Learning in the Age of Information Abundance
Reading Time
Read if

Learning in the Age of Information Abundance

Education Innovation articles are descriptions of the methodology and heutagogical practices of Eskwelabs to adapt learning and apprenticeship models to a technology-intensive modern workplace and job market.

Modern tools like ChatGPT only underscore that our most foundational approaches to knowledge and learning are inadequate for an information-abundant environment. The paradigms dominating our understanding of the world have gone from information scarcity to information abundance. Information was so unreachable that students, prior to the invention of the printing press, would memorize entire chapters of books in order to be able to recall the requisite knowledge on demand (Gomes et al., 2021). We are now on the other end—information is now abundant as everything is accessible at the distance of a single click (Gomes et al., 2021).

Students and workers alike have access to generative AI, search engines, massive online databases, encyclopedias, and communities of varying levels of expertise. But even recent developments in higher education are still designed with the intent to find the equilibrium between the supply of information and the demand for it—which means learning experiences are still closer to teaching the skills required to succeed in an environment of information scarcity than one of information abundance (Smith, 2011).

One way to start thinking about learning is to understand and differentiate the different levels of knowledge. In 1997, Dr. Norman Webb developed the Depth of Knowledge to measure the different levels in which students are expected to express what they learned.

Fig. 1 - The four levels of knowledge illustrated based on the design process of our Learning Experience Designers

Level 1: Your Biological Brain

First, there is a core level of knowledge that is deeply internalized by the learner, a form of memorized knowledge that serves as a muscle memory. In the context of the topic of data storytelling, for example, I can say that I have an internalized understanding of how a histogram works and how to interpret it - I do not require any external resources in order to work with this.This has traditionally been the main focus of academic learning, in order to build a stronger core memorized set of knowledge (Airasian et al., 2001).

Level 2: Your External Brain

The second level is where learners use concepts in applied settings. There is a reference level of knowledge which has not been internalized but can be rapidly accessed with tools deeply familiar to the learner. An example might be a learner’s past project. They may not remember everything in their project, but they remember the general tools and topics associated with it and they can always refer to that project for both knowledge, templates, and workflows. The important thing is not that the project, or the cheatsheet, exists, but that the learner has personally used the cheatsheet in an applied setting before, and therefore is comfortable to use it again. If this specific cheatsheet works for the learner, then it serves as an accessible “external drive” of knowledge—something similar to a second brain.

In the context of data storytelling, I may rely on this to customize a certain histogram using a data visualization library. I may open up an old project to copy code or use a reference cheatsheet that includes the editable parameters for a given visualization. I have not memorized all the editable parameters for the visualization libraries I use in Python, but I have worked with them before, therefore I am comfortable with the syntax and how to use the cheatsheets or past projects to help me structure future projects.

For something to be at this level, it needs to be something that a learner has previously worked with—something that comes to mind when thinking about this subject. An external article or ChatGPT would not function at the level, rather, note-taking would traditionally serve a better purpose for learners to build their own reference systems. By making the learner more actively involved with the material to be learned, taking notes can increase the degree to which a person pays attention to the text, highlighting which ideas should be noted and which should not (Bohay et al., 2011). However there are two challenges to this.

Firstly, the testing of this knowledge appears in a closed-book environment, which is actually a test of the “core level” of knowledge (Van Der Meer, 2012). In order for learners to really become comfortable with using their notes as an external brain, they should be incentivized to do so with open-note exams and tests.

Secondly, organization of notes into a successful knowledge management system is a challenge for many learners (Van Der Meer, 2012). The quantity of notes and the complexity of successful note systems (e.g. networked thought tools, formal knowledge management solutions) means that untrained learners will struggle to get maximum value from this system. For this reason, Eskwelabs has generally shifted to facilitated cheatsheets and projects to serve as the second level of information retrieval for our learners.

Fig. 2 - A breakdown of a cheatsheet sample Eskwelabs will be making for Learning Sprints.

Our experience is that the level of knowledge that educators should seek to train at this level is going up over time, as tools become more powerful and as workflows become more complex.

