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2015 | OriginalPaper | Buchkapitel

4. Modelling of CS Teaching and Learning in Large

verfasst von : Vytautas Štuikys

Erschienen in: Smart Learning Objects for Smart Education in Computer Science

Verlag: Springer International Publishing

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Abstract

In previous chapters (see Chaps. 1 and 2), I have outlined the most general issues of e-learning and CS teaching on the basis of the LO concept. The main focus was given to understanding of the issues through conceptual analysis of the domain literature at the level of LO concepts and their taxonomies. In Chap. 3, I have analysed all these with the emphasis on pedagogical reusability using the software reuse approaches. In this chapter, I provide more in-deep analysis of modelling CS learning and teaching using a systematic approach which is a synthetic product of some domain analysis methods well known in SWE as well as in e-learning domains. In general, the aim of modelling, as it is conceived in the large, for example, in software engineering, is to extract and represent artefacts and knowledge needed to build a software system. As a rule, the extracted artefacts from the domain to be modelled should be represented at a higher level of abstraction. Often we refer to those artefacts as a domain model. Modelling is a primary stage in developing systems.

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Vorheriges Kapitel Reuse Framework of the LO Lo Domain

Nächstes Kapitel Model-Driven Specification in Designing Smart LOs

[ACL+13]

Acher M, Collet P, Lahire P, France RB (2013) FAMILIAR: a domain-specific language for large scale management of feature models. Sci Comput Program 78(6):657–681CrossRef

[AK09]

Apel S, Kästner C (2009) An overview of feature-oriented software development. J Object Technol 8(5):49–8CrossRef

[Ala12]

Ala-Mutka K (2012) Problems in learning and teaching programming. Codewitz needs analysis. http://www.cs.tut.fi~edge/literature_study.pdf

[Bat05]

Batory D (2005) Feature models, grammars, and propositional formulas. Springer, Berlin/Heidelberg, pp 7–20

[BBC+01]

Butler G, Batory DS, Czarnecki K, Eisenecker UW (2001) Generative techniques for product lines. In: Proceedings of the 23rd international conference on software engineering, ICSE 2001, Toronto, 12–19 May 2001, pp 760–761

[BDB+06]

Botturi L, Derntl M, Boot E, Figl K (2006) A classification framework for educational modeling languages in instructional design. In: 6th IEEE international conference on advanced learning technologies (ICALT 2006), Kerkrade, pp 1216–1220

[Bos00]

Bosch J (2000) Design and use of software architectures, adopting and evolving a product-line approach. Addison-Wesley, Reading

[BP99]

Brézillon P, Pomerol J-Ch (1999) Contextual knowledge sharing and cooperation in intelligent assistant systems. Le Travail Humain 62(3):223–246. PUF, Paris

[Bre05]

Brezillon P (2005) Task–realization models in contextual graphs. Modeling and using context. In: Dey A, Kokinov B, Leake D, Turner R (eds) CONTEXT–05. Springer, LNCS, vol 3554, pp 55–68

[BS11]

Burbaite R, Stuikys V (2011) Analysis of learning object research using feature-based models. In: Rimantas B, Butkiene R (eds) Information technologies’ 2011, Proceedings of the 17th international conference on information and software technologies, IT 2011, Kaunas University of Technology, Lithuania, 27–29 Apr 2011, pp 201–208

[Bur14]

Burbaitė R (2014) Advanced generative learning objects in informatics education: the concept, models, and implementation. Summary of doctoral dissertation, physical sciences, informatics (09P), Kaunas University of Technology, Kaunas

[BS99]

De Baud JM, Schmid K (1999) A systematic approach to derive the scope of software product lines. ICSE, Los Angeles, CA, USA, pp 34–43

[BSC10]

Benavides D, Segura S, Cortés AR (2010) Automated analysis of feature models 20 years later: a literature review. Inf Syst 35(6):615–636CrossRef

[BSM12]

Burbaite R, Stuikys V, Marcinkevicius R (2012) The LEGO NXT Robot-based e-learning environment to teach computer science topics. Electron Elect Eng 18(9):113–116

[CAC12]

Costa CJ, Aparicio M, Cordeiro C (2012) A solution to support student learning of programming. In: Proceedings of the workshop on open source and design of communication, ACM, New York, NY, USA, pp 25–29

[CBS+11]

Campos F, Braga R, Souza AC, Santos N, Matos E, Nery T (2011) Projeto BROAD (2011) Busca semântica por objetos de aprendizagem. In: VIII Congresso Brasileiro de Ensino Superior a Distância – ESUD 2011, Ouro Preto, pp 1–15

[CE00]

Czarnecki K, Eisenecker UW (2000) Separating the configuration aspect to support architecture evolution. In: Proceedings of 14th European conference on object-oriented programming (ECOOP’2000), International workshop on aspects and dimensions of concerns, Cannes, 11–12 June 2000

