For instance, in graphene the transversal conductance σ xy is discretized in steps
with half integer multiples of 4e
2 /h and the longitudinal resistivity ρ xx falls to zero in
each plateau (Novoselov et al. 2005)
16.3.5 Evaluation Phase
The quantum Hall Effects result from an intriguing interplay among disorder and
interactions, but the basic physics is that describing an electron subjected to a
magnetic field. Additionally, in a specific case (FQHE), there is indication of the
existence of interaction processes that manifest as a fractional charge and could
facilitate the understanding of physics governing interacting particles. At the end of
the learning experience learners should have consolidated their knowledge about the
different features of the Hall Effect and accomplished a more meaningful knowledge
of the important concepts concerning the quantum behavior of correlated particles
(Persano-Adorno et al. 2019). In particular, they should be capable to make a
comparison between the Cooper pairs in superconductors and the composite electrons in graphene, and to recognize analogies or differences among the concepts of
effective mass of electrons in semiconductors and effective charge of Dirac fermions
in graphene (Persano-Adorno et al. 2018b).
In this perspective, the integration between active learning and numerical simulations could be very fruitful.
16.4 Conclusion
A real understanding of scientific concepts is accomplished when learners can utilize
those concepts to solve problems never encountered before. An appropriate instruction on problem solving should be based on the development and reinforcing of
student reasoning abilities. Higher levels of thinking skills can be established by
“forcing” the students to directly experiment the world and strive for finding answers
to real problems. This can be achieved by training students to pose scientifically
appropriate inquiries, perform scientific explorations, obtain meaningful measurements and analyze experimental data, build explicative models, check findings with
further investigations, share and discuss results with peers. Teacher’s responsibility
on supplying an appropriate scaffolding is central because Inquiry-based learning
settings with a lower teacher supervision may stimulate higher reasoning competencies, but occasionally may produce negative feelings due, for example, to run into
mistakes or achieve unexpected findings. Our results show that the integration
between the use of numerical simulations and a specific activation of the inquiry
process can represent an effective teaching approach to successfully engage undergraduates into an active learning. This may represent a possible example of merging
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D. Persano-Adorno
with half integer multiples of 4e
2 /h and the longitudinal resistivity ρ xx falls to zero in
each plateau (Novoselov et al. 2005)
16.3.5 Evaluation Phase
The quantum Hall Effects result from an intriguing interplay among disorder and
interactions, but the basic physics is that describing an electron subjected to a
magnetic field. Additionally, in a specific case (FQHE), there is indication of the
existence of interaction processes that manifest as a fractional charge and could
facilitate the understanding of physics governing interacting particles. At the end of
the learning experience learners should have consolidated their knowledge about the
different features of the Hall Effect and accomplished a more meaningful knowledge
of the important concepts concerning the quantum behavior of correlated particles
(Persano-Adorno et al. 2019). In particular, they should be capable to make a
comparison between the Cooper pairs in superconductors and the composite electrons in graphene, and to recognize analogies or differences among the concepts of
effective mass of electrons in semiconductors and effective charge of Dirac fermions
in graphene (Persano-Adorno et al. 2018b).
In this perspective, the integration between active learning and numerical simulations could be very fruitful.
16.4 Conclusion
A real understanding of scientific concepts is accomplished when learners can utilize
those concepts to solve problems never encountered before. An appropriate instruction on problem solving should be based on the development and reinforcing of
student reasoning abilities. Higher levels of thinking skills can be established by
“forcing” the students to directly experiment the world and strive for finding answers
to real problems. This can be achieved by training students to pose scientifically
appropriate inquiries, perform scientific explorations, obtain meaningful measurements and analyze experimental data, build explicative models, check findings with
further investigations, share and discuss results with peers. Teacher’s responsibility
on supplying an appropriate scaffolding is central because Inquiry-based learning
settings with a lower teacher supervision may stimulate higher reasoning competencies, but occasionally may produce negative feelings due, for example, to run into
mistakes or achieve unexpected findings. Our results show that the integration
between the use of numerical simulations and a specific activation of the inquiry
process can represent an effective teaching approach to successfully engage undergraduates into an active learning. This may represent a possible example of merging
212
D. Persano-Adorno