Student-Centered Learning Objects to Support the Self-Regulated Learning of Computer Science
Affiliation(s)
School of Electrical Engineering and Computer Science, The University of Newcastle, Newcastle, Australia.
School of Electrical Engineering and Computer Science, The University of Newcastle, Newcastle, Australia.
ABSTRACT
The most current computing curriculum guidelines focus on designing learning materials to prepare students for lifelong learning. Under the lifelong learning paradigm, students are responsible for controlling and monitoring their learning processes. This undoubtedly includes the ability to choose suitable learning materials. Correspondingly, instructional paradigms are shifting from teacher-centered to more student-centered models that require students to be self-regulated learners. On the other hand, recent trends in learning materials’ instructional design focus on moving toward the concept of Learning Object-based instructional technology. A learning object is a unit of instruction with a specific pedagogical objective that can be used and reused in different learning contexts. Designing learning objects to support students in their self-regulated learning is not an easy task due to the lack of underlying pedagogical frameworks. It is difficult to find learning objects related to students’ specific preferences and requirements. In this study, a number of learning objects are designed to support the self-regulated learning of programming languages concepts based on the theory of learning s. Students’ interactions with these learning objects are managed using an online learning object repository. The repository helps students identify their preferred learning s and find the relevant learning objects. The results of the evaluations of these learning objects revealed that students perceive them to be easy to use and effective in supporting their learning about different programming languages concepts.
The most current computing curriculum guidelines focus on designing learning materials to prepare students for lifelong learning. Under the lifelong learning paradigm, students are responsible for controlling and monitoring their learning processes. This undoubtedly includes the ability to choose suitable learning materials. Correspondingly, instructional paradigms are shifting from teacher-centered to more student-centered models that require students to be self-regulated learners. On the other hand, recent trends in learning materials’ instructional design focus on moving toward the concept of Learning Object-based instructional technology. A learning object is a unit of instruction with a specific pedagogical objective that can be used and reused in different learning contexts. Designing learning objects to support students in their self-regulated learning is not an easy task due to the lack of underlying pedagogical frameworks. It is difficult to find learning objects related to students’ specific preferences and requirements. In this study, a number of learning objects are designed to support the self-regulated learning of programming languages concepts based on the theory of learning s. Students’ interactions with these learning objects are managed using an online learning object repository. The repository helps students identify their preferred learning s and find the relevant learning objects. The results of the evaluations of these learning objects revealed that students perceive them to be easy to use and effective in supporting their learning about different programming languages concepts.
Cite this paper
Alharbi, A. , Henskens, F. & Hannaford, M. (2012). Student-Centered Learning Objects to Support the Self-Regulated Learning of Computer Science. Creative Education, 3, 773-783. doi: 10.4236/ce.2012.326116.
Alharbi, A. , Henskens, F. & Hannaford, M. (2012). Student-Centered Learning Objects to Support the Self-Regulated Learning of Computer Science. Creative Education, 3, 773-783. doi: 10.4236/ce.2012.326116.
References
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[1] Akdemir, O., & Koszalka, T. (2008). Investigating the relationships among instructional strategies and learning styles in online environments. Computers & Education, 50, 1451-1461. doi:10.1016/j.compedu.2007.01.004 [2] Alharbi, A., Paul, D., Henskens, F., & Hannaford, M. (2011). An investigation into the learning styles and self-regulated learning strategies for computer science students. In Proceedings Ascilite 2011 (36-46). Hobart: Ascilite. [3] Allert, J. (2004). Learning style and factors contributing to success in an introductory computer science course. In Proceedings of the IEEE International Conference on Advanced Learning Technologies (pp. 385-389). Charlotte: SIGCSE. doi:10.1109/ICALT.2004.1357442 [4] Ben-Ari, M., Berglund, A., Booth, S., & Holmboe, C. (2004). What do we mean by theoretically sound research in computer science education? Proceedings of the 9th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education (pp. 230-231). New York, NY: ACM. [5] Benaya, T., & Zur, E. (2008). Understanding object oriented programming concepts in an advanced programming course. Informatics Education—Supporting Computational Thinking, 5090, 161-170. doi:10.1007/978-3-540-69924-8_15 [6] Berglund, A., Eckerdal, A., Pears, A., East, P., Kinnunen, P., Malmi, L. et al. (2009). Learning computer science: Perceptions, actions and roles. European Journal of Engineering Education, 34, 327-338. doi:10.1080/03043790902989168 [7] Bruning, R., Schraw, G., & Ronning, R. (1999). Cognitive psychology and instruction (3rd ed.). Upper Saddle River, NJ: Prentice-Hall. [8] Chamillard, A., & Karolick, D. (1999). Using learning style data in an introductory computer science course. ACM SIGCSE Bulletin, 31, 