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Objective In medical laboratory science, there is a need to enhance the clinical learning curriculum beyond laboratory skill and diagnostic interpretation competency. Incorporating simulation presents an opportunity to train and produce medical laboratory scientists with the skills to communicate and work effectively in an interprofessional healthcare team. Methods A scoping review was performed to (i) understand the landscape of research literature on medical laboratory science and simulation and (ii) provide a path for future research directions. The International Nursing Association for Clinical Simulation and Learning Standards of Best Practice: Simulation were used as a guiding framework for literature that described simulation activities. Results Out of 439 articles from multiple databases, 32 were eligible for inclusion into this review. Of the 14 articles that described a simulation activity, only 3 described or partially described each component of the best practice criteria for simulation. Articles that did not describe the design and implementation of simulation (n = 18) consisted of 7 opinion-based papers, 4 narrative reviews, 5 case reports, and 2 empirical papers. Conclusion Despite increases in medical laboratory science with simulation, there is a need for more detailed empirical studies, more studies with an interprofessional context, and more methodological rigor.

It is crucial to support students in better understanding water and sustainability issues because water plays a vital role in maintaining global ecosystems, including human life. A wide range of cu...

Modelling competencies are currently included in numerous curricula worldwide and are generally accepted as a complex, process-oriented construct. Therefore, effective measurement should include multiple dimensions, like the sub-competencies required throughout the modelling process. Departing from the characteristics of modelling problems as open and often underdetermined real-world problems, we propose to enrich the current conceptualisation of mathematical modelling competencies by including creativity, which plays an important role in numerous phases of the mathematical modelling process but has scarcely been considered in modelling discourse. In the study described in this paper, a new instrument for the evaluation of this enriched construct has been developed and implemented. The modelling competencies incorporating creativity of the students were evaluated based on the adequacy of the models and the modelling processes proposed, and the appropriateness and completeness of the approaches were evaluated in detail. Adapting measurement approaches for creativity that have been developed in the problem-solving discourse, certain criteria of creativity were selected to evaluate the creativity of the students’ approaches in tackling modelling problems—namely, usefulness, fluency, and originality. The empirical study was conducted among 107 Chinese students at the upper secondary school level, who attended a modelling camp and independently solved three complex modelling problems. The results reveal significant correlations between fluency and originality in students’ performances across all tasks; however, the relationships between usefulness and the other two creativity aspects were not consistent. Overall, the results of the study support the importance of the inclusion of creativity in the construct of modelling competencies.

Statistical modeling continues to gain prominence in the secondary curriculum, and recent recommendations to emphasize data science and computational thinking may soon position algorithmic models into the school curriculum. Many teachers’ preparation for and experiences teaching statistical modeling have focused on probabilistic models. Subsequently, much of the research literature related to the teachers’ understanding has focused on probabilistic models. This study explores the extent to which secondary statistics teachers appear to understand ideas of statistical modeling, specifically the processes of model building and evaluation, when introduced using classification trees, a type of algorithmic model. Results of this study suggest that while teachers were able to read and build classification tree models, they experienced more difficulty when evaluating models. Further research could continue to explore possible learning trajectories, technology tools, and pedagogical approaches for using classification trees to introduce ideas of statistical modeling.

Developing and using models to make sense of phenomena or to design solutions to problems is a key science and engineering practice. Classroom use of technology-based tools can promote the development of students’ modelling practice, systems thinking, and causal reasoning by providing opportunities to develop and use models to explore phenomena. In previous work, we presented four aspects of system modelling that emerged during our development and initial testing of an online system modelling tool. In this study, we provide an in-depth examination and detailed evidence of 10th grade students engaging in those four aspects during a classroom enactment of a system modelling unit. We look at the choices students made when constructing their models, whether they described evidence and reasoning for those choices, and whether they described the behavior of their models in connection with model usefulness in explaining and making predictions about the phenomena of interest. We conclude with a set of recommendations for designing curricular materials that leverage digital tools to facilitate the iterative constructing, using, evaluating, and revising of models.

