More Like this

1. Applying Deliberate Practice to Facilitate Schema Acquisition in Learning Introductory Mechanics

   Tang, Yan ; Bai, Haiyan ; Catrambone, Richard ( July 2021 , ASEE annual conference proceedings)

   Learning is usually conceptualized as a process during which new information is processed in working memory to form knowledge structures called schemas, which are stored in long-term memory. Practice plays a critical role in developing schemas through learning-by-doing. Contemporary expertise development theories have highlighted the influence of deliberate practice (DP) on achieving exceptional performance in sports, music, and different professional fields. Concurrently, there is an emerging method for improving learning efficiency by combining deliberate practice with cognitive load theory (CLT), a cognition-architecture-based theory for instructional design. Mechanics is a foundation for most branches of engineering. It serves to develop problem-solving skills and consolidate understanding of other subjects, such as applied mathematics and physics. Mechanics has been a challenging subject. Students need to understand governing principles to gain conceptual knowledge and acquire procedural knowledge to apply these principles to solve problems. Due to the difficulty in developing conceptual and procedural knowledge, mechanics courses are among those which receive high DFW rates (percentage of students receiving a grade of D or F or Withdrawing from a course) and students are more likely to leave engineering after taking mechanics courses. Since deliberate practice can help novices develop good representations of the knowledge neededmore »to produce superior problem solving performance, this study is to evaluate how deliberate practice helps students learn mechanics during the process of schema acquisition and consolidation. Considering cognitive capacity limitations, we will apply cognitive load theory to develop deliberate practice to help students build declarative and procedural knowledge without exceeding their working memory limitations. We will evaluate the effects of three practice strategies based on CLT on the schema acquisition and consolidation in two mechanics courses (i.e., Statics and Dynamics). Examples and assessment results will be provided to evaluate the effectiveness of the practice strategies as well as the challenges.« less
2. Developing Deliberate Practice for Learning Engineering Dynamics by Analyzing Students’ Mental Models

   Tang, Yan ; Bai, Haiyan ; Catrambone, Richard ( June 2022 , ASEE annual conference exposition)

   Practice plays a critical role in learning engineering dynamics. Typical practice in a dynamics course involves solving textbook problems. These problems can impose great cognitive load on underprepared students because they have not mastered constituent knowledge and skills required for solving whole problems. For these students, learning can be improved by being engaged in deliberate practice. Deliberate practice refers to a type of practice aimed at improving specific constituent knowledge or skills. Compared to solving whole problems requiring the simultaneous use of multiple constituent skills, deliberate practice is usually focused on one component skill at a time, which results in less cognitive load and more specificity. Contemporary theories of expertise development have highlighted the influence of deliberate practice (DP) on achieving exceptional performance in sports, music, and various professional fields. Concurrently, there is an emerging method for improving learning efficiency of novices by combining deliberate practice with cognitive load theory (CLT), a cognitive-architecture-based theory for instructional design. Mechanics is a foundation for most branches of engineering. It serves to develop problem-solving skills and consolidate understanding of other subjects, such as applied mathematics and physics. Mechanics has been a challenging subject. Students need to understand governing principles to gain conceptual knowledgemore »and acquire procedural knowledge to apply these principles to solve problems. Due to the difficulty in developing conceptual and procedural knowledge, mechanics courses are among those that receive high DFW rates (percentage of students receiving a grade of D or F or Withdrawing from a course), and students are more likely to leave engineering after taking mechanics courses. Deliberate practice can help novices develop good representations of the knowledge needed to produce superior problem solving performance. The goal of the present study is to develop deliberate practice techniques to improve learning effectiveness and to reduce cognitive load. Our pilot study results revealed that the student mental effort scores were negatively correlated with their knowledge test scores with r = -.29 (p < .05) after using deliberate practice strategies. This supports the claim that deliberate practice can improve student learning while reducing cognitive load. In addition, the higher the students’ knowledge test scores, the lower their mental effort was when taking the tests. In other words, the students who used deliberate practice strategies had better learning results with less cognitive load. To design deliberate practice, we often need to analyze students’ persistent problems caused by faulty mental models, also referred to as an intuitive mental model, and misconceptions. In this study, we continue to conduct an in-depth diagnostic process to identify students’ common mistakes and associated intuitive mental models. We then use the results to develop deliberate practice problems aimed at changing students’ cognitive strategies and mental models.« less
3. Using Subgoal Labeling in Teaching CS1

