Planning to Hike

5233 Multimedia Resources and Service - Computational Thinking Activity

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Planning to Hike by Mind Map: Planning to Hike

1. Problem Statement: Emma is taking a friend hiking at a nature preserve. Emma has quite a bit of experience with the trails. However, her friend, Lauren, has never been hiking there. Emma wants to make sure she has a plan. She wants to take the trails and make a route combination that fits their needs. She wants the trails to have a moderate or low difficulty level, and she does not want their hike to exceed four miles. She also does not want to have to go back to the entrance to start the next trail. Emma would like the route to flow seamlessly through the trails so that they make one large loop back to the entrance by the end. How can she achieve this goal?

1.1. Decomposition: Emma needs to break down all of the steps in order to plan their excursion. First, she needs a map of all of the trails. Second, she needs to know how long each trail is. Third, Emma needs to determine the difficulty of each trail if they are not already measured on the map. From there, she will plan an appropriate route for a hiker who is new to the area, a route that is seamless, that does not exceed four miles, and does not require going back to the entrance.

1.1.1. Pattern Recognition: Emma notices some patterns after she color codes her map. Each trail has its’ own color. All of the trails are measured in full miles or full quarters. Painted Bunting Trail, Chickadee Trail, and Turtle Trails are one mile and are considered moderately difficult by hikers. Holly Trail is the only full two mile trail, and it has a higher difficulty level. The Roundabout is .75 miles and had a moderate difficulty level. The moderately difficult trails are closer together. Yew Trail is half of a mile and Red Oak Trail is .25 miles. All are considered easy due to their length, and they are interspersed between the more difficult trails. Emma also notices that not all of the trails begin in the same section. When people walk up to the trails from the parking lot, there is one main trailhead. That is the beginning of Turtle Trail (1 mile), and the Yew Trail (.5 miles) is a smaller trail on the left. She notices that Holly Trail (2 miles) connects to Turtle in two places and is almost one large loop. Turtle is the main trail at the beginning and it ends at the pond, but Painted Bunting (1 mile) begins where the other trail ends and loops back into Turtle. Both trails together look like a lasso. The Roundabout Trail (.75 miles) attaches to Turtle at .5 miles and branches back up towards the entrance. There are two trails that form near the beginning of the Roundabout Trail. Chickadee (1 mile) connects in one place, loops out, and ends on a different spot. Red Oak Trail (.25 miles) begins near Chickadee Trail and dead ends into Chickadee Trail.

1.1.1.1. Algorithm: Emma developed instructions for her problem. In this case, she needs a combination of trails that are reasonable in difficulty and add up to no more than four miles. She also wants the route to flow seamlessly. She does not want to start on a trail on one side and have to go back to the entrance to start the next trail. To do this, she looks at the color coded map, then the length of each trail, and she adds up possible options. One combination includes the half mile Yew Trail to Turtle Trail to the Roundabout Trail up to the parking lot. That makes one large loop but is only about two miles long. Another option would be to start on the other end of the trails with the Chickadee Trail to the Roundabout Trail to Turtle Trail around to Painted Bunting Trail which loops back to Turtle and ends at the entrance. This route is about 3.75 miles. A third option is the Cedar Trail (2 miles) down part of Turtle Trail and back up towards the parking lot on the Roundabout Trail. This adds up to just under four miles. All of these combinations are built by using the map, lengths of the trails, and simple addition.

1.1.1.1.1. Abstraction: Emma has several options for hikes planned for her friend’s visit. She realizes that there really are a variety of hiking options! If she is tired one day, then the route can be much easier than a day when she wants to challenge herself. Having a place to hike in the area that allows her to make a variety of routes can help her to test and strengthen her abilities. She may combine longer trails, like Holly Trail, with Turtle Trail and Painted Bunting Trails and hike about four miles. Otherwise, she could keep it easy with the Chickadee and Roundabout Trails. There are options to fit her every need, and to fit every friend who comes to visit!

1.1.1.1.2. Rationale: The instructions on how to create an appropriate hiking trail reflect Google’s description that they must be “step-by-step instructions for solving this and similar problems” (What is computational thinking, n.d.). These steps can be replicated with any set of hiking trails. These steps could also be applied to streets for jogging or even a road trip map. Yadav, Hong, and Stephenson (2016) also compares an algorithm to a couple of daily tasks; they describe, “We use algorithms everyday in our lives from following a cooking recipe to giving directions from point A to point B” (p. 566). This is true of the steps that Emma has developed to solve her problems. Maps are regularly used by people who are traveling or going to a new restaurant for dinner. When it comes to hiking new trails in a new area, it is important to be aware, be prepared, and understand the best route for that person’s needs.

1.1.1.2. Rationale: The trails in a hiking area must have a pattern or connections to one another in order for the hikers to make sense of the paths. In the case of urban hiking, the space is often limited and the paths need to fit within the area while also offering options. Google includes an important phrase when addressing patterns; the definitions states, “…develop your own processes for approaching a problem through pattern recognition” (What is computational thinking, n.d.). When a person analyzes a problem and notices patterns, they do so with their own set of experiences and understandings. Thus, people address and analyze problems differently. In this case, Emma notices the difficulty and usage level before focusing on the individual measurements. It is possible that she may need to dismiss a trail based on difficulty. Once the too difficult or too easy trails are removed, then she can focus on possible patterns of trails appropriate for their needs.

1.1.2. Rationale: Decomposition requires the steps of the problem to be broken down into a process; it is most logical to scaffold the steps. Yadav, Hong, and Stephenson (2016) describe these steps as “…more familiar/manageable sub-problems…” (p. 565). It is easier to locate a map first than measure the length of a trail by walking down it. Each step is needed before the person can move on to the next step. Also, Google’s definition of decomposition reads, “Breaking down data, processes, or problems into smaller, manageable parts” (What is computational thinking, n.d.). This is very similar. In this case, the parts are more manageable by beginning with the most simple step first. If a person visits a new place, then they need to have a map of the area. In this case, the map is of the trails. Once the trails are known, then it is necessary to know how long they are. From there, it will be possible to plan a route using the map and the knowledge of the distances. These steps are all involved in the process of planning a hike.