2013
DOI: 10.1187/cbe.13-01-0011
|View full text |Cite
|
Sign up to set email alerts
|

Student Learning about Biomolecular Self-Assembly Using Two Different External Representations

Abstract: This study found that external representations can support university students' learning in a group discussion about the counterintuitive concept of biomolecular self-assembly. In addition, qualitative differences indicated that the tangible model was particularly well-suited to support learning of dynamic aspects compared with the static image.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
24
0
3

Year Published

2014
2014
2024
2024

Publication Types

Select...
7
1

Relationship

1
7

Authors

Journals

citations
Cited by 24 publications
(27 citation statements)
references
References 40 publications
0
24
0
3
Order By: Relevance
“…Furthermore, 19% of respondents did not correctly express the fact that, "Objects at the nanoscale are kept in random motion by continuous collisions with other particles" (True), which perhaps indicates the conceptual demands of perceiving the "sticky", "shaky" and "bumpy" (Jones et al, 2013) properties of the nanoworld. Moreover, the observation that "Nanotubes spontaneously aggregate together into rope-like structures" (True) was unknown by 56% of the participants could indicate a lack of (albeit cognitively demanding) knowledge that emergent properties may arise from random molecular events (Höst et al, 2013).…”
Section: Conceptual Considerations Arising From Responses To the Nanokimentioning
confidence: 99%
See 2 more Smart Citations
“…Furthermore, 19% of respondents did not correctly express the fact that, "Objects at the nanoscale are kept in random motion by continuous collisions with other particles" (True), which perhaps indicates the conceptual demands of perceiving the "sticky", "shaky" and "bumpy" (Jones et al, 2013) properties of the nanoworld. Moreover, the observation that "Nanotubes spontaneously aggregate together into rope-like structures" (True) was unknown by 56% of the participants could indicate a lack of (albeit cognitively demanding) knowledge that emergent properties may arise from random molecular events (Höst et al, 2013).…”
Section: Conceptual Considerations Arising From Responses To the Nanokimentioning
confidence: 99%
“…In further support of the premise that nano can serve as a "unifying idea" in chemistry education, Jones et al (2015) advocate that chemical concepts such as molecular bonding and molecular motion are connected to developing an understanding of self-assembly at the nanoscale. Similarly, Höst et al (2013) demonstrate the importance of integrating several chemical concepts such as noncovalent interactions and complementarity in conceptualising the nanotechnological implications of selfassembly. Lastly, our own work (e.g.…”
Section: Introductionmentioning
confidence: 96%
See 1 more Smart Citation
“…One non-digital biological example is a tangible model of a virus that was used to study its effects on students' meaning-making of a sub-microscopic process, the self-organization of a virus capsid (Höst et al 2013). This process was perceived as counter-intuitive since a virus capsid is created via random collations of subunits.…”
Section: Randomness and Probability In Visualizationsmentioning
confidence: 99%
“…With the advent of computing and robotics, touch is a sensory channel that continues to receive a great deal of attention, mostly through the use of haptic interaction strategies [ 3 , 4 , 5 ]. Touch is also exploited in systems that utilize tangible physical models [ 6 ] that may be augmented virtually [ 7 ] and which have shown promise in enhancing student learning [ 8 ]. Beyond touch, a variety of sensory channels related to visual and audio feedback may be used to enhance the immersive effect, and preliminary applications of such integrated methods have occurred in the context of docking problems [ 9 ].…”
Section: Virtual and Augmented Reality And Immersive Molecular Simulamentioning
confidence: 99%