[CE01]

Czarnecki K, Eisenecker U (2001) Generative programming: methods, tools and applications. Addison-Wesley, Boston

[CHE05]

Czarnecki K, Helsen S, Eisenecker U (2005) Staged configuration through specialization and multi-level configuration of feature models. Softw Process Improve Pract 10(2005):143–169CrossRef

[Chu07]

Chudá D (2007) Visualization in education of theoretical computer science. In: Proceedings of the 2007 international conference on computer systems and technologies, ACM, p 84

[CHW98]

Coplien J, Hoffman D, Weiss D (1998) Communality and variability in software engineering. IEEE Softw 15:37–45CrossRef

[CKK06]

Czarnecki K, Kim CHP, Kalleberg KT (2006) Feature models are views on ontologies. In: Proceedings of the 10th international on software product line conference, Baltimore, pp 41–51

[CL13]

Collet P, Lahire P (2013) Feature modelling and separation of concerns with FAMILIAR, CMA@RE, IEEE. Rio de Janeiro, Brasil, pp 13–18

[CLA06]

Caeiro-Rodríguez M, Llamas-Nistal M, Anido-Rifón L (2006) A separation of concerns approach to educational modeling languages. In: Frontiers in education conference, 36th annual, IEEE, San Diego, pp 9–14

[CNC12]

Castro J, Nazar JM, Campos F (2012) EasyT: Apoiando a Construção de Objetos de Aprendizagem para uma Linha de Produtos de Software. Conferencias LACLO 3(1)

[CVL14]

Common Variability Language (CVL) standard, http://www.omgwiki.org/variability/doku.php. Accessed on January 2014

[CW07]

Czarnecki K, Wasowski A (2007) Feature diagrams and logics: there and back again. In Proceedings of SPLC’07, Kyoto, pp 23–34

[DDA12]

Díez D, Díaz P, Aedo I (2012) The ComBLA method: the application of domain analysis to the development of e-learning systems. J Res Pract Inf Technol 44(3):331–345

[Dij72]

Dijkstra EW (1972) Notes on structured programming. In: Dahl OJ, Dijkstra EW, Hoare CAR (eds) Structured programming. Academic, London

[DS09]

Damasevicius R, Stuikys V (2009) Specification and generation of learning object sequences for e-learning using sequence feature diagrams and metaprogramming techniques. In: Advanced learning technologies, 2009. ICALT 2009. 9th IEEE international conference, July, Riga, pp 572–576

[DSS+08]

Dorairaj SK, Singh J, Shanmugam M, Shamini S (2008) Experimenting with industry’s pair-programming model in teaching and learning programming. In: Proceedings of the 4th international conference on information technology and multimedia at UNITEN (ICIMU' 2008), Malaysia

[Gre08]

Greer D (2008) The art of separation of concerns. http://ctrl-shift-b.blogspot.com/2008/01/art-of-separation-of-concerns.html

[HHU08]

Hubaux A, Heymans P, Unphon H (2008) Separating variability concerns in a product line re-engineering project. In: EA-AOSD’08, Brussels, 31 Mar 2008

[HS12]

Hamada M, Sato S (2012) A learning system for a computational science related topic. Procedia Comput Sci 9:1763–1772CrossRef

[JCS09]

Jiau HC, Chen JC, Ssu KF (2009) Enhancing self-motivation in learning programming using game-based simulation and metrics. Educ IEEE Trans Enhanc Learn 52(4):555–562CrossRef

[KCH+90]

Kang K, Cohen S, Hess J, Novak W, Peterson S (1990) Feature-oriented domain analysis (FODA) feasibility study. TR CMU/SEI-90-TR-21, Software Engineering Institute, Carnegie Mellon University, November 1990

[KM09]

Koehler M, Mishra P (2009) What is technological pedagogical content knowledge (TPACK)? Contemp Issues Technol Teac Educ 9(1):60–70

[KP05]

Kelleher C, Pausch R (2005) Lowering the barriers to programming: a taxonomy of programming environments and languages for novice programmers. ACM Comput Surv 37(2):83–137CrossRef

[LC06]

Laforcade P, Choquet C (2006) Next step for educational modeling languages: the model driven engineering and reengineering approach. In: 6th international conference on advanced learning technologies, 2006. IEEE, pp 745–747

[LC09]

Laguna MA, Corral JM (2009) Feature diagrams and their transformations: an extensible meta-model. Proceedings of 35th Euromicro conference on software engineering and advanced applications, SEAA 2009, Patras, 27–29 Aug 2009, pp 97–104

[LH10]

Liu GZ, Hwang GJ (2010) A key step to understanding paradigm shifts in e-learning: towards context-aware ubiquitous learning. Br J Educ Technol 41(2):E1–E9CrossRef

