workplace-based learning in a clinical setting, and decision-making skills of nursing students. METHODS: This study was conducted at Shahid Sadoughi University of Medical Sciences in 2021-2023. The participants were 151 nursing students who studied their apprenticeship courses in the teaching hospitals. The three basic components of the cognitive load model, including working memory, cognitive load, and decision-making as the outcome of learning, were investigated in this study. Wechsler's computerized working memory test was used to evaluate working memory. Cognitive Load Inventory for Handoffs including nine questions in three categories of intrinsic cognitive load, extraneous cognitive load, and germane cognitive load was used. The clinical decision-making skills of the participants were evaluated using a 24-question inventory by Lowry et al. based on a 5-point scale. The path analysis of AMOS 22 software was used to examine the relationships between components and test the model. FINDINGS: In this study, the goodness of fit of the model based on the cognitive load theory was reported (GIF = 0.99, CFI = 0.99, RMSEA = 0.03). The results of regression analysis showed that the scores of decision-making skills in nursing students were significantly related to extraneous cognitive load scores (p-value = 0.0001). Intrinsic cognitive load was significantly different from the point of view of nursing students in different academic years (p = 0.0001). CONCLUSION: The present results showed that the CLT in workplace-based learning has a goodness of fit with the components of memory, intrinsic cognitive load, extraneous cognitive load, and clinical decision-making skill as the key learning outcomes in nursing education. The results showed that the relationship between nursing students' decision-making skills and extraneous cognitive load is stronger than its relationship with intrinsic cognitive load and memory Workplace-based learning programs in nursing that aim to improve students' decision-making skills are suggested to manage extraneous cognitive load by incorporating cognitive load principles into the instructional design of clinical education.

WheelSimPhysio-2023 dataset: Physiological and questionnaire-based dataset of immersive multisensory wheelchair simulator from 58 participants.

This data paper presents a unique multimodal dataset collected from a comprehensive experiment using a wheelchair training simulator. The dataset consists of quantitative and qualitative data that represents the user's experience and performance. Participants engaged in a series of navigational tasks in a simulated environment under two distinct system configuration conditions: a. a conventional monitor display and b. a virtual reality (VR) headset. The monitor group has a total of 24 participants data while using the simulator with a standard display and then other two groups of 18 and 16 respectively using the VR headset with a different wheelchair's speed profile. It was collected data from total of 58 participants. The dataset includes physiological data - Heart Rate Variability (HRV), Electrodermal Activity (EDA), Acceleration (ACC), Skin Temperature, Heart Rate (HR), and Blood Volume Pulse (BVP) - collected during both experiments. Additionally, for the standard display condition, more detailed data comprising Electroencephalography (EEG) and eye-tracking metrics were recorded to provide insights into cognitive load and visual attention patterns. System metrics captured from the simulator provide an objective performance report, including task completion times, error rates (collision of the virtual wheelchair), number of joystick commands. Also, the navigation efficiency data is complemented by post-experiment questionnaires, which gathered subjective responses on user experience, perceived difficulty, the user immersive levels, arousal, and simulator sickness symptoms. This dataset is valuable for researchers and practitioners in the fields of assistive technology, human-computer interaction, and rehabilitation. It offers metrics to a comprehensive view of how different display technologies influence the user experience in wheelchair simulation training. The data allows for in-depth analysis of physiological responses, cognitive engagement, and subjective perceptions, providing a foundation for future research on effective wheelchair training methodologies and the potential benefits of VR in rehabilitation settings.

Concept mapping - increased potential as a retrieval-based task.

Concept mapping is a practical task for enhancing learning performance. Learners usually construct concept maps while studying the learning material or after studying. In the first case, the learning material is available during construction, and learners are less involved in retrieval practice from memory (study-based concept mapping; SCM). In the second case, the learning material is absent during construction, and the learners rely on retrieving information from memory (retrieval-based concept mapping, RCM). RCM is assumed to be associated with lower concept map quality and higher cognitive load but better elaboration and learning performance than SCM. This study investigated how the availability of the learning material influenced these variables in biology classrooms. Unlike other studies, this study provided learners with an authentic learning environment and prior concept mapping training. After the concept mapping training, n = 129 secondary school students were assigned to an SCM or RCM condition in a quasi-experimental design. As expected, students in the RCM condition constructed concept maps of lower quality but outperformed SCM students concerning elaboration activities and learning performance. The perceived intrinsic cognitive load was higher in the RCM condition. The results indicate that using concept mapping as a retrieval practice could support students' learning in biology.

Understanding The Role of Cognitive Load In Paramedical Contexts: A Systematic Review.

