research paper in modern physics

Reviews of Modern Physics

Editorial Team

Volume 96, Issue 2 (partial)

April - june 2024, editorial: coauthor coauthor, randall d. kamien and daniel ucko, rev. mod. phys. 96 , 020001 (2024) – published 21 may 2024, colloquium : magnetotactic bacteria: from flagellar motor to collective effects, m. marmol, e. gachon, and d. faivre, rev. mod. phys. 96 , 021001 (2024) – published 4 april 2024.

Magnetotactic bacteria have a built-in compass, in the form of a magnetosome chain made up of magnetic biominerals, that allows them to passively align along terrestrial magnetic field lines. They also sense oxygen gradients and swim using at least one flagellum. Hence, these bacteria are self-propelled active matter capable of displaying flocking behavior. This Colloquium explains the physics behind these various capabilities, as well as their interactions and biological significance.

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Colloquium : topologically protected transport in engineered mechanical systems, tirth shah, christian brendel, vittorio peano, and florian marquardt, rev. mod. phys. 96 , 021002 (2024) – published 18 april 2024.

Artificially engineered mechanical systems, sometimes called metamaterials, offer many promising applications on length scales ranging from macroscopic systems to the nanoscale. A topic of particular interest is the existence of topologically protected phononic edge states in such systems that are analogous to the electronic edge states that give rise to the quantum Hall effect. This Colloquium gives an introduction to topologically protected transport in metamaterials and its applications for controlling acoustic transport.

Single-molecule scale magnetic resonance spectroscopy using quantum diamond sensors

Jiangfeng du, fazhan shi, xi kong, fedor jelezko, and jörg wrachtrup, rev. mod. phys. 96 , 025001 (2024) – published 8 may 2024.

Nitrogen-vacancy centers in diamond are sensitive to magnetic fields, and a single center permits detection of electron and nuclear spins and imaging of single molecules in its vicinity. This article reviews the achievements of advanced methods to obtain spectral and spatial resolution and it points to technical problems that remain to be solved for widespread and multidisciplinary adoption of single-molecule magnetic resonance spectroscopy.

When superconductivity crosses over: From BCS to BEC

Qijin chen, zhiqiang wang, rufus boyack, shuolong yang, and k. levin, rev. mod. phys. 96 , 025002 (2024) – published 23 may 2024.

The theory of unconventional superconductors continues to provide profound puzzles. The crossover between the weakly coupled Bardeen-Cooper-Schrieffer (BCS) state and the strong-pairing Bose-Einstein condensate (BEC) provides a useful perspective on how to address these questions. This paper describes a self-consistent framework for thinking about the crossover regime in between these two limits. The review discusses to what extent this BCS-BEC theory applies to a range of classes of superconducting materials including the cuprates, iron pnictides, twisted bilayer graphene, and interfacial superconductivity among others.

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Reviews of Modern Physics

Editorial Team

Accepted Papers

Colloidal hard spheres: triumphs, challenges, and mysteries, c. patrick royall, patrick charbonneau, marjolein dijkstra, john russo, frank smallenburg, thomas speck, and chantal valeriani, accepted 6 may 2024, ultimate rayleigh-bénard turbulence, detlef lohse and olga shishkina, accepted 22 april 2024, colloquium: inclusions, boundaries, and disorder in scalar active matter, omer granek, yariv kafri, mehran kardar, sunghan ro, julien tailleur, and alexandre solon, accepted 28 march 2024, colloquium: quantum batteries, francesco campaioli, stefano gherardini, james q. quach, marco polini, and gian marcello andolina, accepted 20 march 2024, neutrinos from dense environments: flavor mechanisms, theoretical approaches, observations, and new directions, m. cristina volpe, accepted 7 march 2024, catalysis in quantum information theory, patryk lipka-bartosik, henrik wilming, and nelly h. y. ng, accepted 27 february 2024, colloquium: spin-orbit effects in superconducting hybrid structures, morten amundsen, jacob linder, jason w. a. robinson, igor žutić, and niladri banerjee, accepted 29 january 2024, fluorescence microscopy: a statistics-optics perspective, mohamadreza fazel, kristin s. grussmayer, boris ferdman, aleksandra radenovic, yoav shechtman, jörg enderlein, and steve pressé, accepted 23 january 2024, flash: new intersection of physics, chemistry, biology, and cancer medicine, marie-catherine vozenin, billy w. loo jr., sami tantawi, peter maxim, douglas r. spitz, claude bailat, and charles l. limoli, accepted 17 january 2024.

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New Journal Citation Reports Support Physical Review Journals’ Leading Position

The Physical Review journals published by the American Physical Society (APS) remain among the most trusted, cited, impactful and influential publications in physics, according to the 2022 Journal Citation Reports released this week by Clarivate Analytics.

Clarivate’s annual report assesses the impact and reach of more than 21,500 high-quality academic journals from across more than 250 research disciplines. APS journals held leading positions in a number of categories.

Physical Review Letters (PRL), the APS flagship publication that has published cutting-edge physics research for the last 65 years, leads the way as the most-cited journal in physics and the 8th-most cited journal in science overall. On another key measure, called the Normalized Eigenfactor, PRL ranks as the most influential physics journal in the world, and #15 among all journals across all categories.

Reviews of Modern Physics , the world’s premier physics review journal established in 1929, maintains its #1 rank as the highest-impact journal among all titles in the Physics, Multidisciplinary category, with a Journal Impact Factor of 44.1.

APS has also responded thoughtfully to the scientific community’s growing need for high-quality, open access titles, in support of open research. Among fully open-access publications in the Physics, Multidisciplinary category, the top two by impact factor are APS’s Physical Review X (12.5) and PRX Quantum (9.7). PRX Quantum also ranks as the top primary research journal in Quantum Science & Technology. The fully open access Physical Review Research , which has published more than 5,300 articles since its launch in 2019, received its first-ever impact factor (4.2).

Five additional physics titles published by APS — Physical Review A, B, C, D and E — all sit within the top 10% of publications in their respective categories when ranked by multiple metrics, including Total Articles, Total Citations, and Eigenfactor. Physical Review Applied , Physical Review Fluids and Physical Review Materials each ranked among the top 20% largest (Total Articles) and top 15% most influential (Eigenfactor) in their respective categories.

Physical Review Physics Education Research , the only APS publication indexed in the Social Sciences Citation Index as well as the Science Citation Index Expanded received its highest-ever Journal Impact Factor (3.1). Physical Review Accelerators and Beams , which this year celebrates 25 years of publication, was one of the first open access journals in physics, and is one of science’s longest running Diamond Open Access journals. It received an impact factor of 1.7.

APS is grateful to the countless authors, readers, referees, editors, and staff members who have supported the journals and contributed to these achievements.

Anna Torres
Head of Strategic Communications
[email protected]

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A new theory of quantum gravity could explain the biggest puzzle in cosmology, study suggests

A new theory of quantum gravity, which attempts to unite quantum physics with Einstein's relativity, could help solve the puzzle of the universe's expansion, a theoretical paper suggests.

The nearby Andromeda galaxy with older stars highlighted in blue. A new theory of quantum gravity could help explain why more distant galaxies seem to be retreating faster than nearer ones.

A variation on the theory of quantum gravity — the unification of quantum mechanics and Einstein's general relativity — could help solve one of the biggest puzzles in cosmology, new research suggests.

For nearly a century, scientists have known that the universe is expanding. But in recent decades, physicists have found that different types of measurements of the expansion rate — called the Hubble parameter — produce puzzling inconsistencies.

To resolve this paradox, a new study suggests incorporating quantum effects into one prominent theory used to determine the expansion rate.

"We tried to resolve and explain the mismatch between the values of the Hubble parameter from two different prominent types of observations," study co-author P.K. Suresh , a professor of physics at the University of Hyderabad in India, told Live Science via email.

