Learning for use (LfU) is an educational framework—originating from national science curriculum—that helps students develop deep, interconnected knowledge and inquiry skills . The impetus for LfU stems from how traditional didactic lecture, readings, problems and isolated laboratory experiments lead students to being unable to use their knowledge robustly . The foundation of LfU is designed as a general model of learning, but has historically been organized around an inquiry-based pedagogy to coordinate content and process while learning science.
When students learn something new, they take this information and create some form of knowledge structure, connecting it to what is already known. In order for a student to create a complex interconnected web of knowledge, they need more than simple exposure to content, meaning that information is not just directly transmitted into the student's head. The act of building an understanding happens step-by-step as a student makes sense of an experience and interacts with what they have learned. Developing knowledge in this more engaging and interactive way is critical, as it leads to strong contextual cues during learning—improving retrieval for robust usage [3, 5, 7, 8].
Beyond having a capability to recall knowledge structures, students must also be able to meaningfully use their conceptual knowledge. If a student is unable to operationalize what they have learned, the recalled knowledge is still problematically impotent . LfU addresses how to provide a deep and richly connected context at the same time as giving a student useful experiences in applying that knowledge.
An activity should make the learner realize there is a need for new knowledge. This can be a self-aware realization or one which occurs subconsciously, but is contrived through some limitation or gap in knowledge [2, 7]. Schank  supports that when a student hits such a limit or barrier, it creates a motivating desire to acquire new information and also helps contextually to incorporate new knowledge. The former establishes a goal to achieve, the latter address the incremental nature of knowledge construction. There are two ways to design an activity to leverage this component:
The construction process is the most fundamental step in LfU—a student needs to incrementally construct new knowledge and link it with their existing understanding . New knowledge comes in the way of direct experiences with new concepts, examining old ones, or making connections between any combination of old and new. The intent is to make sure that students can observe and understand the relationships of the to be learned content, and ameliorate their current knowledge.
In order to maximize the usefulness of knowledge, students need to (1) reorganize their declarative knowledge of facts and events into procedural knowledge of knowing how to do things  and (2) make connections between the new knowledge and what situations it can be used in [5, 6, 7, 8] Two ways to address the refinement of knowledge:
The first part of LfU is about establishing the reason or initial motivation to participate in a learning experience. Kerbal Space Program (KSP) provides an example of how you might setup a learning situation. KSP is a space simulation game where you need to get your little green astronauts into space and onto various celestial bodies.
How do you do that? What is needed to be known? In this case, there are a variety of rocket design mechanics and mathematics to consider (e.g., thrust, weight, planetary physics). The student, right from the beginning, is motivated to take on some form of learning, otherwise they will not be able to build a rocket and launch into the unknown wonders of space.
In order to succeed in KSP, you need to actually build the rocket you intend to launch. Where will the engines go? How much thrust do you need? How will the rocket be balanced? What path will the rocket take? Are you going for a simple orbit of Earth? Perhaps you are shooting for the moon.
Everytime you fail in KSP, you need reflect on what went wrong and how you can change your next attempt. This means that with the right learning outcomes in focus, a student would reinforce and test their previous understandings. This iterative experience helps build procedural knowledge in how to do things and begin to see what connections are important when being a space traveler.
1. Anderson, J.R. (1983). The architecture of cognition. Cambridge, MA: Harvard University Press.
2. Berlyne, D.E. (1966). Curiosity and exploration Science 153, 25-33.
3. Chi, M.T.H., Peltovich, P.J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121-152.
4. Edelson, D. C. (2001). Learning‐for‐use: A framework for the design of technology‐supported inquiry activities. Journal of Research in Science Teaching, 38(3), 355-385.
5. Glaser, R. (1992). Expert knowledge and process of thinking. In D. F. Halpern (Ed.), Enhancing thinking skills in the sciences and mathematics. Hillsdale, NJ: Erlbaum
6. Kolodner, J.L. (1993). Case-based reasonin. San Mateo, CA: Morgan Kaufmann.
7. Schank, R.C. (1982). Dynamic memory. Cambridge: Cambridge University Press.
8. Simon, H.A. (1980). Problem solving and educaton. In D.T. Tuma & R. Reif (Eds.), Problem, solving and education: Issues in teaching and research (pp. 81-96). Hillsdale, NJ: Erlbaum.
9. Whitehead, A.H. (1929). The aims of education. Cambridge: Cambridge University Press.
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