Open Access Articles
The continuous growth of STEM (Science, Technology, Engineering and Mathematics) education has set intense pressure on well-established engineering subjects, with a trend of replacing them with less demanding theoretical contents. This paper describes a recent activity with bachelor students to stimulate STEM education via a Robot-Sumo Competition. Students are grouped in teams to design, build and program their robot sumo robots. This course was implemented for the first time at University of Calabria (UNICAL). As a first attempt has been made with six teams each made of six students. Some seminars are delivered to the students to let them understand the assignment and its basic requirements. Then, they are expected to start developing a concept design and competition strategy. Then, they work on a 3D CAD modelling to design their own robot, whose main components will be later 3D printed and assembled. In parallel, the team selects the required sensors and electronic components as based on an Arduino architecture. The robots are completed and programmed for the competition where teams fight to find the most competitive solutions. The competition proves to be highly effective to learn multiple skills with a very practical and stimulating approach.
For students who are academically ineligible to enter a bachelor program in engineering but still want to upskill their knowledge in engineering, many universities provide an associate degree program in engineering to these students. The higher achievers from the associate degree program can transfer to a full degree program in engineering. Mathematics courses in such associate degree programs are often challenging to both the teachers and students due to various reasons. This paper presents a small part of a mathematics revitalization project on pedagogical adjustment to scaffold mathematics learning for students in an associate engineering program at Central Queensland University (CQU), a regional university in Australia, from 2018 to 2020. The design and implementation of the online multi-purpose quizzes (MPQ) to improve both the learning environment and outcomes for the engineering students from 2018 to 2020 are reported in this work. Statistically, the online MPQ empowered students to achieve their best possible outcomes by attempting the questions with time flexibility, on a confined set of topics, and with more chances of amending errors than the traditional written assessments. Hence, their performance in the online MPQ was consistently better than that in the written assignments in 2018-2020. The weaknesses of the online MPQ are also discussed.
In the last decade, major efforts have been made to promote inquiry-based mathematics learning at the tertiary level. The Inquiry-Based Mathematics Education (IBME) movement has gained strong momentum among some mathematicians, attracting substantial funding from US government agencies. This resulted in the successful mobilization of regional consortia in many states, uniting over 800 mathematics education practitioners working to reform undergraduate education. Inquiry-based learning is characterized by the fundamental premise that learners should be allowed to learn 'new to them' mathematics without being taught. This progressive idea is based on the assumption that it is best to advance learners to the level of experts by engaging learners in mathematical practices similar to those of practicing mathematicians: creating new definitions, conjectures and proofs - that way, learners are thought to develop 'deep mathematical understanding'.
However, concerted efforts to radically reform mathematics education must be systematically scrutinized in view of available evidence and theoretical advances in the learning sciences. To that end, this scoping review sought to consolidate the extant research literature from cognitive science and educational psychology, offering a critical commentary on the effectiveness of inquiry-based learning. Our analysis of research articles and books pertaining to the topic revealed that the call for a major reform by the IBME advocates is not justified. Specifically, the general claim that students would learn better (and acquire superior conceptual understanding) if they were not taught is not supported by evidence. Neither is the general claim about the merits of IBME for addressing equity issues in mathematics classrooms.
Cultural differences have a strong influence on the work and study climate in cross-cultural environment. A difference in power distance has been shown to be a major factor in decreasing motivation, especially when the superior follows a hierarchical leadership style but the subordinates expect equality. This can lead to high turnover rates in companies and low learning outcomes in schools if not taken into consideration. In this paper, we use examples to demonstrate how the problems appeared in two case studies of Chinese companies operating in Europe. The findings have been categorized into five themes: hierarchy, authority, closed communication, promotion, and unequal treatment.
This paper sheds light on the impact of the COVID-19 pandemic on society and the surrounding environment, with a special focus on education and the social aspect. Specifically, how the pandemic has disrupted education systems across the globe by forcing the closure of primary and secondary schools, colleges and universities is discussed. Since it is not only the students who were affected by this worldwide health emergency, the impact on educators and parents, as well as all aspects of the education system, including admissions, assessments and evaluations, is also debated. These facets are discussed while emphasizing the shifts that many organizations underwent to maintain operations while adhering to the announced governmental restrictions related to the circulation of the pandemic. Specifically, the needs to rapidly implement significant modifications to their usual practices and standard operational processes and convert their existing teaching materials to another format to make them appropriate for online delivery are highlighted and discussed.