An expanding problem

The universe's expansion was first identified by Edwin Hubble in 1929. His observations with the largest telescope of that time revealed that galaxies farther from us appear to move away at faster speeds. Although Hubble initially overestimated the expansion rate, subsequent measurements have refined our understanding, establishing the current Hubble parameter as highly reliable.

Later in the 20th century, astrophysicists introduced a novel technique to gauge the expansion rate by examining the cosmic microwave background, the pervasive "afterglow" of the Big Bang .

However, a serious problem arose with these two types of measurements. Specifically, the newer method produced a Hubble parameter value almost 10% lower than the one deduced from the astronomical observations of distant cosmic objects. Such discrepancies between different measurements, called the Hubble tension, signal potential flaws in our understanding of the universe's evolution.

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Related: Newfound 'glitch' in Einstein's relativity could rewrite the rules of the universe, study suggests

In a study published in the journal Classical and Quantum Gravity , Suresh and his colleague from the University of Hyderabad, B. Anupama, proposed a solution to align these disparate results. They underscored that physicists infer the Hubble parameter indirectly, employing our universe's evolutionary model based on Einstein's theory of general relativity.

A representation of galaxies twisted by gravity

The team argued for revising this theory to incorporate quantum effects. These effects, intrinsic to fundamental interactions, encompass random field fluctuations and the spontaneous creation of particles from the vacuum of space.

Despite scientists' ability to integrate quantum effects into theories of other fields, quantum gravity remains elusive, making detailed calculations extremely difficult or even impossible. To make matters worse, experimental studies of these effects require reaching temperatures or energies many orders of magnitude higher than those achievable in a lab.

Acknowledging these challenges, Suresh and Anupama focused on broad quantum-gravity effects common to many proposed theories.

"Our equation doesn't need to account for everything, but that does not prevent us from testing quantum gravity or its effects experimentally," Suresh said.

Their theoretical exploration revealed that accounting for quantum effects when describing the gravitational interactions in the earliest stage of the universe's expansion, called cosmic inflation, could indeed alter the theory's predictions regarding the properties of the microwave background at present, making the two types of Hubble parameter measurements consistent.

Of course, final conclusions can be drawn only when a full-fledged theory of quantum gravity is known, but even the preliminary findings are encouraging. Moreover, the link between the cosmic microwave background and quantum gravitational effects opens the way to experimentally studying these effects in the near future, the team said.

"Quantum gravity is supposed to play a role in the dynamics of the early universe; thus its effect can be observed through measurements of the properties of the cosmic microwave background," Suresh said.

— Mysterious 'unparticles' may be pushing the universe apart, new theoretical study suggests

— 'It could be profound': How astronomer Wendy Freedman is trying to fix the universe

— James Webb telescope discovers oldest black hole in the universe

"Some of the future missions devoted to studying this electromagnetic background are highly probable and promising to test quantum gravity. … It provides a promising suggestion to resolve and validate the inflationary models of cosmology in conjunction with quantum gravity."

Additionally, the authors posit that quantum gravitational phenomena in the early universe might have shaped the properties of gravitational waves emitted during that period. Detecting these waves with future gravitational-wave observatories could further illuminate quantum gravitational characteristics.

"Gravitational waves from various astrophysical sources have only been observed so far, but gravitational waves from the early universe have not yet been detected," Suresh said. "Hopefully, our work will help in identifying the correct inflationary model and detecting the primordial gravitational waves with quantum gravity features."

Andrey got his B.Sc. and M.Sc. degrees in elementary particle physics from Novosibirsk State University in Russia, and a Ph.D. in string theory from the Weizmann Institute of Science in Israel. He works as a science writer, specializing in physics, space, and technology. His articles have been published in Elements , N+1 , and AdvancedScienceNews .

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Physics education research for 21 st century learning

Lei Bao ORCID: orcid.org/0000-0003-3348-4198 1 &
Kathleen Koenig 2

Disciplinary and Interdisciplinary Science Education Research volume 1 , Article number: 2 ( 2019 ) Cite this article

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Education goals have evolved to emphasize student acquisition of the knowledge and attributes necessary to successfully contribute to the workforce and global economy of the twenty-first Century. The new education standards emphasize higher end skills including reasoning, creativity, and open problem solving. Although there is substantial research evidence and consensus around identifying essential twenty-first Century skills, there is a lack of research that focuses on how the related subskills interact and develop over time. This paper provides a brief review of physics education research as a means for providing a context towards future work in promoting deep learning and fostering abilities in high-end reasoning. Through a synthesis of the literature around twenty-first Century skills and physics education, a set of concretely defined education and research goals are suggested for future research, along with how these may impact the next generation physics courses and how physics should be taught in the future.

Introduction

Education is the primary service offered by society to prepare its future generation workforce. The goals of education should therefore meet the demands of the changing world. The concept of learner-centered, active learning has broad, growing support in the research literature as an empirically validated teaching practice that best promotes learning for modern day students (Freeman et al., 2014 ). It stems out of the constructivist view of learning, which emphasizes that it is the learner who needs to actively construct knowledge and the teacher should assume the role of a facilitator rather than the source of knowledge. As implied by the constructivist view, learner-centered education usually emphasizes active-engagement and inquiry style teaching-learning methods, in which the learners can effectively construct their understanding under the guidance of instruction. The learner-centered education also requires educators and researchers to focus their efforts on the learners’ needs, not only to deliver effective teaching-learning approaches, but also to continuously align instructional practices to the education goals of the times. The goals of introductory college courses in science, technology, engineering, and mathematics (STEM) disciplines have constantly evolved from some notion of weed-out courses that emphasize content drilling, to the current constructivist active-engagement type of learning that promotes interest in STEM careers and fosters high-end cognitive abilities.

Following the conceptually defined framework of twenty-first Century teaching and learning, this paper aims to provide contextualized operational definitions of the goals for twenty-first Century learning in physics (and STEM in general) as well as the rationale for the importance of these outcomes for current students. Aligning to the twenty-first Century learning goals, research in physics education is briefly reviewed to provide a context towards future work in promoting deep learning and fostering abilities in high-end reasoning in parallel. Through a synthesis of the literature around twenty-first Century skills and physics education, a set of concretely defined education and research goals are suggested for future research. These goals include: domain-specific research in physics learning; fostering scientific reasoning abilities that are transferable across the STEM disciplines; and dissemination of research-validated curriculum and approaches to teaching and learning. Although this review has a focus on physics education research (PER), it is beneficial to expand the perspective to view physics education in the broader context of STEM learning. Therefore, much of the discussion will blend PER with STEM education as a continuum body of work on teaching and learning.

Education goals for twenty-first century learning

Education goals have evolved to emphasize student acquisition of essential “21 st Century skills”, which define the knowledge and attributes necessary to successfully contribute to the workforce and global economy of the 21st Century (National Research Council, 2011 , 2012a ). In general, these standards seek to transition from emphasizing content-based drilling and memorization towards fostering higher-end skills including reasoning, creativity, and open problem solving (United States Chamber of Commerce, 2017 ). Initiatives on advancing twenty-first Century education focus on skills that converge on three broad clusters: cognitive, interpersonal, and intrapersonal, all of which include a rich set of sub-dimensions.

Within the cognitive domain, multiple competencies have been proposed, including deep learning, non-routine problem solving, systems thinking, critical thinking, computational and information literacy, reasoning and argumentation, and innovation (National Research Council, 2012b ; National Science and Technology Council, 2018 ). Interpersonal skills are those necessary for relating to others, including the ability to work creatively and collaboratively as well as communicate clearly. Intrapersonal skills, on the other hand, reside within the individual and include metacognitive thinking, adaptability, and self-management. These involve the ability to adjust one’s strategy or approach along with the ability to work towards important goals without significant distraction, both essential for sustained success in long-term problem solving and career development.

