TY - GEN
T1 - Comparing the effectiveness of online learning approaches on CS1 learning outcomes
AU - Lee, Michael J.
AU - Ko, Andrew J.
N1 - Publisher Copyright:
© 2015 ACM.
PY - 2015/7/9
Y1 - 2015/7/9
N2 - People are increasingly turning to online resources to learn to code. However, despite their prevalence, it is still unclear how successful these resources are at teaching CS1 programming concepts. Using a pretest-posttest study design, we measured the performance of 60 novices before and after they used one of the following, randomly assigned learning activities: 1) complete a Python course on a website called Codecademy, 2) play through and finish a debugging game called Gidget, or 3) use Gidget's puzzle designer to write programs from scratch. The pre- and posttest exams consisted of 24 multiple choice questions that were selected and validated based on data from 1,494 crowdsourced respondents. All 60 of our novices across the three conditions did poorly on the exams overall in both the pre-tests and post-tests (e.g., the best median post-test score was 50% correct). However, those completing the Codecademy course and those playing through the Gidget game showed over a 100% increase in correct answers when comparing their post-test exam scores to their pretest exam scores. Those playing Gidget, however, achieved these same learning gains in half the time. This was in contrast to novices that used the puzzle designer, who did not show any measurable learning gains. All participants performed similarly within their own conditions, regardless of gender, age, or education. These findings suggest that discretionary online educational technologies can successfully teach novices introductory programming concepts (to a degree) within a few hours when explicitly guided by a curriculum.
AB - People are increasingly turning to online resources to learn to code. However, despite their prevalence, it is still unclear how successful these resources are at teaching CS1 programming concepts. Using a pretest-posttest study design, we measured the performance of 60 novices before and after they used one of the following, randomly assigned learning activities: 1) complete a Python course on a website called Codecademy, 2) play through and finish a debugging game called Gidget, or 3) use Gidget's puzzle designer to write programs from scratch. The pre- and posttest exams consisted of 24 multiple choice questions that were selected and validated based on data from 1,494 crowdsourced respondents. All 60 of our novices across the three conditions did poorly on the exams overall in both the pre-tests and post-tests (e.g., the best median post-test score was 50% correct). However, those completing the Codecademy course and those playing through the Gidget game showed over a 100% increase in correct answers when comparing their post-test exam scores to their pretest exam scores. Those playing Gidget, however, achieved these same learning gains in half the time. This was in contrast to novices that used the puzzle designer, who did not show any measurable learning gains. All participants performed similarly within their own conditions, regardless of gender, age, or education. These findings suggest that discretionary online educational technologies can successfully teach novices introductory programming concepts (to a degree) within a few hours when explicitly guided by a curriculum.
KW - Codecademy
KW - Computing education
KW - Debugging
KW - Educational game
KW - Gidget
KW - Learning outcomes
KW - Programming
UR - http://www.scopus.com/inward/record.url?scp=84959307036&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84959307036&partnerID=8YFLogxK
U2 - 10.1145/2787622.2787709
DO - 10.1145/2787622.2787709
M3 - Conference contribution
AN - SCOPUS:84959307036
T3 - ICER 2015 - Proceedings of the 2015 ACM Conference on International Computing Education Research
SP - 237
EP - 246
BT - ICER 2015 - Proceedings of the 2015 ACM Conference on International Computing Education Research
PB - Association for Computing Machinery, Inc
T2 - 11th Annual ACM Conference on International Computing Education Research, ICER 2015
Y2 - 9 August 2015 through 13 August 2015
ER -