The adoption of the new standard of higher education by the specialty 224 «Medical diagnostics and treatment technologies», specialization «Laboratory diagnostics» at the first (bachelor) level of higher education presupposes the possibility of elaborating on its basis new educational curricula and academic programs in specific subject areas including chemistry ones. As the result of the analysis of the content of new standard of higher education, the chemistry component was defined, as well as the learning outcomes of teaching the target category of specialists, the content of students' chemistry competences and their learning outcomes as the result of teaching them chemistry subjects have been formulated. The competences mentioned have been specified in our research in the frameworks of chemistry competences as: the ability to apply the habits of critical thinking to state the interdependence between the content, structure and qualities of chemical compounds and their medical and biological significance, between causes and consequences of physical and chemical processes typical for human liquids; to apply analytical methods of research, chemical equipment, vessels and reagents; to analyse qualitative and quantiative content of chemical compounds using appropriate methodologies; to perform safe activites in a chemistry laboratory; to perform an independent analysis of modern profession-related scientific information in chemistry, to perform researches concerning the chemical content of biological liquids of a human, of environmental objects and food products, to present the results of this work in different forms (as an abstract, report, publication in scientific sources). The results of teaching chemistry subjects include the following: a student understands the essence of professionally-oriented chemistry concepts, methods of conducting chemical researches, ways of applying laboratory equipment, safety rules in a chemical laboratory; conducts mathematical calculations, connected to solutions preparation; prepares solutions; equips a working place with laboratory equipment, reagents, personal safety means according to the methodology of conducting chemical research; finds relations between the composition, structure, qualities of chemical substances and their medical and biological interpretation; implements analytical methods of research, chemical equipment, supplies and reagents; plots curves of relationship between indices that are researched in chemical experiment, is capable of working with them; conducts mathematical calculations of numerical content of substances and their mixtures; sticks to the safety rules while working in the chemical laboratory; conducts exploratory researches of the chemical content of substances and their mixtures; processes, systematizes and presents information obtained using contemporary computer and information technologies. The hierarchy of competences has been designed. The matrix of relations between the learning outcomes of teaching chemistry subjects and the chemistry related competences of the target category of bachelors has been created. The results obtained will be useful for the development of new educational professional programs and curricula in the field of the research. It is planned to substantiate the methodological approaches towards the formation and evaluation of the results of teaching students chemistry courses.

Purpose The practice of medicine is rarely straightforward. Data used to facilitate medical decision making may be conflicting, ambiguous, or scarce, and providing optimal care requires balancing clinicians' expertise and available evidence with patients' preferences. To explore uncertainty in decision making across disciplines, the authors performed a scoping review and thematic analysis of the literature to formulate a model describing the decision-making process in medicine under uncertain conditions. Method In 2016, the authors performed a comprehensive search of key databases using a combination of keywords and controlled vocabulary. They identified and reviewed 3,398 records. After applying their inclusion and exclusion criteria to the titles and abstracts and then full texts, 19 articles were selected. The authors applied a qualitative thematic analysis to these articles, using codes to extract themes related to uncertainty in decision making. Results The 19 articles spanned 6 fields of study and 5 disciplines within the health sciences. The thematic analysis revealed 6 main themes: recognition of uncertainty, classification of uncertainty, stakeholder perspectives, knowledge acquisition, decision-making approach, and evaluation of the decision-making process. Conclusions Based on the themes that emerged from their thematic analysis of the literature characterizing the effects of uncertainty and ambiguity on the decision-making process, the authors developed a framework depicting the interplay between these themes with a visual representation of the decision-making process under uncertain conditions. Future research includes further development and validation of this framework to inform medical school curricula.

