Designing a Better Reading Experience with Matter: Incorporating Social Learning Theory for Optimal Knowledge Acquisition

Designing a Better Reading Experience with Matter: Incorporating Social Learning Theory for Optimal Knowledge Acquisition

Introduction:

When it comes to reading online, there are various behaviors involved, including deciding what to read, the act of reading itself, and what one does with the acquired knowledge. As avid users of read-it-later apps, my co-founder Rob Mackenzie and I recognized the need for a better reading experience, which led us to create Matter. In this article, we will explore how the principles of social learning theory, as proposed by Albert Bandura, can be incorporated into the design of Matter to enhance knowledge acquisition and improve the overall reading experience.

Prioritization, Resurfacing, and Decay:

The first generation of read-it-later apps lacked intelligent features such as prioritization, resurfacing, or decay. However, as highlighted by Jeff Bezos, focusing on needs that won't change is crucial. In the case of reading online, the supply of great content will continue to rise, and attention will always be scarce. Therefore, integrating algorithms that assist in prioritizing and resurfacing relevant articles can greatly improve the reading experience. By taking into account user preferences, interests, and past reading habits, Matter can ensure that users are presented with the most valuable and timely content.

Elevating Writers and Curation:

Trust plays a significant role in determining what to read. People trust other people, which is why at Matter, we have made the conscious decision to elevate writers as first-class citizens within our system. Good curation, especially when it uncovers hidden gems from the vast sea of content, adds immense value to the reading experience. By incorporating curated recommendations from trusted sources and experts, Matter ensures that users have access to high-quality and often overlooked articles.

Balancing New and Evergreen Content:

While the appeal of new content is undeniable, it is essential to recognize that the majority of valuable content is not generated in the past week. Matter aims to strike a balance between providing users with the latest news and surfacing timeless articles that are still relevant and insightful. By curating a diverse range of content, including both new and evergreen pieces, Matter encourages users to explore beyond the immediate and discover articles that have stood the test of time.

Improving the Newsletter Experience: