AlgoPlan

Kabdo Choi, Sally Chen, Hyungyu Shin, J. Son, Juho Kim
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Abstract

Planning a solution before writing code is essential in algorithmic problem-solving. However, novices often skip planning and jump straight into coding. Even if they set up a plan, some do not connect to their plan when writing code. Learners solving algorithmic problems often struggle with high-level components such as solution techniques and sub-problems, but existing representations that guide learners in planning, such as flowcharts, focus on presenting lower-level details. We use subgoal diagrams -- diagrams made of subgoal labels and the relationships between them -- as a representation that guides learners to focus on high-level plans when they develop solutions. We introduce AlgoPlan, an interface that enables learners to build their own subgoal diagram and use it to guide their problem-solving process. A preliminary study with seven students shows that subgoal diagrams help learners focus on high-level plans and connect these plans to their code.
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AlgoPlan
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Trust, Sustainability and [email protected] L@S'22: Ninth ACM Conference on Learning @ Scale, New York City, NY, USA, June 1 - 3, 2022 L@S'21: Eighth ACM Conference on Learning @ Scale, Virtual Event, Germany, June 22-25, 2021 Leveraging Book Indexes for Automatic Extraction of Concepts in MOOCs Evaluating Bayesian Knowledge Tracing for Estimating Learner Proficiency and Guiding Learner Behavior
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