%0 Conference Paper %1 Ericson:2018:EEE:3230977.3231000 %A Ericson, Barbara J. %A Foley, James D. %A Rick, Jochen %B Proceedings of the 2018 ACM Conference on International Computing Education Research %C New York, NY, USA %D 2018 %I ACM %K adaptive-learning parsons-problem programming %P 60--68 %R 10.1145/3230977.3231000 %T Evaluating the Efficiency and Effectiveness of Adaptive Parsons Problems %U http://doi.acm.org/10.1145/3230977.3231000 %X Practice is essential for learning. There is evidence that solving Parsons problems (putting mixed up code blocks in order) is a more efficient, but just as effective, form of practice than writing code from scratch. However, not all students successfully solve every Parsons problem. Making the problems adaptive, so that the difficulty changes based on the learner's performance, should keep the learner in Vygotsky's zone of proximal development and maximize learning gains. This paper reports on a study comparing the efficiency and effectiveness of learning from solving adaptive Parsons problems vs non-adaptive Parsons problem vs writing the equivalent code. The adaptive Parsons problems used both intra-problem and inter-problem adaptation. Intra-problem adaptation means that if the learner is struggling to solve the current problem, the problem can dynamically be made easier. Inter-problem adaptation means that the difficulty of the next problem is modified based on the learner's performance on the previous problem. This study provides evidence that solving intra-problem and inter-problem adaptive Parsons problems is a more efficient, but just as effective, form of practice as writing the equivalent code. %@ 978-1-4503-5628-2

@inproceedings{Ericson:2018:EEE:3230977.3231000, abstract = {Practice is essential for learning. There is evidence that solving Parsons problems (putting mixed up code blocks in order) is a more efficient, but just as effective, form of practice than writing code from scratch. However, not all students successfully solve every Parsons problem. Making the problems adaptive, so that the difficulty changes based on the learner's performance, should keep the learner in Vygotsky's zone of proximal development and maximize learning gains. This paper reports on a study comparing the efficiency and effectiveness of learning from solving adaptive Parsons problems vs non-adaptive Parsons problem vs writing the equivalent code. The adaptive Parsons problems used both intra-problem and inter-problem adaptation. Intra-problem adaptation means that if the learner is struggling to solve the current problem, the problem can dynamically be made easier. Inter-problem adaptation means that the difficulty of the next problem is modified based on the learner's performance on the previous problem. This study provides evidence that solving intra-problem and inter-problem adaptive Parsons problems is a more efficient, but just as effective, form of practice as writing the equivalent code.}, acmid = {3231000}, added-at = {2018-08-13T13:42:16.000+0200}, address = {New York, NY, USA}, author = {Ericson, Barbara J. and Foley, James D. and Rick, Jochen}, biburl = {https://www.bibsonomy.org/bibtex/2b2617611446ed22e870de6f4d75f9ab8/brusilovsky}, booktitle = {Proceedings of the 2018 ACM Conference on International Computing Education Research}, description = {Evaluating the Efficiency and Effectiveness of Adaptive Parsons Problems}, doi = {10.1145/3230977.3231000}, interhash = {68d32984bc2c3a614ea7d09e459fac8b}, intrahash = {b2617611446ed22e870de6f4d75f9ab8}, isbn = {978-1-4503-5628-2}, keywords = {adaptive-learning parsons-problem programming}, location = {Espoo, Finland}, note = {interesting set of ideas on how to adapt Parsons problems. Based on past research, which tells what making Parsons hard or easier (any distractors, unpaired distractors, etc) we can adapt difficulty of Parsons problem to students. Got a study in a class }, numpages = {9}, pages = {60--68}, publisher = {ACM}, series = {ICER '18}, timestamp = {2018-08-13T13:42:16.000+0200}, title = {Evaluating the Efficiency and Effectiveness of Adaptive Parsons Problems}, url = {http://doi.acm.org/10.1145/3230977.3231000}, year = 2018 }