In this paper, we report on an attempt to systematically discover reliable and high-quality evidence on teaching practices that have an impact on student learning. We adopted an innovative approach that was modelled on some of the practices of a systematic review. Papers that met certain quality criteria (population generalisability, ecological validity, measurement validity, logical clarity and design justification) were examined and a weighted-average score for each paper was calculated. These were then ranked to derive lists of best-evidenced and most impactful teaching and curriculum strategies. The results reveal that this method provides a reasonable approach to distilling the available literature into a concise representation of the most effective practices that are backed by good research design attributes. The results will be useful for curriculum designers, university leaders and policy makers, and have already informed policy at one Australian university.

In this article, we report on a three-pronged effort to create a hypothetical learning progression for quantification in science. First, we drew from history and philosophy of science to define the quantification competency and develop hypothetical levels of the learning progression. More specifically, the quantification competency refers to the ability to analyze phenomena through (a) abstracting relevant measurable variables from phenomena and observations, (b) investigating the mathematical relationships among the variables, and (c) conceptualizing scientific ideas that explain the mathematical relationships. The quantification learning progression contains four levels of increasing sophistication: level 1, holistic observation; level 2, attributes; level 3, measurable variables; and level 4, relational complexity. Second, we analyzed the practices in the Next Generation Science Standards for current, largely tacit, assumptions about how quantification develops (or ought to develop) through K-12 education. While several pieces of evidence support the learning progression, we found that quantification was described inconsistently across practices. Third, we used empirical student data from a field test of items in physical and life sciences to illustrate qualitative differences in student thinking that align with levels in the hypothetical learning progression for quantification. By generating a hypothetical learning progression for quantification, we lay the groundwork for future standards development efforts to include this key practice and provide guidance for curriculum developers and instructors in helping students develop robust scientific understanding.

With a growing number of global challenges related to the environment, water, public health, and energy, there is an imminent need to teach chemistry in the context of its interconnectedness with other systems. Project- and problem-based learning are student-centered learning approaches which offer educators the opportunity to engage learners in solving complex real-world problems. By choosing a globally relevant project/problem and requiring students to utilize scientific methods to solve the problem, both problem-based learning and project-based learning are excellent strategies for educators to teach chemistry using a systems approach. This review summarizes key research studies which utilize project- and problem-based learning in the context of enabling learners to confront global problems and the wide applicability of these approaches to systems thinking.

COVID-19 has been extremely difficult to control. The lack of understanding of key aspects of pandemics has affected virus transmission. On the other hand, there is a demand to incorporate computational thinking (CT) in the curricula with applications in STEM. However, there are still no exemplars in the curriculum that apply CT to real-world problems such as controlling a pandemic or other similar global crises. In this paper, we fill this gap by proposing exemplars of CT for modeling the pandemic. We designed exemplars following the three pillars of the framework for CT from the Inclusive Mathematics for Sustainability in a Digital Economy (InMside) project by Asia-Pacific Economic Cooperation (APEC): algorithmic thinking, computational modeling, and machine learning. For each pillar, we designed a progressive sequence of activities that covers from elementary to high school. In an experimental study with elementary and middle school students from 2 schools of high vulnerability, we found that the computational modeling exemplar can be implemented by teachers and correctly understood by students. We conclude that it is feasible to introduce the exemplars at all grade levels and that this is a powerful example of Science Technology, Engineering, and Mathematics (STEM) integration that helps reflect and tackle real-world and challenging public health problems of great impact for students and their families.

Bloom's cognitive learning taxonomy is widely used in medical education. The revised taxonomy published by David Kathwohl (1956) and his group describes the levels in action forms: Remember, Understand, Apply, Analyze, Evaluate, and Innovate. The taxonomy has been commonly used to design and structure educational goals and objectives. However, most uses occur at the course or program curriculum level, as was originally described. Whereas applying the taxonomy at the level of individual educational activities remained limited for different reasons. Hence, the aim of this article is to promote applying the taxonomy in daily clinical teaching by providing practical clinical examples in a simplified way., Highlights • Bloom's taxonomy of cognitive learning is widely used in medical education to design educational curricula. • The taxonomy can be efficiently used in daily educational clinical activities. • Clinician educators are encouraged to apply the taxonomy at clinical encounters. • Understanding the taxonomy through clinical examples can enhance the application of the taxonomy.

In this paper, we make use of systems thinking insights to study education during and beyond COVID-19. Systems thinking is a rich discipline that studies nonlinear models of social complex adaptive systems that has many insights and tools that are relevant for modelling and understanding how interactions unfold in educational systems. An important insight of systems thinking is that the root cause of chronic complex problems often lay in the underlying systemic structure. Using insights from systems thinking to study learning/education has many benefits, including: (1) support for rigorous big-picture thinking; (2) anticipating and managing unintended consequences; (3) understanding dysfunctional learning systems using systems archetypes - which are systemic structures that, experts have noticed, typically lead to a performance rut; and finally (4) identification of high-leverage interventions that lead to long-lasting benefits without being neutralized by the system. In the paper, we have modelled COVID-19 pandemic effects on students learning in a novel way by using system thinking tools (Causal Loop Diagrams and Stock and Flow Diagrams), which help us to understand the complex interconnections of students performance, learning and management reforms. We demonstrate that successful student learning during and beyond COVID-19 requires not only a focus on lectures and curriculum reforms but also on motivating students, instilling a growth mindset, and developing strategies to track and minimize online distractions.

This paper extends prior work establishing an operationalized framework of mathematical sense making (MSM) in physics. The framework differentiates between the object being understood (either physical or mathematical) and various tools (physical or mathematical) used to mediate the sense-making process. This results in four modes of MSM that can be coordinated and linked in various ways. Here, the framework is applied to novel modalities of student written work (both short answer and multiple choice). In detailed studies of student reasoning about the photoelectric effect, we associate these MSM modes with particular multiple choice answers, and substantiate this association by linking both the MSM modes and multiple choice answers with finer-grained reasoning elements that students use in solving a specific problem. Through the multiple associations between MSM mode, distributions of reasoning elements, and multiple-choice answers, we confirm the applicability of this framework to analyzing these sparser modalities of student work and its utility for analyzing larger-scale (N>100) datasets. The association between individual reasoning elements and both MSM modes and MC answers suggest that it is possible to cue particular modes of student reasoning and answer selection. Such findings suggest potential for this framework to be applicable to the analysis and design of curriculum.

This paper seeks to provide some insights into the assessment of student understanding within a systems thinking perspective. Results are based on work carried out using a general chemistry curriculum that, although not developed with such a framework, shares some of its underlying intentions. After describing how chemical systems thinking is conceptualized in the paper, a specific example of an assessment tool is described and discussed to illustrate major points in our analysis. Results of a qualitative pilot study using this instrument are presented and used to highlight potentialities and challenges in teaching and assessing student understanding using a systems thinking framework. A majority of study participants expressed sophisticated ways of reasoning based on the properties and interactions of relevant components and processes in the system under consideration. Nevertheless, they could not easily connect and apply their understanding of theoretical chemical models and practices to the realities of the system.

Given that science and engineering practices are a large focus in the Next Generation Science Standards, biology teachers need to find ways to incorporate the engineering design process into their curriculum. To address this need, I present a lesson that allows for student collaboration in designing and developing a solution to a global problem resulting from overfishing and our use of unsustainable fishing practices. This lesson also demonstrates to students that larger, global issues that seem insurmountable to solve can be broken down into smaller, more manageable pieces. My approach involves having students research a problem related to sustainable fishing practices and design a physical model of a solution to combat their specific issue. Peer review is then used in order to help students revise and edit their models during the lesson in response to the peer feedback received. The lesson will culminate in a presentation to the class about the biological, social, and economic ramifications of both their assigned problem and a potential solution.

Observation is at the heart of the Scientific Method, but students receive very little direct help in science curricula to assess or build this important power. We have addressed this problem with ...

Our situation Interventional research in pharmacy education includes the study of complex challenges that can be difficult to navigate. Design-based research (DBR), is a systematic and iterative approach to interventional research that is attentive to the practical and theoretical contributions to education. Practical contributions include the creation of novel solutions to complex problems that improve learning while theoretical contributions include refining our understanding of context-specific learning. In this paper, we describe how we addressed challenges associated with student collaboration in pharmacy education by applying DBR to bridge theory and practice. Methodological literature review DBR is characterized as authentic, contextually aware, collaborative, theoretically focused, methodologically diverse, practical, iterative, and operation-oriented. DBR includes three iterative phases: (1) analysis and exploration, (2) design and construction, and (3) evaluation and reflection. Our recommendations and their applications To integrate DBR into interventional research, scholars should work collaboratively with diverse teams of experts. DBR also requires extensive planning, a toolkit of expansive research methodologies, and attention to practical and theoretical considerations. Finally, scholars should share their work as often as possible and engage in creative exercises to promote innovative solutions to challenges in education. Potential impact DBR offers an approach to generate practical, theoretical, and scholarly contributions to pharmacy education research. In summary, DBR can aid pharmacy educational scholars by using a flexible, iterative, and systematic process to generate novel and creative solutions to complex problems.

The introduction of the competent approach to the higher education system links with the problem of development of appropriate technologies of formation and assessment of students' competencies. Formation of competences in the process of studying in higher educational institutions depends on many factors. One of the main factors is the students' learning of disciplines. Level of mathematical training is required and is very important for future software engineers. Therefore, mathematical competence is an important component of professional competence for future software engineers. Studying of mathematical sections should ensure the formation of theoretical base and practical skills for students, allowing finding optimal solutions of professional problems in the future. Mathematical competence is formed in the process of studying of different mathematical sections. Therefore, it is important to establish the assessment of formation level of mathematical competence for planning of mathematical training and the process of forming of mathematical competence, and for future analysis of educational process. Sections of mathematical disciplines are the most important for future professional activities. The aim of the article is to determine the importance of mathematical sections for the process of formation of mathematical competence of future software engineers. Method of hierarchy analysis has been used for the processing of expert opinions. The value of mathematical sections has been studied in accordance with the curriculum. The obtained results can be used for solving of problems of educational process organisation. The research results are important for the planning of process of formation of mathematical competence of future software engineers and building of a model for assessing of the formed of mathematical competence.

Purpose of the study. The main purpose of creating a curriculum is to regulate academic disciplines in accordance with the logic of the learning process, defined by the relationship between the basic concepts of the disciplines. Violation of this logic becomes apparent only directly during the training sessions.A large variety of quantitative methods uses indicators that do not reveal structural deficiencies in the curriculum. This makes it difficult to improve the curriculum.The purpose of this work is to demonstrate the application of a general approach to the assessment of the structural inconsistency of systems in relation to the evaluation of the logical structure of the curriculum.Materials and methods. The paper applies a general approach to the assessment of structural integrity, developed on the basis of the provisions of the general theory of systems and graph theory. The approach involves the construction of three interrelated structural models of the system and using them to determine the initial data for calculating the index of inconsistency of the system structure.Results. The overall approach to the assessment of structural integrity is adapted to assess the logical structure of the curriculum. Three models of curriculum structure are developed:Elementary model of interdisciplinary communication;Curriculum network model;Hierarchical curriculum model.Based on the parameters of the hierarchical curriculum model, using three adapted algorithms, the value of the inconsistency index of the curriculum structure in the direction of preparation “Applied Informatics” is calculated. Recommendations on changing the structure of the studied curriculum to reduce the degree of its structural inconsistency are proposed. Conclusion. As a result of the research, the methods were proposed that allow identifying possible contradictions in the structure of the curriculum and evaluating its inconsistency. As the experiments have shown, it is extremely difficult to study the curricula in a manual manner, the number of disciplines in which exceeds 50. In this regard, the development of a complex of computer programs that will automate the assessment of the inconsistency of large curricula is being completed.