Objectives: Cognitive load refers to the working memory resources required during a task. When the load is too high or too low this has implications for an individual's task performance. In the context of paramedicine and emergency medical services (EMS) broadly, high cognitive load could potentially put patient and personnel safety at risk. This systematic review aimed to determine the current understanding of the role of cognitive load in paramedical contexts.Methods: To do this, five databases were searched (Elsevier Embase, ProQuest Psychology, CINAHL, Ovid Medline, and Ovid PsychINFO) using synonyms of cognitive load and paramedical contexts. Included articles were full text, peer reviewed empirical research, with a focus on cognitive load and EMS work. Two reviewers screened titles, abstracts, and full text using a traffic light system against the inclusion and exclusion criteria. The quality of evidence was assessed using the GRADE framework. This study was registered on PROSPERO (CRD42022384246). No funding was received for this research.Results: The searches identified 73 unique articles and after title/abstract and full text screening, 25 articles were included in the final review. Synthesis of the research revealed 10 categories of findings in the area. These are clinical performance, cognitive processes, emotional responses, physical expenditure, physiological responses, equipment and ergonomics, expertise and experience, multiple loads, cognitive load measures, and task complexity.Conclusions: From these findings it was determined that there is agreement in terms of what factors influence cognitive load in paramedical contexts, such as cognitive processes, task complexity, physical expenditure, level of experience, multiple types of loads, and the use of equipment. Cognitive load influences clinical task performance and has a bi-directional relationship with emotion. However, the literature is mixed regarding physiological responses to cognitive load, and how they are best measured. These findings highlight potential intervention points where cognitive load can be managed or reduced to improve working conditions for EMS clinicians and safety for their patients.

Identifying and Exploring the Cognitive Nature of Threshold Concepts in Pharmacology to Improve Medical Students' Learning.

Phenomenon: Pharmacology is a fundamental healthcare discipline, but it can be difficult and counterintuitive for learners to learn. Navigation toward understanding pharmacology can be troublesome, but once the threshold to comprehension is crossed, learners can experience a transformative shift in their ways of thinking and practicing. We conducted an in-depth examination of threshold concepts within pharmacology, aiming to identify and prioritize their learning to improve the medical curriculum and enhance medical treatment and patient safety. Approach: We carried out a consensus generation process using the Nominal Group Technique (NGT) to identify potential threshold concepts in pharmacology. Participant groups of pharmacology experts and medical students considered, identified, reviewed, and ranked potential pharmacology threshold concepts within their own group. Then, using a logical, step-by-step approach, we combined the final ranked data from these multiple NGT sessions. We further analyzed these data using an abductive analysis approach; data were coded, categorized, reorganized, and conceptually mapped after critical evaluation. Conceptual themes were established corresponding to different phases of cognitive schema development. Findings: Six comprehensive conceptual themes were identified: Drug Mechanism of Action; Pharmacotherapeutics; Pharmacokinetics; Drug Receptor Interactions; Drug Terminology and Nomenclature; and Signaling Pathways. These concepts align with many of the key attributes of threshold concepts (e.g., troublesome, integrative and transformative). The cognitive schematic themes generated were (i) acquisition-troublesome; (ii) acquisition-transformative; (iii) automation-troublesome; (iv) automation-transformative. Insights: Transformative learning involves different stages of cognitive schema evolution, including acquisition, elaboration, and automation, and is influenced by both the inherent challenges of the concepts and limitations of human cognition. The high interactivity of these troublesome concepts challenge schema acquisition and automation. Troublesome concepts underpinning procedures or skills, while not easily explained by cognitive rules, can lead to slow, awkward, error-prone performance, creating additional barriers for practice. Integrating concepts into a coherent structure leads to the irreversible assimilation of knowledge and the transferability of both knowledge and skills, influencing learners' epistemological transitions and ontological transformations at theoretical and professional levels. Further work on designing instructional models around assisting and automating schemas around identified troublesome knowledge, while addressing the impact of cognitive load, has the potential to promote transformational learning.

Harnessing open science practices to teach ecology and evolutionary biology using interactive tutorials.

Open science skills are increasingly important for a career in ecology and evolutionary biology (EEB) as efforts to make data and analyses publicly available continue to become more commonplace. While learning core concepts in EEB, students are also expected to gain skills in conducting open science to prepare for future careers. Core open science skills like programming, data sharing, and practices that promote reproducibility can be taught to undergraduate students alongside core concepts in EEB. Yet, these skills are not always taught in biology undergraduate programs, and a major challenge in developing open science skills and learning EEB concepts simultaneously is the high cognitive load associated with learning multiple disparate concepts at the same time. One solution is to provide students with easily digestible, scaffolded, pre-formatted code in the form of vignettes and interactive tutorials. Here, we present six open source teaching tutorials for undergraduate students in EEB. These tutorials teach fundamental ecological concepts, data literacy, programming (using R software), and analysis skills using publicly available datasets while introducing students to open science concepts and tools. Spanning a variety of EEB topics and skill levels, these tutorials serve as examples and resources for educators to integrate open science tools, programming, and data literacy into teaching EEB at the undergraduate level.