Level 3: Your Trusted External Knowledge

A third level refers to external resources that are trusted and understandable for the learner, even when dealing with new topics or issues. In the context of data storytelling, this might be external documentation for a visualization library or an online community forum. I may go here when my reference cheatsheet and past projects are not enough and I have a new problem to solve, and while the information I access may be new I am comfortable with the format of that information from prior exposure.

Those who succeed in a modern knowledge economy are typically very strong at this level (Centre for Educational Research and Innovation, OECD., 2001). The tech sector is a great example of a sector where successful contributors learn very early how to leverage documentation and broader communities to expand knowledge and carry out their projects (“Technology and Innovation Report 2021,” 2021).
The learning experience at this level is designed to familiarize learners with identifying and  accessing trusted sources in the context of their work. This means that the learning experience should be relevant and applicable to the learners' work environment, so they can easily integrate the skills they learn into their everyday workflow.

Level 4: Your Unknown External Knowledge

Finally the last level is when learners search for information they do not know yet. The role of a learning experience at this level is to develop the meta skills to ask the right questions, access expertise, parse information quality, understand how to verify knowledge, and integrate knowledge into the learners’ current knowledge system.

This level has always been the largest level of knowledge. It represents the vast gulf between total human knowledge and our own limited knowledge, but modern tools make this level more and more searchable. At the same time, this level is constantly expanding as the broader size of humanity’s knowledge is pushed by new research and understanding (Atske, 2020).

As workflows become more multidisciplinary, this level of knowledge becomes more significant for knowledge economy workers (“Technology and Innovation Report 2021,” 2021). This is also a core need for an informed citizenry to participate in modern society (Carpini & Keeter, 2002). One of the best ways to acquire and cement this type of skill is through project-based learning in an apprenticeship context, which we have written about before.

In an age of information abundance, it is clear that traditional approaches to education and learning are no longer sufficient. To keep up with the demands of the modern workplace, we must adapt and innovate our learning methodologies. 

Our adoption of facilitated cheatsheets and projects as a resource that can help us manage information effectively is a step towards a future of learning that is dynamic, engaging, and accessible to all. With this, Eskwelabs is excited to adapt and thrive in a world of constant change and innovation.

To learn more about our Learning Sprints and how they can benefit your institution, we encourage you to download our Sprint Catalogue. Together, we can bridge the skills gap and prepare future generations for the changing nature of work.

Airasian, P., Bloom, B. S., Cruikshank, K., Mayer, R., Pintrich, P., Raths, J., & Wittrock, M. (2001). A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives. Pearson.

Atske, S. (2020, July 9). 3. Humanity is at a precipice; its future is at stake. Pew Research Center: Internet, Science & Tech. https://www.pewresearch.org/internet/2019/10/28/3-humanity-is-at-a-precipice-its-future-is-at-stake/

Bohay, M., Blakely, D. P., Tamplin, A. K., & Radvansky, G. A. (2011). Note Taking, Review, Memory, and Comprehension. American Journal of Psychology, 124(1), 63–73. https://doi.org/10.5406/amerjpsyc.124.1.0063

Centre for Educational Research and Innovation, OECD. (2001). Center for the Knowledge Economy. OECD. Retrieved March 17, 2023, from http://www.oecd.org/dataoecd/42/25/1842070.pdf

Gomes, D., Demidova, E., Winters, J., & Risse, T. (2021). The Past Web: Exploring Web Archives. Springer Nature.

Smith, P. (2011). From Scarcity to Abundance: Achieving Quality-Assured Mass Higher Education. Online Learning, 15(2). https://doi.org/10.24059/olj.v15i2.181

Technology and Innovation Report 2021. (2021). Technology and Innovation Report. https://doi.org/10.18356/9789210056588

Van Der Meer, J. (2012). Students’ note-taking challenges in the twenty-first century: considerations for teachers and academic staff developers. Teaching in Higher Education, 17(1), 13–23. https://doi.org/10.1080/13562517.2011.590974