Evolution is a key concept of biology, fundamental to understand the world and address important societal problems, but research studies show that it is still not widely understood and accepted. Several factors are known to influence evolution acceptance and understanding, but little information is available regarding the impacts of the curriculum on these aspects. Very few curricula have been examined to assess the coverage of biological evolution. The available studies do not allow comparative analyses, due to the different methodologies employed by the authors. However, such an analysis would be useful for research purposes and for the development of appropriate educational policies to address the problem of a lack of evolution acceptance in some countries. In this paper we describe the steps through which we developed a valid and reliable instrument for curricula analysis known as FACE: “Framework to Assess the Coverage of biological Evolution by school curricula.” This framework was developed based on the “Understanding Evolution Conceptual Framework” (UECF). After an initial pilot study, our framework was reformulated based on identified issues and experts’ opinions. To generate validity and reliability evidence in support of the framework, it was applied to four European countries’ curricula. For each country, a team of a minimum of two national and two foreign coders worked independently to assess the curriculum using this framework for content analysis. Reliability evidence was estimated using Krippendorf's alpha and resulted in appropriate values for coding the examined curricula. Some issues that coders faced during the analysis were discussed and, to ensure better reliability for future researchers, additional guidelines and one extra category were included in the framework. The final version of the framework includes six categories and 34 subcategories. FACE is a useful tool for the analysis and the comparison of curricula and school textbooks regarding the coverage of evolution, and such results can guide curricula development.

Computational Thinking (CT) allows us to solve complex problems by expressing it in a way that computers, humans, or both, can understand. CT is closely related to problem solving and critical thinking, which are actively used in STEM education. Research on CT has gained steady momentum recently, and many of the institutions around the world have adopted CT into their curriculum. This paper presents a literature review conducted to identify the interventions used to develop CT skills and the methods used to assess CT skills. The review explored various publications on CT and identified that curriculum-based interventions and workshops are the primary interventions used for introducing CT in the educational sector. During the analysis, we have also identified a handful of assessment tools used for measuring CT skills, but they are not standardized assessment tools. Hence, we plan to analyze the existing assessment methods and propose a new sophisticated tool for evaluating CT skills as our future work.

The paper discusses various methods for the Educational Data Mining (EDM), including curricula, based on interdisciplinary teaching. Their advantages and disadvantages are being discussed. The problem of interdisciplinary teaching in engineering and pedagogical education has its own specifics, which is due to the fact that, in essence, this education is complex interdisciplinary, and the training of future teachers of vocational institutions has been implemented at the border of pedagogical and engineering sciences. The authors propose a method for optimizing the curricula of engineering and pedagogical specialties based on the algorithm of phased construction model for structuring interdisciplinary relations. This method is based on the graph theory. The result of the method has been presented as a graph of interdisciplinary relations in tier-parallel form. The construction of the graph and solving the problem of interdisciplinary integration has been implemented using software developed by the authors, the description of which is given in the paper. The paper also discusses the results of optimization.

Although a consensus on the definition of computational thinking (CT) has yet to be achieved, teaching resources and associated reforms of curricula encapsulating CT are in use. As such, the assessment of these efforts is essential in order to successfully introduce CT into curricula. This chapter conducts a literature review of recent studies on CT assessment, presenting them in three categories based on their approach: (a) assessment using specific programming environments, (b) assessment using scales/psychometric tools, and (c) assessment using multiple forms/methods. We find that CT assessment faces unresolved issues, including the inability to cover all concepts and student age groups, the lack of scientific documentation and validation, and the dearth of tools to autonomously and efficiently assess CT. Findings also state a relation of CT with cognitive skills development. We propose that the use of multiple methods continues to be the most appropriate approach for CT assessment.

