UPSI Digital Repository (UDRep)
Start | FAQ | About
Menu Icon

QR Code Link :

Type :article
Subject :L Education (General)
Main Author :Balamuralithara Balakrishnan
Additional Authors :Mariam Nainan
Title :Design and evaluation of worked examples for teaching and learning introductory programming at tertiary level
Place of Production :Tanjong Malim
Publisher :Fakulti Seni, Komputeran dan Industri Kreatif
Year of Publication :2019
Corporate Name :Universiti Pendidikan Sultan Idris

Abstract : Universiti Pendidikan Sultan Idris
Studying worked examples has been found to be effective for learning problem solving, especially among students. However, students need to actively process  example content to benefit from it and content must be structured in a manner  that facilities knowledge construction. This study investigated the use of worked  examples for teaching and learning programming. Programming involves problem  analysis  and  solution  generation.  But  students  tend  to  jump  to  solution  generation without adequately analysing the problem. Consequently, the current  study designed and implemented a new worked example design that emphasised  problem analysis and utilised highlighting through web technology to encourage  active processing of example content. This study also evaluated the new design in  a  quasi‐experiment  in  a  university  course  in  Malaysia,  compared  to  subgoal  labelled  worked  examples,  and  conducted  over  three  sessions.  Posttest  performance  was  analysed  using  independent  samples  t‐test  and  frequency  distributions.  The  results  suggested  that  worked  examples  based  on  the  new  design  were  more  effective  than  subgoal  labelled  worked  examples,  with  statistically significant difference in performance, and medium effect size for the  first  session.  For  the  second  and  third  sessions,  performance  was  marginally  better,  with  learning  in  both  groups  possibly  limited  by  the  complexity  of  the  worked examples and assessments

References

1. Altintas, T., Gunes, A., & Sayan, H.  (2016). A peer‐assisted learning experience in computer programming  language  learning  and  developing  computer  programming  skills.  Innovations  in  Education  and  Teaching International, 53(3), 329‐337. doi: 10.1080/14703297.2014.993418. 

2. Atkinson, R. K., Derry, S. J., Renkl, A., & Wortham, D. (2000). Learning from examples: instructional principles  from  the  worked  examples  research. Review  of  Educational  Research, 70(2),  181.  doi:10.2307/1170661. 

3. Atkinson, R. K., Catrambone, R., & Merrill, M. M. (2003). Aiding transfer in statistics: examining the use of  conceptually  oriented  equations  and  elaborations  during  subgoal  learning.  Journal  of  Educational  Psychology, 95(4), 762‐773. doi: 10.1037/0022‐0663.95.4.762.

4. Bester,  G.,  &  Brand,  L.  (2013).  The  effect  of  technology  on  learner  attention  and  achievement  in  the  classroom. South African Journal of Education, 33(2), pp. 1‐15.  

5. Cardellini, L. (2014). Problem solving: how can we help students overcome cognitive difficulties. Journal of  Technology and Science Education, 4(4), 237‐249. doi: 10.3926/jotse.121. 

6. Catrambone, R.  (1998). The  subgoal learning model:  Creating  better examples  so  that  students  can  solve  novel  problems. Journal  of  Experimental  Psychology:  General, 127(4),  355‐376.  doi:10.1037/0096‐3445.127.4.355.

7. Dos Santos, M. T., Vianna Jr, A. S., & Le Roux, G. A. (2018). Programming skills in the industry 4.0: are chemical  engineering students able to face new problems?. Education for Chemical Engineers, 22, 69‐76. 

8. Driscoll, M. P. (2005). Psychology of learning for instruction, (3rd ed.) Boston: Pearson. 

9. Dunn,  T.  J.,  &  Kennedy,  M.  (2019).  Technology  enhanced  learning  in  higher  education;  motivations, engagement and academic achievement. Computers & Education, 137, 104‐113. 

10. Etikan,  I.,  Musa,  S.  A.,  &  Alkassim,  R.  S.  (2016).  Comparison  of  convenience  sampling  and  purposive sampling. American  Journal  of  Theoretical  and  Applied  Statistics, 5(1),  1‐4.  doi: 10.11648/j.ajtas.20160501.11 

11. Henrie, C. R., Halverson, L. R., & Graham, C. R. (2015). Measuring student engagement in technologymediated learning: A review. Computers & Education, 90, 36-53.

12. Jamet, E.,  &  Fernandez, J.  (2016).  Enhancing  interactive  tutorial  effectiveness  through  visual  cueing. Educational Technology Research and Development, 64(4), 631‐641. doi:10.1007/s11423‐016‐9437‐6.

13. Lin, L.,  Atkinson, R. K.,  Savenye, W. C.,  &  Nelson, B. C.  (2014).  Effects  of  visual  cues  and  self‐explanation prompts: empirical evidence in a multimedia environment. Interactive Learning Environments, 24(4), 799‐813. doi:10.1080/10494820.2014.924531.  

14. Loksa, D., & Ko, A. J. (2016, August). The role of self‐regulation in programming problem solving process and  success. Proceedings of the 2016 ACM Conference on International Computing Education Research (pp. 83‐91). ACM. 