Although many descriptions exist for what qualifies as twenty-first Century skills, student abilities in scientific reasoning and critical thinking are the most commonly noted and widely studied. They are highly connected with the other cognitive skills of problem solving, decision making, and creative thinking (Bailin, 1996 ; Facione, 1990 ; Fisher, 2001 ; Lipman, 2003 ; Marzano et al., 1988 ), and have been important educational goals since the 1980s (Binkley et al., 2010 ; NCET, 1987 ). As a result, they play a foundational role in defining, assessing, and developing twenty-first Century skills.

The literature for critical thinking is extensive (Bangert-Drowns & Bankert, 1990 ; Facione, 1990 ; Glaser, 1941 ). Various definitions exist with common underlying principles. Broadly defined, critical thinking is the application of the cognitive skills and strategies that aim for and support evidence-based decision making. It is the thinking involved in solving problems, formulating inferences, calculating likelihoods, and making decisions (Halpern, 1999 ). It is the “reasonable reflective thinking focused on deciding what to believe or do” (Ennis, 1993 ). Critical thinking is recognized as a way to understand and evaluate subject matter; producing reliable knowledge and improving thinking itself (Paul, 1990 ; Siegel, 1988 ).

The notion of scientific reasoning is often used to label the set of skills that support critical thinking, problem solving, and creativity in STEM. Broadly defined, scientific reasoning includes the thinking and reasoning skills involved in inquiry, experimentation, evidence evaluation, inference and argument that support the formation and modification of concepts and theories about the natural world; such as the ability to systematically explore a problem, formulate and test hypotheses, manipulate and isolate variables, and observe and evaluate consequences (Bao et al., 2009 ; Zimmerman, 2000 ). Critical thinking and scientific reasoning share many features, where both emphasize evidence-based decision making in multivariable causal conditions. Critical thinking can be promoted through the development of scientific reasoning, which includes student ability to reach a reliable conclusion after identifying a question, formulating hypotheses, gathering relevant data, and logically testing and evaluating the hypothesis. In this way, scientific reasoning can be viewed as a scientific domain instantiation of critical thinking in the context of STEM learning.

In STEM learning, cognitive aspects of the twenty-first Century skills aim to develop reasoning skills, critical thinking skills, and deep understanding, all of which allow students to develop well connected expert-like knowledge structures and engage in meaningful scientific inquiry and problem solving. Within physics education, a core component of STEM education, the learning of conceptual understanding and problem solving remains a current emphasis. However, the fast-changing work environment and technology-driven world require a new set of core knowledge, skills, and habits of mind to solve complex interdisciplinary problems, gather and evaluate evidence, and make sense of information from a variety of sources (Tanenbaum, 2016 ). The education goals in physics are transitioning towards ability fostering as well as extension and integration with other STEM disciplines. Although curriculum that supports these goals is limited, there are a number of attempts, particularly in developing active learning classrooms and inquiry-based laboratory activities, which have demonstrated success. Some of these are described later in this paper as they provide a foundation for future work in physics education.

Interpersonal skills, such as communication and collaboration, are also essential for twenty-first Century problem-solving tasks, which are often open-ended, complex, and team-based. As the world becomes more connected in a multitude of dimensions, tackling significant problems involving complex systems often goes beyond the individual and requires working with others who are increasingly from culturally diverse backgrounds. Due to the rise of communication technologies, being able to articulate thoughts and ideas in a variety of formats and contexts is crucial, as well as the ability to effectively listen or observe to decipher meaning. Interpersonal skills can be promoted by integrating group-learning experiences into the classroom setting, while providing students with the opportunity to engage in open-ended tasks with a team of peer learners who may propose more than one plausible solution. These experiences should be designed such that students must work collaboratively and responsibly in teams to develop creative solutions, which are later disseminated through informative presentations and clearly written scientific reports. Although educational settings in general have moved to providing students with more and more opportunities for collaborative learning, a lack of effective assessments for these important skills has been a limiting factor for producing informative research and widespread implementation. See Liu ( 2010 ) for an overview of measurement instruments reported in the research literature.

Intrapersonal skills are based on the individual and include the ability to manage one’s behavior and emotions to achieve goals. These are especially important for adapting in the fast-evolving collaborative modern work environment and for learning new tasks to solve increasingly challenging interdisciplinary problems, both of which require intellectual openness, work ethic, initiative, and metacognition, to name a few. These skills can be promoted using instruction which, for example, includes metacognitive learning strategies, provides opportunities to make choices and set goals for learning, and explicitly connects to everyday life events. However, like interpersonal skills, the availability of relevant assessments challenges advancement in this area. In this review, the vast amount of studies on interpersonal and intrapersonal skills will not be discussed in order to keep the main focus on the cognitive side of skills and reasoning.

The purpose behind discussing twenty-first Century skills is that this set of skills provides important guidance for establishing essential education goals for modern society and learners. However, although there is substantial research evidence and consensus around identifying necessary twenty-first Century skills, there is a lack of research that focuses on how the related subskills interact and develop over time (Reimers & Chung, 2016 ), with much of the existing research residing in academic literature that is focused on psychology rather than education systems (National Research Council, 2012a ). Therefore, a major and challenging task for discipline-based education researchers and educators is to operationally define discipline-specific goals that align with the twenty-first Century skills for each of the STEM fields. In the following sections, this paper will provide a limited vision of the research endeavors in physics education that can translate the past and current success into sustained impact for twenty-first Century teaching and learning.

Proposed education and research goals

Physics education research (PER) is often considered an early pioneer in discipline-based education research (National Research Council, 2012c ), with well-established, broad, and influential outcomes (e.g., Hake, 1998 ; Hsu, Brewe, Foster, & Harper, 2004 ; McDermott & Redish, 1999 ; Meltzer & Thornton, 2012 ). Through the integration of twenty-first Century skills with the PER literature, a set of broadly defined education and research goals is proposed for future PER work:

Discipline-specific deep learning: Cognitive and education research involving physics learning has established a rich literature on student learning behaviors along with a number of frameworks. Some of the popular frameworks include conceptual understanding and concept change, problem solving, knowledge structure, deep learning, and knowledge integration. Aligned with twenty-first Century skills, future research in physics learning should aim to integrate the multiple areas of existing work, such that they help students develop well integrated knowledge structures in order to achieve deep leaning in physics.

Fostering scientific reasoning for transfer across STEM disciplines: The broad literature in physics learning and scientific reasoning can provide a solid foundation to further develop effective physics education approaches, such as active engagement instruction and inquiry labs, specifically targeting scientific inquiry abilities and reasoning skills. Since scientific reasoning is a more domain-general cognitive ability, success in physics can also more readily inform research and education practices in other STEM fields.

Research, development, assessment, and dissemination of effective education approaches: Developing and maintaining a supportive infrastructure of education research and implementation has always been a challenge, not only in physics but in all STEM areas. The twenty-first Century education requires researchers and instructors across STEM to work together as an extended community in order to construct a sustainable integrated STEM education environment. Through this new infrastructure, effective team-based inquiry learning and meaningful assessment can be delivered to help students develop a comprehensive skills set including deep understanding and scientific reasoning, as well as communication and other non-cognitive abilities.