Dynamical systems, i.e., systems that progress along time according to fixed rules, exhibit many special phenomena like the emergence of interesting patterns, bifurcation of behavior, the appearance of chaos despite determinism and boundedness, and sensitive dependence on initial conditions. Such phenomena are encountered in diverse fields, such as fluid dynamics, biological population analysis and economic and financial operations. The study of dynamical systems, their properties, and the mathematical and computerized tools for dealing with them, are often designated as part of advanced curricula in physics or mathematics. Consequently, many computer science students, perhaps the majority thereof, graduate without ever being exposed to such concepts. We argue that with the pervasiveness of dynamical systems and manifestation of their properties in the real world, these concepts should be introduced early on; in undergraduate studies in computer science and related fields, and perhaps even in high school. Available introductory courses demonstrate that only a minimal foundation of knowledge in mathematics is needed for the basic understanding of the key ideas. Such an introduction would deepen one’s understanding of the world and highlight important capabilities and limitations of mathematical and software tools for analysis, simulation, testing and verification of complex systems. In turn, this can lead to enhancement and enrichment of languages, tools and methodologies for dealing with dynamical systems, and of research in computer science and software engineering in general.

Education system is viewed as an important constituent of sustainable development of a society. The spread of information technology reduces the need for mastering the computing apparatus of mathematics. On the other hand, firstly, the role of mathematics is not limited at least to its computing apparatus, the other components of the mathematical apparatus (for example, conceptual, methodological, etc.) and other aspects of mathematics (historical, activity, education of “intellectual honesty”, the formation of specific types of thinking, for example, geometric, ampect, linked with modelling, etc.) are also significant issues; secondly, the use of a computing apparatus is actually the final stage of other types of mathematical and “near-mathematical” activities. The article identifies three factors that ensure the relevance of mathematical education for the sustainable development: 1) the system of teaching mathematics should form the ability to use the mathematical apparatus for solving problems of business, management, engineering, social development, etc. (five components of this factor are highlighted); 2) focus on working with educational material at the level of typical strategies and methodology, not limited to typical algorithms; 3) presentation of mathematics as a multidimensional cultural phenomenon, in which scientific, technical, aesthetic, historical and economic as well as historical and social aspects are distinguished (this in many cases requires the processing of the teaching methods constituents, in particular, curricula alongside with the educational and methodological support).

[This paper is part of the Focused Collection on Curriculum Development: Theory into Design.] Research in physics education has contributed substantively to improvements in the learning and teaching of university physics by informing the development of research-based instructional materials for physics courses. Reports on the design of these materials have tended to focus on overall improvements in student performance, while the role of theory in informing the development, refinement, and assessment of the materials is often not clearly articulated. In this article, we illustrate how dual-process theories of reasoning and decision making have guided the ongoing development, testing, and analysis of an instructional intervention, implemented at three different institutions, designed to build consistency in student reasoning about the application of Newton’s 2nd law to objects at rest. By employing constructs from cognitive science associated with dual-process theories of reasoning (such as mindware and cognitive reflection), we were able not only to examine the overall improvement in student performance but also to investigate the impact of the intervention on two aspects of productive reasoning—mindware and cognitive reflection. Our analysis showed that the intervention strengthened students’ mindware such that students were able to apply it as a criterion while checking the validity of their intuitive responses. Moreover, logistic regression revealed that the success of our intervention was mediated by the students’ cognitive reflection skills. Indeed, for students with comparable mindware, those who demonstrated a weaker tendency toward cognitive reflection were less likely to initiate conflict detection and therefore never had the opportunity to utilize their mindware. We believe that this kind of integrated, theory-driven approach to intervention design and testing represents an important first step in efforts to both account for and leverage domain-general reasoning phenomena in the learning and teaching of physics.

This study reviews published scientific literature on the use of swarm robots for education purposes in the last ten years. It focuses on user studies involving robotics swarm in order to identify the potential contributions of the incorporation of swarm robots as an educational tool and insight future research. We consider here the appearance of swarm robots, the curriculum of the experimental task and the interaction modalities between learners and robots. The outcomes of the literature review are discussed in terms of their existing challenges and opportunities for guiding researchers, educators, and practitioners.

