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• Published: 02 June 2022

A methodological perspective on learning in the developing brain

• Anna C. K. van Duijvenvoorde   ORCID: orcid.org/0000-0001-9213-8522 1 , 2 ,
• Lucy B. Whitmore   ORCID: orcid.org/0000-0002-5672-5081 3 ,
• Bianca Westhoff   ORCID: orcid.org/0000-0003-2481-5661 1 , 2 &
• Kathryn L. Mills   ORCID: orcid.org/0000-0002-6463-186X 3 , 4  

npj Science of Learning volume  7 , Article number:  12 ( 2022 ) Cite this article

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• Cognitive neuroscience
• Human behaviour

The brain undergoes profound development across childhood and adolescence, including continuous changes in brain morphology, connectivity, and functioning that are, in part, dependent on one’s experiences. These neurobiological changes are accompanied by significant changes in children’s and adolescents’ cognitive learning. By drawing from studies in the domains of reading, reinforcement learning, and learning difficulties, we present a brief overview of methodological approaches and research designs that bridge brain- and behavioral research on learning. We argue that ultimately these methods and designs may help to unravel questions such as why learning interventions work, what learning computations change across development, and how learning difficulties are distinct between individuals.

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Introduction.

Childhood and adolescence are considered natural times of learning and adjustment. In the first decades of life, changes in physical appearance, as well as cognitive and social-emotional development, are readily apparent 1 , 2 , 3 , 4 . What is, however, less readily observed are the profound changes in the structure, function, and connectivity of the brain. These changes underlie the development of skills and cognitive processes, for which input from the environment (i.e., experience) is required to fully develop.

Learning, defined as the gain of knowledge or skills through experience, can take on many different forms and can be studied at multiple levels. For instance, cognitive domains of learning—such as learning to read, or the ability to learn through feedback—can be studied together with measures of brain development to eventually inform our understanding of how children and adolescents learn in environments such as school and society. In this review, we discuss three methodological approaches with clear potential for advancing the study of learning in relation to the developing brain.

We will start this review with a concise overview of how the brain is changing over time in structure and function, and the role of plasticity in learning. We will first highlight the opportunities afforded by longitudinal intervention designs, which can inform approaches to understand learning processes during periods of substantial brain development. We then discuss a computational modeling approach that examines how people adjust to their environment based on the processing of positive and negative outcomes. In computational models, learning processes can be broken down into several steps—cognitive computations—that may help to formalize the process of learning and can be linked to underlying brain development. Finally, we highlight the importance of recognizing that developmental patterns differ across individuals when examining learning. As development is not the same for everyone, subgroups of individuals may share learning strategies or even struggles in learning. We will discuss methodological approaches that allow us to study individual differences in learning, and the degree to which these differences in learning are reflected in the developing brain.

Taken together, we present a developmental cognitive neuroscience perspective on child and adolescent learning by summarizing different methodological approaches and their potential combination with brain imaging techniques, such as magnetic resonance imaging (MRI).

Structural and functional brain development

Methods such as MRI have greatly advanced the study of the development of the human brain. The first years of life are characterized by a vast increase in cortical grey matter 5 , which is composed of neural and glial cell bodies, dendritic processes and synapses, as well as blood vessels. This initial overgrowth is followed by a reduction in cortical grey matter volume between roughly ages 8–25 years 6 , 7 . While the resolution of MRI does not allow for us to identify specific cellular changes occurring, the observed reduction in cortical grey matter during childhood and adolescence is thought to, in part, reflect synaptic pruning , in which the brain is cutting back and reorganizing synaptic connections potentially on the basis of how frequently they are used 6 , 7 . This reduction in cortical grey matter is a normative developmental pattern that can vary across individuals and also varies across regions of the cortex 8 , 9 . Another structural brain measure, white matter volume, is composed of the myelinated axons connecting distal regions of the brain and increases until mid-adolescence or early adulthood before it begins to stabilize 6 . This increase in white matter volume reflects, in part, the strengthening of synaptic connections between brain regions 1 , 10 . In short, these changes in the brain result in a more efficient and specialized brain system, with stronger connections between brain regions.

These developmental changes in brain structure are paralleled by changes in brain function and behavior in the affective, cognitive, and social domains 1 , 11 , 12 . Brain function is typically studied in task-based paradigms, examining individuals’ brain responses to a specific event, such as receiving negative feedback or a rewarding outcome. In addition to task-based paradigms, the intrinsic functional connectivity of the brain has been studied during scans called ‘resting-state’. In these scans, participants’ spontaneous brain activation is examined while they are lying in the scanner (but without falling asleep). Resting-state fMRI analyses are designed to probe functional brain connectivity . Functional brain connectivity refers to the correlation of activation signals between different brain regions or networks and is thought to signal to what extent these regions/networks are functionally related. Developmental studies have observed changes in functional connectivity strength, and changes in network interactions 13 . For instance, functional connectivity strength between subcortical and cortical brain regions increased with age 12 , and are tied to changes in reward-sensitivity and learning. Resting-state studies have shown that the brain becomes increasingly ‘modular’ (i.e., functionally segregated) across childhood and adolescence 14 , 15 . An increase in modularity is also seen in structural brain development 16 , and both these functional and structural network-level changes are shown to support the development of, for instance, executive functioning 14 , 16 . Resting-state and task-based studies can thus both provide unique insights into the development of a specific cognitive function or experimental manipulation, as well as the broad network-organization of the brain.

Although not the main focus of this article, when discussing the developing brain and learning, the importance of plasticity (i.e., the brain’s ability to change and adapt as a result of experience) is evident 17 . A typical distinction is made between brain plasticity that is experience-independent , in which brain changes unfolds, relatively independent of experience; brain plasticity that is experience-expectant , in which neural sensitivity is attuned to particular environmental stimuli during specific developmental windows (i.e., sensitive periods); and brain plasticity that is experience-dependent , which reflects experiences and environmental inputs that can vary between individuals and supports learning throughout life 18 . Neuroplasticity, particularly in sensitive periods, is related to molecular processes that can inhibit or stimulate brain plasticity through neurotrophic factors such as brain-derived neurotrophic factor (BDNF) that may result in changes in synaptic and neural pruning 19 .

An example of experience-expectant learning in the brain comes from the development of basic sensory processing regions. Seminal research on visual processing has demonstrated that the development of the visual cortex is dependent on relevant stimulation from the environment. Specifically, depriving visual input to one eye resulted in ocular dominance in the visual cortex of the eye that received input, and an absence of developing binocular vision 20 . Moreover, this work highlighted that the impact of experience on visual cortex development depended on the environmental input in a specific developmental window, referred to as a sensitive period . Sensitive periods are periods of heightened neuroplasticity to specific environmental input. They have been historically studied for the development of the visual neural system, yet are thought to occur across multiple cognitive and social-emotional domains such as language and face processing 17 , 21 . Experience-dependent learning, on the other hand, can be thought of as learning due to practice, exposure, or experience. This type of learning therefore depends on individual’s experiences and can occur at all points of ontogeny. Experience-dependent learning may contribute to brain development by gradually modulating brain connectivity, activation, or structure. The developmental cognitive neuroscience work we will discuss here focuses on experience-dependent learning in the brain across childhood and adolescence.