The suggested research will generate understanding and resources to support education practices that meet the requirements of the Next Generation Science Standards (NGSS), which explicitly emphasize three areas of learning including disciplinary core ideas, crosscutting concepts, and practices (National Research Council, 2012b ). The first goal for promoting deep learning of disciplinary knowledge corresponds well to the NGSS emphasis on disciplinary core ideas, which play a central role in helping students develop well integrated knowledge structures to achieve deep understanding. The second goal on fostering transferable scientific reasoning skills supports the NGSS emphasis on crosscutting concepts and practices. Scientific reasoning skills are crosscutting cognitive abilities that are essential to the development of domain-general concepts and modeling strategies. In addition, the development of scientific reasoning requires inquiry-based learning and practices. Therefore, research on scientific reasoning can produce a valuable knowledge base on education means that are effective for developing crosscutting concepts and promoting meaningful practices in STEM. The third research goal addresses the challenge in the assessment of high-end skills and the dissemination of effective educational approaches, which supports all NGSS initiatives to ensure sustainable development and lasting impact. The following sections will discuss the research literature that provides the foundation for these three research goals and identify the specific challenges that will need to be addressed in future work.

Promoting deep learning in physics education

Physics education for the twenty-first Century aims to foster high-end reasoning skills and promote deep conceptual understanding. However, many traditional education systems place strong emphasis on only problem solving with the expectation that students obtain deep conceptual understanding through repetitive problem-solving practices, which often doesn’t occur (Alonso, 1992 ). This focus on problem solving has been shown to have limitations as a number of studies have revealed disconnections between learning conceptual understanding and problem-solving skills (Chiu, 2001 ; Chiu, Guo, & Treagust, 2007 ; Hoellwarth, Moelter, & Knight, 2005 ; Kim & Pak, 2002 ; Nakhleh, 1993 ; Nakhleh & Mitchell, 1993 ; Nurrenbern & Pickering, 1987 ; Stamovlasis, Tsaparlis, Kamilatos, Papaoikonomou, & Zarotiadou, 2005 ). In fact, drilling in problem solving may actually promote memorization of context-specific solutions with minimal generalization rather than transitioning students from novices to experts.

Towards conceptual understanding and learning, many models and definitions have been established to study and describe student conceptual knowledge states and development. For example, students coming into a physics classroom often hold deeply rooted, stable understandings that differ from expert conceptions. These are commonly referred to as misconceptions or alternative conceptions (Clement, 1982 ; Duit & Treagust, 2003 ; Dykstra Jr, Boyle, & Monarch, 1992 ; Halloun & Hestenes, 1985a , 1985b ). Such students’ conceptions are context dependent and exist as disconnected knowledge fragments, which are strongly situated within specific contexts (Bao & Redish, 2001 , 2006 ; Minstrell, 1992 ).

In modeling students’ knowledge structures, DiSessa’s proposed phenomenological primitives (p-prim) describe a learner’s implicit thinking, cued from specific contexts, as an underpinning cognitive construct for a learner’s expressed conception (DiSessa, 1993 ; Smith III, DiSessa, & Roschelle, 1994 ). Facets, on the other hand, map between the implicit p-prim and concrete statements of beliefs and are developed as discrete and independent units of thought, knowledge, or strategies used by individuals to address specific situations (Minstrell, 1992 ). Ontological categories, defined by Chi, describe student reasoning in the most general sense. Chi believed that these are distinct, stable, and constraining, and that a core reason behind novices’ difficulties in physics is that they think of physics within the category of matter instead of processes (Chi, 1992 ; Chi & Slotta, 1993 ; Chi, Slotta, & De Leeuw, 1994 ; Slotta, Chi, & Joram, 1995 ). More details on conceptual learning and problem solving are well summarized in the literature (Hsu et al., 2004 ; McDermott & Redish, 1999 ), from which a common theme emerges from the models and definitions. That is, learning is context dependent and students with poor conceptual understanding typically have locally connected knowledge structures with isolated conceptual constructs that are unable to establish similarities and contrasts between contexts.

Additionally, this idea of fragmentation is demonstrated through many studies on student problem solving in physics and other fields. It has been shown that a student’s knowledge organization is a key aspect for distinguishing experts from novices (Bagno, Eylon, & Ganiel, 2000 ; Chi, Feltovich, & Glaser, 1981 ; De Jong & Ferguson-Hesler, 1986 ; Eylon & Reif, 1984 ; Ferguson-Hesler & De Jong, 1990 ; Heller & Reif, 1984 ; Larkin, McDermott, Simon, & Simon, 1980 ; Smith, 1992 ; Veldhuis, 1990 ; Wexler, 1982 ). Expert’s knowledge is organized around core principles of physics, which are applied to guide problem solving and develop connections between different domains as well as new, unfamiliar situations (Brown, 1989 ; Perkins & Salomon, 1989 ; Salomon & Perkins, 1989 ). Novices, on the other hand, lack a well-organized knowledge structure and often solve problems by relying on surface features that are directly mapped to certain problem-solving outcomes through memorization (Chi, Bassok, Lewis, Reimann, & Glaser, 1989 ; Hardiman, Dufresne, & Mestre, 1989 ; Schoenfeld & Herrmann, 1982 ).

This lack of organization creates many difficulties in the comprehension of basic concepts and in solving complex problems. This leads to the common complaint that students’ knowledge of physics is reduced to formulas and vague labels of the concepts, which are unable to substantively contribute to meaningful reasoning processes. A novice’s fragmented knowledge structure severely limits the learner’s conceptual understanding. In essence, these students are able to memorize how to approach a problem given specific information but lack the understanding of the underlying concept of the approach, limiting their ability to apply this approach to a novel situation. In order to achieve expert-like understanding, a student’s knowledge structure must integrate all of the fragmented ideas around the core principle to form a coherent and fully connected conceptual framework.

Towards a more general theoretical consideration, students’ alternative conceptions and fragmentation in knowledge structures can be viewed through both the “naïve theory” framework (e.g., Posner, Strike, Hewson, & Gertzog, 1982 ; Vosniadou, Vamvakoussi, & Skopeliti, 2008 ) and the “knowledge in pieces” (DiSessa, 1993 ) perspective. The “naïve theory” framework considers students entering the classroom with stable and coherent ideas (naïve theories) about the natural world that differ from those presented by experts. In the “knowledge in pieces” perspective, student knowledge is constructed in real-time and incorporates context features with the p-prims to form the observed conceptual expressions. Although there exists an ongoing debate between these two views (Kalman & Lattery, 2018 ), it is more productive to focus on their instructional implications for promoting meaningful conceptual change in students’ knowledge structures.

In the process of learning, students may enter the classroom with a range of initial states depending on the population and content. For topics with well-established empirical experiences, students often have developed their own ideas and understanding, while on topics without prior exposure, students may create their initial understanding in real-time based on related prior knowledge and given contextual features (Bao & Redish, 2006 ). These initial states of understanding, regardless of their origin, are usually different from those of experts. Therefore, the main function of teaching and learning is to guide students to modify their initial understanding towards the experts’ views. Although students’ initial understanding may exist as a body of coherent ideas within limited contexts, as students start to change their knowledge structures throughout the learning process, they may evolve into a wide range of transitional states with varying levels of knowledge integration and coherence. The discussion in this brief review on students’ knowledge structures regarding fragmentation and integration are primarily focused on the transitional stages emerged through learning.

The corresponding instructional goal is then to help students more effectively develop an integrated knowledge structure so as to achieve a deep conceptual understanding. From an educator’s perspective, Bloom’s taxonomy of education objectives establishes a hierarchy of six levels of cognitive skills based on their specificity and complexity: Remember (lowest and most specific), Understand, Apply, Analyze, Evaluate, and Create (highest and most general and complex) (Anderson et al., 2001 ; Bloom, Engelhart, Furst, Hill, & Krathwohl, 1956 ). This hierarchy of skills exemplifies the transition of a learner’s cognitive development from a fragmented and contextually situated knowledge structure (novice with low level cognitive skills) to a well-integrated and globally networked expert-like structure (with high level cognitive skills).