Fluids′ viscous behavior is apparent in many everyday life situations, for example, in squeezing shampoo from a bottle or spooning honey from a jar. As a result, it is quite reasonable to assume that students develop (pre)conceptions to explain such phenomena even before they enter kindergarten or elementary school. As yet, however, empirical studies on children′s conceptions regarding the viscous behavior of fluids are remarkably scarce. The present study aims to address this research gap on an exploratory level. More precisely, we conducted a qualitative interview study in which we explored the conceptions about the viscous behavior of honey among N = 6 preschool children attending their final year in a kindergarten in Hamburg (Germany). For stimulating the conversation during the interviews, an easily noticeable phenomenon in which the viscous behavior of honey can be observed (dropping two identical spoons into a honey-filled and a water-filled glass) was demonstrated to the participating children. In summary, the analysis of the transcribed interviews revealed three distinguishable conceptions of the children about the viscous behavior of honey: (1) The viscous behavior of honey results from its stickiness, (2) from its additional physical characteristics, and (3) from its use in everyday life. In this Express Letter, we present the design and results of our study in detail. Recommendations for future research in science education are outlined at the end of this paper.
Motivation is a key factor for success in education and modern working life. Cross-cultural environment is a challenge to it and, if not taken into account, it can impair learning outcome and lead to high turnover rates in companies. We performed an ethnographic study in two Chinese companies expanded to Europe and observed what problems the organizations faced. Our finding is that main problems originate from cultural differences between Chinese and Western organizations, and that they are mostly explained by the different power distance in the two cultures. The host company has a steep hierarchy of the organization, and it did not delegate the decision making to the locals. This led to frustration, loss of motivation, and high turnover rate.
Tertiary education faced unprecedented disruption resulting from COVID-19 driven lockdowns around the world, leaving educators with little understanding of how the pandemic and consequential shift to online environments would impact students′ learning. Utilising the theoretical framework of a student′s affective field, this study aimed to investigate how student achievement, achievement-related affect, and self-perceived well-being contributed to predicting how their learning was impacted. Questionnaire responses and academic achievement measures from students (N = 208) in a New Zealand second-year, tertiary mathematics course were analysed. Despite a return to in-person teaching after eliminating community-transmission of the virus, students reported larger impacts of the disruption to semester on both their learning and well-being at the end of the term than during the lockdown. Hierarchical multiple regression revealed that gender, prior achievement, performance on low-stakes assessment, as well as exam-related self-efficacy and hope, made significant, independent contributions to explaining students′ perceived learning impact. Even when controlling for achievement and achievement-related affect, students′ perceived impact to their well-being made a significant and substantial contribution to the impact on their learning. The findings provide motivation to further investigate whether attempts to address student achievement-related affect can help mitigate the effects of major life disruptions on studying. We suggest that frequent, low-stakes assessment can identify students who are more likely to report greater negative impacts to their learning. We finally conclude that student well-being is paramount to how students perceive their own learning, even when controlling for actual measures of and about their achievement.
Spare-view CT imaging is advantageous to decrease the radiation exposure, acquisition time and computational cost, but suffers from severe streak noise in reconstruction if the classical filter back projection method is employed. Although a few compressed sensing based algorithms have recently been proposed to remedy the insufficiency of projections and have achieved remarkable improvement in reconstruction quality, they face computational challenges for large-scale CT images (e.g., larger than 2000℅2000 pixels). In this paper, we present a fast non-uniform Fourier transform based reconstruction method, targeting at under-sampling high resolution Synchrotron-based micro-CT imaging. The proposed method manipulates the Fourier slice theorem to avoid the involvement of large-scale system matrices, and the reconstruction process is performed in the Fourier domain. With a total variation penalty term, the proposed method can be formulated into an unconstrained minimization problem, which is able to be efficiently solved by the limited-memory BFGS algorithm. Moreover, direct non-uniform Fourier transform is computationally costly, so the developed NUFFT algorithm is adopted to approximate it with little loss of quality. Numerical simulation is implemented to compare the proposed method with some other competing approaches, and then real data obtained from the Australia Synchrotron facility are tested to demonstrate the practical applications of the proposed approach. In short, the significance of the proposed approach includes (1) that it can handle high-resolution CT images with millions of pixels while several other contemporary methods fail; (2) that it can achieve much better reconstruction quality than other methods when the projections are insufficient.
