Improving science and mathematics education with computational modelling in interactive engagement environments

Neves, Rui; Teodoro, Vitor Manuel Neves Duarte

doi:10.1063/1.4756529

Cited by 8 publications

(1 citation statement)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are many works developed in this decade [4][5][6][7][8][9][10][11][12]. With the increasing development of the graphic potentialities associated with the various programming languages, simulation and modelling activities for the teaching of physics become increasingly appealing, enhancing the understanding/visualization of the physical phenomena.…”

Section: Introductionmentioning

confidence: 99%

Computational Programming as a Tool in the Teaching of Electromagnetism in Engineering Courses: Improving the Notion of Field

2019

View full text Add to dashboard Cite

In this study we have attempted, firstly, to describe programming protocols developed for the teaching of an Electromagnetism course in the university degrees of Electrical Engineering and Energy Engineering, and secondly, to evaluate students’ satisfaction with the simulation practices through MATLAB® programming. The main objective of the protocols is to allow students to model and visualize the electric field and magnetic field (both static) and understand the approximation that is made when considering certain distributions of electric charges and electric currents. To evaluate the usefulness of this computational methodology, eighteen students from the two engineering degrees answered a questionnaire with seven questions related to the Electromagnetism course and to the benefits of using computer programming. Their answers are measured by a Likert scale. From the analysis of the results, we can conclude, in a general way, that the use of this methodology has positive effects in the learning of Electromagnetism in these two degrees.

show abstract

Section: Introductionmentioning

confidence: 99%

Computational Programming as a Tool in the Teaching of Electromagnetism in Engineering Courses: Improving the Notion of Field

2019

View full text Add to dashboard Cite

show abstract

Integrating Computational Modelling in Science, Technology, Engineering and Mathematics Education

Neves

Silva

Teodoro

2013

New ICMI Study Series

Self Cite

View full text Add to dashboard Cite

Modelling is a central aspect of the research process in science, technology, engineering, and mathematics (STEM), which occurs in the cognitive context of an interactive balance between theory, experiment, and computation. The STEM learning processes should then also involve modelling in environments where there is a balanced interplay between theory, experiment, and computation. However, an adequate integration of computational themes in STEM high school and undergraduate university curricula remains to be achieved. In this chapter, we present an approach to embed computational modelling activities in the STEM learning processes which may be fruitfully adopted by curricula at secondary and introductory university levels, as well as be a valuable instrument for the professional development of teachers. To illustrate, we consider the example of physics. IntroductionScience, technology, engineering and mathematics (STEM) are evolving structures of knowledge which are symbiotically interconnected. On one hand, science is based on hypotheses and models, leading to theories, which have a strong mathematical character as scientific reasoning, concepts and laws are represented by mathematical reason-1 ing, entities and relations. On the other hand, scientific explanations and predictions must be consistent with the results of systematic and reliable experiments, which depend on technological developments as much as these depend on the progress of science and mathematics (see, e.g., Chalmers, 1999; Crump, 2001;Feynman, 1967). The creation of STEM knowledge is a dynamical cognition process which involves a blend of individual and collective actions where modelling occurs with a balance between theoretical, experimental and computational elements (Blum, Galbraith, Henn & Niss, 2007;Neunzert & Siddiqi, 2000;Schwartz, 2007; Slooten, van den Berg & Ellermeijer, 2006). In this process, computational modelling plays a key role in the expansion of the STEM cognitive horizon through enhanced calculation, exploration and visualization capabilities.Although clearly related to real world phenomena, STEM knowledge is thus built upon abstract and subtle conceptual and methodological frameworks which in addition evolve following historical dependent paths. These epistemological and cognitive features make science, technology, engineering and mathematics difficult fields to learn and to teach. An approach to STEM education that aims to be effective and in phase with the rapid scientific and technological development should then be based on pedagogical methodologies inspired in the modelling processes of STEM professional activities. Meaningful learning (see, e.g., Mintzes, Wandersee & Novak, 2005) should then occur when students go through balanced interactive explorations of the different cognitive phases associated with the modelling cycles of STEM research, starting from a qualitative contextualization phase, setting the stage for the definition, exploration, interpretation and validation of the relevant mathematical models, and ...

show abstract

Teaching physics in science, technology, engineering and mathematics education contexts with interactive computational modelling

Neves

2019

AIP Conference Proceedings

View full text Add to dashboard Cite

Improving science and mathematics education with computational modelling in interactive engagement environments

Cited by 8 publications

References 11 publications

Computational Programming as a Tool in the Teaching of Electromagnetism in Engineering Courses: Improving the Notion of Field

Computational Programming as a Tool in the Teaching of Electromagnetism in Engineering Courses: Improving the Notion of Field

Integrating Computational Modelling in Science, Technology, Engineering and Mathematics Education

Teaching physics in science, technology, engineering and mathematics education contexts with interactive computational modelling

Contact Info

Product

Resources

About