As a student’s learning progresses from lower to higher cognitive levels, the student’s knowledge structure becomes more integrated and is easier to transfer across contexts (less context specific). For example, beginning stage students may only be able to memorize and perform limited applications of the features of certain contexts and their conditional variations, with which the students were specifically taught. This leads to the establishment of a locally connected knowledge construct. When a student’s learning progresses from the level of Remember to Understand, the student begins to develop connections among some of the fragmented pieces to form a more fully connected network linking a larger set of contexts, thus advancing into a higher level of understanding. These connections and the ability to transfer between different situations form the basis of deep conceptual understanding. This growth of connections leads to a more complete and integrated cognitive structure, which can be mapped to a higher level on Bloom’s taxonomy. This occurs when students are able to relate a larger number of different contextual and conditional aspects of a concept for analyzing and evaluating to a wider variety of problem situations.

Promoting the growth of connections would appear to aid in student learning. Exactly which teaching methods best facilitate this are dependent on the concepts and skills being learned and should be determined through research. However, it has been well recognized that traditional instruction often fails to help students obtain expert-like conceptual understanding, with many misconceptions still existing after instruction, indicating weak integration within a student’s knowledge structure (McKeachie, 1986 ).

Recognizing the failures of traditional teaching, various research-informed teaching methods have been developed to enhance student conceptual learning along with diagnostic tests, which aim to measure the existence of misconceptions. Most advances in teaching methods focus on the inclusion of inquiry-based interactive-engagement elements in lecture, recitations, and labs. In physics education, these methods were popularized after Hake’s landmark study demonstrated the effectiveness of interactive-engagement over traditional lectures (Hake, 1998 ). Some of these methods include the use of peer instruction (Mazur, 1997 ), personal response systems (e.g., Reay, Bao, Li, Warnakulasooriya, & Baugh, 2005 ), studio-style instruction (Beichner et al., 2007 ), and inquiry-based learning (Etkina & Van Heuvelen, 2001 ; Laws, 2004 ; McDermott, 1996 ; Thornton & Sokoloff, 1998 ). The key approach of these methods aims to improve student learning by carefully targeting deficits in student knowledge and actively encouraging students to explore and discuss. Rather than rote memorization, these approaches help promote generalization and deeper conceptual understanding by building connections between knowledge elements.

Based on the literature, including Bloom’s taxonomy and the new education standards that emphasize twenty-first Century skills, a common focus on teaching and learning can be identified. This focus emphasizes helping students develop connections among fragmented segments of their knowledge pieces and is aligned with the knowledge integration perspective, which focuses on helping students develop and refine their knowledge structure toward a more coherently organized and extensively connected network of ideas (Lee, Liu, & Linn, 2011 ; Linn, 2005 ; Nordine, Krajcik, & Fortus, 2011 ; Shen, Liu, & Chang, 2017 ). For meaningful learning to occur, new concepts must be integrated into a learner’s existing knowledge structure by linking the new knowledge to already understood concepts.

Forming an integrated knowledge structure is therefore essential to achieving deep learning, not only in physics but also in all STEM fields. However, defining what connections must occur at different stages of learning, as well as understanding the instructional methods necessary for effectively developing such connections within each STEM disciplinary context, are necessary for current and future research. Together these will provide the much needed foundational knowledge base to guide the development of the next generation of curriculum and classroom environment designed around twenty-first Century learning.

Developing scientific reasoning with inquiry labs

Scientific reasoning is part of the widely emphasized cognitive strand of twenty-first Century skills. Through development of scientific reasoning skills, students’ critical thinking, open-ended problem-solving abilities, and decision-making skills can be improved. In this way, targeting scientific reasoning as a curricular objective is aligned with the goals emphasized in twenty-first Century education. Also, there is a growing body of research on the importance of student development of scientific reasoning, which have been found to positively correlate with course achievement (Cavallo, Rozman, Blickenstaff, & Walker, 2003 ; Johnson & Lawson, 1998 ), improvement on concept tests (Coletta & Phillips, 2005 ; She & Liao, 2010 ), engagement in higher levels of problem solving (Cracolice, Deming, & Ehlert, 2008 ; Fabby & Koenig, 2013 ); and success on transfer (Ates & Cataloglu, 2007 ; Jensen & Lawson, 2011 ).

Unfortunately, research has shown that college students are lacking in scientific reasoning. Lawson ( 1992 ) found that ~ 50% of intro biology students are not capable of applying scientific reasoning in learning, including the ability to develop hypotheses, control variables, and design experiments; all necessary for meaningful scientific inquiry. Research has also found that traditional courses do not significantly develop these abilities, with pre-to-post-test gains of 1%–2%, while inquiry-based courses have gains around 7% (Koenig, Schen, & Bao, 2012 ; Koenig, Schen, Edwards, & Bao, 2012 ). Others found that undergraduates have difficulty developing evidence-based decisions and differentiating between and linking evidence with claims (Kuhn, 1992 ; Shaw, 1996 ; Zeineddin & Abd-El-Khalick, 2010 ). A large scale international study suggested that learning of physics content knowledge with traditional teaching practices does not improve students’ scientific reasoning skills (Bao et al., 2009 ).

Aligned to twenty-first Century learning, it is important to implement curriculum that is specifically designed for developing scientific reasoning abilities within current education settings. Although traditional lectures may continue for decades due to infrastructure constraints, a unique opportunity can be found in the lab curriculum, which may be more readily transformed to include hands-on minds-on group learning activities that are ideal for developing students’ abilities in scientific inquiry and reasoning.

For well over a century, the laboratory has held a distinctive role in student learning (Meltzer & Otero, 2015 ). However, many existing labs, which haven’t changed much since the late 1980s, have received criticism for their outdated cookbook style that lacks effectiveness in developing high-end skills. In addition, labs have been primarily used as a means for verifying the physical principles presented in lecture, and unfortunately, Hofstein and Lunetta ( 1982 ) found in an early review of the literature that research was unable to demonstrate the impact of the lab on student content learning.

About this same time, a shift towards a constructivist view of learning gained popularity and influenced lab curriculum development towards engaging students in the process of constructing knowledge through science inquiry. Curricula, such as Physics by Inquiry (McDermott, 1996 ), Real-Time Physics (Sokoloff, Thornton, & Laws, 2011 ), and Workshop Physics (Laws, 2004 ), were developed with a primary focus on engaging students in cognitive conflict to address misconceptions. Although these approaches have been shown to be highly successful in improving deep learning of physics concepts (McDermott & Redish, 1999 ), the emphasis on conceptual learning does not sufficiently impact the domain general scientific reasoning skills necessitated in the goals of twenty-first Century learning.

Reform in science education, both in terms of targeted content and skills, along with the emergence of knowledge regarding human cognition and learning (Bransford, Brown, & Cocking, 2000 ), have generated renewed interest in the potential of inquiry-based lab settings for skill development. In these types of hands-on minds-on learning, students apply the methods and procedures of science inquiry to investigate phenomena and construct scientific claims, solve problems, and communicate outcomes, which holds promise for developing both conceptual understanding and scientific reasoning skills in parallel (Trowbridge, Bybee, & Powell, 2000 ). In addition, the availability of technology to enhance inquiry-based learning has seen exponential growth, along with the emergence of more appropriate research methodologies to support research on student learning.

Although inquiry-based labs hold promise for developing students’ high-end reasoning, analytic, and scientific inquiry abilities, these educational endeavors have not become widespread, with many existing physics laboratory courses still viewed merely as a place to illustrate the physical principles from the lecture course (Meltzer & Otero, 2015 ). Developing scientific ideas from practical experiences, however, is a complex process. Students need sufficient time and opportunity for interaction and reflection on complex, investigative tasks. Blended learning, which merges lecture and lab (such as studio style courses), addresses this issue to some extent, but has experienced limited adoption, likely due to the demanding infrastructure resources, including dedicated technology-intensive classroom space, equipment and maintenance costs, and fully committed trained staff.

