Arbeitsgruppe Prof. Kuhn

Quantum Educational Tools

Learning quantum physics with the Quantum Composer, an interactive visualization and simulation tool

Prof. Dr. Jochen Kuhn
Dr. Stefan Küchemann

Sergey Mukhametov
Dr. David Dzsotjan,

TU Kaiserslautern

Malte S. Ubben
Stefan Heusler

WWU Münster

Carrie A. Weidner
Jacob Sherson

Aarhus University

Prof. Dr. Jochen Kuhn
Dr. Stefan Küchemann

TU Kaiserslautern


- Concepts in quantum mechanics are abstract and counterintuitive – add visual representation to support concept learning
- Central facets of next generation: Enabling students to employ scientific practices to obtain and use information

Aim of this work:
Study of visual attention distribution of experts and novices when using the Quantum Composer (QC) – a quantum simulation & visualization tool

Research question:
How do Experts and Novices visually process information while solving quantum physics problems using the QC?

Study design & details

- N=36 (28 Novices: 22 male/ 6 female/ 1 no statement; 8 Experts: 8 male)
- Minimum language level in German: B2
- original Novices: Master studies in Physics
- original Experts: PhD students and postdocs with degree in physics

Data collection: 
WWU Münster (22 Novices, 2 Experts),
TU Kaiserslautern (4 Novices, 4   Experts),
and at MCQST (LMU, TUM; 2 Novices, 2 Experts)

Pretest & Tasks

- 8 items covering concepts of general Quantum Physics, one dimensional infinite/finite square well, and harmonic oscillator
- resampling of Novices & Experts at a threshold of 0.5 (relative pretest score)

Quantum Composer Tasks:
- 5 items targeting the double well potential,
- time limit of 20 min,
- here we focus on task 1 and 2 as they were completed by all participants

Discussion and conclusion of preliminary results

Novices: exhibit a tendency to overly rely on the graph or they are not as efficient in extracting information from the graph and focus significantly longer on irrelevant information
  -> Novices may be affected by the picture bias when using the quantum composer

Experts: focus significantly longer on task-relevant information and pay less attention to task-irrelevant information
  -> Confirmation of the information reduction hypothesis that experts are more efficient in neglecting task-  irrelevant information and actively focusing on task-relevant information

Suggestions to support novices when using interactive simulation tools
-Initial explanation of relevant and irrelevant parameters for the task
-Initial review of how complex representations depict information
-Eye-Movement Modelling Examples of experts are likely to be helpful for novices

Multiple External Representations (MERs)

- are tools for building conceptual knowledge (Stylianou, 2020)
- can foster learning and problem solving compared to single representations (e.g., Hu et al., 2019)

Each type has specific affordances (Fredlund et al., 2014),  relating MERs can be difficult for students (e.g., van der Meij et al. , 2006).

“Representational competence enables students to learn from visual representations.” (de Jong et al. 1998)

Gaze behavior of Experts and Novices

- People mentally process the information they focus on (Eye-Mind Hypothesis; Just & Carpenter, 1984)
- Experts possess perceptual knowledge (Larkin et al., 1980) and effectively process information in chunks (Simon, 1974)
- Experts are superior in parafoveal processing, i.e., experts have an extended visual range where they can process information (Holistic model of image perception; Gegenfurtner et al., 2011)
- Eperts demonstrate more efficient information processing due to the acqusition of retrieval structures (Theory of long-term working memory; Ericsson and Kintsch, 1995)
- Experts select relevant and neglect irrelevant information more efficiently (Information-Reduction Hypothesis, Haider and Frensch, 1999)

Quantum Composer

•The Quantum Composer can simulate time-dependent quantum mechanics and quantum control in one dimension, both for single particles and Bose-Einstein condensates
•Research results: students can use Composer to visualize systems, get the right answer, explore unfamiliar systems without any apparent intimidation
•Thus, Composer augments traditional lectures, theoretical exercises, and training in computational physics


Preliminary results

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