15. Malhotra, V. M.,  &  Anand, A.  (2019).  Teaching  a  university‐wide  programming  laboratory:  managing  a  C  programming  laboratory  for  a  large  class  with  diverse  interests. Proceedings  of  the  Twenty‐First  Australasian Computing Education Conference on ‐ ACE '19. doi:10.1145/3286960.3286961. 

16. Margulieux, L. E., & Catrambone, R. (2016). Improving problem solving with subgoal labels in expository text  and worked examples. Learning and Instruction, 42, 58‐71. doi:10.1016/j.learninstruc.2015.12.002. 

17. McCracken, M., Almstrum, V., Diaz, D., Guzdial, M., Hagan, D., Kolikant, Y. B.‐D., Laxer, C., Thomas, L., Utting, I., Wilusz, T. (2001). A multi‐national, multi‐institutional study of assessment of programming skills of  first‐year CS students. Working group reports from ITiCSE on Innovation and Technology in Computer  Science Education ‐ ITiCSE‐WGR '01. doi:10.1145/572134.572137.

18. Moreno, R. (2006). When worked examples don't work: Is cognitive load theory at an Impasse? Learning and Instruction, 16(2), 170‐181. doi:10.1016/j.learninstruc.2006.02.006.

19. Morrison, B. B., Margulieux, L. E., & Guzdial, M. (2015). Subgoals, context, and worked examples in learning computing  problem  solving. Proceedings  of  the  eleventh  annual  International  Conference  on International Computing Education Research ‐ ICER '15. doi:10.1145/2787622.2787733.

20. Mulder, Y. G., Lazonder, A. W., & De Jong, T.  (2014). Using heuristic worked examples to promote inquiry‐based learning. Learning and Instruction, 29, 56‐64. doi:10.1016/j.learninstruc.2013.08.001. 

21. Patitsas,  E.,  Craig, M. &  Easterbrook,  S.  (2013).  Comparing  and  contrasting  different  algorithms  leads  to increased  student  learning.  Proceedings  of  the  Ninth  Annual  International  ACM  Conference  on International Computing Education Research , San Diego, 145‐152. doi: 10.1145/2493394.2493409. 

22. Renkl, A.  (2014).  Toward  an  instructionally  oriented  theory  of  example‐based  learning. Cognitive Science, 38(1), 1‐37. doi:10.1111/cogs.12086.

23. Renkl, A. (2017). Learning from worked‐examples in mathematics: students relate procedures to principles.  ZDM, 49(4), 571‐584. doi:10.1007/s11858‐017‐0859‐3. 

24. Schindler, L. A., Burkholder, G. J., Morad, O. A., & Marsh, C. (2017). Computer‐based technology and student engagement:  a  critical  review  of  the  literature. International  Journal  of  Educational  Technology  in Higher Education, 14(1), 25. 

25. Schoenfeld,  A.  H.  (1992).  Learning  to  think  mathematically:  problem  solving,  metacognition,  and  sense making  in  mathematics.  D.  Grouws  (Ed.)  Handbook  for  Research  on  Mathematics  Teaching  and Learning. NY: Macmillan, 334‐370. 

26. Shi, J., Sha, A., Hedman, G., & Rourke, E. O. (2019). Pyrus: designing a collaborative programming game to support  problem‐solving  behaviors.  Proceedings  of  the  2019  CHI  Conference  on  Human  Factors  in Computing Systems. Glasgow, Paper No. 656. doi: 10.1145/3290605.3300886. 

27. Spector, J. M. (2013). Trends and Research Issues in Educational Technology. Malaysian Online Journal of Educational Technology, 1(3), 1-9.

28. Sweller, J.  (1994).  Cognitive  load  theory,  learning  difficulty,  and  instructional  design. Learning  and Instruction, 4(4), 295‐312. doi:10.1016/0959‐4752(94)90003‐5.

29. Sweller, J., & Cooper, G. A. (1985). The use of worked examples as a substitute for problem solving in learning algebra. Cognition and Instruction, 2(1), 59‐89. doi:10.1207/s1532690xci0201_3.

30. Van  Gog, T.,  Kester, L.,  &  Paas, F.  (2011).  Effects  of  worked  examples,  example‐problem,  and  problem‐example  pairs  on  novices’  learning. Contemporary  Educational  Psychology, 36(3),  212‐218.  doi:10.1016/j.cedpsych.2010.10.004.

31. Van Merriënboer, J. J., & Sweller, J. (2005). Cognitive load theory and complex learning: recent developments and future directions. Educational Psychology Review, 17(2), 147‐177. doi:10.1007/s10648‐005‐3951‐0. 


This material may be protected under Copyright Act which governs the making of photocopies or reproductions of copyrighted materials.
You may use the digitized material for private study, scholarship, or research.

Back to previous page

Installed and configured by Bahagian Automasi, Perpustakaan Tuanku Bainun, Universiti Pendidikan Sultan Idris
If you have enquiries, kindly contact us at pustakasys@upsi.edu.my or 016-3630263. Office hours only.