Using the SOLO Taxonomy to Understand Subgoal Labels Effect in CS1

This work extends previous research on subgoal labeled instructions by examining their effect across a semester-long, Java-based CS1 course. Across four quizzes, students were asked to explain in plain English the process that they would use to solve a programming problem. In this mixed methods study, we used the SOLO taxonomy to categorize student responses about problem-solving processes and compare students who learned with subgoal labels to those who did not. The use of the SOLO taxonomy classification allows us to look deeper than the mere correctness of answers to focus on the quality of the answers produced in terms of completeness of relevant concepts and explanation of relationships among concepts. Students who learned with subgoals produced higher-rated answers in terms of complexity and quality on three of four quizzes. Also, they were three times more likely to discuss issues of data type on a question about assignments and expressions than students who did not learn with subgoal labeling. This suggests that the use of subgoal labeling enabled students to gain a deeper and more complex understanding of the material presented in the course.

[1]  Sue Fitzgerald,et al.  'explain in plain english' questions revisited: data structures problems , 2014, SIGCSE.

[2]  J. Sweller The worked example effect and human cognition , 2006 .

[3]  Raymond Lister,et al.  Early relational reasoning and the novice programmer: swapping as the hello world of relational reasoning , 2011, ACE 2011.

[4]  S. Derry,et al.  Learning from Examples: Instructional Principles from the Worked Examples Research , 2000 .

[5]  Mark Guzdial,et al.  Subgoals, Context, and Worked Examples in Learning Computing Problem Solving , 2015, ICER.

[6]  Tony Clear,et al.  An Australasian study of reading and comprehension skills in novice programmers, using the bloom and SOLO taxonomies , 2006 .

[7]  Angela Carbone,et al.  Going SOLO to assess novice programmers , 2008, ITiCSE.

[8]  Kevin F. Collis,et al.  Evaluating the Quality of Learning: The SOLO Taxonomy , 1977 .

[9]  Terry K Koo,et al.  A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. , 2016, Journal Chiropractic Medicine.

[10]  Briana B. Morrison,et al.  Design and Pilot Testing of Subgoal Labeled Worked Examples for Five Core Concepts in CS1 , 2019, ITiCSE.

[11]  Cruz Izu,et al.  A Study of Code Design Skills in Novice Programmers using the SOLO taxonomy , 2016, ICER.

[12]  R. Catrambone The subgoal learning model: Creating better examples so that students can solve novel problems. , 1998 .

[13]  Leigh Ann Sudol-DeLyser Expression of Abstraction: Self Explanation in Code Production , 2015, SIGCSE.

[14]  Mark Guzdial,et al.  Subgoal-labeled instructional material improves performance and transfer in learning to develop mobile applications , 2012, ICER '12.

[15]  Raymond Lister,et al.  Not seeing the forest for the trees: novice programmers and the SOLO taxonomy , 2006, ITICSE '06.

[16]  Sue Fitzgerald,et al.  Ability to 'explain in plain english' linked to proficiency in computer-based programming , 2012, ICER '12.

[17]  Vincent Aleven,et al.  The worked-example effect: Not an artefact of lousy control conditions , 2009, Comput. Hum. Behav..

[18]  Briana B. Morrison,et al.  Learning Loops: A Replication Study Illuminates Impact of HS Courses , 2016, ICER.

[19]  Sue Fitzgerald,et al.  'Explain in plain English' questions: implications for teaching , 2012, SIGCSE '12.

[20]  Neil Brown,et al.  Ten quick tips for teaching programming , 2018, PLoS Comput. Biol..

[21]  Arto Hellas,et al.  Subgoal Labeled Worked Examples in K-3 Education , 2018, SIGCSE.

[22]  Alexander Renkl,et al.  Learning from Worked-Out-Examples: A Study on Individual Differences , 1997, Cogn. Sci..

[23]  Linda M. Seiter Using SOLO to Classify the Programming Responses of Primary Grade Students , 2015, SIGCSE.