291-295. doi:10.1145/384266.299790 [9] Coffield, F. (2004). Learning styles and pedagogy in post-16 learning: A systematic and critical review. London: Learning and Skills Research Centre. [10] Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Should we be using learning styles. London: Learning and Skills Research Centre. [11] De Raadt, M., & Simon (2011). My students don’t learn the way I do. Proceedings of the 13th Australasian Computing Education Conference (ACE 2011) (pp. 105-112). Perth: Australian Computer Society, Inc. [12] Dettori, G., & Persico, D. (2008). Detecting self-regulated learning in online communities by means of interaction analysis. IEEE Transactions on Learning Technologies, 1, 11-19. doi:10.1109/TLT.2008.7 [13] Felder, R. M., & Silverman, L. K. (1988). Learning and teaching styles in engineering education. Engineering education, 78, 674-681. [14] Felder, R. M., & Soloman, B. A. (1997). Index of learning styles. URL (last checked 20 June 2011). http://www4.ncsu.edu/unity/lockers/users/f/felder/public/ILSpage.html [15] Fjuk, A., Bennedsen, J., Berge, O., & Caspersen, M. E. (2004). Learning object-orientation through ICT-mediated apprenticeship. Proceedings of IEEE International Conference on Advanced Learning Technologies (pp. 380-384). Washington, DC: IEEE Computer Society. doi:10.1109/ICALT.2004.1357441 [16] Fleury, A. E. (2001). Encapsualtion and reuse as viewed by java students. URL. http://dis.eafit.edu.co/depto/documentos/p189-fleury%20-%20Encapsulation%20and%20Reuse%20as%20Viewed%20by%20Java%20Stu dents.pdf [17] Hadar, I., & Leron, U. (2008). How intuitive is object-oriented design? Communications of the ACM, 51, 41-46. doi:10.1145/1342327.1342336 [18] Holland, S., Griffiths, R., & Woodman, M. (1997). Avoiding object misconceptions. ACM SIGCSE Bulletin, 29, 131-134. doi:10.1145/268085.268132 [19] Holmboe, C., McIver, L., & George, C. (2001). Research agenda for computer science education. In Proceedings of PPIG (pp. 207-223). Bournemouth: 13th Workshop of the Psychology of Programming Interest Group. [20] IEEE/ACM (2005). Computing curricula 2005: The overview report. URL (last checked 20 June 2011). http://www.acm.org/education/education/curric_vols/CC2005-March06Final.pdf [21] Keefe, J. W. (1988). Profiling and utilizing learning style. Reston, VA: NASSP Learning Style Series. [22] Liberman, N., Beeri, C., & Ben-David Kolikant, Y. (2011). Difficulties in learning inheritance and polymorphism. ACM Transactions on Computing Education (TOCE), 11, 4. doi:10.1145/1921607.1921611 [23] LTSC (2002). Draft standard for learning object metadata. URL (last checked 4 July 2011). http://ltsc.ieee.org/wg12/files/LOM_1484_12_1_v1_Final_Draft.pdf [24] Mills, J., Ayre, M., Hands, D., & Carden, P. (2010). Learning about learning styles: Can it improve engineering education? Mountain Rise, 2, 16. [25] Milne, I., & Rowe, G. (2002). Difficulties in learning and teaching programming—Views of students and tutors. Education and Information Technologies, 7, 55-66. doi:10.1023/A:1015362608943 [26] Or-Bach, R., & Lavy, I. (2004). Cognitive activities of abstraction in object orientation: An empirical study. ACM SIGCSE Bulletin, 36, 82-86. doi:10.1145/1024338.1024378 [27] Pintrich, P., & Zusho, A. (2007). Student motivation and self-regulated learning in the college classroom. The Scholarship of Teaching and Learning in Higher Education: An Evidence-Based Perspective, 3, 731-810. doi:10.1007/1-4020-5742-3_16 [28] Pritchard, A. (2009). Ways of learning: Learning theories and learning styles in the classroom (2nd ed.). London: David Fulton Publishers. [29] Ragonis, N., & Ben-Ari, M. (2005a). A long-term investigation of the comprehension of OOP concepts by novices. Computer Science Education, 15, 203-221 [30] Ragonis, N., & Ben-Ari, M. (2005b). On understanding the statics and dynamics of object-oriented programs. ACM SIGCSE Bulletin, 37, 226-230. [31] Reigeluth, C. M. (1999). What is instructional-design theory and how is it changing. Instructional-Design Theories and Models, 2, 5-29. [32] Sahami, M., Guzdial, M., McGettrick, A., & Roach, S. (2011). Setting the stage for computing curricula 2013: Computer science—Report from the ACM/IEEE-CS joint task force. In Proceedings of the 42nd ACM Technical Symposium on Computer Science Education (161- 162). New York, NY: ACM. [33] Sosteric, M., & Hesemeier, S. (2002). When is a learning object not an object: A first step towards a theory of learning objects. The International Review of Research in Open and Distance Learning, 3, 2. [34] Thagard (Ed.) (2010). The Stanford encyclopedia of philosophy. Palo Alto, CA: Stanford University. [35] Thomas, L., Ratcliffe, M., Woodbury, J., & Jarman, E. (2002). Learning styles and performance in the introductory programming sequence. ACM SIGCSE Bulletin, 34, 33-37. doi:10.1145/563517.563352 [36] Watson, J. (1997). Behaviorism. New Brunswick, NJ: Transaction Publishers. [37] Weinstein, C. E., & Acee, T. W. (2008). Cognitive view of learning. In N. Salkind, & K. Rasmussen (Eds.), Encyclopedia of educational psychology. New York, NY: Sage Publications. [38] Wiley, D. (2000). Connecting learning objects to instructional design theory: A definition, a metaphor, and a taxonomy. Learning Technology, 2830, 1-35. [39] Wiley, D. (2002). Learning objects need instructional design theory. In A. Rossett (Ed.), The ASTD e-Learning Handbook (pp. 115-126). New York, NY: McGraw-Hill. [40] Wiley, D., Waters, S., Dawson, D., Lambert, B., Barclay, M., Wade, D., et al. (2004). Overcoming the limitations of learning objects. Journal of Educational Multimedia and Hypermedia, 13, 507-521. [41] Zander, C., Thomas, L., Simon, B., Murphy, L., McCauley, R., Hanks, B. et al. (2009). Learning styles: Novices decide. ACM SIGCSE Bulletin, 41, 223-227.