In an individual submission, explain how you applied specific Learning Outcomes (LOs) from ACCT in your research paper for your Partner Challenge mentor.
(1) Make an individual copy of your Partner Challenge research paper*. Create a LO appendix at the end of your paper.
(2) In the appendix, identify 5-6 prominent applications of LOs from ACCT. Make sure to include at least 1 LO each from each unit, and no more than two applications of a single LO
-Problem Solving (#rightproblem, #breakitdown, #gapanalysis, #constraints, #analogies)
-Logic (#logic, #fallacies, #estimation)
-Biases (#biases, #heuristics)
Including #scienceoflearning, from the Introduction unit, is optional.
(3) Write a 150-200 word summary of each application. Make sure to clearly indicate where in the paper you applied the LO. In your summary, demonstrate your deep knowledge of the LO. Discuss how your work represents a strong application of the LO. Discuss how you might have improved your application of the LO.
(4) Optional, bonus prompt: Identify 1-2 LOs that you did NOT apply in your Partner Challenge. Write a 150-200 summary of how you could have applied the LO, and how applying it might have improved your project and paper.
Please see below for illustrative Examples of LO appendix entries:
#rightproblem: In the Introduction section of our paper, we clearly identify the initial state, goal state and obstacles for the inefficiency problem the organization faces in its grant searching and application process. We explain how the initial approach was too technical and focusing on the wrong problem: we show how this different approach will be more effective. We then identified the right overarching problem and used #breakitdown to decompose it into two aspects: searching process and application process. We described three main obstacles that we need to overcome to ensure that the funding is successful. One area where we could have improved our application of the LO is by conducting more research and gathering data on the scale of the problem. We could provide statistics to describe, for instance, the size of the target population and the geographic region under consideration to better characterize the scale and impact of the problem.
scienceoflearning: This LO was applied in the design of the website. Our website’s purpose is to educate users, however, without careful thought into how we teach the material, it is unlikely to stick. The first principle of #scienceoflearning that we applied throughout the paper is that of desirable difficulty - if we made the website too easy, our audience would get bored, but if we made it too hard, our audience would tune out. In the end, we may have made the website too difficult in at least one place, but we struck a good balance overall. Because our audience is mainly people who are apprehensive or not knowledgeable about AVs, we chose to maintain a somewhat informal tone and to space out information. Next, we decided to use the benefits of the Generation effect and Deliberate practice by including questions on our subpages to force the reader to stop and reflect over the material covered. While the generation effect will apply to most readers because the mere act of reading the question will bring up the material again, we are relying on the readers to listen to us and answer the question to engage deliberate practice.
logic: We used inductive reasoning to produce the Letter of Intent (Solution Section, pages 4 and 5). We first looked at letters from successful nonprofits and transferred some of their features to the LOI for our partner. This is an implicit argument by analogy - if both letters share characteristics in their content, and if those organizations share some essential attributes with the organization, it is likely that they will share the characteristic of being successful. In addition, this is an argument by generalization. Since we don’t have information about all nonprofits that applied a similar LOI, we can only assume that the success rate of our sample is generalizable for the entire population. Our induction is strong: 1) our analogy considered similarities between organizations relevant to our conclusion (e.g., nonprofit status, location, area of operation, size). 2) Our generalization has a satisfactory sample size. We looked for information from multiple sources and used those that were common. Taken together we can be confident that our conclusion - the LOI we propose will be successful - likely follows from our premises - the letter of intent was successful when used by other organizations. Although the argument is strong, the result can not be guaranteed due to its inductive nature.