Learning shapes the developing brain: language

Although brain development may affect the efficiency with which we can learn about the world, or acquire a new skill, learning can also have an impact on brain structure and function at a level that can be measured through MRI, through observed changes in cortical thickness and changes in functional activation during task or at rest. Given that learning in cognitive domains often occurs at the same time as substantial development in both brain structure and function, it is a challenge to differentiate whether the observed changes in the brain reflect experience-independent maturational processes, or experience-dependent learning. In order to specify the areas of the brain that support learning in cognitive domains, we must be able to disentangle if an observed effect is related to the experience and not just reflective of maturational change that might occur in absence of the experience of learning a specific skill.

By taking an example of one skill that has to be explicitly taught in order to be learned, reading, we can begin to unpack these processes. The left arcuate fasciculus and inferior longitudinal fasciculus are white matter tracts that are considered crucial for skilled reading 22 , 23 . The left arcuate fasciculus connects anterior and posterior brain regions (i.e., frontal, parietal, and temporal lobes). The inferior longitudinal fasciculus connects the occipital lobe, important for vision, with the temporal lobe, which is—among others—important for semantics. In general, these two white matter tracts continue to mature during the same time as children develop reading skills across childhood and into adolescence. Longitudinal MRI studies have demonstrated substantial increases in fractional anisotropy (FA) in these two tracts from early childhood and into early adolescence 24 , 25 . This increase in FA is thought to reflect increased integrity of the white matter fibers. This may increase the potential for communication, and thus signaling between the brain regions connected by these tracts. Increases in FA within these tracts have been associated with improvements in reading skill in children 26 , and the rate to which the arcuate fasciculus and inferior longitudinal fasciculus increases in FA across childhood varies by the reading skill of the child 23 . However, in a given MRI study, how can we tell if it is the experience-independent maturational process or the experience of learning that underlies a change in brain measurement between two time points?

Longitudinal intervention designs are one possible method to disentangle maturational and experience-dependent processes in the brain. Although these designs might incur higher costs and burden on participants, repeatedly measuring the same individual over time brings unique opportunities to study ‘true’ development and the influence of experience. Further, the concurrent acquisition of behavioral and neuroimaging measures in these designs allows us to disentangle if change in a brain measure is coupled or uncoupled with change in the behavioral measure of interest. A recent study examined white matter integrity four times in children across the course of an intensive 8-week reading intervention and compared these children to a group of children who did not complete the reading intervention 27 . Participants of the intervention group were recruited based on parent reports of reading difficulties and/or a clinical diagnosis of dyslexia, and the control group was matched for age but not reading level 27 . By taking this longitudinal intervention approach, this study could compare the magnitude of experience-dependent learning (in this case, through a reading intervention) on white matter integrity to the magnitude of developmental change. This study identified the left arcuate fasciculus and inferior longitudinal fasciculus as being responsive to the experience-dependent learning in the cognitive domain of reading, as the observed change in integrity of these white matter paths was coupled to improved reading skill level in the children who received the intervention 27 . In contrast, this study also identified white matter paths that predicted a child’s reading skill level, but did not change in white matter integrity throughout the intervention, such as posterior callosal white-matter connections 27 . This finding suggests that some parts of the brain are already related to readiness to learn certain skills even during a developmental period marked by changes in brain structure.

When looking at evidence of learning on brain measures from another cognitive learning domain—second language acquisition—the age period when one learns a second language can result in differential effects on observed brain measures. For example, cortical thickness measures did not differ between monolinguals and bilingual individuals who acquired two languages simultaneously in early life 28 . However, bilingual individuals who acquired their second language later in childhood show differences in cortical thickness of the inferior frontal gyrus (thicker cortex in the left IFG, thinner cortex in the right IFG), and the magnitude of observed differences correlated with the age of second language acquisition 28 . Thus, multilingual individuals showed no difference in overall cortical thickness as long as they acquired their languages simultaneously, and only individuals who acquired another language later in life showed a difference in cortical thickness. Given that cortical thickness seems sensitive to experiences, such as later language learning, we must consider what differences in overall measures of cortical thickness could actually represent. Perhaps these group-level differences in cortical thickness changes are more likely to reflect the experience-dependent process of learning, which would be more in line with later second language acquisition, than learning that is expected to occur largely early in life. However, to answer this question, one would need longitudinal designs to compare the magnitude of change in cortical thickness observed in individuals who acquired a second language to magnitude of change observed in individuals of the same age who did not.

Using a computational modeling approach in the study of learning

One way in which we learn is by processing and integrating the good and bad outcomes we experience. For instance, through positive and negative feedback, we may learn to play a new videogame, learn to play the guitar, or learn the correct spelling of a difficult word. A computational approach can help us to understand these behavioral changes and formalize the process of outcome-based learning in the developing brain.

Computational learning models have been used to investigate questions such as how children, adolescents, and adults learn from positive and negative outcomes and integrate information into subsequent decision-making. An important element of learning in computational reinforcement learning models focuses on the difference between an expected outcome and a received outcome 29 , 30 . This difference, a so-called prediction error , forms the basis of a specific learning signal that indicates how much one should update expectations of the world, and thereby one’s subsequent actions. These prediction error computations have been linked to brain activation, as this learning signal was found to correlate with dopamine release 31 , 32 that would instigate neural activation. In the context of understanding learning, reinforcement learning models thus provide a computational link (e.g., a prediction-error signal) between brain-level processes and the observed behavior.

Research examining reinforcement learning in children, adolescents, and adults in combination with the developing brain, has shown that learning signals such as prediction errors are found in brain regions, including the striatum, medial prefrontal cortex, and hippocampus. These brain regions are linked to the processing of reward, value, and memory 33 . A number of studies have investigated differences in prediction-error learning in children, adolescents, and adults to understand sensitivities in learning across development. Some findings highlight that adolescents are particularly sensitive to positive prediction errors (feedback that is better than expected), resulting in higher neural activation in adolescents compared to children and adults in the striatum 34 . Moreover, adolescents outperformed adults in their learning performance, and the strength of functional connectivity between the striatum and hippocampus after positive (compared to negative) outcomes related to subsequent memory performance for positive events. These findings indicate that the striatum, and its closely connected regions (see also 35 ), may contribute to heightened reward-learning in some ages, and a bias towards learning from positive outcomes 36 . Note that other studies suggest that the valence-dependency in children’s and adolescent’s learning is context-specific. For instance, it has been observed that adolescents may be more prone to learn from unexpected negative outcomes than adults in other contexts, such as when reward-structures change quickly 37 , 38 .

Computational models may have several advantages for the study of learning 4 , 39 , 40 . A general advantage is that computational models allow to simulate behavior. Generating behavioral data with specific learning parameter settings, allows for better predictions of (expected) behavioral patterns and helps hypothesis testing as well as theory formation. A specific advantage of computational models for brain-behavioral studies is that they allow us to compute latent variables, i.e., variables (such as prediction errors) that cannot be directly observed in behavioral data, but that theory assumes is happening in the brain. These latent variables can be directly linked to brain activation and compared across groups or ages.

