Msc program aims to address the challenge of forging deeper learning in STEM by integrating design thinking as an approach to teaching in which students construct and demonstrate understanding through a form of design. The project builds on the notion of embracing Design objectives, essentially utilising and blending multimodal STEM-based learning and to introduce STEM students the design process and the creative process, as well as the nature of design thinking. It is expected that this fusion between STEM and design will mitigate shortages and skills mismatches in STEM. On the other hand the Msc aims to include model based computational models in STEM Education and to introduce STEM Msc students the concept of using models as the fundamental instructional unit in their inquiry based teaching and learning scenario.
Significant parts of scientific research are carried out on models rather than on the real phenomena because by studying a model we can discover features of and ascertain facts about the system the model stands for. This cognitive function of models has been widely recognized in the literature, and some researchers even suggest that models give rise to a new form of reasoning, the so-called ‘model based reasoning’ while modelling ability is also associated to model-based reasoning. It is well known that scientific theories are developed through a process of continuous elaboration and modification in which scientific models are developed and transformed to account for new phenomena that are uncovered .Similar processes are involved in students' learning of STEM concepts when they develop conceptual models (e.g. Bell et.al, 2010,Psycharis,2015;16). In a similar fashion, inquiry based learning requires from students to make successive refinements to their mental models in order to transform them to conceptual models that align to scientific theories.
Simulation-based Engineering and Science is considered as the cognitive area that provides the Scientific and Mathematical basis for simulating Natural Science and Engineered systems. According to (Xie et.al, 2011) computational models used for problem solving are the best way to create a curriculum that is both deeper and wider. Resorting to first principles in Physics and Mathematics to build educational tools may be considered as exaggeration by some researchers in STEM Education, but it is essential in order to bring learning experience related to authentic phenomena. Building models of simulation from first principles relies on the use of Computational Thinking (CT). Using the computational model approach, students write the mathematical relations they suppose that govern the problem, they select the simulation method, they develop the algorithm and finally they are engaging in writing source code using software or programming languages.
The specific aims and objectives of the Msc program focus on:
- The creation of a critical mass of teachers with concise and compact knowledge of computational models that will be used by them for the development of Inquiry based educational scenario using the trans0disciplinary approach
- The discovery by teachers and generally by Msc students of new research areas that combine STEM with Didactics, so they will be able to write research papers and develop artefacts
- To help students who will want to continue for PhD degree.
- The knowledge of epistemological models and how they can be integrated in the computational experiment approach
- The acquaintance of students with proper –well established repositories connected with STEM education
- The provision of stents to training of how they will write source code for education purposes, using environments like . Lego Mindstorms ev3, LABVIEW,, Easy java simulations, Mathematica, Python και general STEM Technologies
- The knowledge of issues related to e-learning and authoring tools for e-learning.
- To teach students quantitative and qualitative methods for statistical analysis using SPSS and NVIVO.
- The development of serious games using the UNITY software.
- To get skills related to STEM Economy
Bell, T., Urhahne, D., Schanze, S., & Ploetzner, R.(2010). Collaborative inquiry learning: models, tools and challenges. International Journal of Science Education, 32(3), p. 349-377.
Psycharis, S., (2015).‘Inquiry Based- Computational Experiment, Acquisition of Threshold Concepts and Argumentation in Science and Mathematics Education (Accepted for publication at Journal “Educational Technology & Society”- http://www.ifets.info/ets_journal/preprint.php).
Psycharis, S. (2016). ‘The Impact of Computational Experiment and Formative Assessment in Inquiry Based Teaching and Learning Approach in STEM Education ; Journal of Science Education,25(2),316-326 and Technology (JOST) DOI 10.1007/s10956-015-9595-z
Xie,C., Tinker, R., Tinker, B., Pallant, A., Damelin, D., & Berenfeld, B.( 2011). Computational Experiments for Science Education. Science, 332, p.1516-1517.