The COVID-19 pandemic has accelerated innovations for supporting learning and teaching online. However, online learning also means a reduction of opportunities in direct communication between teachers and students. Given the inevitable diversity in learning progress and achievements for individual online learners, it is difficult for teachers to give personalized guidance to a large number of students. The personalized guidance may cover many aspects, including recommending tailored exercises to a specific student according to the student′s knowledge gaps on a subject. In this paper, we propose a personalized exercise recommendation method named causal deep learning (CDL) based on the combination of causal inference and deep learning. Deep learning is used to train and generate initial feature representations for the students and the exercises, and intervention algorithms based on causal inference are then applied to further tune these feature representations. Afterwards, deep learning is again used to predict individual students′ score ratings on exercises, from which the Top-N ranked exercises are recommended to similar students who likely need enhancing of skills and understanding of the subject areas indicated by the chosen exercises. Experiments of CDL and four baseline methods on two real-world datasets demonstrate that CDL is superior to the existing methods in terms of capturing students′ knowledge gaps in learning and more accurately recommending appropriate exercises to individual students to help bridge their knowledge gaps.
For thousands of years, the compass-and-straightedge tools have dominated the learning and teaching of geometry. As such, these inherited, long-standing instruments have gained a lustre of naturalized pedagogical value. However, mounting evidence suggests that many learners and teachers struggle to efficiently, effectively and safely use compasses when constructing geometric figures. Compasses are difficult for learners to use, can lead to inaccurate drawings, and can be dangerous. Thus, there is value in reconsidering the role of the compass in the learning and teaching of geometric constructions and to offer better tools as alternatives. The purpose of this work is to address the aforementioned need by proposing an alternative tool to the compass that is safer, more efficient and more effective. We will argue that a circle arc template forms such an alternative tool, and we will illustrate how learners and teachers can add value to their classrooms by using it, in conjunction with a straightedge, to establish the well-known constructions seen in geometry curricula around the world.
Discussions about teaching area measurement in primary school have been ongoing over some decades. However, investigations that thoroughly examine the current research on conceptual understanding in area measuring in elementary schools are still lacking. The objective of this paper is to review whether conceptual knowledge in area measurement may support students to obtain better results in primary schools. This study is to gain insight into how conceptual knowledge in area measurement has been portrayed for primary school students, and reveal possible omissions and gaps in the synthesized literature on the subject. To gather information, two databases were used: Scopus and Web of Science. Primary searches pulled up many studies on the subject of investigation. After analyzing abstracts and eliminating duplicates, our systematic review indicates that there seems a direct link between conceptual understanding and area measurement in primary school mathematics. Hence, teaching children the principle of area measurement rather than a procedure for solving problems seems to be the most effective way of improving problem-solving skills and conceptual understanding for primary students.
Integration by parts can be applied in various ways for obtaining solutions for different types of integrations and hence it is taught in all calculus courses in the world. However, the coverage and discourse of various applications of integration by parts in most textbooks, often packed into one section, lack a cohesion of progression for solving different types of integrals. Students may be confused by such incohesive presentation of the method and applications in the textbooks. Based on the author's experiences and practices in teaching applied calculus for undergraduate engineering and education students since 2013, a streamlined approach in teaching integration by parts has been gradually developed to the current state and ready to be shared with the mathematics teaching and learning communities. This streamlined approach allows integration by parts to be applied to solve complicated and integrated problems in a progressive way so that students can improve efficacy in their use of integration by parts gradually. This approach also makes communications easier with students on particular problems involving integration by parts.
The redesign of national curricula across the Anglophone world since the 1990s is demonstrably shaped by common policy trends. Focusing on the profound and uncritiqued changes that have been implemented in New Zealand education, this paper provides a critical commentary on the characterising features of the current New Zealand mathematics curriculum, describing a context within which mathematics education at schools is severely compromised. Drawing on the evidence available from large-scale international indicators, such as PISA and TIMSS, to benchmark associated curriculum changes implemented by the New Zealand government, we hypothesise that the ongoing decline of student mathematical achievement is the result of four main interdependent features which characterise the New Zealand curriculum. The features are (1) its highly generic non-prescriptive nature, (2) a commitment to teacher autonomy in curriculum knowledge selection, (3) competency-based outcomes approach, and (4) a commitment to localisation in curriculum selection. Recognising socio-political forces and ideological and intellectual ideas associated with those forces, we discuss each characterising feature, in turn, to show how they contribute to and draw from the others to create a 'curriculum without content'. We conclude with explicit recommendations and a call for future studies to establish the extent to which each of these four features contributes to the decline of student achievement.
The integration of robotics education with science, technology, engineering, and mathematics (STEM) education has a great potential in future education. In recent years, numerous countries have hosted robotic competitions. This study uses a mixed research method to explore the coaches' views on student participation in the World Robot Olympiad (WRO) by incorporating the questionnaire surveys and interviews conducted at the 2019 WRO finals in Hungary. By quantitative and qualitative analyses, coaches generally agreed that participation in the WRO improved students' STEM learning skills and cultivated their patience and resilience in handling challenging tasks.