Taken together, combining a computational approach with measures of brain functioning allows us to examine learning at different levels of explanation. For instance, on a latent variable level, we can study whether different age groups weigh positive and negative outcomes differently or use different goal-directed strategies in learning 41 , 42 , 43 . On the other hand, developmental change may also occur at the brain (i.e., implementation) level. For instance, learning from experience can involve different brain regions or networks at different ages. Including these levels of explanation in the study of learning can help us to identify mechanisms of learning that may not be apparent, or cannot be disentangled, from observed behavior only.

Examining heterogeneity in the neurocognition of learning

Another challenge in learning research is to characterize individual differences in learning. Most of the studies on learning, or domains of learning, have focused on comparing brain and behavioral differences between ages or condition. This approach is useful for detecting mean-level differences. However, there may be striking heterogeneity in brain development and learning within groups. How could we target those in the study of learning?

An approach that behavioral studies have taken is to use clustering techniques that detect subgroups in the data. For instance, a recent study used such a data-driven approach and has grouped children based on behavioral measures across a range of learning domains, including reading, phonological processing, and executive functioning 44 . This study showed that within a group of 442 struggling learners, three distinct subgroups were found using this range of behavioral indicators. The first group showed symptoms of elevated inattention and hyperactivity/impulsivity. The second group was characterized by learning problems, and the third by aggressive behavior and disturbed peer relations. Moreover, these groups were distinguished by their structural connectivity of the lateral prefrontal cortex, cingulate cortex, and the striatum. In particular, aggression and peer problems loaded on the integration between the prefrontal cortex and the striatum. These findings support the idea that data-driven profiling can distinguish common learning problems in children and provide insight into the neurobiological mechanisms underlying these problems.

Another study from the same group used a clustering technique on white-matter microstructure in a sample of 313 children and adolescents 45 . This analysis showed that the group with higher white matter integrity in the cingulum had profoundly different cognitive abilities. Applying the cingulate-based grouping to independent groups of typically-developing children and struggling learners showed that children with lower cingulum FA showed lower performance across a variety of cognitive performance measures (e.g., fluid intelligence, working memory, and vocabulary) 45 . The value in this approach may particularly relate to children and adolescents with learning difficulties or psychopathologies that show complex behavioral phenotypes that may be better qualified with brain-based than behavioral subtyping.

A recent study compared sub-grouping profiles generated on behavioral measures (e.g., literacy, numeracy, working memory) and structural brain measures (i.e., regional cortical thickness, gyrification, and sulci depth) 46 . This approach was used on a sample of 479 children and adolescents consisting partly of struggling learners. The results based on behavioral measures indicated six cognitive profiles ranging from high- to poor performers on executive function tasks. A similar profile mapping based on structural brain measures indicated that neural and cognitive mappings for individuals were not one-to-one. That is, the same neural profile could be associated with different cognitive impairments in different children 46 . In a subsequent analysis, the authors observed that an individual’s whole-brain network (i.e., the connectome) of white-matter tracts was more strongly related to the cognitive profiles of struggling learners. Particularly, the hub-like structure of individuals’ brain network related to children’s cognitive abilities. Hubs are well-connected nodes in a network and are therefore assumed play an important role in the communication across a network.

Together, these results aid our understanding how the relationship between brain and cognition may be moderated by the organizational properties of developing brain networks. Consequently, it challenges the idea that a neurodevelopmental disorder (such as learning difficulty) is only linked to one specific neuro-anatomical substrate, and instead suggests that learning difficulties are likely to depend on the interactions and organizational properties between different brain systems 47 . These findings also add to the discussion on the transdiagnostic nature of cognitive developmental problems, in which developmental difficulties in learning reflect complex patterns of associations that are not easily matched to singular diagnostic categories.

Note that these reviewed studies identified subgroups using brain and behavioral measures. Although this approach allows to quantify heterogeneity in learning, brain-behavioral relationships can also be studied at the individual level. For instance, finding robust individual-differences markers may help to identify children at risk for developing learning problems. Moreover, questions of heterogeneity in samples have often been tested on cross-sectional datasets with wide age-ranges thereby missing a longitudinal developmental perspective. Finally, these reviewed studies focus on brain structure and not on brain function. Functional brain measures may provide a new mapping for learning profiles, which remains to be explored 47 .

Where do we go from here?

By drawing from research methods and designs in the domains of reading, reinforcement learning, and learning difficulties, we have presented a brief overview of methodological approaches and key findings in developmental cognitive neuroscience research on learning. We started with the central question of how maturational processes can be distinguished from experience-dependent learning. Longitudinal intervention designs are one possible method to examine learning potential and to disentangle maturational and learning-related processes in the brain. Then, we discussed the use of computational modeling for understanding and disentangling the processes that underlie age-related changes in learning from positive and negative outcomes. Computational modeling approaches are rising in developmental studies, and such studies can move this field forward by quantifying the changes in learning processes over age, and their relation to changes in the developing brain. Finally, we discussed handling individual differences using clustering techniques to find data-driven subgroups that may share a commonality in behavioral learning difficulty, or neural patterns of connectivity and/or brain structure. These findings highlight that not all learning brains are the same, and that methods for detecting individual differences are applicable using brain- and behavioral measurements.

Developmental cognitive neuroscience studies have the potential to advance our understanding of learning by combining innovative research methods with longitudinal datasets capturing development from micro (genes, brain) to macro (behavior, environment) levels 48 . That is, (more) rich longitudinal studies are needed to understand learning and learning challenges within individuals, and to address outstanding questions on how interactions between individual characteristics, experience, and environmental influences shape learning across development 26 , 48 , 49 , 50 , 51 . In the methods discussed in this review, the longitudinal element is sometimes central (such as in intervention studies), whereas in other methodological approaches they have yet to be integrated (such as computational modeling approaches). Longitudinal brain research may also help towards better characterization of normative developmental trajectories, and the consequences for functional and structural brain development (see for instance an overview of normative structural development papers 52 ). Eventually, these insights may help in understanding how for instance psychopathology may be explained as a deviation from normative development 53 . Given that longitudinal studies within the field of developmental cognitive neuroscience are time-consuming, valuable, and dependent on long-lasting research funding, the large longitudinal datasets that are becoming increasingly accessible (e.g., 54 , 55 , 56 , 57 ) will be important for advancing the field and examine the neurodevelopmental changes of learning.

In this review, we focused predominantly on individual learning. However, learning obviously does not happen in a vacuum, and humans learn the vast majority of their knowledge from other humans or are influenced by the social context of learning. Learning in a social context is hugely complex and encompasses interactions between learning and the regulatory demands of a social context (e.g., distraction by others), motivational processes (e.g., the desire to interact and engage with others), and our experience with others (e.g., learned trustworthiness of others). As such, an individual’s social context can impact the rate of learning, as well as what is learned in a given situation depending on the developmental period. For instance, reinforcement learning models have been used to study how we update our expectations about others across development and how this is distinct from non-social learning (e.g., 58 , 59 , 60 , 61 , 62 , 63 ). Although the social context of learning warrants a review article of itself, we do want to highlight that the methods displayed in the current review are also valuable to apply to research that studies learning in a social context.

