Barbara Ericson

  • Barb Ericson
    Barbara Ericson

HCC PhD student, Georgia Institute of Technology

Parsons Problems and Adaptive Parsons Problems: A More Efficient Form of Programming Practice

Parsons problems are a type of code completion problem in which the correct code for a problem is provided, but is broken into blocks of statements and mixed up. The blocks must be placed in the correct order and may have to be indented correctly as well. Parsons problems can also have distractors which are extra blocks that are not needed in a correct solution. These extra blocks can have common syntactic or semantic errors. My research on Parsons problems provides evidence that learners enjoy them, but sometimes find them too difficult. Adaptive Parsons problems can be changed to be easier if learners are struggling to solve them or made harder if learners are solving them too easily. This poster will report on my research on Parsons problems and my future directions. Parsons problems could make it easier and less frustrating to learn how to program in textual languages.

Barbara Ericson is a Senior Research Scientist and a part-time PhD student in Human-Centered Computing at Georgia Tech. She has a master’s degree in computer science from the University of Michigan and a bachelor’s degree in computer science from Wayne State University. Her extensive work experience includes 3d graphics and user interface work at General Motors Research Labs, database work and speech output at Bell Communications Research, a case-based reasoning system for detecting strokes and brain tumors for NCR, and artificial intelligence software for robots and medicine at Clark Atlanta University. She holds two patents for her work for NCR.

She has worked since 2004 to increase the quantity and quality of secondary computing teachers and the quantity and diversity of computing students. She and her husband, Dr. Mark Guzdial, were the winners of the 2010 Karl V. Karlstrom Outstanding Computing Educator Award for their work on media computation. In media computation students write programs to manipulate media such as negating a picture or reversing a sound. She was also the winner of the Richard A Newton award in 2012 for her work to increase the percentage of women in computing. She is also a co-author of four books on media computation.

For the last several years she has been co-authoring and studying free interactive ebooks for introductory programming courses. These books are available at In the spring of 2013 she started a project called Rise Up 4 CS to help underrepresented high school students succeed in their Advanced Placement (AP) Computer Science A (CSA) course and on the exam. Each year since that project started a new record number of African American high school students have passed the AP CSA exam in Georgia (from 22 in 2012 to 60 in 2016). The number of women passing the exam in Georgia doubled from 119 in 2014 to 238 in 2016.

For her dissertation work she is studying Parsons problems in which the learner is given the correct code for a program, but the code is broken into blocks and mixed up. The learner must select the blocks and place them in the correct order. Some Parsons problems contain extra blocks, called distractors, which are not needed in a correct solution. These distractors can contain common syntactic or semantic errors. She is currently studying the effectiveness and efficiency of learning by solving Parsons problems with distractors, versus fixing code with the same errors as the distractors, versus writing the equivalent code. She is also studying adaptive Parsons problems in which the difficulty of the problem can dynamically change based on the learner’s performance. If the learner is struggling to solve the problem, the problem is made easier. If the learner is performing well then the next problem is made harder. The idea is to maximize learning by keeping the learner in the Zone of Proximal Development (ZPD). ZPD is defined as what the learner can accomplish with help versus what he or she can accomplish individually.

Barbara Ericson’s Research webpage
Research statement