Therefore, there is an immediate need to transform the existing standalone lab courses, within the constraints of the existing education infrastructure, into more inquiry-based designs, with one of its primary goals dedicated to developing scientific reasoning skills. These labs should center on constructing knowledge, along with hands-on minds-on practical skills and scientific reasoning, to support modeling a problem, designing and implementing experiments, analyzing and interpreting data, drawing and evaluating conclusions, and effective communication. In particular, training on scientific reasoning needs to be explicitly addressed in the lab curriculum, which should contain components specifically targeting a set of operationally-defined scientific reasoning skills, such as ability to control variables or engage in multivariate causal reasoning. Although effective inquiry may also implicitly develop some aspects of scientific reasoning skills, such development is far less efficient and varies with context when the primary focus is on conceptual learning.

Several recent efforts to enhance the standalone lab course have shown promise in supporting education goals that better align with twenty-first Century learning. For example, the Investigative Science Learning Environment (ISLE) labs involve a series of tasks designed to help students develop the “habits of mind” of scientists and engineers (Etkina et al., 2006 ). The curriculum targets reasoning as well as the lab learning outcomes published by the American Association of Physics Teachers (Kozminski et al., 2014 ). Operationally, ISLE methods focus on scaffolding students’ developing conceptual understanding using inquiry learning without a heavy emphasis on cognitive conflict, making it more appropriate and effective for entry level students and K-12 teachers.

Likewise, Koenig, Wood, Bortner, and Bao ( 2019 ) have developed a lab curriculum that is intentionally designed around the twenty-first Century learning goals for developing cognitive, interpersonal, and intrapersonal abilities. In terms of the cognitive domain, the lab learning outcomes center on critical thinking and scientific reasoning but do so through operationally defined sub-skills, all of which are transferrable across STEM. These selected sub-skills are found in the research literature, and include the ability to control variables and engage in data analytics and causal reasoning. For each targeted sub-skill, a series of pre-lab and in-class activities provide students with repeated, deliberate practice within multiple hypothetical science-based scenarios followed by real inquiry-based lab contexts. This explicit instructional strategy has been shown to be essential for the development of scientific reasoning (Chen & Klahr, 1999 ). In addition, the Karplus Learning Cycle (Karplus, 1964 ) provides the foundation for the structure of the lab activities and involves cycles of exploration, concept introduction, and concept application. The curricular framework is such that as the course progresses, the students engage in increasingly complex tasks, which allow students the opportunity to learn gradually through a progression from simple to complex skills.

As part of this same curriculum, students’ interpersonal skills are developed, in part, through teamwork, as students work in groups of 3 or 4 to address open-ended research questions, such as, What impacts the period of a pendulum? In addition, due to time constraints, students learn early on about the importance of working together in an efficient manor towards a common goal, with one set of written lab records per team submitted after each lab. Checkpoints built into all in-class activities involve Socratic dialogue between the instructor and students and promote oral communication. This use of directed questioning guides students in articulating their reasoning behind decisions and claims made, while supporting the development of scientific reasoning and conceptual understanding in parallel (Hake, 1992 ). Students’ intrapersonal skills, as well as communication skills, are promoted through the submission of individual lab reports. These reports require students to reflect upon their learning over each of four multi-week experiments and synthesize their ideas into evidence-based arguments, which support a claim. Due to the length of several weeks over which students collect data for each of these reports, the ability to organize the data and manage their time becomes essential.

Despite the growing emphasis on research and development of curriculum that targets twenty-first Century learning, converting a traditionally taught lab course into a meaningful inquiry-based learning environment is challenging in current reform efforts. Typically, the biggest challenge is a lack of resources; including faculty time to create or adapt inquiry-based materials for the local setting, training faculty and graduate student instructors who are likely unfamiliar with this approach, and the potential cost of new equipment. Koenig et al. ( 2019 ) addressed these potential implementation barriers by designing curriculum with these challenges in mind. That is, the curriculum was designed as a flexible set of modules that target specific sub-skills, with each module consisting of pre-lab (hypothetical) and in-lab (real) activities. Each module was designed around a curricular framework such that an adopting institution can use the materials as written, or can incorporate their existing equipment and experiments into the framework with minimal effort. Other non-traditional approaches have also been experimented with, such as the work by Sobhanzadeh, Kalman, and Thompson ( 2017 ), which targets typical misconceptions by using conceptual questions to engage students in making a prediction, designing and conducting a related experiment, and determining whether or not the results support the hypothesis.

Another challenge for inquiry labs is the assessment of skills-based learning outcomes. For assessment of scientific reasoning, a new instrument on inquiry in scientific thinking analytics and reasoning (iSTAR) has been developed, which can be easily implemented across large numbers of students as both a pre- and post-test to assess gains. iSTAR assesses reasoning skills necessary in the systematical conduct of scientific inquiry, which includes the ability to explore a problem, formulate and test hypotheses, manipulate and isolate variables, and observe and evaluate the consequences (see www.istarassessment.org ). The new instrument expands upon the commonly used classroom test of scientific reasoning (Lawson, 1978 , 2000 ), which has been identified with a number of validity weaknesses and a ceiling effect for college students (Bao, Xiao, Koenig, & Han, 2018 ).

Many education innovations need supporting infrastructures that can ensure adoption and lasting impact. However, making large-scale changes to current education settings can be risky, if not impossible. New education approaches, therefore, need to be designed to adapt to current environmental constraints. Since higher-end skills are a primary focus of twenty-first Century learning, which are most effectively developed in inquiry-based group settings, transforming current lecture and lab courses into this new format is critical. Although this transformation presents great challenges, promising solutions have already emerged from various research efforts. Perhaps the biggest challenge is for STEM educators and researchers to form an alliance to work together to re-engineer many details of the current education infrastructure in order to overcome the multitude of implementation obstacles.

This paper attempts to identify a few central ideas to provide a broad picture for future research and development in physics education, or STEM education in general, to promote twenty-first Century learning. Through a synthesis of the existing literature within the authors’ limited scope, a number of views surface.

Education is a service to prepare (not to select) the future workforce and should be designed as learner-centered, with the education goals and teaching-learning methods tailored to the needs and characteristics of the learners themselves. Given space constraints, the reader is referred to the meta-analysis conducted by Freeman et al. ( 2014 ), which provides strong support for learner-centered instruction. The changing world of the twenty-first Century informs the establishment of new education goals, which should be used to guide research and development of teaching and learning for present day students. Aligned to twenty-first Century learning, the new science standards have set the goals for STEM education to transition towards promoting deep learning of disciplinary knowledge, thereby building upon decades of research in PER, while fostering a wide range of general high-end cognitive and non-cognitive abilities that are transferable across all disciplines.

Following these education goals, more research is needed to operationally define and assess the desired high-end reasoning abilities. Building on a clear definition with effective assessments, a large number of empirical studies are needed to investigate how high-end abilities can be developed in parallel with deep learning of concepts, such that what is learned can be generalized to impact the development of curriculum and teaching methods which promote skills-based learning across all STEM fields. Specifically for PER, future research should emphasize knowledge integration to promote deep conceptual understanding in physics along with inquiry learning to foster scientific reasoning. Integration of physics learning in contexts that connect to other STEM disciplines is also an area for more research. Cross-cutting, interdisciplinary connections are becoming important features of the future generation physics curriculum and defines how physics should be taught collaboratively with other STEM courses.