Taken together, the study of behavioral learning can benefit from both structural and functional MRI research. We discussed methodological approaches that aim to unravel why learning interventions work, what learning computations change across development, and how learning difficulties are distinct between subgroups of individuals. These corresponding findings indicate that these approaches have the potential to have a lasting impact on promoting children’s and adolescents’ positive development.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

No datasets were generated or analyzed during the current study.

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K.L.M. was supported by the Research Council of Norway, grant number 288083. A.C.K.D. and B.W. were supported by an Open Research Area (ORA) grant, grant number 464-15-176, financed by the Netherlands Organization for Scientific Research (NWO). A.C.K.D. was supported by the Gratama Foundation and the Leiden University Fund. We thank Marieke G.N. Bos and Kiki Zanolie for carefully reviewing the manuscript.

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Specific Learning Disorder

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Dyscalculia ; Dysgraphia ; Dyslexia ; Learning disabilities

The current chapter reviews and integrates conceptual and empirical research on specific learning disorder (SLD), including the following core topics: the definition and diagnostic criteria for SLD; its comorbidity with other disorders such as attention deficit hyperactivity disorder; its etiology; common practices for assessment and diagnosis; various domains of functioning such as academic, behavioral, and socioemotional adjustment; and major directions for intervention. This chapter uniquely focuses on adolescents with SLD, considering that trajectories are set during adolescence and young adulthood that can lead to difficulties in adulthood.

Introduction

Specific learning disorder (SLD) is one of the most common neurodevelopmental disorders in children and adolescents, with 5–15 % prevalence rates across different languages and cultures ( Diagnostic and Statistical Manual of Mental Disorders – DSM - 5 ,...

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Al-Yagon, M., Margalit, M. (2016). Specific Learning Disorder. In: Levesque, R. (eds) Encyclopedia of Adolescence. Springer, Cham. https://doi.org/10.1007/978-3-319-32132-5_806-1

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Students with specific learning disabilities experiences of pre-registration physiotherapy education: a qualitative study

• M. Norris   ORCID: orcid.org/0000-0001-7779-5612 1 ,
• J. Hammond 2 ,
• A. Williams 3 &
• S. Walker 2  

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Attainment gaps for students with disabilities have been noted in pre-registration physiotherapy courses in the UK. Previous research suggests disclosure, lack of staff knowledge and poor communication between University and placement sites may be relevant, but these are limited to small case studies with students with visual or physical disabilities. The purpose of this study was to explore disabled physiotherapy students’ experiences of their education in order to elucidate factors that may influence success.

Qualitative study drawing on phenomenological traditions. Four focus groups including 15 students with disabilities were conducted. Transcripts were analysed thematically. Procedures for transparency and rigour such as member checking and peer debriefing were implemented.

Three major themes were derived from data. “It was quite a relief” explores the personal and social implications of diagnosis. “They’re not natural” focuses on academic assessment and the specifics of adjustments made and not made within that context. “My dyslexia doesn’t switch off” explores the inaccessibility of the learning environment and dissects the contrast between the 24-h nature of having a specific learning condition and the somewhat piecemeal nature of adjustments during their education.

Conclusions

This study indicates that having a specific learning disability or anxiety creates a number of hurdles to success in physiotherapy education. Most were within the University setting and were perceived to result from staff ignorance or piecemeal approaches to inclusion. A lack of consistency alongside facilitated dialogue and acknowledgement of enhancements results in frustration, ambiguity towards disclosure and reinforcement of a deficit model. Such an approach belies the intention of the profession and the NHS and does not maximise the potential of widening participation.

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There has been a specific focus on widening participation to higher education in the United Kingdom (UK) and worldwide since the beginning of the twenty-first century. Initial focus in the UK was on improving access and increasing participation for all [ 1 , 2 ]. However, in the last decade evidence has emerged of attainment inequalities [ 3 ]. Hence attention has been drawn to not only making higher education accessible to all, but also ensuring that those who enter successfully complete their course of studies. This has been bolstered by the Equality Act published in 2010 [ 4 ], and specific action to monitor metrics of learning gain through the Teaching Excellence Framework [ 5 ], practices to enable equal access and appropriate support for all.

Disability is one area where attainment inequalities have been found within higher education. This is of specific relevance to physiotherapy, as 12% of pre-registration students across all UK Higher Education Institutions (HEIs) declared a disability in 2016–17 on entry to their course [ 6 ], with the majority reporting dyslexia or other specific learning disabilities. This is equivalent to national data for all courses in 2016–17 [ 7 ]. The physiotherapy profession has a long history of including people with disability within education and the workforce, in particular people with visual impairment [ 8 ]. This is supported by the National Health Service (NHS) which has stated the aim of employing people with disability [ 9 ]. However, a number of issues have been raised within the literature.

First is a recent study which demonstrates an attainment gap exists for pre-registration physiotherapy students with a disability, particularly those studying on pre-registration MSc courses [ 10 ]. While this study in physiotherapy mirrors a pattern in medicine, dentistry and higher education more generally [ 11 ], it did not explore potential reasons for attainment inequalities; other related literature in physiotherapy may give some indications. Reluctance to disclose disability before, during and after clinical training has been highlighted as an issue due to concerns with negative judgement and prejudice [ 8 , 12 , 13 ]. Likewise, poor levels of staff knowledge and familiarity with specific disabilities, has been linked with reduced acceptability and unsupportive behaviour [ 14 ]. This has specifically been related to placements where communication between sites (clinical and academic personnel) has not been optimised [ 12 ].

Research in higher education in other clinical professions is more prolific and highlights additional concerns such as the construction of disability within education generally and the consequential focus on ‘adjustments’ in a concessionary structure [ 15 ]. Stigma, marginalization and discrimination have been noted, both directly in universities and with clinical staff but also indirectly through the regulatory frameworks related to fitness to practice [ 16 , 17 , 18 , 19 ]. In contrast, studies also highlight agency of students with disabilities with potential enhancement as a consequence of living with a disability [ 15 , 20 ]. To date it is not explicitly known how these relate to the broad experience of physiotherapy education, or disabilities such as dyslexia. Likewise, while there are a number of recommendations for inclusive education [ 21 ], it is not clear how these are being implemented and perceived in physiotherapy.

To complicate things further, the term disability itself is debated. We have approached this research with an awareness of current debates, but without a specific lens, remaining open to the various narratives of the participants. Given the literature on stigma and discrimination [ 8 , 12 , 13 , 16 , 17 ], we are mindful of the social model, where focus is directed towards barriers created by society [ 22 ]. However, in-keeping with critiques of this model we acknowledge that a focus on society should not detract from a need to consider the individual and their specific situation which is strongly supported in the limited physiotherapy literature [ 8 , 23 ]. Furthermore, recognizing the narratives on agency and enhancements [ 15 , 20 ] draws attention to the affirmative model in which the celebration of positive social identity and ownership of impairment is highlighted [ 24 ]. In contrast, Campbell’s [ 25 ] call for a more radical refocusing of disability studies that critiques the processes and practices that support and perpetuate ableism as homonormativity within society, requires a consideration of how those processes and practices may play out in physiotherapy education. This is in part reflected by Bryne [ 26 ] who reminds us to remain vigilant to the dominant discourse of ability in which ‘support’ and ‘adjustment’ are considered both as unfluctuating and as a concession which have to be earned through assessment and evidence.

