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2019 ASEE Annual Conference & Exposition

Board 37: Developing Subgoal Labels for Imperative Programming to Improve Student Learning Outcomes

Presented at NSF Grantees Poster Session

There have been many calls recently for computing for all across the nation. While there are many opportunities to study and use computing to advance the fields of computer science, software development, and information technology, computing is also needed in a wide range of other disciplines, including engineering. Most engineering programs require students take a course that teaches them introductory programming, which covers many of the same topics as an introductory course for computing majors (and at times may be the same course). However, statistics about the success of a course that is an introductory programming course are sobering; approximately half the students will fail, forcing them to either repeat the course or leave their chosen field of study if passing the course is required.

This NSF IUSE project incorporates instructional techniques identified through educational psychology research as effective ways to improve student learning and retention in introductory programming. The research team has developed worked examples of problems that incorporate subgoal labels, which are explanations that describe the function of steps in the problem solution to the learner and highlight the problem-solving process. Using subgoal labels within worked examples, which has been effective in other STEM fields, students are able to see an expert's problem solving process, which helps students learn to solving problems before they can solve problem themselves. Experts, including instructors, teaching introductory level courses are often unable to explain the process they use in problem solving at a level that learners can grasp because they have automated much of the problem-solving processes after many years of practice. This submission will present the results of the first part of development of subgoals and will explain how to integrate them into classroom lessons in introductory computing classes.

Authors
  1. Dr. Adrienne Decker Orcid 16x16http://orcid.org/0000-0002-0822-4813 University at Buffalo [biography]

    Adrienne Decker is a faculty member in the newly formed Department of Engineering Education at the University at Buffalo. She has been studying computing education and teaching for over 15 years, and is interested in broadening participation, evaluating the effectiveness of pre-college computing activities, and issues of assessment, particularly in the introductory programming courses. She has been actively involved with the Advanced Placement Computer Science A course since 2011, first serving as a reader, and as part of the development committee for the exam since 2015, serving as higher ed co-chair since 2018. She has received more than $1M in NSF funding for her work in computing education. Active in the computing education community, she is currently the ACM Special Interest Group on Computer Science Education board treasurer (2016-2019) and has served as program co-chair in 2014 and symposium co-chair in 2015 to the SIGCSE Technical Symposium on Computer Science Education.

  2. Dr. Briana Morrison Orcid 16x16http://orcid.org/0000-0003-4260-4278 University of Nebraska Omaha [biography]

    Briana Morrison is an Assistant Professor at the University of Nebraska Omaha. Prior to joining the college of IS&T, Briana worked for IBM for 8 years as a software developer and then transitioned to academia. She was an Assistant Professor at Southern Polytechnic State University (now Kennesaw State University) for 20 years in the Computer Science department. She was the Undergraduate Coordinator for the Computer Science and Software Engineering programs, helped to found the Computer Game Design and Development degree program, and served as the lead for 2 successful ABET accreditation visits. She has a PhD in Human-Centered Computing from the Georgia Institute of Technology, a master's in Computer Science, and a bachelor's degree in Computer Engineering. Her research area is Computer Science Education where she explores cognitive load theory within programming, broadening participation in computing and expanding and preparing computing high school teachers.

  3. Dr. Lauren Elizabeth Margulieux Georgia State University [biography]

    Lauren Margulieux is an Assistant Professor of Learning Sciences at Georgia State University. She received her Ph.D. from Georgia Tech in Engineering Psychology, the study of how humans interact with technology. Her research interests are in educational technology and online learning, particularly for computing education. She focuses on designing instructions in a way that supports online students who do not necessarily have immediate access to a teacher or instructor to ask questions or overcome problem solving impasses.

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