This paper proposed meaningful areas for future research that are aligned with clearly defined education goals for twenty-first Century learning. Based on the existing literature, a number of challenges are noted for future directions of research, including the need for:

clear and operational definitions of goals to guide research and practice

concrete operational definitions of high-end abilities for which students are expected to develop

effective assessment methods and instruments to measure high-end abilities and other components of twenty-first Century learning

a knowledge base of the curriculum and teaching and learning environments that effectively support the development of advanced skills

integration of knowledge and ability development regarding within-discipline and cross-discipline learning in STEM

effective means to disseminate successful education practices

The list is by no means exhaustive, but these themes emerge above others. In addition, the high-end abilities discussed in this paper focus primarily on scientific reasoning, which is highly connected to other skills, such as critical thinking, systems thinking, multivariable modeling, computational thinking, design thinking, etc. These abilities are expected to develop in STEM learning, although some may be emphasized more within certain disciplines than others. Due to the limited scope of this paper, not all of these abilities were discussed in detail but should be considered an integral part of STEM learning.

Finally, a metacognitive position on education research is worth reflection. One important understanding is that the fundamental learning mechanism hasn’t changed, although the context in which learning occurs has evolved rapidly as a manifestation of the fast-forwarding technology world. Since learning is a process at the interface between a learner’s mind and the environment, the main focus of educators should always be on the learner’s interaction with the environment, not just the environment. In recent education developments, many new learning platforms have emerged at an exponential rate, such as the massive open online courses (MOOCs), STEM creative labs, and other online learning resources, to name a few. As attractive as these may be, it is risky to indiscriminately follow trends in education technology and commercially-incentivized initiatives before such interventions are shown to be effective by research. Trends come and go but educators foster students who have only a limited time to experience education. Therefore, delivering effective education is a high-stakes task and needs to be carefully and ethically planned and implemented. When game-changing opportunities emerge, one needs to not only consider the winners (and what they can win), but also the impact on all that is involved.

Based on a century of education research, consensus has settled on a fundamental mechanism of teaching and learning, which suggests that knowledge is developed within a learner through constructive processes and that team-based guided scientific inquiry is an effective method for promoting deep learning of content knowledge as well as developing high-end cognitive abilities, such as scientific reasoning. Emerging technology and methods should serve to facilitate (not to replace) such learning by providing more effective education settings and conveniently accessible resources. This is an important relationship that should survive many generations of technological and societal changes in the future to come. From a physicist’s point of view, a fundamental relation like this can be considered the “mechanics” of teaching and learning. Therefore, educators and researchers should hold on to these few fundamental principles without being distracted by the surfacing ripples of the world’s motion forward.

Availability of data and materials

Not applicable.

Abbreviations

American Association of Physics Teachers

Investigative Science Learning Environment

Inquiry in Scientific Thinking Analytics and Reasoning

Massive open online course

New Generation Science Standards

Physics education research

Science Technology Engineering and Math

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The research is supported in part by NSF Awards DUE-1431908 and DUE-1712238. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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A modern way to teach and practice manual therapy

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1 School of Health Sciences, Queens Medical Centre, University of Nottingham, Nottingham, NG7 2HA, UK.
2 Allied Health Research Unit, University of Central Lancashire, Preston, PR1 2HE, UK. [email protected].
3 Centre of Precision Rehabilitation for Spinal Pain, School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
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PMID: 38773515
PMCID: PMC11110311
DOI: 10.1186/s12998-024-00537-0

Background: Musculoskeletal conditions are the leading contributor to global disability and health burden. Manual therapy (MT) interventions are commonly recommended in clinical guidelines and used in the management of musculoskeletal conditions. Traditional systems of manual therapy (TMT), including physiotherapy, osteopathy, chiropractic, and soft tissue therapy have been built on principles such as clinician-centred assessment, patho-anatomical reasoning, and technique specificity. These historical principles are not supported by current evidence. However, data from clinical trials support the clinical and cost effectiveness of manual therapy as an intervention for musculoskeletal conditions, when used as part of a package of care.

Purpose: The purpose of this paper is to propose a modern evidence-guided framework for the teaching and practice of MT which avoids reference to and reliance on the outdated principles of TMT. This framework is based on three fundamental humanistic dimensions common in all aspects of healthcare: safety, comfort, and efficiency. These practical elements are contextualised by positive communication, a collaborative context, and person-centred care. The framework facilitates best-practice, reasoning, and communication and is exemplified here with two case studies.

Methods: A literature review stimulated by a new method of teaching manual therapy, reflecting contemporary evidence, being trialled at a United Kingdom education institute. A group of experienced, internationally-based academics, clinicians, and researchers from across the spectrum of manual therapy was convened. Perspectives were elicited through reviews of contemporary literature and discussions in an iterative process. Public presentations were made to multidisciplinary groups and feedback was incorporated. Consensus was achieved through repeated discussion of relevant elements.

Conclusions: Manual therapy interventions should include both passive and active, person-empowering interventions such as exercise, education, and lifestyle adaptations. These should be delivered in a contextualised healing environment with a well-developed person-practitioner therapeutic alliance. Teaching manual therapy should follow this model.

Keywords: Chiropractic; Evidence-based healthcare; Manual Therapy; Osteopathy; Person-centred healthcare; Physiotherapy; Soft-tissue therapy.

Publication types

Musculoskeletal Diseases / therapy
Musculoskeletal Manipulations* / education
Musculoskeletal Manipulations* / methods

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How Neanderthal language differed from modern human—they probably didn't use metaphors

by Steven Mithen, The Conversation

The Neanderthals (Homo neanderthalensis) fascinate researchers and the general public alike. They remain central to debates about the nature of the genus Homo (the broad biological classification that humans and their relatives fall into). Neanderthals are also vital for understanding the uniqueness or otherwise of our species, Homo sapiens.

We shared an ancestor with the Neanderthals around 600,000 years ago. They evolved in Europe while we did so in Africa, before dispersing multiple times into Eurasia. The Neanderthals became extinct around 40,000 years ago. We populated the world and continue to flourish. Whether that different outcome is a consequence of differences in language and thought has been long debated.

But the evidence points to key differences in the brains of our species and those of Neanderthals that allowed modern humans (H. sapiens) to come up with abstract and complex ideas through metaphor—the ability to compare two unrelated things. For this to happen, our species had to diverge from the Neanderthals in our brain architecture .

Some experts interpret the skeletal and archaeological evidence as indicating profound differences. Others believe there were none. And some take the middle ground .

Disagreement is not surprising when trying to infer such intangibles from material remains such as bones and artifacts. The evidence is piecemeal and ambiguous, providing us with a complex puzzle for how, when and why language evolved. Fortunately, recent discoveries in archaeology and other disciplines have added several new pieces to this language puzzle, enabling a viable picture of the Neanderthal mind to emerge.

New anatomical evidence indicates the Neanderthals had vocal tracts and auditory pathways not significantly different to our own, indicating that, from an anatomical perspective, they were as capable as us at communicating through speech . The discovery of Neanderthal genes in our own species indicates multiple episodes of interbreeding, which implies effective inter-species communication and social relationships.

The discovery of Neanderthal wooden spears, and the use of resins for making tools from separate components, have also enhanced our views of their technical skills . Pendants made from bird talons and the likely use of feathers as body adornments are claimed as examples of symbolism, along with geometric engravings on stone and bone .

Cave painters?

The most striking claim is that Neanderthals made art, painting red pigment on cave walls in Spain . But several of these cave art claims remain problematic. The evidence for Neanderthal cave art is compromised by unresolved methodological issues and is unlikely to be correct, in my view.

Rapidly accumulating evidence for the pre-40,000-year presence of modern humans in Europe challenges the idea that Neanderthals made these geometric designs, or at least that they did so prior to the influence of the symbol-using modern humans. However well-crafted, a wooden spear is little more than a pointed stick, and evidence of technological progress is absent throughout the entirety of Neanderthal existence.