Within this context, the purpose of this study was to explore disabled physiotherapy students’ experiences of their education in order to elucidate what factors might be relevant in student success. Due to the dearth of literature in physiotherapy it was impossible to predict which factors (social/environmental/individual) are more prominent in the lived experiences of physiotherapy students. Therefore, the study purposefully focused on the broad educational experience of the participants so that any factors relevant to them could be raised.

This was a qualitative study informed by phenomenological traditions [ 27 ], in-keeping with the focus on the students’ experiences of life as a student physiotherapist with a disability.

For practical reasons two HEI’s in the South East of England were chosen to conduct the study. The total pool of students studying BSc and MSc pre-registration courses was approximately 500, therefore there were approximately 60 potential participants based on the 12% prevalence estimate of physiotherapy students with a disability previously indicated [ 6 ]. Students at the two HEI’s were invited to participate in the study via a cohort wide email. Inclusion criteria included current students, who had completed both academic modules and clinical placement and who had a confirmed disability (self-declared but also documented in University records). To maximize inclusion further sampling restrictions were not included. This can be considered a convenience sample [ 28 ] of those with the relevant experience to respond to the study aims.

Focus groups were selected given their ability to support collective responses and increased depth often prompted through interaction. A focus group at the penultimate (MSc yr 1 and BSc yr 2) and final (MSc yr 2 and BSc yr3) year level were conducted at each HEI to explore the shared phenomenon of physiotherapy education. They followed a topic guide developed in relation to previous literature and discussed and agreed by the research team (Additional file  1 ). It included opportunities for participants to discuss their identity, positive and more challenging experiences in university and placement, garner their thoughts on the previous study that showed an attainment gap [ 10 ] and opportunities for enhancement. Open questions were intentionally used in order to avoid leading participants in particular apriori directions.

All focus groups were facilitated by experienced qualitative researchers from outside the host institution, and therefore were previously unknown to the participants, who were also physiotherapy faculty members (MN with AW as co-facilitator, JH with SW as co-facilitator). One had a disability which was shared with the participants in order to enhance an atmosphere of openness. The focus groups were audio-recorded and key points were noted on flip charts during the focus groups to aid in collective member checking of the data. This was deemed particularly important as all researchers are academic faculty and these checks served to highlight potential presuppositions of priority areas.

Audio-recordings were transcribed verbatim and anonymised. They were analysed thematically by one lead researcher [ 29 ]. This followed a process of familiarisation through reading of the transcripts, detailed inductive line coding and iterative development of categories and super-ordinate themes. An example of a thematic tree is given in Fig.  1 . Negative case analysis was conducted to check thematic development. Three co-researcher’s read the transcripts closely and engaged in critical discussions with the lead researcher to enhance depth of analysis and transparency. One of these researchers has a specific learning disability which offered the opportunity to consider a perspective from inside the community and to challenge potential emergence of ableist discourse.

Example thematic tree

The sample included 15 students (11 F, 4 M, 12 BSc, 3 MSc) with a range of predominantly specific learning disabilities including dyslexia, anxiety, dyspraxia, Attention Deficit Disorder -ADD and Attention Deficit Hyperactivity Disorder - ADHD (Table  1 ). While one student with physical disability volunteered, they were unable to attend the focus group. The focus groups lasted on average 92 min (range 83–99).

Three major themes were derived from the focus group data. The first theme “it was quite a relief” explores the personal and social implications of diagnosis on a bedrock of previous hard work and social ignorance. “They’re not natural” focuses on academic assessment and the specifics of adjustments made and not made within that context. The final theme “My dyslexia doesn’t switch off” highlights aspects of education delivery which are not ideal to access learning. Students noted that while these issues would resonate with most students, they had particular significance for those with specific learning conditions. These illustrate the contrast between the 24-h nature of having a specific learning condition and the somewhat piecemeal nature of adjustments during their education. This theme ends with a clear call for institutional practices to support rather than hinder the self-management strategies that the students own. On the basis of the experiences discussed in the focus groups, students suggested specific recommendations to education and practice. These are presented in the discussion.

“It was quite a relief”: the personal and social implications of diagnosis

As a starting point the students shared their own personal histories of struggle. Most had completed the majority of their earlier education without any formal diagnosis and therefore described how they had often felt isolated and somewhat confused by the difficulties they faced as this female participant describes:

“I was diagnosed with dyslexia when I was 19. Beforehand I’d struggled all the way through…so I was just average but working extremely hard to be average…I think if you don’t know …then you feel like you’re struggling by yourself…no one understands” F3 FG2

One student related how this lack of understanding of herself and her condition impacted on her emotionally resulting in a diagnosis of anxiety at an earlier age. Yet these are students that had succeeded in their education despite this lack of knowledge and support and the sense they were working harder than their peers in order to achieve resonated through all focus groups.

While diagnosis came late for the majority and the categorisation as having a disability itself was not unproblematic, when it came it was met with a degree of relief:

“I quite like it [diagnosis]…it was quite a relief…it justifies things…I could identify an issue” They later continue, “it’s kind of something to make me aware, I’ve got an idea of how I think and I’ve got some ideas of where I should go with it” M1 FG1

Diagnosis was usually accompanied with detailed reporting of their own specific condition. As the participant above indicates this knowledge led to understanding and a re-framing of their previous struggles. Participants talked about a sense of empowerment, awareness and insight which ultimately led to clearer ideas of personal action and acceptance which this example shows:

“once I understood it, it kind of made me feel a lot better about myself and just umm, those negative emotions and feeling they kind of dissipated a lot over time, it’s cos I understood better myself.” M2 FG1

The positive benefits of detailed reporting were noted particularly when they were accompanied by a clear and relevant introduction to strategies and how they could be implemented in real life. For one student this came through work alongside an Occupational Therapist, while another noted the usefulness of a report which specifically focused on physiotherapy related skills.

This reframing of their past history led to an increase in confidence but also appreciation of the positive traits. The students discussed their increased capacity to problem solve, be creative with ideas, look outside the box and have empathy with people who struggle, all skills which they saw as relevant additions to their future careers as therapists. This personal understanding was not present for all, influenced by the timing of their diagnosis, or the recent onset of new challenges such as placement. For those most recently diagnosed (within the last 12 months), their strategies were still developing and the work of re-understanding and reframing was still in progress.

The majority of the participants were not diagnosed until University (current or previous degree), which raised the issue of identification processes. The driver to seek testing came from a number of sources: previous work colleagues, medical personnel, personal tutors, a generic talk at induction, advice from other students and placement educators. While all were grateful for the prompt, and the awareness of role models within the profession was noted particularly favourably, the haphazard way in which it occurred was the source of concern for the participants. Students strongly expressed the need for early identification to maximise their capacity on the course which they indicated required more robust and reliable processes of identification.

