Disrupting scientific podcasts. Prototype and blueprints for an ergodic neuroscientific talk.
In this paper, we propose an innovative framework for scientific podcasts that integrates principles of ergodic literature and hypertext theory to enhance user engagement and educational depth. Traditional podcasts follow a linear structure, limiting user interaction and exploration. Our approach disrupts this norm by transforming podcasts into non-linear, interactive experiences. We introduce a prototype that segments expert interviews into concise, interconnected video fragments, each augmented with hyperlinked references to related scientific articles, interactive diagrams, and educational resources. This method allows users to navigate content in a personalized, exploratory manner, facilitating deeper engagement with complex topics in computational neuroscience. Detailed metadata annot- doi
- 10.1145/3648188.3678217
- isbn
- 979-8-4007-0595-3
- name
- Disrupting scientific podcasts. Prototype and blueprints for an ergodic neuroscientific talk.
- source
- publisher_html_pdf
- acm_url
- https://dl.acm.org/doi/10.1145/3648188.3678217
- authors
- Jan K. Argasiński, Kamil Pilch, Joan Falcó-Roget, Anna Partyka, Katarzyna Baliga-Nicholson
- doi_url
- https://doi.org/10.1145/3648188.3678217
- license
- CC BY-NC-SA 4.0
- summary
- In this paper, we propose an innovative framework for scientific podcasts that integrates principles of ergodic literature and hypertext theory to enhance user engagement and educational depth. Traditional podcasts follow a linear structure, limiting user interaction and exploration. Our approach disrupts this norm by transforming podcasts into non-linear, interactive experiences. We introduce a prototype that segments expert interviews into concise, interconnected video fragments, each augmented with hyperlinked references to related scientific articles, interactive diagrams, and educational resources. This method allows users to navigate content in a personalized, exploratory manner, facilitating deeper engagement with complex topics in computational neuroscience. Detailed metadata annot
- published
- 2024-09-10
- conference
- HT '24: 35th ACM Conference on Hypertext and Social Media, Poznan, Poland, September 10-13, 2024
- open_access
- true
- acm_html_url
- https://dl.acm.org/doi/full/10.1145/3648188.3678217
- displayAuthor
- Jan K. Argasiński, Kamil Pilch, Joan Falcó-Roget, Anna Partyka, Katarzyna Baliga-Nicholson
- displayPublishTime
- 2024-09-10
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