[LLY10]

Law KM, Lee V, Yu YT (2010) Learning motivation in e-learning facilitated computer programming courses. Comput Educ 55(1):218–228CrossRef

[OMG03]

OMG. MDA Guide Version 1.0.1, 2003. Version 1.0.1, OMG document omg/03-06-01

[Par72]

Parnas DL (1972) On the criteria to be used in decomposing a system into modules. Communications of ACM, December, pp 1053–1058

[Pea10]

Pears AN (2010) Enhancing student engagement in an introductory programming course. In: 40th Frontiers in education conference, ser. Proceedings of the Frontiers in education conference (No. 40)

[PLL+06]

Paquette G, Léonard M, Lundgren-Cayrol K, Mihaila S, Gareau D (2006) Learning design based on graphical knowledge-modeling. J Educ Technol Soc 9(1):97–112

[RM04]

Rodríguez-Artacho M, Maillo MFV (2004) Modeling educational content: the cognitive approach of the PALO language. Educ Technol Soc 7(3):124–137

[ŠBD13]

Štuikys V, Burbaitė R, Damaševičius R (2013) Teaching of computer science topics using meta-programming-based GLOs and LEGO robots. Inform Educ Int J 12(1):125–142

[Sch06]

Schmidt DC (2006) Model-driven engineering. IEEE Comput 39(2):25–31CrossRef

[ŠD08]

Štuikys V, Damaševičius R (2008) Development of generative learning objects using feature diagrams and generative techniques. Inf Edu 7(2):277–288

[ŠD13]

Štuikys V, Damaševičius R (2013) Meta-programming and model-driven meta-program development: principles processes and techniques. Springer, Heidelberg/New York/Dordrecht/LondonCrossRef

[ŠDB+08]

Štuikys V, Damaševičius R, Brauklytė I, Limanauskienė V (2008) Exploration of learning object ontologies using feature diagrams. Proceedings of world conference on educational multimedia, hypermedia & telecommunications (ED-MEDIA 08), 30 June 30–4 July 2008, Vienna, pp 2144–2154

[SDN+04]

Sinnema M, Deelstra S, Nijhuis J, Bosch J (2004) Covamof: a framework for modeling variability in software product families. In: Proceedings of 3rd international conference on software product lines, SPLC. LNCS, vol 3154, Springer, pp 197–213

[SHL+13]

Schäfer A, Holz J, Leonhardt T, Schroeder U, Brauner P, Ziefle M (2013) From boring to scoring–a collaborative serious game for learning and practicing mathematical logic for computer science education. Comput Sci Educ 23(2):87–111CrossRef

[SHT+07]

Schobbens PY, Heymans P, Trigaux JC, Bontemps Y (2007) Generic semantics of feature diagrams. Comput Netw 51(2):456–479CrossRefMATH

[SHT06]

Schobbens PY, Heymans P, Trigaux JCh (2006) Feature diagrams: a survey and a formal semantics. In: Proceedings of the 14th IEEE international requirements engineering conference, 11–15 Sept 2006. IEEE CS Washington, DC, pp 136–145

[SMG11]

Salleh N, Mendes E, Grundy J (2011) Empirical studies of pair programming for CS/SE teaching in higher education: a systematic literature review. Softw Eng IEEE Trans 37(4):509–525CrossRef

[SMS08]

Starr CW, Manaris B, Stalvey RH (2008) Bloom’s taxonomy revisited: specifying assessable learning objectives in computer science. ACM SIGCSE Bull 40(1):261–265CrossRef

[Sne96]

Snelting G (1996) Reengineering of configurations based on mathematical concept analysis. ACM Trans Softw Eng Methodol 5(2):146–189CrossRef

[SPL09]

SPLOT, http://gsd.uwaterloo.ca:8088/SPLOT/splot_open_source.html

[TBK09]

Thüm T, Batory D, Kästner C (2009) Reasoning about edits to feature models, In: Proceedings of ICSE’09. ACM/IEEE, pp 254–264

[Tou12]

Touretzky DS (2012) Seven big ideas in robotics, and how to teach them. In: Proceedings of the 43rd ACM technical symposium on computer science education. ACM, pp 39–44

[WG04]

Webber DL, Gomaa H (2004) Modeling variability in software product lines with the variation point model. Sci Comput Program 53(3):305–331CrossRefMATHMathSciNet

Titel: Modelling of CS Teaching and Learning in Large
verfasst von: Vytautas Štuikys
Verlag: Springer International Publishing
Buch: Smart Learning Objects for Smart Education in Computer Science
Print ISBN: 978-3-319-16912-5

Electronic ISBN: 978-3-319-16913-2

Copyright-Jahr: 2015
DOI: https://doi.org/10.1007/978-3-319-16913-2_4

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