“I suppose one of the really key things is just getting diagnosed like early, so you can get support in place, I suppose that's quite a major part” F10 FG4

Early identification and diagnosis, for many, lay in better awareness of the conditions. The students discussed many misconceptions they held prior to their own diagnosis, relating conditions such as dyslexia with lower intelligence. But while their own understanding developed, there were significant concerns raised about others in society, including in the academic arena. Some students reported not declaring their disability on their application for fear of judgement as a ‘problem’. This also extended to disclosure on placement through concerns of being treated differently or being supervised by staff who are “not gonna know where to start with you” F2 FG1. Mostly though, the students described positive experiences on placement with staff who were well informed or indeed had specific learning difficulties themselves. The majority of the issues raised were within the Universities themselves and specifics of this will be discussed in the following themes.

Overall this theme illustrates the complex journey students with disability have in relation to diagnosis and subsequent understanding of self. They highlight the importance of early and consistent identification which requires better awareness of conditions and signposting.

“They’re not natural”: the false glare of assessment

This theme unpacks the assessment process and how students perceive their disability within that specific context. While the participants on the whole were appreciative of adjustments made to exams, their insights draw on potential misconceptions about their conditions resulting in apparently random decisions on adjustments to assessment.

Of particular concern were practical exams and participants consistently raised their frustration and confusion over the lack of adjustment to these assessments. A key feature of this was a lack of adjustment in time. While it was inconsistent, most described additional time for reading components of practical exams but nothing for the actual delivery of the practical skill and discussion. For them, this separation between reading and oral/aural/practical components made little sense when they had recognised problems with processing and organising information. For them this was often harder in aural/oral form then in written, which led to high levels of anxiety about the questioning processes in such exams as this example demonstrates:

“I find it hard when they ask you questions on the spot and you don’t have a couple of minutes to process it…I find if I take a couple of minutes I can produce quite an outstanding answer, but if you want answer like that, which in the exam conditions you just kind of go blurgh” F3 FG2

The anticipation of facing these exams without additional time created a vicious circle for these students. Knowledge of their own challenges with processing and delivery, led to fear of not completing the exams on time. This created anxiety and pressure to speed up, which resulted in more errors and heightened awareness of their difficulties.

A further challenge was distraction within their exam. For written assessments they were often in a room with few students or on their own. However, with practical exams they were with other students with several exams happening simultaneously. While they appreciated the complexity of organising such exams, this format resulted in a mix of distraction and pressure. The noise of others speaking and moving disturbed their focus, already a recognised challenge for many, and as a result they had to regather their thoughts, ask for questions to be repeated or misunderstood what was being asked of them. All were seen to contribute to additional stress, loss of time, but also the potential of responding to what they thought they had been asked rather than the actual question/task.

“I’ve had to ask a number of times for them to repeat the question to me because I’m fixing on something else, or like I hear a beep or something’s happening and they’ve asked me a question and cos you’re under pressure and time, I’ve suddenly forgotten, I wasn’t even listening to the question and that, I then need to ask, “Oh sorry, can you repeat that again?” F1 FG1

The participants in these focus groups frequently commented that the problems they faced were common to all students, but highlighted that they were exacerbated when you had a specific learning difficulty.

Many had raised their concerns about the lack of adjustments with academic tutors and had been told that exams were designed to mimic the clinical environment. However, this contrasted with experiences on placement where they described a greater willingness of colleagues to consider adjustments as demonstrated here:

F10: “I asked about that first year for my bad auditory memory for practical exams and they said to me, it’s not like the actual setting of being on placement…but I got extra time for my initial assessments [on placement]…When you’re here (university) they’re sort of well that’s not how it’s gonna be in real life”

F8: “but you’re learning, there’s a difference…we’re learning at uni so we should get extra time…which is why we get extra time on placement” FG4

They highlighted numerous cases where exam conditions created problems which were never replicated on placement. Time was one factor, as students described a number of placements which considered additional time to be a holistic requirement not just for writing notes. Similarly, instructions and feedback were adjusted to be given on paper rather than verbally to assist with processing and retention. Likewise, students were encouraged to create templates as memory assistance while on placement, whereas in exams they were entirely reliant on immediate recall. Mostly though it was the pressure of exams and the intense time limited focus on the student. This restriction was not perceived in clinical practice leading the participants to conclude that the assessment process placed a false glare on their abilities.

“Again it’s not natural, when you do it you’re in a placement on a ward, it’s so natural you just do it whereas in an exam in the OSCEs [Objective Structured Clinical Examination] you, as I said, it just doesn’t feel…“F3 FG2

This theme highlights a clear perceived discrepancy between how practical assessments operate within the university environment, which are not replicated within the clinical field. The complex processing and problem solving required within case based practical exams appeared not to be considered, coupled with limitations placed on strategies participants were encouraged to develop when working clinically.

“My dyslexia doesn’t switch off”: inaccessible learning environments and piecemeal approaches to disability support

In the previous theme, an acceptance that some experiences may parallel those of non-disabled students became apparent. This next theme dissects the minutiae of the learning experience, unpacking features that create general inaccessibility, but which further impact on students with specific learning difficulties. This highlights a perceived piecemeal approach to support which contrasts with the 24 h experience of living with a disability.

Students consistently flagged the lecture arena as a complex minefield to navigate. While they acknowledged their lecturers were generally knowledgeable and engaging, the forum of the lecture, it’s structure, pace and density of material, as well as length were seen as a significant obstacle to learning. Students referred to ‘zoning out’ or metaphorically ‘leaving the room’ while remaining in it as words washed over them. The result was frustration, not only in their lack of understanding but also the awareness that they had lost time which they would have to compensate for later.

“I leave a lecture and I can hear some people being like “oh that’s really interesting” and I’m like you heard that? When was that mentioned 'cos I’ve not picked that up?...because to me it’s like someone throwing stuff at me, but in no particular order for me to actually contemplate or even put down on paper what they’ve said…it’s a bit of a set back for me ‘cos I feel like now I’ve got to go and do double the work to try and actually understand what that hour lecture was actually about” F2 FG1

A specific challenge was the necessity to write notes while listening and trying to understand. This was deemed essential as the students perceived many lecturers left slides minimally populated. This was matched with a perceived delay in posting slides prior to lectures so participants had inadequate time to familiarise themselves with the material to ease the complexity of the lecture format. Of particular note here was the participants understanding that the decision to have minimalist slides and late posting was a positive decision by lecturers based in part on pedagogical principles. This frustrated the students at a number of levels. First was the sense that their learning styles may be different to standard research as this participant describes:

“it was kind of like that kind of paternalism of “this is how you should learn”, which I think they can be really frustrating because it’s not actually, it might be the best way to learn in terms of research or whatever but we learn differently” M1 FG1

But it was not just a potential mismatch between their learning style with research, but also on perceived intention. The students in this research interpreted the lack of detail and delay as obstruction by lecturers, reinforced by a lack of change following requests. The consequence was they perceived a lack of flexibility for them to use their own style and strategies to maximise their learning and indeed take ownership of their learning.

Timely posting of material generally was raised in relation to Virtual Learning Environments (VLE’s), the online portals where most learning resources are stored. The students suggested that a key strategy for most of them was to organise themselves early, so they knew what they needed to attend to well in advance. This was rendered impossible when materials were not posted in good time. But they also commented on their frustration when the location of materials changed, different modules posted things in different, seemingly random places or indeed the VLE itself changed.