With advances in science and technology, several innovative researches have been developed trying to figure out the main problems related to children’s learning. It is known that issues such as frustration and inattention, between others, affect student learning. In this fashion, robotics is an important resource that can be used towards helping to solve these issues, empowering our students in order to push their learning up. In this case, robotic tools are generally used considering two different paradigms: as the main focus and as a secondary focus. Actually, these paradigms define the way that Educational Robotics is implemented in schools. Most of the approaches have implemented it as the main focus, which is teaching Robotics. Nevertheless, there are quite a few works that implement robotics as a secondary focus, which is currently assisting the learning process in several disciplines. The main contribution of this work is a complete three steps methodology for Robotics in Education to guide projects in order to either use it alone or to teach robotics with others topics. Our experiments show the importance of devising a study plan and evaluation method because the process is iterative and could improve the final results. As a novelty, here we have joined and extended our previous works by proposing a new set of methods with guidelines and strategies for applying the educational robotics standard curriculum for kids, named EDUROSC-Kids. We propose several tools that have been developed to organize the learning topics of Robotics for children, including the desired outcomes during the learning process. As said our current approach is divided in three steps (or phases): setting up the environment, defining the project, and performing evaluation. The proposed curriculum organizes robotics contents into five disciplines: Robotics and Society, Mechanics, Electronics, Programming, and Control Theory. Also, it considers a set of topics for each discipline and defines the level of knowledge that is recommended to achieve each group of children based on Bloom’s Nomenclature. The contribution on this paper is a crucial step towards linking the general learning process with Educational Robotics approaches. Our methodology is validated by presenting practical experiences with application of EDUROSC-kids and the proposed method with a rubric guidelines into groups of children.

In this paper, we propose a method to analyse the coherence of existing curricula at higher education institution. We focus our attention to engineering programmes at universities but the proposed method is by no means restricted to those cases. In contrast to other known methods, our approach is quantitative, decentralised, and asynchronous and allows to analyse entire programmes (in contrast to single courses) and does not depend on using specific teaching methods or tools. We propose to perform this quantitative assessment in two steps: first, representing the university programme as an opportune graph with courses and concepts as nodes and connections between courses and concepts as edges; second, analysing the structure of the programme using methods from graph theory. We thus perform two investigations, both leveraging a practical case – data collected from three engineering programmes at two Swedish universities: (a) how to represent university programmes in terms of graphs (here called concepts-courses graph (CCG)) and (b) how to reinterpret the most classical graph-theoretical node centrality indexes and connectivity and network flow results in order to analyse the programme structure, including to discover flows and mismatches. © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.

Over the years, there are various reports that confirmed the importance of complex problem solving in the workplace. Complex problem solving is the top identified skill to thrive in the 4th Industrial Revolution and emphasised in the Washington Accord’s 12 Graduate Attributes. However, in most cases, engineering educators often fail to design complex engineering problems to equip the students with the mastery of this skill in preparing them for the workforce. This paper attempts to present a systematic approach for engineering educators in designing assessments with complex engineering problems. Methods of qualitative analysis was employed namely field notes from accreditation site visits to the Higher Learning Institutions (HLIs); document analysis on the guidelines by accreditation bodies; and extensive literature review on various learning theories to support the implementation of complex problems. The results showed that engineering educators have poor understanding of the attributes of complex problems and often failed to construct complex problems for their courses. The proposed approach has outlined two strategies in addressing the problems. Firstly, it detailed out the attributes of complex engineering problem as guidance for the HLIs in implementing the engineering curriculum. Secondly, it identified the most appropriate learning theory, appropriate teaching and delivery methods, as well as suitable courses to address complex engineering problem solving. The approach is heuristic in nature with an iterative process in observing the attainment of this important skill.