Modelling activities are very important in the field of STEM and represent a common ground among those disciplines. One of the objectives of teaching STEM is to lead students to develop models: representations that can describe and explain the phenomena of reality. Using a model, it is possible to obtain predictions on the progress of experiments, mechanisms and processes. Modelling can be a highly educational didactic activity because it allows students to see analogies and differences among phenomena that are traditionally treated in different areas. Modelling can also be considered a valid approach to many different problems, making it a common ground among the various STEM disciplines. The use of new technologies, such as an Advanced Computing Environment (ACE), can support modelling activities. An ACE is a system that allows to perform numerical and symbolic calculation, make graphical representations in 2 and 3 dimensions and create mathematical simulations through interactive components. Moreover, it is able to support students in reasoning processes, in the formulation of exit strategies and in the generalization and re-adaptation of the solution in different contexts. The activity involved 72 university students attending a 15-hour training course on the use of an ACE for scientific research. Students are enrolled in degree courses in various STEM disciplines, and they attend different years of bachelor and master's degree. During the training course, students learned the functionalities of an ACE and used it for visualization and modelling, to write procedures and for problem solving. For the modelling activity, proposed at the end of the training course, 6 problems of different topics and contexts were proposed to the students: a problem of population dynamics; a problem of kinematic; a problem of inventory management; a linear programming problem; a parameter regression problem; and an encryption problem. After choosing one, students had to model the proposed situation and solve the problem using the ACE. The research questions are the following. Did the students model the same situation differently or using different types of representations? How did using an ACE support the modelling activity? All72 students' works were examined for the analysis, in particular the resolutions of the kinematics problem that was chosen by 50% of the students. Students' responses to two questionnaires that they completed at the beginning and end of the training course were also considered. The analysis shows that the students made different models, in some cases incorrect, depending on the interpretation of the text of the problem. The use of an ACE allowed the students to make different models - characterized by the use of different types of registers (graphs, formulas, algorithms, etc.) - and to generalize the problematic situation with a system of interactive components. The ability to see how the results vary as the initial data changes allows students to have immediate feedback on any prediction and verify the accuracy of the model.
Modelling with an Advanced Computing Environment in a STEM problem-solving activity by university students
Cecilia Fissore;Francesco Floris;Marina Marchisio
2020-01-01
Abstract
Modelling activities are very important in the field of STEM and represent a common ground among those disciplines. One of the objectives of teaching STEM is to lead students to develop models: representations that can describe and explain the phenomena of reality. Using a model, it is possible to obtain predictions on the progress of experiments, mechanisms and processes. Modelling can be a highly educational didactic activity because it allows students to see analogies and differences among phenomena that are traditionally treated in different areas. Modelling can also be considered a valid approach to many different problems, making it a common ground among the various STEM disciplines. The use of new technologies, such as an Advanced Computing Environment (ACE), can support modelling activities. An ACE is a system that allows to perform numerical and symbolic calculation, make graphical representations in 2 and 3 dimensions and create mathematical simulations through interactive components. Moreover, it is able to support students in reasoning processes, in the formulation of exit strategies and in the generalization and re-adaptation of the solution in different contexts. The activity involved 72 university students attending a 15-hour training course on the use of an ACE for scientific research. Students are enrolled in degree courses in various STEM disciplines, and they attend different years of bachelor and master's degree. During the training course, students learned the functionalities of an ACE and used it for visualization and modelling, to write procedures and for problem solving. For the modelling activity, proposed at the end of the training course, 6 problems of different topics and contexts were proposed to the students: a problem of population dynamics; a problem of kinematic; a problem of inventory management; a linear programming problem; a parameter regression problem; and an encryption problem. After choosing one, students had to model the proposed situation and solve the problem using the ACE. The research questions are the following. Did the students model the same situation differently or using different types of representations? How did using an ACE support the modelling activity? All72 students' works were examined for the analysis, in particular the resolutions of the kinematics problem that was chosen by 50% of the students. Students' responses to two questionnaires that they completed at the beginning and end of the training course were also considered. The analysis shows that the students made different models, in some cases incorrect, depending on the interpretation of the text of the problem. The use of an ACE allowed the students to make different models - characterized by the use of different types of registers (graphs, formulas, algorithms, etc.) - and to generalize the problematic situation with a system of interactive components. The ability to see how the results vary as the initial data changes allows students to have immediate feedback on any prediction and verify the accuracy of the model.
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