Enhanced Features of SLOs: Focus on Specialization

Smart LOs being reusable items in terms of generative capabilities may also offer new opportunities to create individual and highly adaptable content for learning processes. As it was shown in the previous chapters, reusability is a central topic in LO research. However, reusability cannot be generally understood without the educational context. The main goal of reusability is to adapt the teaching content to the context of use in some learning processes. The adaptive aspects of reusability should be discussed from a wider perspective than it was done so far. We need to have a framework enabling to connect reuse issues with the educational context in order we could be able first to specialize and then having the specialized SLO to consider the adaptability problem in some well-defined manner. Therefore, the aim of this chapter is to introduce such a framework and discuss the SLO problem.

[1]  Alanah-Rei Castledine,et al.  Lego robotics : an authentic problem solving tool? , 2011 .

[2]  Martin Fowler,et al.  Refactoring - Improving the Design of Existing Code , 1999, Addison Wesley object technology series.

[3]  Vytautas Stuikys,et al.  Generative Learning Object (GLO) Specialization: Teacher's and Learner's View , 2014, ICIST.

[4]  Julia L. Lawall,et al.  Towards bridging the gap between programming languages and partial evaluation , 2002, PEPM '02.

[5]  Carsten Ullrich Pedagogically Founded Courseware Generation for Web-Based Learning, An HTN-Planning-Based Approach Implemented in PAIGOS , 2008, Lecture Notes in Computer Science.

[6]  Yoshihiko Futamura,et al.  Partial Evaluation of Computation Process--An Approach to a Compiler-Compiler , 1999, High. Order Symb. Comput..

[7]  Margaret Hamilton,et al.  A taxonomic study of novice programming summative assessment , 2009, ACE '09.

[8]  Paulo Borba,et al.  Automatically Checking Feature Model Refactorings , 2011, J. Univers. Comput. Sci..

[9]  Walid Taha,et al.  Multi-Stage Programming: Its Theory and Applications , 1999 .

[10]  Tim Sheard,et al.  Accomplishments and Research Challenges in Meta-programming , 2001, SAIG.

[11]  Peter Sestoft,et al.  Partial evaluation and automatic program generation , 1993, Prentice Hall international series in computer science.

[12]  Krzysztof Czarnecki,et al.  Staged configuration through specialization and multilevel configuration of feature models , 2005, Softw. Process. Improv. Pract..

[13]  Dave A. Thomas Refactoring as Meta Programming , 2005, J. Object Technol..

[14]  Matteo Gaeta,et al.  An Ontology-Based Approach for Context-Aware E-learning , 2011, 2011 Third International Conference on Intelligent Networking and Collaborative Systems.

[15]  Mathieu Acher,et al.  FAMILIAR: A domain-specific language for large scale management of feature models , 2013, Sci. Comput. Program..

[16]  Semantics-Based Program Manipulation PPoPP '03 : the Ninth ACM SIGPLAN Sympoium on Principles and Practice of Parallel Programming, June 11-13, 2003 [and] PEPM '3 : ACM SIGPLAN workshop on Partial Evaluation and Semantics-based Program Manipulation, June 7, 2003, San Diego, CA, USA , 2003 .

[17]  Benjamin S. Bloom,et al.  A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives , 2000 .

[18]  Tim Trew,et al.  Using Feature Diagrams with Context Variability to Model Multiple Product Lines for Software Supply Chains , 2008, 2008 12th International Software Product Line Conference.

[19]  Rajendra Prasath,et al.  Qualitative Learning Outcome through Computer Assisted Instructions , 2013, MIKE.

[20]  Thomas Thüm,et al.  Reasoning about edits to feature models , 2009, 2009 IEEE 31st International Conference on Software Engineering.

[21]  Paul van Schaik,et al.  Learning Spaces, Tasks And Metrics For Effective Communication In Second Life Within The Context Of Programming Lego Nxt Mindstorms™ Robots: Towards A Framework For Design And Implementation , 2010 .

[22]  Tom Mens,et al.  Identifying refactoring opportunities using logic meta programming , 2003, Seventh European Conference onSoftware Maintenance and Reengineering, 2003. Proceedings..

[23]  Robertas Damasevicius,et al.  Teaching of Computer Science Topics Using Meta-Programming-Based GLOs and LEGO Robots , 2013, Informatics Educ..

[24]  Zoran Budimac,et al.  Ontology-based architecture with recommendation strategy in java tutoring system , 2013, Comput. Sci. Inf. Syst..

[25]  Neil D. Jones,et al.  An introduction to partial evaluation , 1996, CSUR.

[26]  Walid Taha,et al.  A Gentle Introduction to Multi-stage Programming , 2003, Domain-Specific Program Generation.

[27]  Manju Bhaskar,et al.  Context Aware E-Learning System with Dynamically Composable Learning Objects , 2010 .

[28]  Robertas Damasevicius,et al.  Meta-Programming and Model-Driven Meta-Program Development , 2012, Advanced Information and Knowledge Processing.

[29]  Dragan Gasevic,et al.  Configuring Software Product Line Feature Models Based on Stakeholders' Soft and Hard Requirements , 2010, SPLC.

[30]  Roberto Giacobazzi,et al.  Obfuscation by partial evaluation of distorted interpreters , 2012, PEPM '12.

[31]  Peter Sestoft,et al.  An experiment in partial evaluation: the generation of a compiler generator , 1985, SIGP.

[32]  Tom Mens,et al.  A survey of software refactoring , 2004, IEEE Transactions on Software Engineering.

[33]  Masaki Murakami An Application of Partial Evaluation of Communicating Processes to System Security , 2012, FOCS 2012.