While the archaeological evidence remains contested, that from neuroscience and genetics provides a compelling case for linguistic and cognitive differences between H. neanderthalensis and H. sapiens.

A 3D digital reconstruction of the Neanderthal brain, created by deforming that of H. sapiens and fitting it into a cast of the brain (endocast) from a Neanderthal, indicates significant differences in structure . The Neanderthals had a relatively large occipital lobe, devoting more brain matter to visual processing and making less available for other tasks such as language.

They also had a relatively small and differently shaped cerebellum. This sub-cortical structure, which is packed with neurons, contributes to many tasks including language processing, speaking and fluency . The uniquely spherical shape of the modern human brain evolved after the first Homo sapiens had appeared at 300,000 years ago.

Some of the genetic mutations associated with that development are associated with neuronal development and how neurons are connected in the brain. The authors of a comprehensive study of all mutations known to be unique to H. sapiens (as of 2019) concluded that "modifications of a complex network in cognition or learning took place in modern human evolution."

Iconic words

While such evidence has been accumulating, our understanding of language has also changed. Three developments are of particular significance. First is the 2016 discovery via brain scanning that we store words, or rather the concepts we associate with words, throughout both brain hemispheres and in clusters , or semantic groups, of similar concepts in the brain. This is significant because, as we'll see, the way these clusters of ideas are connected—or not—was probably different between H. sapiens and Neanderthals.

Second is the recognition that iconic sounds—those that provide a sensory impression of the thing they represent—had provided the evolutionary bridge between ape-like calls of our common ancestor of 6 million years ago and the first words spoken by Homo —though we're not sure which species that was.

Iconic words remain pervasive in languages today , capturing aspects of the sound, size, movement and texture of the concept the word represents. This contrasts with words that are only arbitrarily related to the thing they refer to. For example, a canine can equally be called a dog, chien or hund—none of which provide a sensory impression of the animal.

Third, computer simulation models of language transmission between generations have shown that syntax—consistent rules for how words are ordered to generate meaning— can spontaneously emerge . This shift of emphasis from genetic encoding of syntax to spontaneous emergence suggests that both H.sapiens and Neanderthal language contained these rules.

The key difference

While it may be possible to join the puzzle pieces in several different ways, my long wrestle with the multi-disciplinary evidence has found only one solution. This begins with iconic words being spoken by the ancient human species Homo erectus around 1.6 million years ago.

As these types of words were transmitted from generation to generation, arbitrary words and rules of syntax emerged, providing the early Neanderthals and H. sapiens with equivalent linguistic and cognitive capacities.

But these diverged as both species continued to evolve. The H. sapiens brain developed its spherical form with neural networks connecting what had been isolated semantic clusters of words. These remained isolated in the Neanderthal brain. So, while H. sapiens and Neanderthals had equivalent capacity for iconic words and syntax, they appear to have differed with respect to storing ideas in semantic clusters in the brain.

By linking up different clusters in the brain that are responsible for storing groups of concepts, our species gained the capacity to think and communicate using metaphor. This allowed modern humans to draw a line between widely different concepts and ideas.

This was arguably the most important of our cognitive tools, enabling us to come up with complex and abstract concepts . While iconic words and syntax were shared between H. sapiens and Neanderthals, metaphor transformed the language, thought and culture of our species, creating a deep divide with the Neanderthals. They went extinct, while we populated the world and continue to flourish.

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The heavy-fermion compound CeCu 2 Si 2 has long been known to be an unconventional superconductor with d -wave symmetry. Ordinarily, this would imply that the gap function has nodes on the Fermi surface. This Colloquium explains that recent experiments have shown that the gap is nonzero everywhere, if small where a single-band wave gap would vanish. The Colloquium discusses theoretical scenarios to explain these observations, as well as the implications for other unconventional superconductors.

Colloquium : Anomalous statistics of laser-cooled atoms in dissipative optical lattices

Gadi afek, nir davidson, david a. kessler, and eli barkai, rev. mod. phys. 95 , 031003 (2023) – published 27 september 2023.

The standard central limit theorem does not apply to sums of many random variables with heavy-tailed probability distributions. The anomalous statistics for such sums have exotic properties and they are applied phenomenologically across the natural sciences, economics, and the social sciences. This Colloquium reviews how anomalous statistics can be derived from first principles and how they govern the observed diffusive motion of ultracold atoms in laser fields.

Computational advantage of quantum random sampling

Dominik hangleiter and jens eisert, rev. mod. phys. 95 , 035001 (2023) – published 20 july 2023.

Quantum computers have improved and recent experiments have claimed quantum advantage – completion of a computational task that is evidently hard for any conventional computer. The problem solved is that of obtaining samples, by quantum measurement, from a certain probability distribution. This review shows in what precise way quantum random sampling can be seen as a computation. It explains what that computation solves, in what way it outperforms classical computations, and what methods of verification are available. Quantum random sampling becomes a first test of the presumed exponential computational advantage of quantum computers over classical ones.

Long-range interacting quantum systems

Nicolò defenu, tobias donner, tommaso macrì, guido pagano, stefano ruffo, and andrea trombettoni, rev. mod. phys. 95 , 035002 (2023) – published 29 august 2023.

Many-body quantum physics with long-range interactions of variable range and strength can be studied in experiments with Rydberg atom arrays, dipolar systems, trapped ions, and cold atoms in cavities. This review identifies common and universal features induced by the long-range interactions such as the extensive or nonextensive character of the total energy and features that deviate from the case of short-range interactions. A comparison with the corresponding results for classical systems is presented.

Weak gravity conjecture

Daniel harlow, ben heidenreich, matthew reece, and tom rudelius, rev. mod. phys. 95 , 035003 (2023) – published 6 september 2023.

The weak gravity conjecture, at the simplest level stating that “gravity is the weakest force,” has motivated many recent works aiming to understand quantum gravity and to put constraints on field theories that can be coupled to quantum gravity, including the one describing the real world. This review surveys the motivation, historical development, and recent advances related to this conjecture.

Quantitative theory of magnetic interactions in solids

Attila szilva, yaroslav kvashnin, evgeny a. stepanov, lars nordström, olle eriksson, alexander i. lichtenstein, and mikhail i. katsnelson, rev. mod. phys. 95 , 035004 (2023) – published 11 september 2023.

The physics of fast radio bursts

Rev. mod. phys. 95 , 035005 (2023) – published 25 september 2023.

Fast radio bursts, milliseconds-duration radio bursts predominantly originating from cosmological distances, figure among the unsolved puzzles of contemporary astrophysics. The rapid accumulation of observational data has generated an equally intense theoretical activity toward the understanding of the physical processes at the origin of these events. This review presents a thorough survey of the current knowledge about fast radio bursts, starting with the generic constraints that can be placed on theoretical models based on current observations and plasma physics considerations, then moving to a critical discussion of coherent radiation mechanisms and source models currently debated in the scientific community.

Atom counting with accelerator mass spectrometry

Walter kutschera, a. j. timothy jull, michael paul, and anton wallner, rev. mod. phys. 95 , 035006 (2023) – published 28 september 2023.

Accelerator mass spectrometry (AMS) is a mass-spectrometric method using entire accelerator systems to measure ultralow traces of long-lived radioisotopes. AMS spectrometers produce an ion beam from a sample of interest and separate ions according to their magnetic, electric, and atomic characteristics. It is thus possible to identify both the mass number and the atomic number of a very rare radioisotope, and count it atom by atom. The review describes the 45-year history since the discovery of AMS, detailed technical aspects, and a wide range of research fields.

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Reviews of Modern Physics

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Single-molecule scale magnetic resonance spectroscopy using quantum diamond sensors

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