Other areas participants highlighted included class numbers and room layout, all perceived to impact on their ability to engage. These students were aware that ‘putting things together’ is often an area that they have to work hard to achieve. Rather than facilitating that process, the academic practices created further obstacles which they were forced to navigate. As this participant suggests:

“So I think here they just limit it, you’ve got dyslexia, great, we’ll help you if you need to. Here’s extra time in exams, but that’s it. They (staff) don’t think about things like, so the presentations and what they look like and how visually it can affect. They don’t think about room sizes or, you know, one to one sessions or smaller group sessions and I think that is, is a big thing”. F3 FG2

Other points raised were the perception that timetables and group changes were haphazard which limited capacity to plan ahead or work with the people who understood their learning styles. The participants suggested that changes came with a lack of adequate explanation as to why they had occurred or an appreciation that such changes were disproportionately disruptive to some students with disabilities. For the participants in this study, this rather piecemeal approach to their disability was frustrating. They sensed that support was inconsistently applied which was in direct contrast to their 24-h experience of living with a disability.

For many this was a result of perceived staff ignorance of their diagnosis. While examples were given on placement, more often participants discussed clinical educators who themselves had specific learning difficulties. They were mostly seen as allies. Consequently, the call for more education was firmly directed towards University based staff.

“Personally in the physio department there’s not a big awareness of specific learning difficulties I don’t think…. My educator, I’d be on placement for two weeks, said I think you maybe should consider going and get tested, I’d been at university for two or three years now and I know, I get on with the lecturers and I give them pieces of work to have a look at, none of them advised that I get a test or anything like that “F6 FG3

This sense of staff ignorance was not universal, but like the adjustments was seen as piecemeal. It was chance if you had a tutor who recognised signs, made the effort to signpost appropriately, and who made suggestions on how placement could be approached. And chance was considered a problem.

Cumulatively, this lack of awareness, lack of consideration of the on-going challenges of studying with a disability and adjustments that were only periodically considered had one overriding impact on the participants; an impedance to them managing their own situation. This disempowerment lay at odds with a clear sentiment across the participants in this study, that they were aware of their own dis/abilities and they were very willing to take ownership of their personal situation.

The narratives from this group of students with disabilities highlight a number of aspects which they associate with potentially impeding their success.

Early identification and orientation to the physiotherapy context facilitated recognition, understanding and development of strategies in order for these students to succeed as the independent professionals they aspired to be. When successful, these processes had the potential to shift the participants’ identity resulting in confirmation of their skills and capabilities. Clouder et al. [ 15 ] note that students with a disability often have strong agency and a desire to engage. This was also evident in this study as the participants demonstrated how an understanding of self, resulted in a desire to reject the deficit view of their disability and affirm their positive skills and attributes, possibly reflecting an emerging affirmation model [ 24 ]. The findings suggest that the process of transformation and the students’ confidence in engagement was hampered as a consequence of inadequate and inconsistently applied systems and staff ignorance. Therefore informed, proactive, timely and responsive systems that are equitably delivered to maximise the students’ potential for self-discovery and development are important and may impact positively on their successful progression in the course.

The further findings from this study illustrate some of the challenges of the learning environment and practices for students. Interestingly, issues identified were most frequently situated within the university arena rather than the clinical environment which is surprising, given that previous literature in the field has largely focused on the practice environment [ 8 , 12 , 13 , 18 , 19 , 23 ].

One issue relevant to the clinical and university settings was ambiguity in disclosure. Disclosure of their disability was rarely discussed by the participants in relation to potential prejudice as described by other authors [ 8 , 30 , 31 , 32 , 33 , 34 , 35 ]. Rather, in-line with Opie and Taylor [ 13 ] concern was situated once more in ignorance. On one side the students were unclear how their disability may impact on placement and as a consequence questioned the need for disclosure. On the other, the students perceived their educators both at university and on placement to be ignorant of specific disabilities and therefore disclosure may not be met with a supportive response. This insight suggests that the ambiguity around disclosure requires more nuanced examination and perhaps further exploration of qualified staff awareness of disability (particularly specific learning disabilities) is needed.

In relation to the university environment, numerous examples were highlighted by the participants indicating how their engagement and assessment potential were hampered. These raise some significant questions about what might be done to make the education experience more inclusive and what adjustments might be considered reasonable alongside the expectations of professional behaviour and competence. Understanding these opportunities may assist in facilitating engagement and subsequent assessment success.

One example noted by the students was the inaccessibility of the learning environments, whether through lecture format and notes, class sizes and structure or the virtual learning sites. A number of possible contributing factors were implied for this apparent lack of consideration of the wider features of education delivery such as: i) lack of familiarity of staff with principles of inclusive education (as described by Hockings [ 21 ]), ii) a lack of willingness to deliver on it or alternatively iii) a mismatch between the students’ expectations of specific delivery methods (e.g. introductory lectures) and the pedagogical considerations by the faculty. What was explicit in this study is that standardised and inflexible teaching and learning practices actively impede the students’ engagement, autonomy and management of self, a view supported by related literature and linked to success [ 20 , 26 , 36 , 37 ]. Furthermore, there appeared to be little opportunity for effective dialogue with academic staff to redress this.

A potentially more complex example was that of a lack of consideration and flexibility in practical examinations. The ability of these assessments to reflect clinical reality was questioned by the students who found the clinical environment to be more accommodating of alternative ways of processing and delivering information. This contradiction in experience raises some key questions about the purpose and process of practical assessments.

While personal fitness to practice was not expressly raised in this study, the implied necessity of clinical competence suggests the concept of ensuring students are fit to practice may influence faculty staff decision making about flexibility within practical assessment. For instance, extra time adjustments may be given for reading preparation but not within situations that apparently replicate a clinical encounter, which is similar to guidance for medical education [ 38 ]. However, this neither considers the iterative real time clinical reasoning processes that occur during practical examinations that were often described by the participants in this study. Nor does it potentially reflect many therapeutic clinical encounters in which the assumption of immediate and time restricted response (for purposes of safety) are not necessarily required. Discrepancy is also noted in students’ descriptions of proactive use of templates to support their organisation and decision-making while on placement which are explicitly not permitted within university assessments. Interestingly, alternative formats for students to respond to clinical questions, such as use of paper and diagrams, is recommended by the General Medical Council [ 38 ].

As a consequence, the very purpose of reasonable adjustments is questioned and a dilemma of prioritising safety over effectiveness is created (also reported in nursing education [ 39 ]). A focus on examination competence that does not reflect clinical need and competence suggests an approach to university assessment based on homonormativity and ableist processes. This limits students’ potential and autonomy, decreases their capacity to explore and be appropriately assessed on strategies they could use in practice, but also inappropriately homogenises all clinical situations. Eaterbrook et al. [ 20 ] and Bulk et al. [ 36 ] note that there needs to be greater clarity on necessary competencies and appropriate inflexibility alongside acceptance of where approaches and structures can be changed. A more considered approach to practical based assessments which involves closer dialogue with both clinical partners and students would result in an improved capacity to align assessment with clinical reality and assist visibility of decision making. This is particularly required given that currently the students perceive that the support they receive on placement is more appropriate and flexible and utilises their enhanced skill set rather than remaining in a deficit model.