   https://doi.org/10.1145/3287324.3287540  

   Morrison, Briana ; Margulieux, Lauren ; Decker, Adrienne ( February 2019 , Proceedings of the 50th ACM Technical Symposium on Computer Science Education)

   Subgoal labeling is an instructional design framework for breaking down problems into pieces that are small enough for novices to grasp, and often difficult for instructors (i.e., experts) to articulate. Subgoal labels have been shown to improve student performance during problem solving in disciplines both in and out of computing. Improved student performance occurs because subgoal labels improve student transfer and retention of knowledge. With support from NSF (DUE-1712025, #1712231), subgoal labels have been identified and integrated into a CS1 course (variables, expressions, conditionals, loops, arrays, classes). This workshop will introduce participants to the materials and demonstrate how the subgoal labels and worked examples are integrated throughout the course. Materials include over 100 worked examples and practice problem pairs that increase in complexity and difficulty within each topic. The materials are designed to be integrated into CS1 courses as homework or classroom examples and activities. Assessment of topics using subgoal labels will also be discussed. Participants will also engage in an activity where they create an example for their own course using subgoal labels.
4. Using Subgoal Labeling in Teaching CS1

   https://doi.org/10.1145/3478432.3499164  

   Decker, Adrienne ; Morrison, Briana B. ; Bart, Austin Cory ( March 2022 , Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 2 (SIGCSE 2022))

   Subgoal labeling is an instructional design framework for breaking down problems into pieces that are small enough for novices to grasp, and often difficult for instructors (i.e., experts) to articulate. Subgoal labels have been shown to improve student performance during problem solving in disciplines both in and out of computing. Improved student performance occurs because subgoal labels improve student transfer and retention of knowledge. With support from NSF (DUE-1712025, #1712231), subgoal labels have been identified and integrated into a CS1 course (variables, expressions, conditionals, loops, arrays, classes). This workshop will introduce participants to the materials and demonstrate how the subgoal labels and worked examples are integrated throughout the course. Materials include over 100 worked examples and practice problem pairs that increase in complexity and difficulty within each topic. The materials are designed to be integrated into CS1 courses as homework or classroom examples and activities. Assessment of topics using subgoal labels will also be discussed. Participants will also engage in an activity where they create an example for their own course using subgoal labels.
5. Using Subgoals to Improve Student Performance in CS1: (Abstract Only)

   https://doi.org/10.1145/3159450.3162185  

   Morrison, Briana B. ; Decker, Adrienne ( February 2018 , Proceedings of the 49th ACM Technical Symposium on Computer Science Education)

   Subgoal labels are function-based instructional explanations that describe the problem-solving steps to the learner, highlighting the solution process. There is strong evidence that the use of subgoal labels within worked examples improves student learning in other STEM fields. Initial research shows that using subgoal labels within computer science improves student learning, but this has only been tested using a single programming concept (indefinite loops) with text-based programming languages. The proposers are currently expanding subgoal labels to the main programming concepts taught in an introductory programming course using an imperative programming language. In this BOF we seek to uncover tacit knowledge that programming instructors have in order to develop instructional materials that bridge the gap between students, who are CS novices, and instructors, who are CS experts, to improve learning for students who are under-prepared for or struggle in CS1. We will be seeking feedback on the selection of programming topics to be covered, the defined subgoals for those topics and the worked examples created for instructional purposes.