This study set out to evaluate an intervention that introduced a period of non-routine problem-solving into tertiary STEM lectures at four tertiary institutions in New Zealand for 683 students. The aim was twofold: to attempt to increase student engagement and to introduce them to the kind of domain-free abstract reasoning that involves critical, creative, and innovative thinking. This study was conducted using a mixed-methods approach, utilizing different types of instruments to gather data: comprehensive student pre- and post-test questionnaires, a content validation survey for the questionnaires, focus group interviews (student participants), open-ended questionnaire (lecturer participants), and naturalistic class observations. The main findings are as follows. Students' behavioural engagement was significantly greater during the intervention. Perceptions of the utility value of the activity improved at the end of the semester for all students. There were no significant changes in students' convergent thinking (problem-solving), intuition, or creativity (originality, fluency, and elaboration traits of the divergent thinking) during the course, probably due to the relatively short timescale of the intervention. However, overall, the results of the investigation suggest that with a relatively small effort, teachers can improve STEM student engagement by devoting a few minutes per lecture on non-routine problem-solving. This is something that can be easily implemented, even by those who primarily teach in a traditional lecturing style.
The goal of this paper is to examine the place of modelling in STEM education and teacher education. First, we introduce modelling as a cyclical process of generating, testing, and applying knowledge while highlighting the epistemological commonalities and differences between the STEM disciplines. Second, we build on the four well-known frameworks, to propose an Educational Framework for Modelling in STEM, which describes both teacher and student roles in the modelling cycle. Third, we use this framework to analyze how modelling is presented in the new mathematics and science school curricula in two Canadian provinces (Ontario and British Columbia), and how it could be implemented in teacher education. Fourth, we emphasize the epistemological aspects of the Educational Framework for Modelling in STEM, as disciplinary epistemological foundations may seem too abstract to both teacher educators and teachers of STEM school subjects. Yet, epistemologies are the driving forces within each discipline and must be considered while teaching STEM as a unified field. To nurture critical thinkers and innovators, it is critical to pay attention to what knowledge is and how it is created and tested. The Educational Framework for Modelling in STEM may be helpful in introducing students and future teachers to the process of modelling, regardless of if they teach it in a single- or a multi-discipline course, such as STEM. This paper will be of interest to teacher educators, teachers, researchers, and policy makers working within and between the STEM fields and interested in promoting STEM education and its epistemological foundations.
With the rise of the COVID-19 pandemic and its inevitable consequences in education, increased demand for robust online learning frameworks has occurred at all levels of the education system. Given the transformative power of Artificial Intelligence (AI) and machine learning algorithms, there have been determined attempts through the design and application of intelligent tools to overcome existing challenges in online learning platforms. Accordingly, educational providers and researchers are investigating and developing intelligent online learning environments which share greater commonalities with real-world classroom conditions in order to better meet learners' needs. However, short attention spans and the widespread use of smart devices and social media bring about new e-learning systems known as microlearning (ML). While there has been ample research investigating ML and developing micro-content, pedagogical challenges and a general lack of alternative frameworks, theories and practices still exist. The present models have little to say about the connections between social interaction, including learner–content, learner–instructor and learner–learner communication. This has prompted us to investigate the complementary aspects of Computer-supported Collaborative Learning (CSCL) as an interactive learning model, along with an embedded ML module in the design and development of a comprehensive learning platform. The purpose of this study is to explore the pedagogical frameworks and challenges with reference to interaction and retention in online learning environments, as well as the theoretical and pedagogical foundations of ML and its applications. In addition, we delve into the theories and principles behind CSCL, the main elements in CSCL, identifying the issues and challenges to be faced in improving the efficacy of collaboration processes and outcomes. In short, we aim to synthesize how microlearning and CSCL can be applied as effective modules within a comprehensive online learning platform, thereby offering STEM educators a relevant roadmap towards progress that has yet to be offered in previous studies.
The Laplace transform is a popular approach in solving ordinary differential equations (ODEs), particularly solving initial value problems (IVPs) of ODEs. Such stereotype may confuse students when they face a task of solving ODEs without explicit initial condition(s). In this paper, four case studies of solving ODEs by the Laplace transform are used to demonstrate that, firstly, how much influence of the stereotype of the Laplace transform was on student's perception of utilizing this method to solve ODEs under different initial conditions; secondly, how the generalization of the Laplace transform for solving linear ODEs with generic initial conditions can not only break down the stereotype but also broaden the applicability of the Laplace transform for solving constant-coefficient linear ODEs. These case studies also show that the Laplace transform is even more robust for obtaining the specific solutions directly from the general solution once the initial values are assigned later. This implies that the generic initial conditions in the general solution obtained by the Laplace transform could be used as a point of control for some dynamic systems.
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