A key aspect of these findings is that understanding these students’ experiences and the implication of education has broad relevance. Their narratives are a challenge not only to how education providers engage with students with disabilities, but how they engage with educating all students. Shakespeare [ 40 ] calls for a deconstruction of an assumed normality and in highlighting discontinuities in their experience, which they note impacts on all students, the students in this study echo that call.

The overall sense of these data is that these students are caught within a focus and indeed the language of deficit by a system that they perceive prioritises normalisation, while they indicate a desire to explore, affirm and express their able diversity. Adjustments for them were not seen as a concession to normalise but an opportunity to learn and perform to the best of their ability and reflected their experience in the clinical environment. This lay in contrast to what they perceive as the fractured institutional processes which appeared to remain in concessionary structure, but specifically one that only pertained to particular tasks, reading and written assessments. As a consequence, the inclusivity of the curricula and its delivery may be questioned, and the opportunities to celebrate able diversity need to be reconsidered.

This study has number of strengths and limitations which are important to consider. The limited representation of different disabilities, specifically physical and visual is acknowledged. Likewise, the specific locality of the study and its focus on two institutions may limit that relevance of the findings to a wider audience, however readers are encouraged to consider similarities to their own context. To counter some of these limitations a researcher with a disability was included during all stages, care was taken to encourage open conversations within the focus groups and the rigour of the analysis and the member checking of initial summaries gives strength to the depth and direction of the analysis.

These focus groups with physiotherapy students with a range of different specific learning difficulties and other long term mental health disorders, has demonstrated that studying physiotherapy involves complex dynamics, which the students have to learn to navigate. The students navigate factors that include ignorance of their conditions within the profession and educational institutions which results in often haphazard routes to diagnosis, ambiguity with disclosure, and critically, both a lack of continuity in the institutions approach to support and inadequate consideration of the impact of the learning environment, assessment and resources. While the students accepted that these concerns often relate to all students, they felt that they disproportionately impacted on those with disabilities.

As a result, the students felt somewhat disempowered by structures and processes throughout their course. These hurdles also impede use of their self-management strategies that they have worked hard to develop and wish to implement.

This was a small study based in a particular region of the UK. However, given the dearth of research to date within physiotherapy, it is an important step forward. Specifically, this study extends the literature in this area by highlighting the issues experienced within the university setting which have been under-reported in physiotherapy. This particularly relates to the concepts of and limitations to reasonable adjustments. It further highlights the ambiguity of disclosure, indicating a need for further exploration.

There is a need for more studies looking at the experience and attainment of students with disabilities nationally, with a focus on the factors that impact on their learning experience and successful strategies to facilitate that process. Specific focus on the transition from University to clinical environments is also warranted.

Implications

Students have a wealth of knowledge based on their experiences of living with a disability while undertaking pre-registration physiotherapy studies. The insights they raise pose a number of challenges to education providers both in academic and clinical environments. While caution is appropriately raised in regard to generalisations for what is a very heterogeneous group, some general considerations can be raised from this study. These include; consistent and accessible signposting to facilitate early self-understanding and recognition of strategies and skills; increase staff awareness of individual experiences of disability and how this can impact on learning in different environments; critical examination of the justifications for what is considered ‘reasonable’ in terms of adjustments; improved interaction between clinical and university based education providers to share understanding and expectations in relation to adjustments and clinical competence; and a reconsideration of inclusive education that creates opportunity to allow and celebrate able diversity.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Attention deficit disorder

Attention deficit hyperactive disorder

Higher education institutions

National Health Service

Objective structured clinical examination

United Kingdom

Virtual learning environment

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Acknowledgements

Thanks to the students who volunteered to participate in this study and offered to share their experiences.

The study was funded by Health Education England North West London, but the design of the study, data collection, analysis, interpretation and writing was entirely the responsibility of the authors.

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MN, JH, AW, SW conducted the focus groups. MN analysed the data. JH, AW, SW all reviewed the data and analysis and participated in critical discussions. MN drafted the article. JH, AW and SW made significant contributions to the final draft, which all authors have approved.

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Norris, M., Hammond, J., Williams, A. et al. Students with specific learning disabilities experiences of pre-registration physiotherapy education: a qualitative study. BMC Med Educ 20 , 2 (2020). https://doi.org/10.1186/s12909-019-1913-3

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Learning from Ricardo and Thompson: Machinery and Labor in the Early Industrial Revolution, and in the Age of AI

David Ricardo initially believed machinery would help workers but revised his opinion, likely based on the impact of automation in the textile industry. Despite cotton textiles becoming one of the largest sectors in the British economy, real wages for cotton weavers did not rise for decades. As E.P. Thompson emphasized, automation forced workers into unhealthy factories with close surveillance and little autonomy. Automation can increase wages, but only when accompanied by new tasks that raise the marginal productivity of labor and/or when there is sufficient additional hiring in complementary sectors. Wages are unlikely to rise when workers cannot push for their share of productivity growth. Today, artificial intelligence may boost average productivity, but it also may replace many workers while degrading job quality for those who remain employed. As in Ricardo’s time, the impact of automation on workers today is more complex than an automatic linkage from higher productivity to better wages.

The authors are co-directors of the MIT Shaping the Future of Work Initiative, which was established through a generous gift from the Hewlett Foundation. Relevant disclosures are available at shapingwork.mit.edu/power-and-progress, under “Policy Summary.” For their outstanding work, we thank Gavin Alcott (research and drafting), Julia Regier (editing), and Hilary McClellen (fact-checking). We also thank Joel Mokyr for his helpful comments. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

We are grateful to David Autor for useful comments. We gratefully acknowledge financial support from Toulouse Network on Information Technology, Google, Microsoft, IBM, the Sloan Foundation and the Smith Richardson Foundation.

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Computer Science > Computer Vision and Pattern Recognition

Title: weakly-supervised semantic segmentation via dual-stream contrastive learning of cross-image contextual information.

Abstract: Weakly supervised semantic segmentation (WSSS) aims at learning a semantic segmentation model with only image-level tags. Despite intensive research on deep learning approaches over a decade, there is still a significant performance gap between WSSS and full semantic segmentation. Most current WSSS methods always focus on a limited single image (pixel-wise) information while ignoring the valuable inter-image (semantic-wise) information. From this perspective, a novel end-to-end WSSS framework called DSCNet is developed along with two innovations: i) pixel-wise group contrast and semantic-wise graph contrast are proposed and introduced into the WSSS framework; ii) a novel dual-stream contrastive learning (DSCL) mechanism is designed to jointly handle pixel-wise and semantic-wise context information for better WSSS performance. Specifically, the pixel-wise group contrast learning (PGCL) and semantic-wise graph contrast learning (SGCL) tasks form a more comprehensive solution. Extensive experiments on PASCAL VOC and MS COCO benchmarks verify the superiority of DSCNet over SOTA approaches and baseline models.

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